Percent Agriculture Research Articles

Influence of land use and rainfall variability on nutrient concentrations in Florida Lakes

Xiong C, Hoyer MV. Influence of land use and rainfall variability on nutrient concentrations in Florida lakes. Lake Reserv Manage. 35:25–37.This research examined impacts of regional differences (total phosphorus zones [TP Zones]), land uses within watersheds (agriculture, urban, forest and wetland), and rainfall variability on nutrient concentrations (phosphorus and nitrogen) in Florida lakes (n = 87). Nutrient concentrations varied directly with TP Zones, which can be used as background nutrient concentrations within regions of Florida. After accounting for regional differences, lakes within watersheds with high percent agriculture tended to have higher nutrient concentrations, though relationships with nitrogen were strongest, suggesting different nutrient-transport mechanisms. Lakes within watersheds with high percent urban development showed no significant effect on nutrient concentrations, suggesting good nutrient management in urban areas. Lakes in watersheds dominated by forested land cover had low nitrogen concentration reflecting nutrient-buffering capabilities of forest stands. Lakes in watersheds with greater wetland coverage tended to have high nutrient concentrations, conflicting with previous studies and reflecting the complex nutrient-related processes that occur within wetlands. Cumulative rainfall deviations measured over a 20 yr period were significantly correlated (both positively and negatively) with nutrient concentrations within approximately 40% of the study lakes and the mechanisms driving these relations may overshadow impacts of land use within watersheds and changes in land use over time on lake nutrient concentrations. A thorough investigation of watershed land uses and relations between rainfall and limnological mechanisms must be considered before applying a nutrient management strategy to individual lakes.

Relative importance of landscape versus local wetland characteristics for estimating wetland denitrification potential.

Wetlands can be significant sinks for Nr, via denitrification. There is a lack of understanding about factors controlling denitrification. Research suggests that hydrology, geomorphology, and nitrogen loading are dominant controls. We compared site-scale characteristics with denitrification enzyme activity (DEA) in wetlands along gradients of drainage basin land use to explore the relative importance of landscape and site-scale factors for determining denitrification potential. DEA rates ranged between 0.01-1.69 (μg N gdw-1 hr-1), with most sites falling at the lower end. Sites with higher DEA rates had higher percentages of soil carbon and nitrogen, concentrations of soil extractable NO3 and percent loss on ignition. Sites with upstream agricultural activity had higher DEA rates than more natural sites, but there existed a wide range of DEA rates along both agricultural and urban land gradients. When multiple site and landscape-scale explanatory factors were compared to DEA rates, two site and one landscape scale characteristic (Soil NO3, Soil Percent N, and Percent Agriculture) had significant (p<0.001, cum. r2 = 0.77) correlations with DEA rates. Our results suggest that DEA is controlled mainly by local-scale site characteristics with more work needed to determine the interdependencies and relative importance among these and potentially related landscape-scale factors.

Crop spatiotemporal dominance is a better predictor of pest and predator abundance than traditional partial approaches

Landscape-scale agricultural intensification can concentrate pest resources (high host density) and impede natural enemy populations through a reduction in non-crop resources or disturbance events. Current approaches examine the impacts of crop dominance on pest pressure through a simple lens, either spatially (i.e. landscape complexity), or temporally (i.e. diversity of crop rotation schedules). However, these partial approaches are inadequate because they do not take into account the impact of multiple years of non-rotation, or the impacts of the surrounding landscape, respectively. In this study, we use a unique method that allows land use in both space and time to be quantified simultaneously with a single metric, “spatiotemporal dominance”. We examined the impact of spatiotemporal dominance of sweet corn on populations of a key insect pest, Ostrinia nubilalis, and its potential predators. Additionally, we evaluated site-specific variables such as crop rotation, percent agriculture in the landscape, cover crop use, and frequency of insecticide applications, to determine their relative importance in predicting pest pressure, alongside our metric of spatiotemporal crop dominance in the landscape. Ostrinia nubilalis adult abundance was positively associated with spatiotemporal dominance of sweet corn in the landscape (space and time) and high proportional agricultural land use (space), but was unrelated to the previous year’s crop (time). Predatory soldier beetle abundance was negatively associated with sweet corn spatiotemporal dominance (space and time), but not associated with the previous year’s crop (time) nor percent agricultural land use (space). Our contrasting results between the new spatiotemporal dominance metric and either crop rotation history or percent agricultural land use or both emphasized that the new method predicts impacts of agricultural intensification on arthropods that were not captured by traditional techniques. In general, pest populations were more abundant in areas with high host dominance, whereas certain predators were less abundant when high disturbance management practices were used (e.g. no cover crop, high insecticide use). Therefore, quantifying spatiotemporal crop dominance refines and strengthens our ability to implicate intense agricultural land use in creating high pest pressure situations through simultaneous bottom-up and top-down effects.

Canada goose gosling survival of the Atlantic Flyway Resident Population

ABSTRACTGosling losses account for the majority of summer mortality for Canada geese (Branta canadensis), but survival at this stage can be difficult to estimate because of their small size, precocial behavior, and the land cover in which they live. Previous methods of measuring gosling survival often used individual markers, which can bias estimates when not accounting for total brood loss or emigration. We estimated gosling survival of Canada geese in the Atlantic Flyway Resident Population (AFRP) in New Jersey, USA, during 2009–2010 through use of marked parents and young to incorporate total and partial brood losses. The proportion of marked parents who lost their entire brood occurring during the first 3 weeks after hatch and prior to banding was 0.316. Gosling survival that accounted for partial brood loss was 0.461 ± 0.027 (SE), and was most influenced by nest density and the percent agriculture land use within 215 m of the nest site. The gosling survival estimate incorporating total and partial brood losses during this study was 0.315 ± 0.018. Acquiring current reproductive vital rates will assist in understanding the dynamics of recruitment as a function of population size. The above information, in combination with nest survival and annual survival estimates from band recovery and recapture analyses, has been used to inform a population model for Canada geese in the AFRP. © 2018 The Wildlife Society.

The effects of climate, catchment land use and local factors on the abundance and community structure of sediment ammonia-oxidizing microorganisms in Yangtze lakes

Ammonia-oxidizing archaea (AOA) and bacteria (AOB) play important roles in regulating the nitrification process in lake ecosystems. However, the relative effects of climate, catchment land use and local conditions on the sediment ammonia-oxidizing communities in lakes remain unclear. In this study, the diversity and abundance of AOA and AOB communities were investigated in ten Yangtze lakes by polymerase chain reaction (PCR), clone library and quantitative PCR techniques. The results showed that the abundances of both AOA and AOB in bare sediments were considerably but not significantly higher than those in vegetated sediments. Interestingly, AOB communities were more sensitive to changes in local environmental factors and vegetation characteristics than were AOA communities. Amongst climate and land use variables, mean annual precipitation, percentage of agriculture and percentage of vegetation were the key determinants of AOB abundance and diversity. Additionally, total organic carbon and chlorophyll-a concentrations in lake water were significantly related to AOB abundance and diversity. The results of the ordination analysis indicated that 81.2 and 84.3% of the cumulative variance for the species composition of AOA and AOB communities could be explained by the climate, land use and local factors. The climate and local environments played important roles in shaping AOA communities, whereas catchment agriculture and water chlorophyll-a concentration were key influencing factors of AOB communities. Our findings suggest that the composition and structure of sediment ammonia-oxidizing communities in Yangtze lakes are strongly influenced by different spatial scale factors.

Annual precipitation regulates spatial and temporal drivers of lake water clarity.

Understanding how and why lakes vary and respond to different drivers through time and space is needed to understand, predict, and manage freshwater quality in an era of rapidly changing land use and climate. Water clarity regulates many characteristics of aquatic ecosystems and is responsive to watershed features, making it a sentinel of environmental change. However, whether precipitation alters the relative importance of features that influence lake water clarity or the spatial scales at which they operate is unknown. We used a data set of thousands of northern temperate lakes and asked (1) How does water clarity differ between a very wet vs. dry year? (2) Does the relative importance of different watershed features, or the spatial extent at which they are measured, vary between wet and dry years? (3)What lake and watershed characteristics regulate long-term water clarity trends? Among lakes, water clarity was reduced and less variable in the wet year than in the dry year; furthermore, water clarity was reduced much more in high-clarity lakes during the wet year than in low-clarity lakes. Climate, land use/land cover, and lake morphometry explained most variance in clarity among lakes in both years, but the spatial scales at which some features were important differed between the dry and wet years. Watershed percent agriculture was most important in the dry year, whereas riparian zone percent agriculture (around each lake and upstream features) was most important in the wet year. Between 1991 and 2012, water clarity declined in 23% of lakes and increased in only 6% of lakes. Conductance influenced the direction of temporal trend (clarity declined in lakes with low conductance), whereas the proportion of watershed wetlands, catchment-to-lake-area ratio, and lake maximum depth interacted with antecedent precipitation. Many predictors of water clarity, such as lake depth and landscape position, are features that cannot be readily managed. Given trends of increasing precipitation, eliminating riparian zone agriculture or keeping it <10% of area may be an effective option to maintain or improve water clarity.

Benthic algal community composition across a watershed: coupling processes between land and water

One of the main goals of ecology is to understand how the abiotic environment influences the biotic characteristics of the ecosystem. Various processes at multiple scales interact to affect the physical and chemical environments that are experienced by organisms, which ultimately influence community composition. We aimed to understand the processes that control benthic algae community composition within a watershed. We investigated the impact of both land cover and physiochemical variables on benthic algal community composition. We sampled benthic algae along with multiple habitat and water chemistry parameters within three microhabitats across eight sites along the mainstem of the Kiamichi River in southeastern Oklahoma. We used the benthic light availability model to assess the amount of light reaching the bottom of the stream. Additionally, we conducted a GIS analysis of the watershed to determine the land cover affecting each of these sites. Several of the in-stream site-scale variables that were measured (e.g., conductivity, pH and canopy cover) were strongly correlated with both position within the watershed and percent agriculture within the watershed. The physiochemical parameters that were correlated with watershed position and land cover were then used to understand the linkage with algae community composition. Algae genera composition was strongly correlated with both light reaching the bottom of the stream and conductivity. Our results suggest a hierarchy of factors that determine species composition and show the dependence of community composition on differing light regimes.

Early-Career Residential Migration of Agriculture and Human Environmental Sciences B.S. Graduates: Evidence from One Land-Grant University

The zip codes of agriculture (n = 346) and human environmental sciences (n = 304) bachelor’s degree graduates were examined six to seven years after graduation to describe and compare pre-college and post-college residences (rural versus metropolitan) by major and overall. A majority of agriculture graduates were from rural areas (61.6%), and a majority of human environmental sciences graduates were from metropolitan areas (55.9%). Majorities of both agriculture (54.9%) and human environmental sciences (70.1%) graduates lived in metropolitan areas post-graduation, resulting in a net loss of 100 college-educated rural youth. Among rural graduates, there was no significant difference in the percentage of agriculture (62.4%) and human environmental sciences (57.5%) graduates currently living in rural areas. Among metropolitan graduates, twice as many agriculture graduates lived in rural areas after graduation as compared to human environmental sciences graduates. Graduates from rural areas were 11 times more likely than graduates from metropolitan areas to live in rural areas after graduation. Regardless of precollege residence or major, nearly 40% of graduates lived in their home community after graduation, and 60% lived within 50 miles of their home community. Further research is needed to understand the decision-making processes and factors undergirding these residential patterns.

Examining Relationships Between Socioeconomic Factors and Landscape Metrics in the Southern Basin of the Caspian Sea

Socioeconomic forces are not only among the main drivers of landscape dynamics; they are also influenced by landscape patterns. Landscape structure and functions are closely related to natural and social factors. The objective of this study was to investigate the relationships among some human-related factors and landscape ecological metrics as landscape pattern indicators and to identify suitable metrics for modeling these relationships. To this goal, landscape ecological metrics were calculated for each of the 32 counties of Mazandaran and Guilan provinces located in the southern basin of the Caspian Sea using land use/cover maps in class level. Stream network metrics were calculated using a digital elevation model, road density metrics were calculated using map of main roads separately, and significant metrics were selected according to results of correlation tests and factor analysis. The correlations between these metrics and socioeconomic factors were tested, and their relationships were modeled with multiple linear regressions. Significant relationships were found among socioeconomic factors and landscape ecological metrics, and land use/cover data are applicable for modeling socioeconomic factors, especially demographic and employment structure factors. Among the landscape metrics applied in this study, road density, mean patch size, mean nearest neighbor distance, and percentage of a land use/cover class in landscape were important metrics for predicting socioeconomic factors. Our findings indicated that road density metric and percentages of urban class are useful for predicting urban socioeconomic factors and percentage of agriculture and forest classes in the landscape are suitable metrics for predicting rural socioeconomic factors.

Cropping Pattern and Socio-Economic Study of Ethnic People in the Hilly Areas of Bangladesh

The study was conducted at some hilly areas of Bangladesh during the period of January to May 2009 and during April to May, 2010. This was done to evaluate socio-economic condition of the ethnic people and to find out the existing cropping pattern in the hilly areas of Bangladesh. A total of 810 households from Rangamati, Khagrachari and Bandarban were selected randomly. Socio-economic profiles of the households indicated that the most household respondent belonged to thirty-forty five years age group followed by forty five- sixty years, fifteen- thirty years and sixty-seventy five years age group. This indicates that household respondents were younger (thirty-forty five years) in the study areas. It was found that, among the tribal people Marma were found highest rate of illiteracy followed by Shaontal, Tanchanga, Chakma, and Tripura. The tribal people of Tripura were not found to be below Primary level in the study area. The percentage of agriculture and service were found equal in Chakma tribal people in the study area. The Marma people were not found as a service holder because of their low education level. Cultivable land use pattern among the ethnic people revealed that out of 810 ethnic households 222 households were involved in cultivation (27.4%). It also showed that 55.4% households harvested single crop, 26.3% households harvested double crops, 10.8% households harvested triple crops in a year and only 7.5% households practiced jhum cultivation.The Agriculturists 2015; 13(1) 119-126

Catchment agriculture and local environment affecting the soil denitrification potential and nitrous oxide production of riparian zones in the Han River Basin, China

Riparian zones play an important role in reducing nitrogen (N) loading to rivers and streams primarily through soil denitrification which reduces nitrate (NO3–) to nitrous oxide (N2O) and dinitrogen (N2) gases. Although the relationships between local environments and soil denitrification are well understood, relatively little is known about the indirect effects of landscape factors (e.g., catchment agriculture) on the soil denitrification of riparian zones. In this study, we used the acetylene block technique to measure the denitrification potential and net N2O production of soils collected from 62 riparian sites in 15 subtropical rivers of varying catchment land uses. The results indicated that, among the local factors studied, the soil moisture, organic matter and NO3– concentrations were positively associated with both the denitrification potential and N2O production rate. Agricultural riparian zones had a denitrification potential (2.81±1.01ngNg−1h−1) significantly higher than forested riparian zones (0.66±0.24ngNg−1h−1). Additionally, the riparian denitrification potential increased with the percentage of agriculture in the catchments (R=0.53, P<0.05). Structural equation modeling revealed that the indirect effects of catchment agriculture on the riparian denitrification potential and N2O production rate were mediated primarily through soil NO3–. Our findings suggest that, compared to forested riparian zones, agricultural riparian zones have greater potential to remove N from polluted runoff. The conversion of original vegetation to agricultural lands in catchments may have a profound impact on the soil N cycles and NO3– removal capacity of riparian zones.

The challenge of accurately documenting bee species richness in agroecosystems: bee diversity in eastern apple orchards.

Bees are important pollinators of agricultural crops, and bee diversity has been shown to be closely associated with pollination, a valuable ecosystem service. Higher functional diversity and species richness of bees have been shown to lead to higher crop yield. Bees simultaneously represent a mega-diverse taxon that is extremely challenging to sample thoroughly and an important group to understand because of pollination services. We sampled bees visiting apple blossoms in 28 orchards over 6 years. We used species rarefaction analyses to test for the completeness of sampling and the relationship between species richness and sampling effort, orchard size, and percent agriculture in the surrounding landscape. We performed more than 190 h of sampling, collecting 11,219 specimens representing 104 species. Despite the sampling intensity, we captured <75% of expected species richness at more than half of the sites. For most of these, the variation in bee community composition between years was greater than among sites. Species richness was influenced by percent agriculture, orchard size, and sampling effort, but we found no factors explaining the difference between observed and expected species richness. Competition between honeybees and wild bees did not appear to be a factor, as we found no correlation between honeybee and wild bee abundance. Our study shows that the pollinator fauna of agroecosystems can be diverse and challenging to thoroughly sample. We demonstrate that there is high temporal variation in community composition and that sites vary widely in the sampling effort required to fully describe their diversity. In order to maximize pollination services provided by wild bee species, we must first accurately estimate species richness. For researchers interested in providing this estimate, we recommend multiyear studies and rarefaction analyses to quantify the gap between observed and expected species richness.

Assessing California's bar-built estuaries using the California Rapid Assessment Method

Bar-built estuaries are generally found at the mouths of smaller watersheds with seasonal precipitation, episodic streamflow and seasonal swell dynamics. Low streamflows and constructive wave forces form a sand bar at the mouth isolating the stream from the ocean, creating a ponded lagoon, and inundating the surrounding marsh plain. Bar-built estuaries are wide spread in California comprising over 50 percent of California's more than 500 estuaries. By connecting terrestrial, freshwater, and marine realms bar-built estuaries are complex and dynamic providing great habitat and ecosystem services. California has suffered some of the highest losses of wetland habitats, and the wetland habitats of bar-built estuaries continue to be threatened by further development, pollution, and climate related changes including diminished streamflows and sea level rise. Given this loss and threat we developed a California Rapid Assessment Method (CRAM) to assess the condition of California's bar-built estuaries. CRAM uses visual indicators to accurately reflect current wetland condition with regards to buffer habitat, hydrology, physical complexity, plant diversity and structure, and landscape influences. Here we validate this method by comparing results of CRAM for bar-built estuaries to other accepted measures of wetland condition that we simultaneously collected with CRAM including vegetative surveys, water nutrient levels, and GIS landscape scale measures of stress for 32 sites throughout California. CRAM correlated well with each of these three independent methods of assessing condition. Notably, the Environmental Monitoring and Assessment Program (EMAP) number of natives metric significantly correlated with CRAM Index and all Attribute scores. The strong correlations of CRAM to nutrient levels is particularly important considering the documentation of the negative impact of nutrients on fish populations, the use of bar-built estuaries by juveniles of commercially important species, and the nursery role of bar-built estuaries for maintaining imperiled populations of species such as steelhead. GIS measured percent impervious, percent agriculture, and percent dams all correlated well with expected CRAM Attribute scores at appropriate watershed scales relative to the area of inference for each CRAM metric. Further, CRAM for bar-built estuaries works well throughout California's diversity of environmental conditions and regardless of geography, timing, or whether the bar was open or closed during the survey. We hope that the availability of CRAM combined with available data repositories will enable local, state, and federal decision makers to better manage, restore, and conserve valuable bar-built estuaries in the face of continual threats like development, drought, and sea level rise.

Regional scale estimates of baseflow and factors influencing baseflow in the Upper Colorado River Basin

Abstract Study region The study region encompasses the Upper Colorado River Basin (UCRB), which provides water for 40 million people and is a vital part of the water supply in the western U.S. Study focus Groundwater and surface water can be considered a single water resource and thus it is important to understand groundwater contributions to streamflow, or baseflow, within a region. Previously, quantification of baseflow using chemical mass balance at large numbers of sites was not possible because of data limitations. A new method using regression-derived daily specific conductance values with conductivity mass balance hydrograph separation allows for baseflow estimation at sites across large regions. This method was applied to estimate baseflow discharge at 229 sites across the UCRB. Subsequently, climate, soil, topography, and land cover characteristics were statistically evaluated using principal component analysis (PCA) to determine their influence on baseflow discharge. New hydrological insights for the region Results suggest that approximately half of the streamflow in the UCRB is baseflow derived from groundwater discharge to streams. Higher baseflow yields typically occur in upper elevation areas of the UCRB. PCA identified precipitation, snow, sand content of soils, elevation, land surface slope, percent grasslands, and percent natural barren lands as being positively correlated with baseflow yield; whereas temperature, potential evapotranspiration, silt and clay content of soils, percent agriculture, and percent shrublands were negatively correlated with baseflow yield.

Presoja prostorskega stratificiranja za vzorčno ocenjevanje gozdnih zemljišč

Stratification based on Slovenian forest typology has been proposed for sampling forest land-use/ land-cover data and changes over time. Using land-use map and forest typology map we evaluated geographic scales of variance for landscape-level indices and compared stratification by administrative units and regions. As forest prevails in 10 out of 12 statistical regions in terms of its surface area, these regions cannot be effective stratification tool for sampling and mapping land-use. Statistical regions accounted for 21 percent of the total variance of percent agriculture and 17 percent of total variance in amount of forest. Through the classification of quadratic 1 square kilometre tiles according to the typology of forest site types, somewhat greater proportion of total variance has been explained by stratification than on the spatial scale of statistical regions, although on the account of the high number of groups (29 strata). The great differences in fragmentation indices for these forest groups illustrate that the spatial scale for the formation of strata is smaller than the regional one.

Habitat variables influencing chukar partridge decrease in Southeastern Bulgaria

The aim of our study was to identify the most important ecological factors influencing the breeding density of chukar partridges (Alectoris chukar) in Southeastern Bulgaria. Identified habitats were divided into two categories: 1) natural habitats with an extant population of the species, and 2) habitats in which it was absent. In each habitat, annual precipitation, lowest elevation in the habitat, Paliurus cover, grazing livestock per 100 ha, shrub height, shrub density, bedrock type, percentage of pastures, percentage of agriculture, percentage of wetlands, percentage of rocks, presence/absence of buildings, presence/absence of highways, plant species composition, plant layer coverage, and chukar breeding pairs were measured. We have found several habitat variables that probably affect the density of nesting chukar partridge. These are: 1) grazing intensity, 2) percentage of rock outcrops, 3) percentage of grasslands, 4) shrub cover, and 5) elevation. Grazing intensity and rock outcrop presence, together with the elevation gradient, influence the breeding pair distribution and abundance most significantly. Our study has confirmed only three types of habitats that the chukar currently prefers to nest in. Unknown factors probably changed the other sites in a way that they are no longer suitable for the species’ existence and reproduction.

Survival of Atlantic Flyway resident population Canada geese in New Jersey

ABSTRACTAtlantic Flyway Resident Population Canada geese (Branta canadensis) are long‐lived birds that were established during the mid‐1900s. At high densities, resident Canada geese reduce water quality, impair landscape aesthetic, damage crops, and cause safety concerns. Managers need information about survival to more effectively manage these populations via implementation of harvest and cull regulations. We analyzed records for 39,711 Canada geese captured 54,309 times during 1994–2011, of which 5,883 were recovered by the summer of 2012. We used the Burnham model to estimate survival, recapture rate, recovery, and fidelity and identify factors that affect them. Candidate models included combinations of sex, age class, year, hunting season length, bag limit, total harvest, number culled, the North Atlantic Oscillation Index, density, an indicator for urban banded birds, and percent agriculture, natural, rural, and urban land cover at the last known capture location. The best‐supported model included effects of age class, year, and whether the individual was banded in an urban or rural locale on survival and effects of year and locale on Seber recovery rate. We used it to construct a hierarchical model to estimate mean survival and Seber recovery rates for urban and rural birds and their variances. Mean survival of after‐hatch‐year urban Canada geese was 0.724 (95% CI: 0.675–0.772) and that of after‐hatch‐year rural geese was 0.718 (0.665–0.770). Based on estimates of survival and recovery, mean harvest rate was 3.8% (3.4–4.2%) for after‐hatch‐year urban geese and 7.8% (6.7–9.0%) for after‐hatch‐year rural geese. Hatch‐year geese in rural areas had lower survival and higher harvest rates than after‐hatch‐year geese, but the opposite was true in urban areas. Survival generally decreased over the course of the study and harvest increased. Hatch‐year males had the lowest fidelity of any group, and after‐hatch‐year geese of both sexes had fidelity greater than 85%. Knowledge of survival and its relationship with management and environmental factors will allow managers to better predict population responses to harvest and cull and to achieve population goals. © 2014 The Wildlife Society.

Quality of surface water related to land use: a case study in a catchment with small farms and intensive vegetable crop production in southern Brazil

Water degradation is strongly related to agricultural activity. The aim of this study was to evaluate the influence of land use and some environmental components on surface water quality in the Campestre catchment, located in Colombo, state of Parana, Brazil. Physical and chemical attributes were analyzed (total nitrogen, ammonium, nitrate, total phosphorus, electrical conductivity, pH, temperature, turbidity, total solids, biological oxygen demand, chemical oxygen demand and dissolved oxygen). Monthly samples of the river water were taken over one year at eight monitoring sites, distributed over three sub-basins. Overall, water quality was worse in the sub-basin with a higher percentage of agriculture, and was also affected by a lower percentage of native forest and permanent preservation area, and a larger drainage area. Water quality was also negatively affected by the presence of agriculture in the riparian zone. In the summer season, probably due to higher rainfall and intensive soil use, a higher concentration of total nitrogen and particulate nitrogen was observed, as well as higher electrical conductivity, pH and turbidity. All attributes, except for total phosphorus, were in compliance with Brazilian Conama Resolution Nº 357/2005 for freshwater class 1. However, it should be noted that these results referred to the base flow and did not represent a discharge condition since most of the water samples were not collected at or near the rainfall event.

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Geospatial and Temporal Analysis of a 20‐Year Record of Landsat‐Based Water Clarity in Minnesota's 10,000 Lakes

AbstractA large 20‐year database on water clarity for all Minnesota lakes ≥8 ha was analyzed statistically for spatial distributions, temporal trends, and relationships with in‐lake and watershed factors that potentially affect lake clarity. The database includes Landsat‐based water clarity estimates expressed in terms of Secchi depth (SDLandsat), an integrative measure of water quality, for more than 10,500 lakes for time periods centered around 1985, 1990, 1995, 2000, and 2005. Minnesota lake clarity is lower (more turbid) in the south and southwest and clearer in the north and northeast; this pattern is evident at the levels of individual lakes and ecoregions. Temporal trends in clarity were detected in ~11% of the lakes: 4.6% had improving clarity and 6.2% had decreasing clarity. Ecoregions in southern and western Minnesota, where agriculture is the predominant land use, had higher percentages of lakes with decreasing clarity than the rest of the state, and small and shallow lakes had higher percentages of decreasing clarity trends than large and deep lakes. The mean SDLandsat statewide remained stable from 1985 to 2005 but decreased in ecoregions dominated by agricultural land use. Deep lakes had higher clarity than shallow lakes statewide and for lakes grouped by land cover. SDLandsat decreased as the percentage of agriculture and/or urban area increased at county and catchment levels and it increased with increasing forested land.