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At least 343 records · Page 19Linked to original sources
USGS2012

Factors controlling nitrate fluxes in groundwater in agricultural areas

The impact of agricultural chemicals on groundwater quality depends on the interactions of biogeochemical and hydrologic factors. To identify key processes affecting distribution of agricultural nitrate in groundwater, a parsimonious transport model was applied at 14 sites across the U.S. Simulated vertical profiles of NO 3 - , N 2 from denitrification, O 2 , Cl - , and environmental tracers of groundwater age were matched to observations by adjusting the parameters for recharge rate, unsaturated zone travel time, fractions of N and Cl - inputs leached to groundwater, O 2 reduction rate, O 2 threshold for denitrification, and denitrification rate. Model results revealed important interactions among biogeochemical and physical factors. Chloride fluxes decreased between the land surface and water table possibly because of Cl - exports in harvested crops (averaging 22% of land-surface Cl - inputs). Modeled zero-order rates of O 2 reduction and denitrification were correlated. Denitrification rates at depth commonly exceeded overlying O 2 reduction rates, likely because shallow geologic sources of reactive electron donors had been depleted. Projections indicated continued downward migration of NO 3 - fronts at sites with denitrification rates <0.25 mg-N L -1 yr -1 . The steady state depth of NO 3 - depended to a similar degree on application rate, leaching fraction, recharge, and NO 3 - and O 2 reaction rates. Steady state total mass in each aquifer depended primarily on the N application rate. In addition to managing application rates at land surface, efficient water use may reduce the depth and mass of N in groundwater because lower recharge was associated with lower N fraction leached. Management actions to reduce N leaching could be targeted over aquifers with high-recharge and low-denitrification rates.

Water Resources Research↗
USGS2021

Integrated hydrology and operations modeling to evaluate climate change impacts in an agricultural valley irrigated with snowmelt runoff

Applying models to developed agricultural regions remains a difficult problem because there are no existing modeling codes that represent both the complex physics of the hydrology and anthropogenic manipulations to water distribution and consumption. We apply an integrated groundwater – surface water and hydrologic river operations model to an irrigated river valley in northwestern Nevada/northern California, United States to evaluate the impacts of climate change on snow-fed agricultural systems that use surface water and groundwater conjunctively. We explicitly represent individual surface water rights within the hydrologic model and allow the integrated code to change river diversions in response to earlier snowmelt runoff and water availability. Historically under-used supplemental groundwater rights are dynamically activated within the model to offset diminished surface water deliveries. The model accounts for feedbacks between the natural hydrology and anthropogenic stresses, which is a first-of-its-kind assessment of the impacts of climate change on individual water rights, and more broadly on river basin operations. Earlier snowmelt decreases annual surface water deliveries to all water rights, not just the junior water rights, owing to a lack of surface water storage in the upper river basin capable of capturing earlier runoff. Conversely, downstream irrigators with access to reservoir storage benefit from earlier runoff flowing past upstream points of diversion prior to the start of the irrigation season. Despite regional shifts toward greater reliance on groundwater for irrigation, crop consumption (a common surrogate for crop yield) decreases due to spatiotemporal changes in water supply that preferentially impact a subset of growers in the region.

California↗
USGS2010

Combined use of groundwater dating, chemical, and isotopic analyses to resolve the history and fate of nitrate contamination in two agricultural watersheds, Atlantic coastal plain, Maryland

The history and fate of groundwater nitrate (NO 3 − ) contamination were compared in 2 small adjacent agricultural watersheds in the Atlantic coastal plain by combined use of chronologic (CCl 2 F 2 , 3 H), chemical (dissolved solids, gases), and isotopic (δ 15 N,δ 13 C, δ 34 S) analyses of recharging groundwaters, discharging groundwaters, and surface waters. The results demonstrate the interactive effects of changing agricultural practices, groundwater residence times, and local geologic features on the transfer of NO 3 − through local flow systems. Recharge dates of groundwaters taken in 1990–1992 from the surficial aquifer in the Chesterville Branch and Morgan Creek watersheds near Locust Grove, Maryland, ranged from pre-1940 to the late 1980’s. When corrected for localized denitrification by use of dissolved gas concentrations, the dated waters provide a 40-year record of the recharge rate of NO 3 − , which increased in both watersheds by a factor of 3–6, most rapidly in the 1970's. The increase in groundwater NO 3 − over time was approximately proportional to the documented increase in regional N fertilizer use, and could be accounted for by oxidation and leaching of about 20–35% of the fertilizer N. Groundwaters discharging upward beneath streams in both watersheds had measured recharge dates from pre-1940 to 1975, while chemical data for second-order reaches of the streams indicated average groundwater residence times in the order of 20+ years. At the time of the study, NO 3 − discharge rates were less than NO 3 − recharge rates for at least two reasons: (1) discharge of relatively old waters with low initial NO 3 − concentrations, and (2) local denitrification. In the Chesterville Branch watershed, groundwaters remained oxic throughout much of the surficial aquifer and discharged relatively unaltered to the stream, which had a relatively high NO 3 − concentration (9–10 mg/L as N). In the Morgan Creek watershed, groundwaters were largely reduced and denitrified before discharging to the stream, which had a relatively low NO 3 − concentration (2–3 mg/L as N). Chemical and isotopic data indicate that quantitative denitrification occurred within buried calcareous glauconitic marine sediments that are present at relatively shallow depths beneath the Morgan Creek watershed. NO 3 − removal by forests, wetlands, and shallow organic-rich soils in near-stream environments was largely avoided by groundwaters that followed relatively deep flow paths before converging and discharging rapidly upward to the streams.

Maryland↗
USGS2016

Agricultural damages and losses from ARkStorm scenario flooding in California

Scientists designed the ARkStorm scenario to challenge the preparedness of California communities for widespread flooding with a historical precedence and increased likelihood under climate change. California is an important provider of vegetables, fruits, nuts, and other agricultural products to the nation. This study analyzes the agricultural damages and losses pertaining to annual crops, perennial crops, and livestock in California exposed to ARkStorm flooding. Statewide, flood damage is incurred on approximately 23% of annual crop acreage, 5% of perennial crop acreage, and 5% of livestock, e.g., dairy, feedlot, and poultry, acreage. The sum of field repair costs, forgone income, and product replacement costs span \$3.7 and \$7.1 billion (2009) for a range of inundation durations. Perennial crop loss estimates dominate, and the vulnerability of orchards and vineyards has likely increased with recent expansion. Crop reestablishment delays from levee repair and dewatering more than double annual crop losses in the delta islands, assuming the fragile system does not remain permanently flooded. The exposure of almost 200,000 dairy cows to ARkStorm flooding poses livestock evacuation challenges.

California↗
USGS2011

Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna river basin (India)

The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km 2 (26 575 200 ha), comparing a water-surplus year (2000–2001) and a water-deficit year (2002–2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61–100% for various land‐use classes and 61–81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R 2 -values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002–2003) when compared with the water-surplus year (2000–2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.

International Journal of Remote Sensing↗
USGS2017

Using interviews and biological sign surveys to infer seasonal use of forested and agricultural portions of a human-dominated landscape by Asian elephants in Nepal

Understanding how wide-ranging animals use landscapes in which human use is highly heterogeneous is important for determining patterns of human–wildlife conflict and designing mitigation strategies. Here, we show how biological sign surveys in forested components of a human-dominated landscape can be combined with human interviews in agricultural portions of a landscape to provide a full picture of seasonal use of different landscape components by wide-ranging animals and resulting human–wildlife conflict. We selected Asian elephants ( Elephas maximus ) in Nepal to illustrate this approach. Asian elephants are threatened throughout their geographic range, and there are large gaps in our understanding of their landscape-scale habitat use. We identified all potential elephant habitat in Nepal and divided the potential habitat into sampling units based on a 10 km by 10 km grid. Forested areas within grids were surveyed for signs of elephant use, and local villagers were interviewed regarding elephant use of agricultural areas and instances of conflict. Data were analyzed using single-season and multi-season (dynamic) occupancy models. A single-season occupancy model applied to data from 139 partially or wholly forested grid cells estimated that 0.57 of grid cells were used by elephants. Dynamic occupancy models fit to data from interviews across 158 grid cells estimated that monthly use of non-forested, human-dominated areas over the preceding year varied between 0.43 and 0.82 with a minimum in February and maximum in October. Seasonal patterns of crop raiding by elephants coincided with monthly elephant use of human-dominated areas, and serious instances of human–wildlife conflict were common. Efforts to mitigate human–elephant conflict in Nepal are likely to be most effective if they are concentrated during August through December when elephant use of human-dominated landscapes and human–elephant conflict are most common.

Ethology Ecology and Evolution↗
USGS2017

Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.

Journal of Land Use Science↗
USGS2024

Evaluation of classified ground points from National Agriculture Imagery program photogrammetrically derived point clouds

Studies have shown that digital surface models and point clouds generated by the United States Department of Agriculture’s National Agriculture Imagery Program (NAIP) can measure basic forest parameters such as canopy height. However, all measured forest parameters from these studies are evaluated using the differences between NAIP digital surface models (DSMs) and available lidar digital terrain models (DTMs). A survey of NAIP point cloud classification and related ground point-generated DTMs has not yet been undertaken. This study applies a Support Vector Machine (SVM) to classifying ground and nonground points from NAIP point clouds for test sites in Wyoming and Arizona, USA. Light detection and ranging (lidar) data from the U.S. Geological Survey 3D Elevation Program (3DEP) are used to validate the classified NAIP ground points and their corresponding DTMs. Comparing height differences between filtered NAIP ground points and 3DEP ground points, the SVM classifier’s results show that the vertical root mean square error value is 1.87 m and 1.69 m for the Wyoming and Arizona sites, respectively. If NAIP point clouds were continuously measured, the resulting availability of medium-resolution DTMs would benefit the application of multitemporal forest health monitoring and DTM generation.

Remote Sensing Letters↗
USGS2024

Agricultural tile drains increase the susceptibility of streams to longer and more intense streamflow droughts

Streamflow droughts are receiving increased attention worldwide due to their impact on the environment and economy. One region of concern is the Midwestern United States, whose agricultural productivity depends on subsurface pipes known as tile drains to improve trafficability and soil conditions for crop growth. Tile drains accomplish this by rapidly transporting surplus soil moisture and shallow groundwater from fields, resulting in reduced watershed storage. However, no work has previously examined the connection between tile drainage and streamflow drought. Here, we pose the question: does the extent of watershed-level tile drainage lead to an increased susceptibly and magnitude of streamflow droughts? To answer this, we use daily streamflow data for 122 watersheds throughout the Midwestern United States to quantify streamflow drought duration, frequency, and intensity. Using spatial multiple regression models, we find that agricultural tile drainage generates statistically significant ( p < 0.05) increases in streamflow drought duration and intensity while significantly reducing drought frequency. The magnitude of the effect of tile drainage on streamflow drought characteristics is similar to that of water table depth and precipitation seasonality, both of which are known to influence streamflow droughts. Furthermore, projected changes in regional precipitation characteristics will likely drive the installation of additional tile drainage. We find that for each 10% increase in tile-drained watershed area, streamflow drought duration and intensity increase by 0.03 d and 12%, respectively, while frequency decreases by 0.10 events/year. Such increases in tile drainage may lead to more severe streamflow droughts and have a detrimental effect on the socio-environmental usage of streams throughout the Midwest.

Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio↗
USGS2003

Agricultural landscapes: Can they support healthy bird populations as well as farm products?

At the beginning of the twentieth century, prospects for bird populations occupying farmlands were promising. Agricultural expansion and the resulting deforestation produced wholesale changes to the landscape of eastern North America (Trautman 1977, Zeranski and Baptist 1990, Nicholson 1997). Regional avifaunas were transformed as Horned Larks ( Eremophila alpestris ), Dickcissels (Spiza americana), and other farmland birds undertook range expansions (Hurley and Franks 1976, Askins 1999). Those farmland birds became conspicuous, frequently in numbers that are hard to imagine today (Trautman 1940). One hundred years later, many of those once plentiful species experienced dramatic population declines (Askins 1993, Peterjohn and Sauer 1999). Those trends were evident for many decades, although pre-1965 trends were largely based on anecdotal accounts and were frequently attributed to changing regional landscapes due to urban expansion, farm abandonment resulting in increased forest cover, and the more intensive use of remaining agricultural fields (Trautman 1940, Herkert 1991, Askins 2000). However, numerous specific factors were implicated in local declines of individual species (Kantrud 1981, Bollinger et al. 1990, Lymn and Temple 1991, Bowen and Kruse 1993, Herkert 1994, Houston and Schmutz 1999, Blackwell and Dolbeer 2001). Understanding factors responsible for population changes can be approached at various geographic scales. Local studies identify specific factors influencing small populations, but the applicability of those results across broad geographic areas is often uncertain. Studies conducted at large geographic scales identify broad patterns of change, but those patterns frequently involve interrelated factors that may be only loosely related to the actual causes of population change. However, correlations between broad patterns of changes in bird populations and land-use characteristics provide a basis for directing future studies conducted at smaller geographic scales.

The Auk↗
USGS2020

Non-crop habitat use by wild bees (Hymenoptera: Apoidea) in a mixed-use agricultural landscape

Homogeneous, agriculturally intense landscapes have abundant records of pollinator community research, though similar studies in the forest-dominated, heterogeneous mixed-use landscape that dominates the northeastern United States are sparse. Trends of landscape effects on wild bees are consistent across homogeneous agricultural landscapes, whereas reported studies in the northeastern United States have not found this consistency. Additionally, the role of noncrop habitat in mixed-use landscapes is understudied. We assessed wild bee communities in the mixed-use lowbush blueberry ( Vaccinium angustifolium Ait.) production landscape of Maine, United States at 56 sites in eight land cover types across two regional landscapes and analyzed effects of floral resources, landscape pattern, and spatial scale on bee abundance and species richness. Within survey sites, cover types with abundant floral resources, including lowbush blueberry fields and urban areas, promoted wild bee abundance and diversity. Cover types with few floral resources such as coniferous and deciduous/mixed forest reduced bee abundance and species richness. In the surrounding landscape, lowbush blueberry promoted bee abundance and diversity, while emergent wetland and forested land cover strongly decreased these measures. Our analysis of landscape configuration revealed that patch mixing can promote wild bee abundance and diversity; however, this was influenced by strong variation across our study landscape. More surveys at intra-regional scales may lead to better understanding of the influence of mixed-use landscapes on bee communities.

Environmental Entomology↗
USGS2018

Importance of riparian forest corridors for the ocelot in agricultural landscapes

Worldwide, private lands have attracted increased attention from conservationists, not only because most of the globe is privately owned, but also because private lands can be an asset to the protected area conservation strategy. In Brazil, the riverine Areas of Permanent Protection (APPs) is a key instrument of the Forest Code to protect native vegetation on private lands. Although APPs were conceived to function as potential wildlife corridors, this putative role has been rarely assessed. Further, recent debatable changes in the Forest Code have decreased the extent of APPs. Given this lack of information and the declining area being protected along with the growing demand for agricultural and biofuel production, which stimulate additional deforestation, it is timely to assess the role of APPs in wildlife conservation. We did this analyzing how ocelot (Leopardus pardalis) occurrence is influenced by covariates in 3 cerrado landscapes dominated by sugarcane and managed forests of eucalyptus and pine trees. We collected detection/non-detection data by camera trapping during 2 dry seasons (2013 and 2014) at 208 stations (6606 camera-days). We estimated ocelot detection and mean relative abundance using a single-species/single-season occupancy model that accounts for heterogeneous detection probability induced by variation in abundance. Modeling results showed that percentage of native forest was the most important covariate to explain ocelot mean relative abundance. This parameter was also affected positively by APPs, with ocelots being more abundant inside than outside APPs and, unexpectedly, by sugarcane. Given study design, however, the positive effect of this crop likely reflects the contact zone between sugarcane and native forest. Our findings show that landscape composition affects ocelot abundance and highlight the importance of APPs and Legal Reserves in agricultural landscapes. We conclude that, in such landscapes, compliance to the Forest Code by private land owners is key to supporting ocelot occurrence.

Journal of Mammalogy↗
USGS2021

Land use change and climate-smart agriculture in the Sahel

In the 1970s and 1980s, the Sahel experienced recurrent drought and famine. Farmers and their development partners reacted to this crisis by developing climate-smart agricultural practices and changes in land use, including water-harvesting techniques to restore degraded land to productivity. In several densely populated parts of the Sahel, farmers began to protect and manage woody species that regenerated naturally on their farmland. Farmer-managed natural regeneration (FMNR) is a foundational practice that produces multiple benefits, such as maintaining or improving soil fertility, which raises crop yields, and increasing the production of tree-based fodder, fruit, and firewood. In Niger’s Maradi and Zinder Regions alone, farmers have applied FMNR practices on 4.2 million hectares. The findings presented in this chapter suggest that the future of agriculture in the Sahel will be largely determined by whether low-income smallholder farmers will manage to improve soil fertility, which will depend on maintaining substantial densities of on-farm trees thus increasing tree cover.

Sahel Region↗
USGS2003

Fungal biology and agriculture: revisiting the field

Plant pathology has made significant progress over the years, a process that involved overcoming a variety of conceptual and technological hurdles. Descriptive mycology and the advent of chemical plant-disease management have been followed by biochemical and physiological studies of fungi and their hosts. The later establishment of biochemical genetics along with the introduction of DNA-mediated transformation have set the stage for dissection of gene function and advances in our understanding of fungal cell biology and plant-fungus interactions. Currently, with the advent of high-throughput technologies, we have the capacity to acquire vast data sets that have direct relevance to the numerous subdisciplines within fungal biology and pathology. These data provide unique opportunities for basic research and for engineering solutions to important agricultural problems. However, we also are faced with the challenge of data organization and mining to analyze the relationships between fungal and plant genomes and to elucidate the physiological function of pertinent DNA sequences. We present our perspective of fungal biology and agriculture, including administrative and political challenges to plant protection research.

Molecular Plant-Microbe Interactions↗
USGS2014

Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications

An important application of unmanned aircraft systems (UAS) may be remote-sensing for precision agriculture, because of its ability to acquire images with very small pixel sizes from low altitude flights. The objective of this study was to compare information obtained from two different pixel sizes, one about a meter (the size of a small vegetation plot) and one about a millimeter. Cereal rye (Secale cereale) was planted at the Beltsville Agricultural Research Center for a winter cover crop with fall and spring fertilizer applications, which produced differences in biomass and leaf chlorophyll content. UAS imagery was simulated by placing a Fuji IS-Pro UVIR digital camera at 3-m height looking nadir. An external UV-IR cut filter was used to acquire true-color images; an external red cut filter was used to obtain color-infrared-like images with bands at near-infrared, green, and blue wavelengths. Plot-scale Green Normalized Difference Vegetation Index was correlated with dry aboveground biomass ( ${mbi {r}} = 0.58$ ), whereas the Triangular Greenness Index (TGI) was not correlated with chlorophyll content. We used the SamplePoint program to select 100 pixels systematically; we visually identified the cover type and acquired the digital numbers. The number of rye pixels in each image was better correlated with biomass ( ${mbi {r}} = 0.73$ ), and the average TGI from only leaf pixels was negatively correlated with chlorophyll content ( ${mbi {r}} = -0.72$ ). Thus, better information for crop requirements may be obtained using very small pixel sizes, but new algorithms based on computer vision are needed for analysis. It may not be necessary to geospatially register large numbers of photographs with very small pixel sizes. Instead, images could be analyzed as single plots along field transects.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2023

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km 3 /year in 1985 to 18.2 km 3 /year in 2015, while irrigated croplands increased from 71,928 km 2 in 1985 to 78,464 km 2 in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.

Journal of the American Water Resources Associatio↗
USGS2024

Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation

Many agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water-quality effects of MPs are uncertain. We interpreted water-quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek (Virginia), Upper Chester River (Maryland), and Conewago Creek (Pennsylvania) watersheds. We synthesized patterns in MPs, climate, land use, and nutrient inputs to better understand factors affecting nutrient and sediment loads. Relations between MPs and expected water-quality improvements were not consistently identifiable. The number of MPs increased in all watersheds since the early 2010s, but most monitored nutrient and sediment loads did not decrease. Nutrient and sediment loads increased or remained stable in Smith Creek and the Upper Chester River. Sediment loads and some nutrient loads decreased in Conewago Creek. In Smith Creek, a 36-year time-series model suggests that changes in manure affected flow-normalized total nitrogen loads. We hypothesize that increases in nutrient applications may overshadow some expected MP effects. MPs might have stemmed further water-quality degradation, but improvements in nutrient loads may rely on reducing manure and fertilizer applications. Our results highlight the importance of assessing MP performance with long-term monitoring-based studies.

Journal of the American Water Resources Assocation↗
USGS2020

Forecasting the combined effects of anticipated climate change and agricultural conservation practices on fish recruitment dynamics in Lake Erie

Many aquatic ecosystems are experiencing multiple anthropogenic stressors that threaten their ability to support ecologically and economically important fish species. Two of the most ubiquitous stressors are climate change and non‐point source nutrient pollution. Agricultural conservation practices (ACPs, i.e. farming practices that reduce runoff, prevent erosion, and curb excessive nutrient loading) offer a potential means to mitigate the negative effects of non‐point source pollution on fish populations. However, our understanding of how ACP implementation amidst a changing climate will affect fish production in large ecosystems that receive substantial upstream sediment and nutrient inputs remains incomplete. Towards this end, we explored how anticipated climate change and the implementation of realistic ACPs might alter the recruitment dynamics of three fish populations (native walleye Sander vitreus and yellow perch Perca flavescens and invasive white perch Morone americana ) in the highly productive, dynamic west basin of Lake Erie. We projected future (2020–2065) recruitment under different combinations of anticipated climate change ( n = 2 levels) and ACP implementation ( n = 4 levels) in the western Lake Erie catchment using predictive biological models driven by forecasted winter severity, spring warming rate, and Maumee River total phosphorus loads that were generated from linked climate, catchment‐hydrology, and agricultural‐practice‐simulation models. In general, our models projected reduced walleye and yellow perch recruitment whereas invasive white perch recruitment was projected to remain stable or increase relative to the recent past. Our modelling also suggests the potential for trade‐offs, as ACP implementation was projected to reduce yellow perch recruitment with anticipated climate change. Overall, our study presents a useful modelling framework to forecast fish recruitment in Lake Erie and elsewhere, as well as offering projections and new avenues of research that could help resource management agencies and policy‐makers develop adaptive and resilient management strategies in the face of anticipated climate and land‐management change.

Michigan, Ohio, Indiana↗