The interpretation of the technique is based on a ratio of classification error to that of baseline error

Posted on October 16, 2023 by hemp2022

Across studies, different passive samplers have been used—samplers that vary in the nature of the material, size, and subsequent laboratory handling—and it has been questioned whether the specific sampler chosen could influence comparisons of different environments. In this study, we compare the microbial composition and quantity of settled dust that emerged when using different types of passive sampling approaches.Several lines of evidence indicate that, within each experimental setting, bacterial composition was similar within a sampling environment regardless of the sampler type used to characterize that environment. That is, bacterial composition of the passively collected dust correlated most strongly with the particular environment in which the sample was collected rather than with the particular method of dust collection, and this was true both for in situ building samples and for experimental conditions . Statistical analysis confirmed that the sampling environment was the single largest predictor of microbial community composition within a study and that sampler type was found to have much less predictive power, even if differences between sampler types reached statistical significance . Moreover, we utilized supervised learning to determine if unlabeled communities could be classified as belonging to a particular sampler type based on a set of labeled training communities.For each of the USA homes, Finland buildings, and experimental chamber, this ratio was ~1, indicating that the classifier performed no better than random guessing at which sampler types from which experimentally unlabeled microbial communities were derived . On the other hand, the ratio of classification error to baseline error for classifying sampling environment was ≥2.3,vertical cannabis grow indicating that the classifier performs at least twice as well as random guessing for determining the particular dust environment. Lastly, we examined the diversity of taxa detected in the different sampler types within a given study component , as this study was not focused on how diversity compared across the environments.

Using a mixed effect model, Shannon diversity was not found to vary across the sampler types , and observed richness significantly varied only in the chamber component , where it was lower in the EDCs compared to other sampling approaches. In addition, our data speak to two aspects of sampling repeatability. In the USA homes, samplers were placed at two heights, and in the Finland buildings, duplicate samplers were placed side by side at the same location. In each of these trials, duplicate samples were statistically indistinguishable with regard to bacterial composition . The taxonomic composition observed was largely consistent with other recent studies of indoor bacterial microbiomes . Ten groups—the Staphylococcaceae, Micrococcaceae, Moraxellaceae, Corynebacteriaceae, Streptococcaceae, Sphingomonadaceae, Bartonellaceae, Enterobacteriaceae, Rhodobacteraceae, and Streptophyta—combined to ~50 % of sequence reads . Within the chamber trials, for which the microbial community composition of the input dust is known through direct sequencing, there are modest differences in the compositional proportions between the vacuum dust and passive samplers. However, the passive samplers are all skewed in the same direction, such that Pseudomonadales, Enterobacteriales, and Streptophyta are underrepresented in the passive collectors, relative to their abundance in the vacuum dust that was aerosolized into the chamber . Figure 2 highlights the top-most abundant taxa by sequence reads, and the full dataset is available as Additional file 2. Within the building-based observations, taxa tended to vary in their relative abundances rather than in their detection. For example, within Finland buildings, 21 of the 25 most abundant taxa found in the petri dishes were common to the top taxa detected in the EDC and 15 were common to the top taxa in the TefTex. It was only the more rare taxa that were detected in one sampler and missed entirely in others. For instance, a bacterial operational taxonomic unit belonging to the family Dermatophilaceae represented 0.08 % of the sequences in the Petri dish sequences and 0.004 % of the sequences in the EDC but was not detected in the TefTex samples. Within USA homes, Streptophyta comprised a much larger percentage of the reads in petri dishes than the other sampler types. Fungal data were available for only one component of the study, that from USA homes.

Using an approach similar to that used for bacteria, the sampling environment of the USA homes explained over half the variation in fungal composition while sampler type was not a significant predictor .Quantitative PCR was used to estimate the microbial quantity collected in each of the samplers. Tables 3 and 4 report the bacterial and fungal counts, respectively, and additional quantitative PCR markers and more detailed information on analyses of the Finland building samples are included . Because experimental protocols were different in the USA and Finland , absolute values of microbial quantities across study components are difficult to compare. This was particularly the case for the extraction protocol of EDC and TefTex samplers, where the Finnish protocol included a rigorous and more efficient dust extraction procedure. In the USA homes, the highest yields of microbial biomass were found in the petri dish, followed by TefTex and the two EDCs, which had similar yields. The relative differences across locations matched predictions based on occupancy, although we acknowledge low sample numbers. For example, within the USA, quantities were lowest for house 1, which was occupied by a single occupant, and highest for house 3 occupied by a family of five with three dogs. In Finland, houses showed higher microbial biomass than work settings . In contrast to the home settings, yields from the chamber did not show such clear trends. In the chamber, which had much higher particle loading onto the samplers compared to the buildings, TefTex samplers most often showed the highest yields, followed by the petri dish samplers. For bacteria, the mean ratios of biomass detected relative the highest yield in TefTex were 0.7 for petri dish, 0.5 for EDC1, and 0.2 for EDC2; for fungi, the mean ratios were 0.7 for petri dish, 0.5 for EDC1, and 0.2 for EDC2. Side-by-side samplers in the Finland component of the study allows for examination of the correlation between duplicate samplers. Table 5 summarizes Pearson’s correlations of duplicate sampler qPCR determinations. Overall, strong and highly significant correlations were observed for the duplicate determinations in most cases, except in some cases for the TefTex material. The highest correlations were found for EDC3, followed by petri dish, and then TefTex. Although limited by a small number of different sampling environments and duplicate samples, analyses of the intraclass correlation and coefficient of variation of duplicates showed similar trends, with highest correlation/ lowest variation observed for EDC3, followed by petri dish sampling, then the TefTex material. Lastly, correlations of biomass determinations between different sampler types were strong .

Further information is detailed in Additional file 4.Passive collection of dust settled over a defined period represents a valuable tool for assessing microbial exposures in indoor environments, and this study sought to examine how the choice of passive sampler could affect estimates of the community composition and microbial biomass from the settled dust of different environments. We found that, for a given dust environment, estimates of bacterial community composition and diversity in passively collected airborne dust were similar regardless of the sampler type, as were estimates from our smaller study of fungal community composition. In the experimental chamber study, we did note an underestimate of some groups of bacteria, Pseudomonadales, Enterobacteriales, and Streptophyta, relative to the vacuum dust used in the dispersion, but the underestimation was similar for all collection methods. In contrast,vertical farming system estimation of the quantity of microbes was more sensitive to differences in both the dust loading of the environment and the experimental procedures used to collect, extract, and process the dust from the samplers. We discuss three areas of the experimental pipeline in which the different sampler types could vary in their efficiencies: collection, retention, and extraction.For collection efficiency, we refer to the properties of the sampler itself for collecting settling dust. For instance, the electrostatic properties of some surfaces could potentially bias the kind of settling particles that deposit. Many microbial spores carry a small net electrical charge, either positive or negative, although it is generally thought that most are slightly negative. A similarly negatively charged sampler surface could repel particles. All sampler types used here are electronegative to varying degrees, but it is unclear how much charge the samplers retain after heat treatment, if used, or after time employed in the field. Another property of the sampler that could affect collection is whether the material is likely to become saturated, thereby preventing further dust collection. It remains to be tested whether the small bias observed in the collection of some bacteria taxa in passive samplers relative to the source dust is a consequence of disproportional aerosolization of the source dust, size dependence of particle settling, surface charge of the sampler relative to the surface charge of the bioaerosols, or some other process. Another component of sampling efficiency is related to the retention of particles once collected or whether the forces generated by air speeds indoors are sufficient to overcome the adhesion forces between particles and passive collection surfaces. There are observations that the release of dust collected on “smooth” surfaces, such as petri dishes, are greater than from fibrous materials such as TefTex and EDCs. However, the microbial compositions in cow stables were similar between a plastic passive sampler and an electrostatic wipe. Under experimental conditions, resuspension of particles has been studied at air speeds that are orders of magnitude higher than the typical range of speeds in indoor air. In a typical household, the likelihood for a passive sampler to encounter air speeds sufficient to resuspend particles likely depends on the location of the sampler with regard to occupant movements and ventilation strategies. Lastly, the release of biological material from the sampling matrix and subsequent collection is the dominant factor affecting the extraction efficiency of dust and associated microbial material. In all samplers, the dust must first be isolated from the sampler, and in this study, the quantity of airborne dust in the experimental system affected the quantitative estimates that resulted. Within the building-based trials, under levels of particle loading typically encountered in the built environment, the petri dishes almost always yielded higher cell abundance than TefTex or EDCs , likely due to the simple process of using a swab to recover microbes from the sampler.

The step of pre-extraction of the dust from the fabric-based samplers requires specialized equipment and suspension in buffers. A more rigorous microbial recovery process that was employed in Finland, as compared to the USA , narrowed the gap in recovery between plain petri dishes and EDCs. In the chamber system, particle loading was much higher than representative conditions. For instance, with 1.77 g of dust fed, the surface dust loading at the bottom of the chamber was approximately 2.3 g/m2 . With a typical dust fall rate in residences of ~0.005 g/, it would take approximately 460 days to reach this level of dust in the sampler. Under this high particle loading such that a thick layer of dust was left in the samplers , one swab was insufficient to remove all the dust from one petri dish, resulting in an underestimation of microbial biomass per petri dish. As microbial differences across different environments were detectable with each of the passive sampling methods tested here , another consideration is the practical implications of employing the different samplers in field studies. Each sampler had limitations in particular aspects . For instance, sampling materials will vary in their ease of acquiring, preparing, and shipping the material. More importantly, however, are the different protocols—and accompanying equipment—required for isolating the dust from the samplers. The pre-extraction steps of the dust from the fabric-based samplers increase the time and expense of the protocol compared to the petri dish protocol. Considering the economics of implementing and processing the samplers in light of the composition and quantitative results here, petri dish samplers represent a robust method for passive dust collection, although the extraction process may require some additional labor in high particle loading environments compared to more typical building environments.

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Soil moisture monitoring practices help ensure precise frequency and duration of irrigations

Posted on October 13, 2023 by hemp2022

The significant vgsc mutations observed could be a result of selection pressure build-up that is due to more contact with insecticides in indoor-based interventions. From Kisian, the G119S mutation was present at low frequencies even though it was higher in the progeny of mosquitoes resting indoors compared to those resting outdoors. This was more in Kisian, where the vgsc mutations were at lower frequencies than in Kimaeti. These findings suggest that these mutations could be arising from different pressures that could be present in the lowland and absent in the highland.The metabolic enzymes, associated with insecticide resistance activities were found to be elevated, more in indoor resting malaria mosquitoes compared to the outdoor counterparts from both sites. From the phenotypic assays, pre-exposure to PBO synergist restored the susceptibility of the malaria vectors to the pyrethroids commonly used in LLINs by public health. Phenotypic exposures with prior PBO contact demonstrated more activity of monooxygenases in aiding metabolic resistance. The involvement of monooxygenases in pyrethroid resistance has been reported in Western Kenya. In Kimaeti, there was increased levels β-esterases, higher indoors than outdoors. Kisian, on the other hand, did not show involvement of β-esterases in contributing to resistance as shown by similar levels in indoor and outdoor resting mosquitoes. The glutathione-S-transferase possibly played a part in the resistance levels as a previous study reported since it was higher in mosquitoes resting indoors than those resting outdoors from both Kisian and Kimaeti. These levels, therefore, suggest that monooxygenases were the main mechanism of insecticide resistance in Kisian, especially with the low frequency of resistant alleles, whereas in Kimaeti, the case pointed be a combination of genotypic and metabolic mechanisms. The expression of phenotypic,grow solutions greenhouse genotypic and metabolic resistance appears to be higher in indoor than outdoor resting malaria mosquitoes in these regions.

The widespread use of LLINs in attempts to controlling these vectors and the extensive agrochemical use could be strengthening the increase of insecticide resistance in the sites. The higher levels indoors suggest that these mosquitoes could be resting indoors because they are adequately resistant to the insecticides used in LLINs, posing a threat to the wide coverage LLINs. On the other hand, outdoors, the resistance mechanisms were present as well pointing to exposure to these insecticide-based interventions in just enough pressure to elicit expression of the resistance traits. The levels of resistance could be enough to elicit an increase in malaria incidence due to the reduced mortality of resistant malaria vectors that could hinder current vector control interventions.Increasing temperatures and higher variability in precipitation in California are part of a larger regional trend in the Western United States . This is consistent with global trends that indicate that 2000-2010 has been warmer at the Earth’s surface than any preceding decade since 1850 . Observed increases in temperature and precipitation extremes in semi-arid regions, such as Southern California, clearly translate into more severe future impacts than analogous trends in temperate regions, such as projections of increased frequency and duration of heat waves and droughts over the remainder of the current century . Previous studies suggest that agriculture in the largely irrigated Western United States may not be as susceptible to precipitation trends as agriculture in the more temperate East . This holds for long-run mean precipitation conditions . However, this conclusion minimizes the severity of the recent drought experienced in California with historically low precipitation and soil moisture levels . The recurrence and longer duration of droughts in California over the past two decades has greatly affected the agricultural industry, which, on average, uses about 80% of freshwater resources . Figure 1.1 illustrates the percentage of California’s area in drought from 2000-2016. Not only does this reveal the large spatial and temporal extent of the most recent drought, but the colors reveal the large area under extreme and exceptional drought from mid-2013 to 2017. The most immediate economic impacts are lost agricultural revenue emanating from fallowed acres and yield declines, and farm job losses for one of the most vulnerable socioeconomic groups. For example, the 2009 drought resulted in revenue losses of $370 million with fallowing of 285 thousand acres in the San Joaquin Valley, and almost 10 thousand farm jobs losses .

Arguably the most important variables explaining how agriculture will be affected by climatic changes are those of human ingenuity at the farm level. Human ingenuity is simply another word for adaptation to climate change in order to minimize welfare losses. Thus, the overarching theme of our three subsequent analyses is quantifying grower responsiveness to farm-level microclimate in Southern California, our study area. Using original survey data, we study differential impacts of short-run weather and long-run climate—based on farm size, type, and water source—on productivity per acre and likelihood of adopting water management practices, which have not been studied in previous county-level analyses. Further, we are able to decompose water sources into price, pricing structure, frequency of rate increases, senior water rights, quality, and type of source . In addition to studying farm-level productivity, we study short-run fluctuations in weather on likelihood of adoption of water management technologies and practices, and on parcel-level land sales. Our contribution to the literature is based upon an original survey instrument we developed and disseminated to growers in the region . The contact information was taken from the respective county Agricultural Commissioner Offices. This survey is comprised of 28 multiple choice and fill-in questions on grower, farm, and water source characteristics. This was disseminated via mail by a team of 3 undergraduate students, to growers in the study region, with a 14.6% response rate. We focus on Southern California agriculture, specifically Imperial, Riverside, San Diego, and Ventura counties. The region is often overlooked as analyses tend to focus on the Central Valley, California’s most productive agricultural region. Yet, there are several crops for which 50% or more of California’s production originates in these four counties, including raspberries, lemons, flowers and foliage, avocado, and sudan hay. All of the state’s date and sugar beet production originates in these four counties . Imperial, Riverside, San Diego, and Ventura counties are amongst the top 15 agricultural counties in the state, representing approximately 16% of statewide agricultural revenue . They also represent the diverse climate of the region with two coastal , and two desert counties.

The 4 counties also vary in farm size with San Diego County having the largest share of farms under 10 acres, and, at the other extreme, Imperial County having the largest share of farms with 1000 or more acres . There is also a wide distribution in gross revenue across these counties . An immediate concern with aggregation at the county level is the omission of data on decision-maker/grower , farm ,marijuana drying rack and detailed water source attributes . Excluding such information assumes a priori a limited role of the economic agent to influence farmland productivity. It also simplifies the inherent complexity in representing farm and water source characteristics. It is not for lack of explanatory power that these variables are excluded. It is more likely that they would have been studied had they been available in existing data sources. The USDA Farm and Ranch Irrigation Survey , a major source of US agricultural data for economic analyses, does not provide these variables at the farm level to researchers. There is, however, little reason to assume that the climate, soil, and water variables in county-level studies are correlated with any of these microlevel variables, thus ruling out the potential bias in climate, soil, and water estimators. Aggregation at the county level also leaves the model susceptible to measurement error on certain explanatory variables . Measurement error is defined as an imprecise measure of an economic variable, dependent or explanatory, which has a well-defined quantitative meaning . 1 Following the classical errors-in variable assumption, this could lead to estimators that are asymptotically inconsistent and biased downward in their respective probability limits . 2 The remaining sections in this chapter present the theoretical framework behind each of the 3 empirical analyses in this dissertation: the Farm-Level Ricardian, the Discrete Choice of Adoption, and the Parcel-Level Models. Each subsection also includes hypotheses on the impact of climate and other key variables on the respective dependent variables . In addition to studying the impact of climate and other relevant variables on farmland productivity, we study the factors influencing the adoption of technologies to monitor soil moisture and salinity.5 Adoption of climate-effective monitoring practices is particularly important as projections of prolonged drought continue throughout the current century. Most growers in our sample have already adopted micro-irrigation practices for vegetables, orchards, and vineyards, and extension experts suggest that consistent and/or sophisticated monitoring of growing conditions represents the next stage of irrigation efficiency adaptations .

Salinity monitoring affects water availability in both the short and long run. Too much leaching leads to water waste and, ultimately poor irrigation and economic efficiency. Too little leaching affects soil salinity and water quality at both the farm and basin level, and ultimately water availability at the farm-level in the long run. We implement logistic regression, consistent with previous studies on technology adoption , to study the factors influencing adoption of at least one soil moisture monitoring practice , or at least one water salinity monitoring practice . Prior to implementing the pilot survey, we received approval from the UCR Institutional Review Board.There were two primary objectives to the pilot survey: field-test survey questions, and gauge response rate. Rather than rely on focus groups to field-test the survey questions, we chose to disseminate a pilot survey. The major benefit of sending a pilot survey is that we could potentially receive valuable input from respondents who could not participate in focus groups due to financial, time, or physical constraints. A second benefit was time savings in survey implementation. Focus groups require managing multiple schedules to find a convenient meeting time and place, and possibly funding travel and accommodation. Although we planned to disseminate an online survey, we had not yet at that stage secured assistance from either Agricultural Extension or Farm Bureaus in each county to host our survey. In order to save time, we sent the pilot survey via postal mail using contact information from the Agricultural Commissioner Pesticide Permit Database . An informal team of fellow graduate students and family/friends helped prepare the pilot phase mailings. Each mailing package included invitation letters , consent documents , first version of questionnaire , and a self-addressed return envelope. Using a random-number function in Microsoft Excel, we randomly selected 300 respondents in total from Riverside and San Diego counties. We selected these counties as they are representative of the type of agriculture found in the region . Based on our discussions with extension experts,8 we were sensitive to the potential apprehension with which Imperial County growers, in particular, would react to our survey. Growers in Imperial County have held senior water rights for over a century due to the Seven-Party Agreement.They are aware that they have been criticized for using less efficient irrigation practices , and many fear that they will be mandated to change these practices . Thus, they may be hesitant to providing any information on irrigation and other practices. In order to minimize Imperial growers’ time burden, we chose to field test the survey on a potentially more receptive audience, and send only the final survey to Imperial. Since Ventura County has a relatively similar distribution of farm types as San Diego County , we also decided to exclude Ventura from the pilot. The pilot survey consists of 20 questions, including grower characteristics , farm characteristics , water source characteristics , water management practices , perceptions of water scarcity , and an open-ended comment space at the end of the survey . The majority of these questions are multiple choice often with an “other” choice that included an option to write in a response that was not pre-determined. Eight questions are fill-in style. We received a roughly 10% response rate from the pilot phase , and learned valuable lessons on question structure for preparing the final survey. First, there were far too many questions on water scarcity perceptions, which could be consolidated into fewer questions. Second, income questions were better placed at the end of the survey to minimize participant suspicion.

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Dogs have been identified as a major identifiable source of endotoxin

Posted on October 12, 2023 by hemp2022

Analyses were conducted across both regions and separately by region given the difference noted above. We also used mixed models to analyze the prediction of personal and indoor endotoxin exposure by the following household characteristics: dog and cat ownership, including the number of dogs or cats and whether dogs or cats were allowed in the house ; number of people living in the home, carpet , whether it was it customary to remove shoes before entering the home, observed cockroaches, observed rodents, flooding damage, surface mold or mildew, livestock, central air conditioning, and region . Personal and family characteristics were also used in the prediction models and included age group , sex, race-ethnicity, mother’s education, and family income. For predictor variables in the indoor endotoxin models, we found insufficient variability across the 12 homes for the more refined categories used in the personal models . Therefore, we dropped carpet cleaning, cockroach and rodent presence, shoe removal, livestock, and air-conditioning. We also dichotomized cat and dog ownership and family income. We began with crude prediction models adjusted for personal temperature, personal relative humidity and study region for personal endotoxin, and study region for indoor endotoxin . We then selected the best multivariate model based on stepwise backward elimination of predictors with the largest p-value over 0.05, and on model fit by AIC. Removed variables were added back singly to the final model to test the appropriateness of the final model.We found detectable endotoxin concentrations in 376 daily personal PM2.5 filters analyzed [median 0.57, range 0.002 – 25.3 EU/m3 ]. All 52 personal field blank filters showed low or non-detectable endotoxin . Within-subject coefficients of variation for personal endotoxin ranged from 69% to 224% . We also successfully extracted and found detectable endotoxin concentrations in all 317 daily Harvard Impactor filters from the stationary site active samplers. As described in Table 1, these included 97 ambient, 109 indoor and 101 outdoor home filters,greenhouse racking and 10 filters from a site in Whittier that served as both an outdoor home and ambient site during one 10-day run, and served as the central ambient site for remaining 10-day runs.

The 42 blank filters at the stationary sites showed low or non-detectable endotoxin . For the comparisons with available indoor and outdoor measurements there were 116 and 113 personal endotoxin measurements, respectively, among the 14 subjects living in those 12 homes. For the comparisons with available ambient endotoxin measurements there were 339 personal endotoxin measurements among the 45 subjects. For the analysis of personal vs. fixed site endotoxin in regression models, one subject for just one day lacked personal temperature and humidity as covariates leaving 338 ambient, 115 indoor, and 112 outdoor observations for analysis. There were all or nearly all 376 personal endotoxin measurements for the comparisons with available ambient air pollution. Ambient air pollutant measurements were nearly complete with at least 407 days for each variable available for comparison with the 423 days of ambient endotoxin measurements. Descriptive statistics regarding all of the exposures by region are shown in Table 2. Arithmetic mean and median personal endotoxin exposures were higher in Riverside than in Whittier. Consistent with this, outdoor home and ambient endotoxin were higher in Riverside than in Whittier. However, indoor endotoxin exposures were higher in Whittier than in Riverside. Although arithmetic mean personal endotoxin was higher than indoor, outdoor or ambient levels across both regions, the median personal endotoxin was only higher in Riverside. This is a reflection of the typical skewed distribution of endotoxin exposures. Indoor to outdoor endotoxin ratios of medians were clearly opposite between the two sites with a ratio < 1.0 at Riverside and a ratio > 1 at Whittier .Actual indoor concentrations reflected this difference with a much lower indoor concentration in Riverside than in Whittier. We show correlation matrixes separately for Riverside and Whittier relating personal endotoxin and stationary site endotoxin to personal and stationary site endotoxin and air pollutants . We found personal endotoxin in both Riverside and Whittier was not significantly correlated with indoor endotoxin or any of the indoor air pollutants. Personal endotoxin was not significantly correlated with outdoor home endotoxin in either Riverside or Whittier. We observed small positive correlations between personal and ambient endotoxin in Riverside but not Whittier. Outdoor home and ambient endotoxin measurements were strongly correlated. In both Riverside and Whittier, personal endotoxin showed a small inverse correlations with personal PM2.5, and small positive correlations with personal PM2.5 EC and OC, which were larger in Whittier.

Personal endotoxin positively correlated with personal temperature in Riverside but negatively correlated with personal temperature in Whittier.Personal endotoxin in both Riverside and Whittier were not significantly correlated with any of the indoor air pollutants. Indoor endotoxin in Riverside, on the other hand, was strongly positively correlated with indoor PM2.5 EC and moderately correlated with indoor PM2.5 mass and OC, whereas in Whittier these correlations were positive but much smaller. Both personal and outdoor home endotoxin in Riverside were not significantly correlated with any outdoor home air pollutant measurement. We observed a small inverse correlation between personal endotoxin and outdoor home PM2.5 in Whittier. Outdoor home endotoxin showed small positive correlations with outdoor home PM2.5, EC and OC in Whittier. In Whittier, ambient temperature and O3 were negatively correlated with personal endotoxin. In Whittier, but not Riverside, ambient endotoxin showed small positive correlations with ambient traffic-related air pollutants and temperature and small inverse correlations with relative humidity.The prediction of personal endotoxin in mixed regression models by the various stationary site measurements of endotoxin are shown in Table 4 including both sites together and separately by region. Ambient endotoxin for the 14 subjects in monitored homes, and their exposure to indoor and outdoor home endotoxin were not significant predictors of personal endotoxin. However, ambient endotoxin for all 45 subjects was a significant positive predictor of personal endotoxin. The regional models show that the overall association was attributable to measurements at both sites, although the regression coefficient for Riverside was twice as large as Whittier. However, the regression coefficient for Whittier was more significant than Riverside . Figures 1-2 show scatter plots and results of linear regression models for the relation between log transformed indoor and outdoor home endotoxin across the 10-day monitoring sessions in 4 homes in Riverside and 8 homes in Whittier. In both regions, the relation was positive, with outdoor endotoxin explaining 25-28% of the variability in indoor endotoxin. The analysis of the relation between personal endotoxin and household or subject characteristics shows a clear positive association with dog ownership in crude models adjusted for personal temperature, personal relative humidity and region .

For each dog owned, personal endotoxin exposure approximately doubles. Interestingly, compared with having no dogs, the strongest and only significant association with personal endotoxin in crude models was for dogs that were only occasionally indoors. This contrasts the finding for cats since the only significant association was for having cats that were often indoors compared with having no cats. Other variables were significantly positively associated with personal endotoxin in the crude models,equipment for growing weed and they included reports of flooding damage and sex . Nominal associations included increasing personal endotoxin by the number of household residents and lower personal endotoxin among Hispanics. The final selected multivariate model included only cat and dog numbers adjusted for personal temperature, personal relative humidity and region. We found a relative increase in endotoxin for each dog of 1.76 , and for each cat of 1.39 . Residence of dogs and cats were not included due to expected dependent relations with the number of animals Chi-Square p-value < 0.0001. Adding back single excluded variables to this final model did not improve the fit of the model and showed that each of those variables were non-significant including flooding damage and male sex . Flood and cat were positively associated with each other . As a result, cat number confounded the association with flood and the association with cats also decreased by 37.5% as well . The analysis of the relation between indoor endotoxin and household or subject characteristics shows that unlike the personal exposure models, dog and cat ownership was not associated with indoor endotoxin . Only three variables were significant in the crude models,reports of flood damage, which was unexpectedly associated with lower endotoxin, Hispanic subjects associated with higher endotoxin , and high school or lower education level in mothers that was associated with lower endotoxin. The final selected multivariate model included only flooding damage and lower education levels in mothers.Our results suggest that fixed site measurements of endotoxin in the home environment may not adequately represent daily personal exposures. The finding of a positive association between ambient and personal endotoxin exposure is not particularly relevant to research used to investigate relations of respiratory health to endotoxin , but it does have some relevance regarding potential impacts of regional sources on personal exposure. It is possible that the limited sample size was insufficient to detect an association of personal with home endotoxin. Evidence in support of that view is that when we limited the analysis of prediction of personal endotoxin by ambient endotoxin to the monitored homes , associations were non-significant but point estimates were similar to those for the 45 subjects . Nevertheless, although we had a limited sample size in the 14 subjects, the findings for the relation of personal endotoxin exposure with indoor home endotoxin exposure , suggest that other micro-environments and personal activities are important to assess.

Given that our analysis was based on daily exposures using measurements all conducted with active 24-hour samplers, our conclusion that any one fixed site measurement may not adequately represent personal exposure applies to short-term exposures that may be involved in the acute exacerbation of asthma. We assessed the potential importance of other locations and physical activity by using previously reported data on quarter-hourly time-activity reports from an electronic diary that each subject filled out throughout follow-up. We found that on average, around 73% of time was spent at home indoor, 1.7% at home outdoor, 12.6% at school indoor, 1.8% at school outdoor, 4% in-transit, 4.3% indoor elsewhere, and 2.6% outdoor elsewhere. Out of an estimated average of 40 min per day of diary reported moderate to strenuous activity , 82% occurred while away from home. Such higher levels of activity may be important in promoting personal endotoxin exposure as a result of the so-called “personal dust cloud.” This is a phenomenon where localized personal activities lead to increased PM exposure by re-suspension of settled PM, which brings the breathing zone of subjects into closer contact with PM from various sources. The highly skewed distribution of personal endotoxin we observed may be partly due to the generation of personal clouds that results from subject activity, including activity around sources of resuspended dust. Our findings of a general lack of correlation between personal and home micro-environmental endotoxin are consistent with the findings of Rabinovitch et al.. In a panel of school children with asthma, they found geometric mean personal endotoxin was higher than indoor or outdoor school endotoxin levels, and personal endotoxin was not correlated with these stationary site measurements.The present results show a positive association between personal endotoxin and the number of dogs and cats owned, as expected, and this substantiates the utility of the personal exposure measurements. This finding is consistent with a sub-study of 10 children by Rabinovitch et al. who found personal endotoxin exposures were significantly higher in 3 households with dogs and one with cats compared with 6 households with no furry pets. We found the association of personal endotoxin was strongest among subjects with dogs that were only occasionally indoors. This could be attributed to entrainment of debris from the outdoor environment into the indoor environment, including fecal matter. However, we found no association between indoor endotoxin and dog or cat ownership. This may be due to either the smaller sample size or that personal exposure is more dynamic as would be expected from the generation of personal dust clouds.

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Even stratification into more sensitive subgroups did not yield any significant findings

Posted on October 11, 2023 by hemp2022

Further evidence of plausibility comes from the finding that PM associated adverse health effects cover a continuous spectrum of severity . In addition to increased mortality, this spectrum includes increased hospitalizations for cardiovascular and respiratory diseases , emergency department and other health care visits for asthma and other respiratory symptoms , prevalence of atherosclerosis , decreased lung function and lung function growth , and increased respiratory infections and respiratory symptoms .In addition to cross-sectional and prospective cohort studies, panel studies have become an important tool for assessing the effects of particulate pollution on respiratory and other health outcomes. Such studies use repeated measurements of the outcome of interest in a fairly small group of subjects and correlate them with daily changes in ambient concentrations of PM and other air pollutants, which are generally obtained from central monitoring sites. A significant association between particulate pollution and declines in PEFRs as well as increased prevalence of cough and lower respiratory symptoms has been reported in some panels of unselected children but not in others . In other studies, only children with asthma or asthmatic symptoms appeared to be susceptible to the effects of particulate air pollution . Similarly, in panels of unselected adults, associations of PM and other air pollutants with increases in the prevalence of decrements in PEFR greater than 20 or in respiratory symptoms were only observed in those with chronic respiratory symptoms or increased airway lability but not in those without . Such findings suggest that patients with obstructive airway disease are more susceptible to the adverse effects of particulate air pollution. Therefore,vertical farming units most panel studies have focused on children and adults with asthma or, more rarely, COPD. Significant negative associations between daily fluctuations in PM10 and PEF deviation or prevalence of PEF decrements greater than 10 and 20% have been reported in asthmatic children . An association of borderline significance was also noted in one panel of patients with COPD .

These are not entirely consistent findings . Notably, no effect of PM10 on PEFR were observed in the Pollution Effects on Asthmatic Children in Europe study, one of the largest panel studies on air pollution and respiratory health in children with chronic respiratory symptoms, involving more than 2000 children in 14 European centers .The association between exposure to PM10 and other lung function measures, such as FEV1 or FVC, has been investigated more rarely. Significant negative associations between residential outdoor and, to a lesser extent, central site PM10 values and FEV1 were observed in children with asthma from southern California . In a panel of 86 children with asthma from Detroit, PM10 and 8-h peak O3 levels with a 2-d lag showed a significant negative correlation with diurnal variability in FEV1 and lowest daily FEV1 value . However, others were unable to detect an effect of PM10 on FEV1 or FVC . In numerous panel studies of children and adults with asthma, a significant association has been detected between elevations in PM10 concentrations and increased incidence and prevalence of cough, phlegm, specific respiratory symptoms, or symptom scores . Similar associations have been reported in patients with COPD . Again, there have been studies that have not confirmed these findings, including the large PEACE study . Some panel studies with asthmatic children and adults have indicated that the prevalence of asthma medication use rises during, or shortly after, periods of elevated PM pollution . Associations have been reported between both bronchodilator and maintenance medication use and various PM size fractions, including PM10 and PM2.5 as well as UFPs. However, others failed to observe a significant effect of PM on the prevalence of asthma medication intake or the daily dose . Several studies have analyzed potential interactions between the effects of anti-inflammatory medication use and exposure to ambient PM on asthma symptoms and lung function .

In some investigations, associations between PM and increased symptoms and/or decreased lung function were only noted, or were stronger, in those subjects who were taking anti-inflammatory medication . This was even reported from panels whose prevalence of asthma medication use increased in association with elevated particulate pollution . Note that this increased overall medication use did not necessarily affect the associations of PM with lung function in the same way it influenced the association with symptoms . Others were unable to detect a significant interaction between the effects of anti-inflammatory medication use at baseline and PM10 exposure on asthma symptoms or lung function . Finally, there have also been studies in which particulate air pollution significantly affected lung function, exhaled NO , or symptoms to a much greater extent, or exclusively in children who did not take inhaled corticosteroids. Some of these discrepancies may have resulted from the fact that some studies assessed medication use only at baseline, whereas others assessed medication use during the entire follow-up period. Additionally, the effects of particulate pollution on lung function and symptoms were observed at different lag and averaging times in the various studies. The averaging time for particulate concentrations, symptom severity of the subjects, and medication use were all found to have a major impact on the association between PM pollution and increased symptom scores in a study of 25 children and adolescents with asthma in southern California . The largest effect of 24-h mean PM10 concentrations was noted in less symptomatic children who did not take anti-inflammatory medications, whereas more symptomatic asthmatics showed the greatest increase in symptoms in association with short-term PM10 excursion . No association between PM10 at any averaging or lag time could be detected in subjects who took anti-inflammatory medications, whereas non-medicated subjects exhibited large and significant increases in symptom scores in association with same day 8-h maximum and 24-h mean PM10 levels as well as with their 5-d moving averages. Overall, the available data suggest that anti-inflammatory medication and possibly bronchodilator use provide some protection from the effects of particulate pollution on lung function and symptoms in patients with asthma.

Protection may be incomplete if the type or dose of medication is inadequate. In some patient groups, however, medication use appears to be a marker of asthma severity, which confounds the protective effects of anti-inflammatory therapy. Interactions have been observed not only with medication use but also with respiratory infections. In a panel of 86 children with asthma living in Detroit, both PM2.5 and PM10 were significantly associated with decreased lung function in children with upper respiratory infections with a 3- to 5-d lag, whereas PM2.5 did not show significant effects in the absence of upper respiratory infections . Others did not detect a significant interaction between the effects of respiratory infections and concentrations of particulate air pollution on percent predicted FEV1 . When symptom severity was the outcome of interest, however, the same investigators found significantly stronger associations with various averaging times of PM10, O3 , and NO2 during respiratory infections, with some of the ORs increasing up to fivefold .Numerous panel and some cross-sectional population-based studies have investigated the association of PM10 and PM2.5 with time- and frequency-domain parameters of heart rate variability . In panel studies, small, but significant, decreases in time domains, such as the standard deviation of all normal-to normal intervals and the square root of the mean of the sum of the squares of differences between adjacent NN intervals were observed in association with daily fluctuations in centrally monitored PM2.5 and PM10 concentrations as well as in association with personal exposure to UFPs . Frequency domains of HRV,weed drying room such as high- and low-frequency power, also showed small but significant inverse associations with daily changes in outdoor and indoor PM2.5 concentrations or the time-weighted total exposure derived from them . They also decreased significantly in association with fluctuation in personal exposure to sub-micrometer particles . The inability to detect significant effects of PM2.5 and PM10 on HRV in some other panel studies likely results from the small sample sizes, low absolute pollution levels in both of the locations, low variability of PM2.5 measurements for most subjects, and, possibly, differences in the composition of particles from these cities compared with other metropolitan areas. Most of these panel studies were conducted in elderly subjects, and there are indications that the elderly are more susceptible to the effects of particulate pollution on HRV than younger adults . Susceptibility appears to be further enhanced in subjects with underlying cardiovascular disease and hypertension , although others did not observe a significant effect modification by CVD . However, some effects on HRV have also been reported in young subjects in association with personal PM2.5 and UFP exposure , with the effects of UFPs being smaller in young subjects than in older subjects studied simultaneously . Additionally, brief occupational and environmental exposures to PM2.5 were significantly associated with decreased SDNN in relatively young cohorts of boilermakers . In striking contrast to the fairly consistent finding of decreased HRV, in nine North Carolina State Highway Patrol troopers, PM2.5 exposure inside their vehicles was associated with increased HRV and other changes suggestive of increased vagal tone . Principal factor analysis of components of PM2.5 and associated pollutants indicated that these changes were associated most strongly with PM resulting from brake wear and engine emissions .

This type of PM may exert different effects than ambient particles from other sources. The results of controlled exposure studies are also not entirely consistent with these findings . Note that particle concentrators used to generate CAPS concentrate fine particles but not UFPs. This could account for some of the differences between the results of controlled exposure studies with CAPS compared with those of panel studies because UFPs were shown to exert significant effects on HRV . Overall, however, there is rather consistent evidence that exposure to PM results in changes in cardiac autonomic control, and the decreases in SDNN in r-MSSD suggest reduced parasympathetic tone. Exposure to particulate air pollution is also associated with a decrease in heart rate , which is consistent with an increase in sympathetic tone; however, an association has not been evident in all studies .Specific rotation factor analysis of the elemental composition of fine and course PM measured in six US cities indicated that PM2.5 from mobile sources showed the strongest association with overall daily mortality, followed by particles from coal combustion sources . Fine particles from crustal sources were not associated with mortality. Interestingly, a 10-µg/m3 increase in particles from mobile sources was associated with a 2% increase in deaths from ischemic heart disease, but this was not statistically significant. An adverse effect of traffic-related particles on respiratory deaths was not evident. Conversely, deaths from COPD and pneumonia increased with increased exposure to particles from coal combustion sources, whereas this factor did not affect deaths from ischemic heart disease. Similarly, analysis of data from 14 US cities regarding PM10 emissions by source category indicated that hospital admissions for CVD were most strongly correlated with increasing percentage of PM10 from highway vehicles and highway diesels . A correlation between percentage of PM10 from highway vehicles/ diesels and hospitalization for COPD was not observed for the entire data set but became significant after exclusion of two cities . These findings are consistent with reports of increased mortality and morbidity in association with indicators of traffic and traffic-related air pollution, such as black smoke and NO2 . Additionally, in several studies, , including some analyses of the effects of air pollution on respiratory health , some investigators found black smoke to be more strongly associated with adverse health effects compared with PM10 or PM2.5 . EC and organic carbon are also likely to be derived largely from traffic emissions. In Hispanic children living in an area of Los Angeles with high traffic density, an asthma symptom score was more strongly associated with EC and OC than with PM10 . In two-pollutant models that included EC and OC along with PM10, the OR for PM10 was reduced to 1.0, whereas the ORs of EC and OC remained unchanged. The composition of PM does not vary only by emission source; even ambient particles used for CAPS studies show considerable day to-day variation in their OC, EC, and elemental composition .

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Sea mammals are predators at the top of their food chains and contain very high levels of OCs

Posted on October 10, 2023 by hemp2022

Total, dimethyl, and diethyl DAP in urine were all significantly associated with an increased number of abnormal reflexes and the proportion of neonates with more than three abnormal reflexes . Interestingly, the association differed depending on the age at which the Brazelton Neonatal Behavioral Assessment Scale was administered. The association was negative in neonates examined after age 3 d but was unexpectedly positive in infants assessed within the first 3 d of life . An ecological study of 4- to 5-yr-old Yaqui children in Mexico demonstrated decreases in stamina, hand–eye coordination, and recall and an almost complete inability to draw a person in children living in an agricultural valley who were exposed to multiple pesticides compared to children from families living in the foothills who were employed in ranching . Notably, the two groups shared genetic, cultural, and social traits and differed mostly in type of parental employment and the use of pesticides and chemical fertilizers. Several other cohorts have been established for the investigation of the effects of in utero OP pesticide exposure on pregnancy and neurodevelopmental outcomes. Only pregnancy outcomes have been reported for these cohorts as well as for women of the CHAMACOS project. In the CHAMACOS cohort, DAP metabolites were associated with a significant increase in head circumference and a marginally significant increase in birth length . Only dimethyl phosphate, and not DEP, metabolites and cord cholinesterase activity were significantly associated with decreased length of gestational duration. In marked contrast, in a cohort of African-American and Dominican women from New York, cord blood concentrations of chlorpyrifos were a significant independent predictor of decreased birth weight and birth length . Ethnic-specific regressions indicated that the effect on birth weight was statistically significant only among African-American women, whereas the effect on birth length was significant only in Dominican women. An extension of this study confirmed the significant association between cord plasma chlorpyrifos and diazinon levels and decreased birth weight and length in a somewhat larger cohort,vertical growing systems but it was unable to detect an association with insecticide concentrations in maternal personal air during pregnancy.

Notably, although the associations between cord plasma concentrations of chlorpyrifos and diazinon were highly significant in children born before the US EPA started to phase out residential use of these pesticides, they were no longer detected in children born after. However, only cord plasma chlorpyrifos, but not diazinon, levels were significantly decreased in the relevant period. In a different cohort of pregnant women in New York, no association was detected between self-reported pesticide use during pregnancy, urinary levels of TCPy, or pyrethroid metabolites obtained during the third trimester and birth weight, length, head circumference, or gestational age . However, when maternal activity of the phase-II detoxifying enzyme paraoxonase 1 activity was accounted for, maternal urinary chlorpyrifos metabolite levels were associated with a small, but significant, decrease in head circumference. Most of the enzymes involved in the metabolism, activation, and detoxification of OP pesticides and other chemicals discussed here exhibit polymorphisms that greatly influence enzyme activity. This study represents one of the rare examples where at least one of these polymorphisms was accounted for. Notably, urinary levels of pesticide metabolites are highly variable, and measurements obtained at three different time-points show significant within-person variability . Therefore, one or two spot-urine samples are unlikely to provide a reliable measure of pesticide exposure throughout pregnancy. This may partially explain the inconsistent findings regarding birth outcomes in the aforementioned studies. Whether cord plasma or meconium concentrations constitute a more reliable measure remains to be established.Chronic exposure of rats to the pesticide rotenone has been found to constitute an animal model of Parkinson’s disease that reproduces the typical biochemical, molecular, anatomical, and behavioral findings in Parkinson’s disease . These include binding to complex I in the brain, selective nigrostriatal dopaminergic degeneration with relative sparing of the dopaminergic fibers in medial aspects of striatum, cytoplasmic inclusions containing ubiquitin and α-synuclein resembling the Lewy bodies associated with Parkinson’s disease, and hypokinesia and rigidity.

Notably, rotenone is a “natural” plant-derived compound that even organic farmers use on vegetable crops. Several epidemiological studies have suggested an association between agricultural work, which usually includes pesticide exposure, or pesticide exposure per se and idiopathic Parkinson’s disease , although others have found only suggestive evidence for such an association or have found no association . There is increasing evidence that occupational exposure to certain pesticides increases the risk of several cancers, including cancers of the brain and lungs , acute myeloid leukemia , and possibly multiple myeloma . Children may be particularly sensitive to the carcinogenic effects of pesticides, as suggested by numerous reports of associations between residential pesticide exposure and childhood cancers—particularly brain cancer and leukemia but also Wilm’s tumor, Ewing’s sarcoma, and germ cell tumors . Because cholinergic nerves in the vagi provide the major neural control of airway tone and reactivity, it seems plausible that OPs could induce airway hyperreactivity and asthma . Seven days after a single subcutaneous injection of 70 mg/kg of chlorpyrifos, vagally induced bronchoconstriction was found to be potentiated in guinea pigs in the absence of AChE inhibition . This effect was accompanied by decreased M2 muscarinic receptor function, whereas M3 receptor function was not affected. Similar results were obtained 24 h after administration of 1 or 10 mg/kg of parathion and 0.75 or 75 mg/kg of diazinon, although only the higher doses inhibited AChE . Intraperitoneal administration of parathion to guinea pigs increased lung resistance and mucus secretion and induced pulmonary edema . These broncho-obstructive effects were demonstrated to depend on the biotransformation of parathion by P450 enzymes. Even doses that did not increase lung resistance were able to induce airway hyper responsiveness not only to ACh but also to histamine. The latter was prevented by atropine, suggesting the involvement of a cholinergic mechanism. In the Agricultural Health Study, data collected on more than 20,000 farmers indicated that use of the OPs malathion and chlorpyrifos dose-dependently increased the risk of wheeze, and parathion also carried an elevated OR . It remains to be established whether OP pesticides at environmental exposure levels increase the risk of asthma and asthma-like symptoms.

OCs comprise a diverse group of synthetic chemicals that include not only pesticides but polychlorinated biphenyls , polybrominated biphenyls, polychlorinated dibenzofurans , and polychlorinated dibenzodioxins . OC pesticides include 1,1,1-trichloro- 2,2-bisethane ; lindane and other hexachlorocyclohexanes; cyclodienes such as dieldrin, chlordane, and heptachlor; and hexachlorobenzene. Many OCs—particularly the more heavily chlorinated ones—resist biotic and abiotic degradation and are lipophilic; therefore, they not only bio-accumulate in all parts of the environment,curing marijuana but are bio-concentrated from one trophic level to the next. PCDDs and PCDFs are tricyclic aromatic compounds. Because they can be substituted with between one and eight chlorine atoms, there are potentially 75 different PCDD and 135 PCDF congeners . However, the actual number present in biotic samples is much lower, and mainly 2,3,7,8-substituted congeners are detected. The most toxic congener is 2,3,7,8-tetrachlorodibenzo-p-dioxin , often referred to simply as “dioxin,” whereas the PCDDs are called dioxins. There are 209 possible PCB congeners, which differ in the degree of chlorination and the position of the chlorine atom; however, depending on the species and its trophic level, only between 50 and 150 congeners are detectable in biotic samples . Whereas PCDDs and PCDFs have rigid planar structures, the two rings of PCB molecules are joined by a single carbon–carbon bond, thus allowing axial rotation of the benzene rings. This freedom is restricted by the number and positions of the chlorine substituents and decreases from nonortho via mono-ortho to di-, tri-, and tetraortho PCBs. Planar PCBs exhibit the greatest resemblance to the dioxins. Whereas PCBs and polybrominated biphenyls were purposely produced for use as dielectric fluid in transformers and capacitors, hydraulic fluid, plasticizers, and fire retardants, PCDD/Fs arise as byproducts of thermal and industrial processes, particularly via incineration of municipal and hazardous waste. PCBs were produced in the United States from the 1920s until they were banned in 1977, with peak production occurring during the 1960s and 1970s. Historical global production of PCBs is conservatively estimated at 1.3 million tons, which were used almost exclusively in the Northern hemisphere . Emissions of PCBs were estimated to be in the range of 440 and 92,000 tons , and other data strongly have suggested that actual emissions were closer to the upper estimate . The environmental residence times of two of the major PCB congeners, PCBs 153 and 180, were recently estimated to be 110 and 70 yr, respectively ,suggesting that although the production of PCBs was halted approx 30 yr ago, exposure will continue for decades, if not centuries.Because persistent OCs are lipophilic, resist metabolism and bio-degradation, and bio-accumulate to similar extents in various biota, humans are simultaneously exposed to complex mixtures of these compounds. However, the precise nature of the mixture depends on various factors such as solubility, volatility, and rates of degradation as well as dietary and other lifestyle factors and geographic location. For the purposes of risk assessment and regulatory action, the concept of toxic equivalency factors has been developed . It is based on evidence that PCDDs, PCDFs, and certain PCBs exert their toxicity via binding to the aryl hydrocarbon receptor and subsequent induction of gene expression, particularly of various cytochrome P450 isozymes. The TEF concept assumes that the combined effects of these OCs can be predicted by a model of concentration addition. TEF values can then be used to calculate toxic equivalent concentrations by multiplying the concentrations of each PCDD, PCDF, or PCB by its TEF. Commonly, either the World Health Organization TEQs or the international TEQs developed by the NATO are used.

Inhalation of airborne OCs, stemming mostly from municipal and industrial incinerators and open burning of household trash, and dermal exposure make comparatively minor contributions to exposure. More than 90% of current exposure to background levels of PCBs and DDT and its metabolite dichlorophenyl dichloroethylene is believed to come from the dietary intake of contaminated foods—particularly dairy products, meat, and fish . Fish can contribute 75% or more of total PCDD/F and PCB TEQ ingestion in countries with high fish consumption , and in several studies, intake of fish—particularly from highly contaminated waters like the Great Lakes or the Baltic sea— has shown a significant association with serum concentrations of PCBs and their metabolites and PCDD/Fs . Notably, the traditional diet of many Arctic populations includes substantial amounts of marine foods, including sea mammals. Although OCs have been produced and used primarily in the lower and middle latitudes of the Northern hemisphere, long-range transport via the predominantly northward flow of rivers and ocean and atmospheric currents results in high exposure levels in the Arctic . Because of their lipophilicity and resistance to bio-degradation, many OCs bio-accumulate in fatty tissues and are bio-magnified in the aquatic food webs. Their consumption is associated with concentrations of PCBs and other OCs in serum, breast milk, and adipose tissue samples obtained from various Inuit populations that are up to fivefold higher than in other North American or European populations . In the United States, daily dietary intake of dioxin TEQs in the early 1990s was estimated to be 0.3 to 3.0 pg/kg body weight TEQs for an adult who weighed 65 kg . Estimates in eight European countries during the 1990s varied between 65 pg I-TEQ/d in the Netherlands and 210 pg I-TEQ/d in Spain, which is equivalent to 1 to 3 pg I-TEQ/kg body weight/d assuming a body weight of 70 kg . A more recent market basket study conducted in Finland on almost 4000 samples representing 228 food items, combined with results of a 1997 dietary survey, produced a similar estimate of 115 pg WHOTEQ/d, or 1.5 pg WHO-TEQ/kg body weight using an average weight of 76 kg . Up to threefold higher values for mean daily PCB and dioxin intake estimates have been reported for children . In most of the countries,the contributions of dioxins and dioxin-like PCBs to total TEQs were roughly equal, varying between approx 40 and 60%. Together, these data indicate that the daily intake of dioxin TEQs of many Europeans exceeded and probably still exceeds the TDI of 1 to 4 pg/kg/d recommended by the WHO .

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Formaldehyde is well-established as an irritant of the eye and upper respiratory tract

Posted on October 9, 2023 by hemp2022

A much smaller study also indicated that many VOCs are present at higher levels in homes than in offices . In the absence of exposure to environmental tobacco smoke , the geometric mean time-weighted micro-environment concentrations of many VOCs closely approximated measured personal concentrations of these compounds in subjects from Helsinki . Acceptable lifetime cancer risk benchmarks have been established for various VOCs. In a recent study that monitored VOC exposure of 25 adults in three districts in Minneapolis/St. Paul, only the 90th percentile of outdoor concentrations of benzene and carbon tetrachloride exceeded such benchmark concentrations . Conversely, even the median personal and residential indoor concentrations of benzene exceeded the benchmark, and the 90th percentile indoor and personal exposure levels were higher than the risk threshold for three of the other five VOCs for which benchmarks are available. Similarly, in the SHIELDS study of children from two inner-city schools in Minneapolis, researchers found that median indoor residential and personal exposure levels of p-dichlorobenzene and benzene were above the acceptable risk thresholds during at least one of the seasons of measurement . Other hazardous air pollutants listed in the Clean Air Act Amendment, such as styrene, benzaldehyde, phenol, 2-butoxyethanol, and hexanal,indoor cannabis grow system are mucous membrane irritants, although at far greater concentrations than are generally encountered in indoor environments. 2-Butoxyethanol and oxidation products of Dlimonene are skin-contact allergens .It was recently reported that formaldehyde at a concentration of 0.1 µg/mL increased the expression of intracellular adhesion molecule – 1 and vascular adhesion molecule-1 on human mucosal microvascular endothelial cells to an extent similar to the combination of interleukin -4 and tumor necrosis factor -α . It also promoted adhesion of eosinophils isolated from patients with allergic rhinitis to these cells.

No induction of adhesion molecules was observed with the VOCs; 1,2-, 1,3-, or 1,4- benzene; o-, m-, or p-xylene; or toluene at the same concentration. These observations might explain the finding of an increased number and proportion of eosinophils in nasal lavage fluid of healthy volunteers up to 18 h after exposure to 0.5 mg/m3 of formaldehyde for 2 h . In Swedish school personnel, formaldehyde concentrations were significantly associated with decreased nasal patency and increased levels of the inflammatory markers eosinophil cationic protein and lysozyme, but not myeloperoxidase, in nasal lavage . There are increasing indications that formaldehyde not only affects the upper respiratory tract but that it can also enhance allergic sensitization and, through this and possibly other mechanisms, can cause lower respiratory tract symptoms, including asthma. Formaldehyde has been shown to enhance sensitization in ovalbumin -immunized guinea pigs . Although chronic inhalation of formaldehyde does not appear to induce significant inflammation in the lower respiratory tract of non-sensitized mice or guinea pigs , it has been shown to increase the number of inflammatory cells in bronchoalveolar lavage fluid of OVA-immunized mice and to potentiate allergen-induced bronchoconstriction in OVA-immunized guinea pigs . Occupational or accidental exposure to formaldehyde occasionally has been associated with the development of asthma that can persist even after further exposure to formaldehyde is avoided . In some of these cases, specific inhalation challenges identified formaldehyde resin dust, but not gaseous formaldehyde, as the cause of asthma symptoms . Whereas formaldehyde gas is largely absorbed in the upper respiratory tract, formaldehyde in particulate form could reach the lower respiratory tract, which could explain its greater ability to cause airway responses. Because products made from urea–formaldehyde resins, such as particleboard and medium-density fiberboard, are used extensively in the construction of new houses, formaldehyde resin dust may also be in residential environments. Although wood products are the sources that emit the highest amounts of formaldehyde, a wide variety of other products also contribute to indoor formaldehyde pollution .

ETS is another important source of formaldehyde. Mean or median residential indoor formaldehyde concentrations of 15 to 30 µg/m3 have been reported in several recent studies from the United States and Australia . Maxima ranged between 139 and 408 µg/m3 , indicating that some homes largely exceed current indoor guidelines . Notably, with increasing awareness of the adverse health effects of formaldehyde, the guideline values have been steadily decreasing. Currently, the lowest guideline value is the chronic inhalation reference exposure level of 3 µg/m3 set by the Office of Environmental Health Hazard Assessment of the California EPA. Chronic relevance exposure levels are concentrations or doses at or below which adverse health effects are not likely to occur. Despite the relatively low concentrations of formaldehyde in homes compared with occupational exposure levels, chronic domestic or other indoor exposure to this chemical can result in sensitization to formaldehyde itself and can enhance the incidence and severity of atopic sensitization to common allergens . Importantly, residential formaldehyde exposure has been associated with inflammation of the lower respiratory tract as well as asthma and other lower respiratory tract symptoms in children and adults. Concentrations of exhaled nitric oxide , which is believed to represent a marker of pulmonary inflammation, were found to be significantly higher in healthy children age 6 to 13 yr who were exposed to residential concentrations of formaldehyde of 50 ppb or greater compared to those exposed to levels less than 50 ppb . The technique used in this study ensured that the exhaled NO originated from the lower respiratory tract. This suggests that formaldehyde exposure may have induced an inflammatory response, even in children without signs or symptoms of upper or lower respiratory tract disease. The prevalence of asthma and chronic bronchitis was significantly greater in children, but not adults, from homes with formaldehyde concentrations greater than or equal to 60 ppb compared with those exposed to lower levels . A linear decrease in peak expiratory flow rates was observed with increasing formaldehyde exposure. A study of Swedish adults found significantly higher levels of both VOCs and formaldehyde in connection with indoor painting within the last 12 mo, and, in turn, exposure to recently painted surfaces was associated with increased symptoms related to asthma and current asthma as well as at least one asthma-related symptom in adults .In young children who were discharged from the emergency department with asthma as the primary diagnosis, there was a significant association between case status and higher residential formaldehyde exposure compared with age-matched controls .

In the same group of children, a significant correlation was also detected between total and individual domestic VOC levels and asthma; benzene, ethylbenzene, and toluene were each associated with significantly increased ORs . Note that it is difficult to determine whether wheezing illness in such young children truly constitutes asthma. Total VOCs measured in 96 Japanese homes carried significantly elevated ORs for throat and respiratory symptoms in the 317 residents of these buildings . Xylene, α-pinene, and nonanal were the three individual VOCs significantly associated with these symptoms. An association between VOC exposure and asthma has further been suggested by the finding that urinary concentrations of muconic acid and 1-hydroxypyrene were elevated in children with asthma compared with children without wheezing episodes or atopic diseases . In partial contrast, in a study of 193 children with persistent wheezing illness and 223 controls age 9 to 11 yr, no association was detected between formaldehyde or individual or total VOCs and case status . However, the frequency of nocturnal symptoms was associated with formaldehyde exposure but not with VOC concentrations. In Swedish adults, cannabis grow equipment nocturnal breathlessness was significantly associated with both the formaldehyde and the VOC concentrations in their homes . Residential formaldehyde exposure was not significantly associated with the risk of asthma or respiratory symptoms in a group of 148 Australian children age 7 to 14 yr, although the maximum recorded formaldehyde values of four 4-d samples were associated with atopic sensitization . Note that this is one of the few studies in which exposure was measured on several occasions through the year. In most studies, only single measurements of formaldehyde and/or VOCs were taken. Therefore, in our opinion, the associations with allergic sensitization or asthma observed in such studies should be interpreted with considerable caution. The limited data available indicate that there are substantial day-to-day, daytime vs nighttime, and seasonal fluctuations in VOC exposure resulting not only from changes in the environment over time but also from differences in sources and activities that result in exposure . Intra-individual variation over multiple monitoring periods was found to span two orders of magnitude for each of the 14 VOCs measured in personal air . Additionally, residential indoor VOC concentrations are consistently lower than levels measured in the personal air space of both adults and children , indicating that they do not fully reflect personal exposure. Furthermore, it is not clear whether peak exposure or chronic low-level exposure constitutes a greater risk for atopy and asthma. Concentrations of indoor VOCs and formaldehyde generally exceed outdoor concentrations by as much as an order of magnitude . This clearly shows that they are emitted from indoor sources and are not transported in from the outside. Sources, rather than types and rate of ventilation, were associated with indoor formaldehyde, VOC, CO, and NO2 levels in homes . This was at least partly confirmed by a Finnish study of VOCs that combined personal exposure assessment with measurements in residential and work environments . ETS was found to be a dominant source of personal VOC exposure. In ETS-free homes, variability in VOC exposure stemmed from compounds associated with cleaning products, followed by compounds associated with traffic emissions, long-rangetransport of pollutants, and product emissions . Together, these data suggest that source control constitutes the most effective way of reducing environmental exposure to formaldehyde and VOCs.Phthalates are dialkyl- or alkylarylesters of 1,2-benzenedicarboxylic acid.

The major representative is di phthalate , of which the worldwide annual consumption exceeds two million tons . Waste that contains DEHP is estimated to emit another 100,000 tons of DEHP annually. Total worldwide phthalate consumption is estimated at 3.25 million tons. DEHP and other phthalates are used as plasticizers in polyvinyl chloride products, which may contain up to 40% DEHP. PVC resins are used to manufacture a wide variety of items, including floor tiles, vinyl upholstery, toys, disposable medical examination and surgical gloves, medical tubing, blood storage bags, components of paper, and paperboard. Additionally, phthalates are used as fixatives, detergents, lubrication oils, and solvents as well as in cosmetics and personal care products. Because phthalates are not covalently bound to PVC-based products, they leach and vaporize from plastic over time.The main exposure route is generally assumed to be ingestion, with fatty foods, such as dairy, fish, meat, and oils containing the highest levels, whereas inhalation and dermal contact make lesser contributions . However, in the case of diethyl phthalate used in personal care products, dermal absorption can probably substantially contribute to total exposure. Recently, the detection of several phthalate metabolites was reported in human breast milk, indicating that oral exposure can begin immediately after birth . Additionally, direct intravenous exposure occurs in patients undergoing dialysis or receiving blood transfusions. Note that there is limited evidence to support the hypothesis that food constitutes the major source of phthalates . Rather, a recent study found a significant correlation between the concentrations of di-n-butyl , butyl benzyl , and DEP in inhaled air and their urinary monoester metabolites . Correlation coefficients ranged from 0.65 for BBzP to 0.42 for DEP. Substantial amounts of various phthalates were also found to be adsorbed to suspended PM and may make even greater contributions to inhalation exposure than phthalates in the vapor phase . Together, these results suggest that inhalation may represent an important exposure route for at least some phthalates. Tables 4 and 5 summarize measurements of various phthalates in air and dust of residences, schools, and day care centers. The ubiquity of phthalates and the resulting high level of contamination of laboratory equipment made it difficult to assess the extent of exposure until measurement of monoester metabolites was introduced . After oral ingestion, phthalate diesters are hydrolyzed to their respective monoesters. The relatively polar and low-molecular-weight phthalates are excreted primarily as monoesters. The monoesters of phthalates with higher molecular weights, such as DEHP, di-n-octyl phthalate, and di-isononyl phthalate, undergo rather extensive ω-1 and ω-oxidation of their aliphatic sidechains . In humans, monoesters and the oxidative metabolites are excreted primarily as glucuronides .

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Five species had a meaningful space use response to cannabis farms

Posted on October 8, 2023 by hemp2022

Private land sites may use high-powered grow lights, drying fans, and visual barrier fencing, which could create potential wildlife disturbance . Such practices are less common on public land. It is possible that as cannabis production expands, particularly in the licensed industry, these forms of indirect impact may be more typical of cannabis production overall. Indeed, indirect effects of production practices on wildlife space use and behavior is a common concern for other agricultural crops , and may also interact with direct effects on mortality . Therefore, it is critically important to study both indirect and direct effects of cannabis on wildlife communities, particularly on private lands where research is lacking. Because outdoor cannabis farming is a land use frontier and therefore often characterized by different land use practices and patterns from traditional established farming in the US, it is uncertain whether other agricultural systems provide the best models to predict wildlife responses to cannabis development. Wildlife may use, avoid, or display differential responses to cannabis development, depending on whether production more resembles small scale countryside farming , industrial agriculture , or exurban/suburban development . In the case of differential responses, it’s also unclear whether cannabis production would have widespread enough effects to trigger mesopredator release , or generate novel food sources that could be exploited by behaviorally adaptable species like omnivores and small mammals . The small-scale, private-land cannabis farms for this study included one licensed recreational production site, one medically licensed production site, and six unlicensed sites. All farms were producing cannabis for sale, though in different markets depending on their access to licensed markets. We also had cameras placed in three hemp fields next to cannabis farms. We selected these eight cannabis growing equipment farms because they: were representative of the size and style of cultivation predominant in Josephine County in the years immediately following recreational legalization in 2015 , were all established after recreational legalization except for the medical farm, did not replace other plant-based agriculture, granted us permission to set up cameras on site, and were located next to a large section of unfarmed land that could grant researchers access in order to place cameras across a gradient of distance to cannabis farms.

Our sampled farms were small , had conducted some form of clearing for production space, and three had constructed some form of fence or barrier around their crop. Nonetheless, specific land use practices and production philosophies differed between farms . We cannot disclose farm locations, as per our research agreement for access. Monitored farms were clustered within each watershed: one farm in Slate Creek, five in Lower Deer Creek, and two in Lower East Fork Illinois River; however, most farms were also located near other nearby cannabis farms that were not directly monitored in this study. We placed unbaited motion sensitive cameras on cannabis farms as well as in random locations up to 1.5 km from the monitored farms. This is an expansion on previous camera research that only assessed on-site wildlife at these same farms . We placed cameras approximately 0.5 m off the ground to capture animals squirrel-sized and larger. We set cameras to take bursts of 2 photos, with a quiet period of 15 seconds. To guide the placement of cameras, we overlaid the area surrounding each cannabis farm cluster with a 50 x 50 m grid and then selected a random sample of at least one quarter of grid cells . We selected a 50 x 50 m grid size because we wanted to be able to detect fine scale space use responses of wildlife. The random sample was stratified by vegetation openness and distance to cannabis farm in all watersheds, and additionally by distance to clearcut in the Slate Creek watershed, such that cameras were placed in proportion to the landscape attributes and a distance gradient was achieved. When a selected site was inaccessible, we selected a new one that also met the same stratification criteria. We rotated 15-20 cameras through the sampled grid cells, ensuring each camera was deployed for at least one round of two week duration. Because of rotations and field constraints, all cannabis sites were not monitored at the same time or for the same length of time . Altogether, we monitored a total of 149 camera stations for a combined 4,664 trap nights. We then used a team of researchers trained to identify species found in the study area to sort photos by hand, grouping by species. We calculated spatial and descriptive covariates for each site to use in wildlife occupancy and detection models . First, we calculated spatial distance covariates. Our main covariate of interest was distance to cannabis farms.

To calculate distance to cannabis, we combined the location data for participating farms in our study with mapped data on Josephine County cannabis farms from 2016 aerial imagery . Then we calculated the minimum distance from each camera to its nearest farm using the package sf in R. We transformed distance to cannabis using a square root to help fit potential thresholds in wildlife responses. Next, we again used the sf package, this time to calculate the distance from each camera to the nearest major paved roadway, which was primarily highway 99 for most sites. For our two raster-based covariates, we used the raster , and exactextractr packages in R. We calculated the proportion of forested land cover within a 50 m buffer around each camera, and extracted the elevation in meters at each camera site. We also included some non-spatial covariates. We included a covariate for Julian date of each interval, as well as Julian date squared, to capture seasonal peaks. We then included an estimated distance at which a camera could still detect an animal , which was measured at camera setup. We also generated activity indices for dogs and humans by calculating the number of observations of humans or dogs, respectively, at each camera within the last three days, divided by the number of days the camera was active. This produced an activity rate where the beginnings or ends of placement rounds were on the same relative scale as all other days. All continuous variables were scaled so that they centered on 0 with a standard deviation of 1 and checked for correlations in R. Finally, we used additional categorical covariates to account for potential effects of geographic region and camera type. We assigned each camera a binary region variable based on which USGS Unit 12 watershed it was located in, such that Region1 represents Lower Deer Creek, Region2 for Lower East Fork Illinois River, and Region3 for Slate Creek. We created a binary variable for camera type. We gave a 0 to camera models that generally performed well in our study system and a 1 to camera models that generally seemed to perform worse or were older models .To assess the local space use response of wildlife to cannabis production, we used single-season, hierarchical single and multi-species occupancy models. Our approach is a departure from the typical use of these models to estimate occupancy in that we knowingly violated multiple assumptions of occupancy models: first, because cameras were spaced relatively close together compared to the home range of species included in the study, we have likely violated the assumption of independent cameras; second, as a result of the aforementioned spacing as well as sampling across two years , we likely violated the model’s assumption of geographic and demographic closure . We have done our best to account for these violations in our use of regional fixed effects, as well as our narrow interval of replication . However, given our interest was in space use associations and not estimates of occupancy, we believe the violations are a minimal issue. This use of occupancy models is not particularly unusual, as the use of occupancy modeling to assess space use is becoming more common in wildlife response studies, and even traditional uses of occupancy modeling are influenced by wildlife space use .

With the closure assumption violated, the occupancy probability estimate represents the likelihood that the animal occupied the site at any point during the study period, while the detection probability represents a combination of the probability that the species is detected and the intensity of use of the site within its larger range . This interpretation is common in camera trapping studies , but we proceed while being careful to acknowledge where appropriate that any covariate’s influence on detection probability is a combination of its effect on detection and the intensity with which an animal uses a given space. In addition, we have taken care to include variables in the detection process to account for what we anticipate to be the largest sources of variation in detectability, so that the other variables should primarily reflect space use intensity. We therefore interpret occupancy for the models as space use rather than true occupancy . We operationalize detection as a combination of intensity of use, and camera detectability or error . To examine animals’ space use in relation to distance from cannabis grow table farms, we first conducted single species occupancy analyses on nine wild and one domestic species . We summarized species observations on and surrounding cannabis farms and created detection histories using the package CamtrapR in program R using Rstudio . We used a 24-hr time interval because our focus was on estimating space use associations instead of occupancy , and a short interval reduced the likelihood of the same individual animal being detected on neighboring cameras . We modeled the space use probabilities of the most commonly detected species or those of particular ecological interest, including: black-tailed deer , black bear , bobcat , coyote , gray fox , black-tailed jackrabbit , striped skunk , California ground squirrel , tree squirrels , and domestic dog using the NIMBLE and nimble Ecology packages in Program R . We selected these species because they had sufficient detections to model , and because they covered a range of functional groups, including predators and mesopredators , omnivores , large and small prey , and a domestic predator . We included dogs as an added check on our modeling approach, as their general distributions and associations are already well known in the study system, unlike wildlife species. We modeled the observed data as a binary variable where 1 was an observation for a given species at camera station s, and 0 was a non-detection. We modeled the observed data for each species as a product of both true occurrence of a given species at a site and our probability of actually detecting it , which is also influenced by intensity of use at a given site. The model assumes that true occupancy is an outcome of a Bernoulli-distributed random variable, denoted zs~ Bern, where is is the probability that a given species used site s on any day during the survey period. We assumed that occurrence and detection probabilities varied by species, and that cannabis might influence both in different ways. For occupancy, we expected that increasing distance from cannabis farms would increase animal space use for all species except domestic dogs, and ground squirrels. We also expected that elevation and forested land cover would influence space use based on their importance in other wildlife studies . We expected distance to highways to negatively affect space use, and to function as a proxy for other non-cannabis forms of human land use in our study system. While we initially wished to include distance from clear cuts as the other major source of human disturbance in the study system, it was highly correlated with distance to highways, so we did not include it in our models. Finally, we accounted for potential regional differences in the three watersheds by including a fixed effect of region. We parameterized regional fixed effects using region-specific intercepts as described in the following equations. For the single species occupancy models, occupancy and detection varied by species . Recall that for our models, we are interpreting occupancy as space use, and detection as a combination of detectability and space use intensity .

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Our results indicate a large overlap of cannabis farms with areas of high projected fisher occupancy

Posted on October 7, 2023 by hemp2022

See the supplement for a more local comparison in which we calculated the proximity and overlap metrics for all parcels within a buffer around each cannabis site. For buffer size we used the average home range of fishers from southern Oregon. Outdoor cannabis production across Josephine County in 2016 was generally small-scale but also pervasive, and suggested that recreational legalization greatly expanded the industry locally. We mapped nearly 4,000 individual gardens and greenhouses on 2,220 different farms, all identified as highly likely to be cannabis . Most sites were new since legalization . Most production was in outdoor gardens , but a greater proportion of greenhouses were new . Farms contained an average of 1.76 individual sites, with a maximum of 14. The average size of individual sites and farms was small but highly variable in terms of cultivated area and number of plants . The average parcel size for farms was 0.098 km2 . 99.6% of detected farms were on private land parcels. Out of all private land parcels in the county, 5.7% contained a farm identified as highly likely to be cannabis. Cannabis sites were clustered at multiple spatial scales. The Ripley’s K analysis indicated that cannabis sites were clustered at all observed spatial scales . At the county level, the Getis-Ord Hotspot maps identified two regional hotspots near Williams in the SouthEast, and in the Illinois Valley in the South-West . The sub-watershed analysis indicated that even within these larger regional hotspots, there were pockets of more and less intensive production . Both the county and sub-watershed hotspots seem to follow primary roads or river networks.Overall, cannabis was produced on more undeveloped and forested parcels compared to all available private lands as a whole . The most common land cover for individual outdoor gardens was shrubland , followed by cultivated , and forest . Greenhouse cannabis production occurred in areas already cultivated with other crops , followed by shrubland , and forest . At the farm scale, however,hydro tray where outdoor and greenhouse production was combined, forest was the most common land cover type .

The predominance of cannabis in forest and undeveloped land covers was also supported by the Gradient Nearest Neighbor data on forest structure. Although the GNN dataset uses a broader categorization for forest, it also indicated that cannabis was disproportionately grown in forested areas . Nevertheless, the forest structure of farms was similar to that on all available private parcels . Cannabis farms occurred in areas with intermediate carnivore richness, similar to all available private parcels . However, at the individual species level, cannabis farms overlapped with higher projected fisher and ring tail occupancy, and lower gray fox occupancy . These differences were consistent across land cover, forest structure, and zoning. However, median fisher occupancy values were larger on high elevation parcels, and a greater proportion of cannabis farms were at higher elevations compared with private parcels. There was no difference in richness between existing or new cannabis farms, and no difference at the species level except for gray fox, which had a slightly higher median occupancy on existing farms compared with new farms .Cannabis was located slightly closer to rivers compared with all available private parcels, though the interquartile range intervals overlap . There were also a higher proportion of cannabis farms located within 15 m of a river or stream, compared to private parcels . However, the proximity of farms to threatened fish species was mixed. For example, although there was a large variation in distances and overlap of IQR intervals, on average cannabis was nearly 1.5 times closer to coho salmon habitat than all private parcels, yet more than 5 times farther from spring chinook habitat. The variation in proximity to fish habitat may be in part due to the proximity of cannabis to smaller streams by order . This study is one of the first landscape-scale assessments of small-scale outdoor cannabis farming and its potential broad-scale ecological effects in a rural biodiversity hotspot. Our results suggest two main conclusions. First, private land cannabis farming in Josephine County, Oregon in 2016 was common and spatially clustered, expanded post-recreational legalization , and yet only covered a small portion of the total land area.

This supports our expectation that cannabis farming in Josephine County would exhibit characteristics typical of the legacy development pathway, but that these farms would largely be new post legalization. Second, our spatial proximity results highlighted areas of overlap or proximity of cannabis farms and sensitive habitats and species. Compared to the surrounding context of all available private land parcels, cannabis was more frequently located in forested areas and undeveloped land, closer to rivers/streams and coho salmon habitat, and in areas of high value as fisher habitat. These results provided mixed support for our expectation that cannabis production would be in areas that increase its potential ecological impact. Recent research on public land production in the broader region highlights similarities and differences between public and private land production. For example, both seem to be located relatively close to rivers and streams, with ~50% canopy cover, and in relatively young stands . However, while we may presume that all production on public lands represents new clearing for production, our results indicate that 32% of farms are on already developed and unforested parcels. Additionally, public lands provide critical refuges for many of the region’s carnivores, which may help explain why public land production appears to overlap more with carnivore habitat than our results for private land production . Perhaps most importantly at a landscape scale, farm size and total extent appear to be much smaller for legacy pathway private land cannabis mapped in this study compared to estimates of public land production practices . Despite the differences between public and private land cannabis production, private land cannabis farming still has characteristics that warrant continued research and planning. Our results suggest that legacy pathway cannabis farming could be compatible and comparable with existing rural land use in Josephine County. In order to ensure this continues to be the case, however, further attention should be given to conservation outreach, policies to support small scale farming, and attention to land use practices on farms, particularly those that may affect carnivores and coho salmon. As the industry continues to expand, policymakers and conservationists need to clarify landscape level strategies to ensure a sustainable future.

Care should be taken when interpreting these results, since cannabis agriculture takes many forms and often exhibits regional differences in production practices that may influence its ecological impact . Our study, by nature of our mapping approach, evaluated outdoor production on private lands. We were unable to quantify whether the farms we mapped were illegal or licensed medically or recreationally, nor how many farms we may have missed by farmers effectively concealing their crop. Given our mapped sites included 2,227 farms in 2016 compared to the 43 recreationally licensed locations in 2016 , it is likely that most of the farms we georeferenced were not licensed. If this is the case,planting table the lack of effort to conceal crops is notable. We suspect because cannabis was pervasive , that enforcement would not have been feasible . Therefore, we were confident that our study accurately quantified the distribution of private-land cannabis production because of the visibility of both licensed and unlicensed farms from aerial imagery. Further, our data likely does not capture all of the cannabis being grown in Josephine County as we were unable to quantify concealed farms on public land or indoor cannabis production. Instead, our study offers critical insights into the ecological consequences of the growing industry in legacy production regions. The overall cultivated area of private land cannabis agriculture at the landscape scale in Josephine County in 2016 appears to be similar to small-scale rural development already occurring regionally. For example, in a county of 4,250 km2 , the total cannabis cultivation area was only 1.34 km2 . This small size is similar to other agricultural production in the county: in 2017, Josephine County produced 2.98 km2 of grapes and 0.48 km2 of vegetables . Cannabis in Josephine County was also considerably smaller in scale than other legacy cannabis-producing regions in Northern California in 2016, where averages ranged from 53-119 plants per site, compared with the median of 21 found in our study . While we do not have comparative research on the ecological effects of other agriculture in the study area, small-scale agriculture in rural areas often creates a landscape mosaic that supports species richness . The ability of small-scale cannabis farming to function like agriculture in other working lands systems, however, requires a deeper understanding of land use practices associated with cannabis production. Specifically, to be ecologically sustainable, small scale private land cannabis farms would need to create a significantly smaller ecological footprint than public land cannabis . Although the area of cultivation for cannabis in Josephine County was small, this study did not evaluate the edge effects of cannabis cultivation, nor take into account other forms of disturbance associated with the sites, such as clearing beyond the cultivated area, road construction, or water storage development. Therefore, the actual overlap and potential ecological effect from cannabis farming in the region is likely to be larger than what was documented in this study. Our understanding of these broad scale impacts would be enhanced in future studies that may be able to assess the fine scale response of wildlife on and surrounding cannabis farms.

While our study does not address direct effects of cannabis production, we did identify spatial relations of cannabis development that could pose unique risks to terrestrial and freshwater ecosystems. We found that cannabis production was clustered in its distribution, which is consistent with research from northern California . This clustering could be an ecological concern if cannabis is occurring disproportionately in sensitive ecological areas. Similarly, the proliferation of fences associated with cannabis could be a concern for habitat fragmentation as the industry expands . The overlap results indicate that cannabis may be grown disproportionately in forests and at higher elevations, which suggests cannabis could be associated with greater land clearing than other development on private parcels. However, the forests where cannabis was grown did not appear to be denser or older than comparable parcels.This overlap was greater on cannabis farms than private land generally, but could be due to a higher proportion of cannabis farms located at higher elevations . However, elevation alone doesn’t explain this overlap. Fisher occupancy was projected to be higher on cannabis farms than the areas immediately surrounding them . This suggests that even at fine scales, farms are appearing in areas of potential for high quality habitat for fisher. What this overlap may mean for fisher populations is unclear, given the lack of research on the impacts of private land cannabis production. Private land cannabis has not been documented to have the same negative effects on fishers as public land production, and in particular pesticide and toxicant use appears to be lower on private land farms, according to self-reported farmer surveys . However, anecdotal reports and local news stories raise concerns for these private land farms as well, and many grower organizations have emphasized a need for stronger environmental norms among farmers. Given the remaining uncertainty, these results emphasize the potential need for conservation attention to private land farms as well. Surprisingly, the individual species differences did not add up to differences in overall carnivore richness, which was relatively consistent across the study area. This raises the possibility that the differences in carnivore distributions might be driven by competitive interactions , though finer scale research would be needed to disentangle the drivers of these species distribution patterns in relation to cannabis production. Regarding potential interactions between cannabis production and freshwater ecosystems, the picture was also somewhat mixed. There were a number of farms within 15 m of rivers and streams, but this was not surprising given the high density of rivers and streams in the study area. On average, most farms were only slightly closer to rivers and streams than the surrounding context of all private land parcels.

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Farmers with low human agency and low access to assets struggle to survive every cold night

Posted on September 28, 2023 by hemp2022

The lack of indoor thermal comfort brings farmers to use their kitchen for warmth, and the lack of well-designed kitchens in the region creates health complications for many farmers and their families. Distributing blankets and food should not be the sole response to such conditions. Long-term solutions are needed to abolish the never-ending cycle of the harmful effects of cold temperatures in the region. The optimal solution would continue using reactive approaches, such as humanitarian aid when needed, but add to those a focus on creating robust long-term proactive approaches to improving indoor thermal comfort in the region.When talking about impacts related to low temperatures, the primary concerns are due to social vulnerability and a lack of resources. However, impacts related to drought are complex and go beyond social vulnerability. Governance, access to water, good quality of wells, and other methods of collecting water are of great importance. The information provided by different agencies can be contradicting and confusing at times. Access to certain kinds of information alone does not provide everything that leaders need to understand what is happening on the ground and everything farmers need to adequately prepare for drought. Dealing with drought-related impacts would benefit from a stronger network of information and improved methods of transmitting a concise and less confusing message to stakeholders . Both qualitative and quantitative analyses point to concerns about social capital in the region and indicate the need for a stronger understanding of the role of social networks in vulnerability. Social networks are a critical component of the social capital that protects against vulnerability,grow tray stand but vulnerability assessments often reduce social networks to an asset.

These assessments rarely study how social networks can aid members to cope with a crisis, including finding alternative livelihood strategies. Furthermore, a binary approach to social network is problematic, because while membership bolsters trust and access to resources, the distribution of such benefits are uneven across specific networks and specific positions within a network. A network does not benefit all its members equally, nor does each network benefit its members equally. These variations raise questions about how to measure network interactions in vulnerability assessments. Should social networks even be included as part of social capital? Should social networks be treated as a new component of vulnerability that connects entities forming such networks? I included social networks only as an asset in this dissertation, but the qualitative results suggest that more effort should be focused on how best to include social network structures and connectivity in spatial vulnerability assessments. Mapping social vulnerability indices allows areas of extremely high or low vulnerability to emerge. However, vulnerable populations remain unseen at certain levels of aggregation. The level of analysis optimal for decision-making likely varies according to who the information is aiding and the purpose of the analysis. Therefore, a single correct scale of analysis cannot be suggested. This brings interest to the uses of an interactive interface to study vulnerability at multiple scales rather than the typical static map for assessing vulnerability. The results of the present research suggest the value of a more detailed look into the impacts that result from weather-events of less intensity and duration. Social vulnerability might be strongly spatially associated with such impacts. Also, the reason that socioeconomic vulnerability indicators are spatially associated with some aspects of topography is unknown, and this association clearly deserves further study. The geon methodology creates homogenous areas that do not necessarily follow administrative divisions. Region officials can use these maps to address concerns at the level of phenomena and not just according to imposed administrative boundaries.

Many cases showed homogeneity in vulnerability indicators across neighboring municipality boundaries. In such cases, municipalities can work together with neighbors to address similar concerns. However, patterns linked to administrative boundaries are present in some of the geon maps. For example, physical and social capital present two neighboring geons at both extremes of the index values. When municipality boundaries are added to the map, it is revealed that the boundary separating the geons coincides with the municipality boundary. Therefore, while it is quite valuable to map vulnerability according to the boundaries of phenomena instead of administrative boundaries, in some circumstances, the boundary patterns do coincide. In su, this dissertation demonstrates how qualitative and quantitative research methods can build on each other to create a more comprehensive assessment. With the increase in the uncertainty due to weather and climate hazards, using ethnographic approaches to understand the local context is imperative. Such methodologies could act as a bridge that connects local understandings with a multitude of stakeholders and scales. Results from this dissertation have the potential to serve as scaffolding for future adaptation strategies in Puno and, eventually, in other areas less developed parts of the world where agriculture provides the main livelihood. Ethnographic components of these research provide an in-depth understanding of the location; however, they possess transferability. The results from this dissertation could be transferable to the study of social vulnerability in other high mountainous regions or rural environments.While the Japanese islands have been prone to a variety of natural disasters throughout their history, the magnitudes of some of these omnipresent threats are observed to have increased in recent years. My informants, for example, anecdotally spoke of perceived increase in the temperature throughout the years.

The relatively cool rainy season which lasted from the middle of June into July, which used to require heating equipment, turned into “wet summers.” They also talked about orange trees they planted that used to produce sour Hlavors now yielded sweeter Hlavors presumably due to the warmer climate. Relatedly, storms of many kinds are reported to have intensiHied in recent years. In the past, the term tornados were unheard of, but today they are new and frequent occurrences. Other severe storms are accompanied by larger hails than in the past. In fact, in the winter of 2014, the year this Hield work took place, the eastern Japan, including Tokyo, experienced record-breaking snowfalls. As a result, many of the informants’ green houses were destroyed. Yet the informants appeared composed and nonchalant about the effects of these changing climates on their food production. Most of them did not bring up the topic during the interviews until they were asked specifically about it. What could be some of the reasons for this? For one,garden racks wholesale the general increase in temperature and the intensity of the rain and snowfall has not significantly affected the informants’ “outdoor crops,” which are predominantly rice and wheat. The majority of other products, mainly vegetables, are produced indoor. The destruction of the green houses due to the record amount of snow was a major loss. Nonetheless, the informants seemed to have accepted the incidence as a by-gone, and showed a sense of gratitude toward the Japanese government, which helped cover about ninety percent of the loss. Such is a reminiscent of the way the people of northern Japan reacted calmly to the calamity of the tsumani in 2011 . What implications do these preliminary observations offer in terms of “cultural models” of nature that are purported to have influenced the informants’ narratives about food production? I hypothesize that the informants relied on an overarching cultural model that nature can be “humanized” to enhance human endeavors particularly in the areas of self-cultivation and associated interpersonal relationships. Using this cultural model works as a buffer against and around which to circumvent the perceived and real harms of raw, untamed nature. According to this cultural model, raw nature is un-natural. Nature is “natural” only when it is humanized to enhance human existence and activities . Since Japan is a highly industrialized society with complex economic systems, none of the informants engaged in subsistence farming. As such, their farming did not rely directly or solely on naturally given soil conditions or weather patterns. Instead, they utilized advanced in-door food productions facilities and technologies. They also took advantage of the wealth of current, and research-based farming knowledge provided by the municipal and national farmers organizations such as JA, Japan Agricultural Cooperatives. They also exchanged ideas and tips with other farmers, which they acquired through experience or the sources mentioned above. As to what makes plants and animals grow, informants shared basic knowledge which they saw as fundamental to successful farming: i.e., knowledge about optimal soil conditions , lights, winds, temperatures, timing of planning and harvesting and other maintenance activities , and ways to prevent diseases. They said that such knowledge comes from experiences, from other farmers including their parents and family members, and from the government-based, local and national farming bureaus such as JA. No one mentioned supernatural factors such as “gods” or “spirits” as factors contributing to the growth. In terms of their commercial success, informants revealed two distinctive yet complementary models. The first model may be called ‘rational and profit-oriented.’ Here the food producers worked in concert with the information provided by JA about the crops and seeds types, kinds of diseases that are prevalent and how to prevent them to maximize their productivity.

The JA’s also organized chains of marketing outlets into which the farmers could distribute their product at a timely fashion. Most of the large-scale rice, wheat, tomatoes, plums and pears farmers relied on such support system. The second model may be termed ‘non-rational and relational,’ and even ‘moral’ and ‘spiritual,’ in a sense that it seeks higher level of meaning and satisfactions from farming than merely profiting from it. Informants often used the terms kodawari and tsunagari to express this view. To kodawaru means to produce foods that bear one’s ‘signature’ heart/effort. Many of the consumers who tasted such foods become ‘repeaters,’ loyal customers who develop a special and lasting tie to the food producers. Many famers noted that they gain most satisfactions out of their job from such special relationships. In short, the first model is essential because without it, farmers cannot sustain their livelihood. The second model complements the first as it helps them to create deeper and more personalized meaning out of their work. Below are some examples of the second perspective from the semi-structured interviews and the nature walks. Michiko Sekiguchi, a sixty-four year old woman, married into a multi-generational farming family. While her husband takes charge of the rice and wheat, which supports family’s main income, she grows greenhouse tomatoes, along with a variety of other green vegetables. She says her operation is “small and not profitable,” but had continued it for the last eighteen years. Asked why, she responded, “It’s [my] kodawari.” Asked to explain what kodawari means to non-Japanese, she said, “it means to be particular [about your mission] and not to compromise .” In a practical term, “it means to…wake up at three or four in the morning every day” to take her vegetables to the local stores. “That way, people say when they eat my vegetales, oishii! . I pick them first thing in the morning and have people eat that way. I especially want young children to know how great they taste.” Another expression of Michiko’s kodawari, in addition to always hand delivering her vegetables fresh, is the farm stand she created for herself, which she named, Daichi No Megumi , which happens to be the brand name given to the rice they produce. The space is filled with wall hangings and gifts she received from her friends. Many of them contain words of appreciation for the relationships they cultivated over the years. Secondarily, she sells the vegetables she produced at low prices. She said that the room symbolizes her connection with other female farmers. It is also worth noting that this farm stand is located next to the family grave. Michiko is grateful that she and her husband inherited the land from their ancestor. She says, “I know how our ancestors were attached to this land, so I would never let it go. When I think of their feelings, I, too, cannot let go of this land.” During our ‘nature walk’ around the family grave, she said, “this [having the grave next to their farm] is a reminder that our ancestors are always watching over for us.” Shinji Amada is a thirty-two year old pig farmer who also took over the business from his father, who inherited it from his father forty years ago.

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Farmers performed religious rituals to attract rainfall to the area

Posted on September 27, 2023 by hemp2022

It is coordinated with the arrangement of doors and windows, to avoid any heat leakage. The improved kitchen, as mentioned before, is implemented to reduce health related effects. Another project in the region, using the same technology described in the K’ONICHUYAWASI project, is named Mi Abrigo . This is a national project sponsored by the Ministry of Development and Social Inclusion through their national program named the Cooperation Fund for Social Development . As a prevention effort for winter 2017, Mi Abrigo started building houses in December 2016 in three Peruvian departments: Apurimac, Cusco, and Puno. A total of 1,146 houses were modified in 33 communities from 12 districts. The program modified 400 houses in seven communities from four districts of Puno. However, the program is a national one, and the subsequent home modifications for the 2018 winter do not include Puno. The second stage of the program will modify 1,100 houses in 17 districts from four departments outside of Puno. Furthermore, the plans for the third stage that will modify houses for the 2019 winter does not include Puno either. This third stage will modify 980 homes in 14 districts of four departments outside of Puno. The problem with regulating indoor heating is not only a concern for private housing. Education and health facilities also present poor levels of indoor thermal comfort. Many people in the area express concern for the indoor thermal comfort inside hospitals. Their indoor thermal comfort is of greatest concern to the population experiencing childbirth. Education facilities also possess infrastructure and thermal insulation problems. These problems lead to an environment uncomfortable for learning, especially in the morning. Public education comprises 93% of Puno’s educational facilities, and 65% of them are in rural areas. According to regional agencies, 75% of these facilities are mainly constructed with adobe and are considered to possess environments too cold for pedagogy. About 50% have very old-style constructions. The Ministry of Education has proposed to delay the time classes start every morning to aid in dealing with indoor thermal comfort. Furthermore,plant growing stand the national government has campaigned to educate teachers on how to properly close these facilities when they leave in order to maximize the indoor thermal comfort in the mornings. So it is clearly imperative to prevent temperature-related deaths, but focusing only on heatwaves is not sufficient.

Every year, farmers in the Peruvian Altiplano suffer and die due to cold temperatures in the region. Focusing only on heatwaves due to their increasing frequency and intensity around the world is similar to stakeholders forgetting about farmers in specific locations because the world is urbanizing. And temperature-related events do not result only in deaths, but in negative impacts on livelihoods, health, and comfort. People should not have to merely survive cold temperatures, and stakeholders should pay attention to improving indoor thermal comfort. Farmers with low human agency and low access to assets struggle to survive every cold night. Distributing blankets and food should not be the central response to such impacts. Long-term solutions are needed to avoid the repeated return of the harmful effects of cold temperatures in the region. Drought conditions entail a slow onset and combine multiple factors which make its prediction difficult. Some droughts are easy to predict and can be foreseen a month in advance, while others catch decision-makers by surprise. The prediction, report, and quantification of drought-related impacts remain a significant challenge. Unlike other weather phenomena, droughts are not a single distinct event; just a lack of rain does not equate to drought conditions. During my fieldwork campaign, both austral summers reported drought conditions. However, they had different spatial coverage—as seen in Figure 12—regarding the emergencies reported. The first drought had a more widespread spatial coverage and presented a more significant challenge to both farmers and decision-makers. On the other hand, the second drought was more localized, and the difficulties experienced in many aspects of the emergency cycle were at a smaller scale than in the first drought. The prediction of the drought in Summer 2015–2016, including the report of emergencies, was confusing and inconsistent. The national weather service agency provides monthly agrometeorological reports summarizing meteorology characteristics and providing information related to precipitation’s probabilities for the next trimester. Three factors are essential to understand droughts in Puno and their impacts: the agricultural calendar starts in August, the rainy season covers from October to April, and the beginning of the austral summer presents a crucial stage for crop survival. Agrometeorological reports for the three months before the beginning of the fieldwork campaign in January 2016 aid in understanding the complexity of the drought in the region. Predictions in October for the November to January trimester had two scenarios that contradicted each other. Figure 13 presents a prediction with most of Puno experiencing normal precipitation and certain areas experiencing above normal precipitation conditions.

However, the International Research Institute for Climate and Society at Columbia University in New York had different probabilities for the region . These probabilities expressed areas with more than a 50% decrease in precipitation for Puno. Local meteorology reports for November 2015 and December 2015 presented a rainfall deficit of -17% and -19% respectively for the entire department. Moreover, most of the stations were indicating between -20% and -100% of rainfall deficit. Station analysis performed by the regional SENAMHI office in Puno presented similar percentages of rainfall deficit from the start of the rainfall season in October. However, 2015 had only one report related to drought received toward the last week of December. This emergency report mentioned the lack of rainfall in the entire area of the municipality but reported only four hectares of crops affected by the drought. Also, it could be noted that the reported impacts during both austral summers were different from the areas identified to have a higher level of drought risk. Let’s consider the difficulties of predicting the droughts, the conflicting information provided to farmers,the discrepancies in ground experiences in reports, and the farmers’ perceptions. Aside from the discrepancy of the reports predicting normal precipitation conditions versus stations reporting deficits, the region was not expecting extreme drought conditions. The title of a local news article published on December 17 stated that the “drought would be mild in the Peruvian highlands.” The article affirmed that the precipitation would be slightly less than in other years but “according to the experts it will not result disastrously for farmers in the region.” An expert working for INDECI emphasized that if “it is true, according to the forecast of the climate entity, there would not be a drought scenario, the prevention of possible flooding of the rivers should be a priority.” In the same article,plant grow table other experts mentioned the changes in precipitation of -10% to -20% for individual municipalities. Towards the end of December, the Laguna Colorada in Lampa utterly dried up. The Lagoon had been drying for three years due to high daily temperatures and lower precipitation in the area . The representative of the Lagoon area mentioned that on multiple occasions, he presented projects to the provincial government to create a passage from the nearby river into the Lagoon. The provincial authorities emphasized that in November 2015, they brought the case to the Ministry of Agriculture and were expecting a response. As the fieldwork campaign started, available information indicated that drought conditions were expected to be light, and the condition in the Lagoon resulted from a more extended timescale problem. However, the regional ministry of agriculture stated in early January that the drought conditions had affected up to 40% of the crops in the region. Furthermore, farmers pointed out that natural pastures were drying, and farming organizations were asking for oat bales for the animals. Toward the border with Bolivia, in the province of Chucuito, farmers told me stories about current drought conditions and their concerns that it was beyond “abnormal” drought.

They showed dead birds and dead livestock. An elderly farmer cried as he explained to me what was happening: “We are all sad, it makes us want to cry, in June and July there will be nothing; then, this will be dry, and there will be no food for the animals.” The display of farmers crying and showing me dead animals was repeated in various locations in the region. Farmers expressed concern with the availability of natural grassland. The grass available is not tall enough for their animals, and they recounted how it was supposed to be taller this time of the year. Many farmers were alarmed and often revisited stories from 1983. Many farmers did not mention a specific date, but those who did never mentioned anything other than the 1983 drought. Even the regional director of SENAMHI indicated the 1983 drought as a reference while talking about the drought in the area. Everyone admitted that conditions were getting drier every year. But how severe was the 1983 drought for farmers remembering its impacts more than 30 years after? Maps produced by SENAMHI show the Standardized Precipitation Index for a severe drought during the El Niño of 1982–1983 and a more localized drought during the El Niño of 1997– 1998. One of the strongest El Niño events worldwide was experienced during 1997–1998, but the extent of the drought was not severe in Puno. Furthermore, other years with El Niño conditions do not present drought conditions for the region. There is no doubt that the 1983 drought was real and caused numerous problems for the region. However, were the farmers correct in comparing the recent El Niño year with the 1983 drought conditions? During my fieldwork in mid-January 2016, the National Water Authority declared a state of emergency for Lake Titicaca for 90 days. The imminent danger of water deficit in four of the Lake sources of water prompted the decision, a decision praised by the director of the local meteorology agency. Furthermore, smaller towns in the provinces of Chucuito and Azángaro canceled activities that are usually celebrated all over the region. These cancellations, according to local officials, were due to the lack of water in their municipalities. Towards the end of January, Puno’s agricultural sector was declared an emergency zone by the regional agrarian authorities. This decision was necessary due to the loss of up to 60% of the essential crops in the region. The declaration was not only for droughts but included the out-of-season frost and hail that occurred in the region.The month of January ended with a deficit of – 45% of the total monthly accumulated rainfall for the region. Figure 18 presents the anomalies in precipitation per weather station. One can see in yellow the stations reporting from -20% to -60% in precipitation for January 2016. While many stations, in orange, presented from – 60% to -99% in precipitation. SENAMHI also provided a map with SPI to show the depth of the drought for January . Such SPI map patterns and water deficits do not completely explain the occurrence of reported emergencies, as seen in Figure 12. The second drought experienced in the region during my fieldwork campaign had a smaller spatial coverage in terms of emergencies, but below normal precipitation happened in many municipalities outside that area.The level of emergency from the farmers and local authorities was lower than the previous season. The government did not declare a state of emergency, and farmers’ still suffered losses but to a lower degree. The government created and started to work on plans for water management and improvement of water wells in the region. The emergency reports related to drought still do not possess a standardized methodology for explaining impacts experienced on the ground. Many lacks crucial information, making it difficult to use those data for comparison with other social vulnerability indicators. When talking about impacts related to low temperatures, the primary concern is social vulnerability and a lack of resources. But drought impacts are complex and go beyond social vulnerability indicators. Governance, access to water, and good quality wells and other methods of collecting water are of great importance. Furthermore, the information provided by different agencies can be contradicting and confusing at times. Access to information does not necessarily allow leaders to understand what is happening on the ground nor farmers to adequately prepare for drought.

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