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USGS2013

Semi-automted analysis of high-resolution aerial images to quantify docks in Upper Midwest glacial lakes

Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on ) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors.

Minnesota↗

USGS2011

Land use and climate influences on waterbirds in the Prairie Potholes

Aim We examined the influences of regional climate and land‐use variables on mallard ( Anas platyrhynchos ), blue‐winged teal ( Anas discors ), ruddy duck ( Oxyura jamaicensis ) and pied‐billed grebe ( Podilymbus podiceps ) abundances to inform conservation planning in the Prairie Pothole Region of the United States. Location The US portion of Bird Conservation Region 11 (US‐BCR11, the Prairie Potholes), which encompasses six states within the United States: Montana, North Dakota, South Dakota, Nebraska, Minnesota and Iowa. Methods We used data from the North American Breeding Bird Survey (NABBS), the National Land Cover Data Set, and the National Climatic Data Center to model the effects of environmental variables on waterbird abundance. We evaluated land‐use covariates at three logarithmically related spatial scales (1000, 10,000 and 100,000 ha), and constructed hierarchical spatial count models a priori using information from published habitat associations. Model fitting was performed using a hierarchical modelling approach within a Bayesian framework. Results Models with the same variables expressed at different scales were often in the best model subset, indicating that the influence of spatial scale was small. Both land‐use and climate variables contributed strongly to predicting waterbird abundance in US‐BCR11. The strongest positive influences on waterbird abundance were the percentage of wetland area across all three spatial scales, herbaceous vegetation and precipitation variables. Other variables that we included in our models did not appear to influence waterbirds in this study. Main conclusions Understanding the relationships of waterbird abundance to climate and land use may allow us to make predictions of future distribution and abundance as environmental factors change. Additionally, results from this study can suggest locations where conservation and management efforts should be focused.

Iowa, Minnesota, Montana, Nebraska, North Dakota, ↗

USGS2017

Sandhill crane roost selection, human disturbance, and forage resources

Sites used for roosting represent a key habitat requirement for many species of birds because availability and quality of roost sites can influence individual fitness. Birds select roost sites based on numerous factors, requirements, and motivations, and selection of roosts can be dynamic in time and space because of various ecological and environmental influences. For sandhill cranes (Antigone canadensis) at their main spring-staging area along the Platte River in south-central Nebraska, USA, past investigations of roosting cranes focused on physical channel characteristics related to perceived security as motivating roost distribution. We used 6,310 roost sites selected by 313 sandhill cranes over 5 spring migration seasons (2003–2007) to quantify resource selection functions of roost sites on the central Platte River using a discrete choice analysis. Sandhill cranes generally showed stronger selection for wider channels with shorter bank vegetation situated farther from potential human disturbance features such as roads, bridges, and dwellings. Furthermore, selection for roost sites with preferable physical characteristics (wide channels with short bank vegetation) was more resilient to nearby disturbance features than more narrow channels with taller bank vegetation. The amount of cornfields surrounding sandhill crane roost sites positively influenced relative probability of use but only for more narrow channels < 100 m and those with shorter bank vegetation. We confirmed key resource features that sandhill cranes selected at river channels along the Platte River, and after incorporating spatial variation due to human disturbance, our understanding of roost site selection was more robust, providing insights on how disturbance may interact with physical habitat features. Managers can use information on roost-site selection when developing plans to increase probability of crane use at existing roost sites and to identify new areas for potential use if existing sites become limited.

Nebraska↗

USGS2010

Modelling detection probabilities to evaluate management and control tools for an invasive species

For most ecologists, detection probability (p) is a nuisance variable that must be modelled to estimate the state variable of interest (i.e. survival, abundance, or occupancy). However, in the realm of invasive species control, the rate of detection and removal is the rate-limiting step for management of this pervasive environmental problem. For strategic planning of an eradication (removal of every individual), one must identify the least likely individual to be removed, and determine the probability of removing it. To evaluate visual searching as a control tool for populations of the invasive brown treesnake Boiga irregularis, we designed a mark-recapture study to evaluate detection probability as a function of time, gender, size, body condition, recent detection history, residency status, searcher team and environmental covariates. We evaluated these factors using 654 captures resulting from visual detections of 117 snakes residing in a 5-ha semi-forested enclosure on Guam, fenced to prevent immigration and emigration of snakes but not their prey. Visual detection probability was low overall (= 0??07 per occasion) but reached 0??18 under optimal circumstances. Our results supported sex-specific differences in detectability that were a quadratic function of size, with both small and large females having lower detection probabilities than males of those sizes. There was strong evidence for individual periodic changes in detectability of a few days duration, roughly doubling detection probability (comparing peak to non-elevated detections). Snakes in poor body condition had estimated mean detection probabilities greater than snakes with high body condition. Search teams with high average detection rates exhibited detection probabilities about twice that of search teams with low average detection rates. Surveys conducted with bright moonlight and strong wind gusts exhibited moderately decreased probabilities of detecting snakes. Synthesis and applications. By emphasizing and modelling detection probabilities, we now know: (i) that eradication of this species by searching is possible, (ii) how much searching effort would be required, (iii) under what environmental conditions searching would be most efficient, and (iv) several factors that are likely to modulate this quantification when searching is applied to new areas. The same approach can be use for evaluation of any control technology or population monitoring programme. ?? 2009 The Authors. Journal compilation ?? 2009 British Ecological Society.

Journal of Applied Ecology↗

USGS2025

Assessing decadal-scale coastal change likelihood to define the accuracy and application of scientific information

Defining the accuracy and uncertainties of scientific data products is critical to the usability and trustworthiness of scientific information for environmental management and conservation purposes, such as coastal resource prioritization, design, adaptation, and mitigation. The U.S. Geological Survey has a new decadal-scale coastal change assessment product that synthesizes nearly two dozen coastal datasets. A supervised machine-learning framework is used to combine existing datasets that describe the landscape and the hazards that affect it to determine the coastal change likelihood (CCL) in the coming decade at a resolution of 10 m per pixel for the NE United States from Maine to Virginia. Here, results from a series of statistical tests conducted on source data, the supervised classification, and the CCL outcomes as compared with historical land-cover change are presented. The overall accuracy of the aggregated land-cover dataset that serves as the foundation to which other source datasets are appended is 94%. The supervised learning classification that determines the final CCL output has an overall accuracy of 92%. The CCL predictions of high expected coastal change were consistent with 95% of the coastal and low-elevation landscape change in the last 20 years, as recorded by the Coastal Change Analysis Program land-cover change atlas. Results suggest that CCL provides accurate estimates of coastal landscape change in the next decade that are consistent with recent observed change. Additionally, best practices for applying CCL for planning purposes are outlined, and citing limitations, knowledge gaps, and opportunities for improved accuracy and further investigation are considered.

Journal of Coastal Research↗

USGS2025

RAD (Resist-Accept-Direct) switch points and triggers for adaptation planning

Climate change is transforming ecosystems globally. The Resist-Accept-Direct (RAD) framework has gained traction within many natural resource management institutions to help consider the decision space in response to this transformation. Because RAD helps manage for directional change, RAD choices entail considering which RAD pathway to implement and for how long. For example, one may accept a slowly changing ecosystem, but at a certain point, decide to begin resisting or directing the change an ecosystem is experiencing. Alternatively, one may begin resisting an ecosystem transformation, but ultimately realize resistance is no longer feasible based on cost or efficacy. These choices are challenging and encompass broad domains of cultural, ecological, financial, organizational, public, regulatory, and technological considerations to determine when to switch RAD pathways. We introduce the concepts of RAD switch points and triggers to help support these decision processes. We illustrate these concepts using case studies on walleye ( Sander vitreus ) stocking decisions in Wisconsin, wildfire response in the Greater Yellowstone Ecosystem, and bull trout ( Salvelinus confluentus ) management in Oregon, USA. Synthesizing across these examples, we delineate key points for decision makers as they (iteratively) reevaluate among the RAD pathways as conditions continue to change.

Journal of Environmental Management↗

USGS2017

No substitute for survival: Perturbation analyses using a Golden Eagle population model reveal limits to managing for take

Conserving populations of long-lived birds of prey, characterized by a slow life-history (e.g., high survival and low reproductive output), requires a thorough understanding of how variation in their vital rates differentially affects population growth. Stochastic population modeling provides a framework for exploring variation in complex life histories to better understand how environmental and demographic variation within individual vital rates affects population dynamics. Specifically, we used life-stage simulation analysis (LSA) to identify those life-history characteristics that most affect population growth and are amenable to management actions. The Golden Eagle ( Aquila chrysaetos ) is a wide-ranging raptor of conservation concern, which has been adopted as a focal species for conservation planning. Golden Eagle population trends in western North America currently appear stable. Yet an expanding human footprint that may increase mortality stimulated our investigation into the ability of populations to sustain reduced survival. We fit mixed-effects models to published estimates of vital rates to estimate the mean and process variation of productivity (young fledged per pair) and survival for use in a LSA framework. As expected, breeding adult survival had the greatest relative effect on population growth, though productivity explained the most variation in growth. Based on perturbation analyses, we demonstrate that even minor reductions in breeding adult survival (<4.5%) caused otherwise stable populations to decline. Despite its importance, precise estimates of spatial and temporal variation in breeding adult survival are poorly documented. Importantly, we found that the ability for increases in reproductive output to compensate for decreased survival was very limited. To maintain stable populations, declines in survival >4% required increases in productivity that generally exceed the evolutionary potential for Golden Eagles. Our findings support the current U.S. Fish and Wildlife conservation strategy which mitigates eagle “take” via efforts to reduce mortality elsewhere.

Journal of Raptor Research↗

USGS2025

Summer roost site suitability analyses for 4 special status bat species in the Eastern United States

Data describing habitat suitability are crucial for implementing effective conservation planning but are often lacking at regional and continental scales. We address this gap for 4 bat species that are listed, proposed for listing, or under Endangered Species Act listing review by highlighting a framework for estimating summer roost suitability with a presence-background approach to aid development of conservation policy and management plans. The 4 species of concern are the Little Brown Bat ( Myotis lucifugus ), the Northern Long-eared Bat ( M. septentrionalis ), the Indiana Bat ( M. sodalis ), and the Tricolored Bat ( Perimyotis subflavus ). Our estimates of summer roost suitability were developed for the eastern United States at a fine spatial resolution (250 m pixels) suitable for conservation planning across multiple scales. Summer roost habitat suitability was higher in areas with higher tree canopy cover for each of these species, though subtle differences were observed between the species that often use buildings (e.g., Little Brown Bat), tree crevices, cavities, and elements of dead or dying trees (e.g., Northern Long-eared Bat and Indiana Bat), and foliage (e.g., Tricolored Bat). To this end, roost suitability was not identical among species, and each showed subtly different relationships to the environmental covariates considered here. We also use a novel approach, gradient surface metrics, to quantify differences in the spatial pattern of summer roost suitability among the 4 species and found that tricolored bats and northern long-eared bats showed the most homogeneous and spatially smooth habitat suitability surfaces. Estimates of summer roost suitability developed here were also used to identify areas of good summer habitat where our models showed the least uncertainty that may be beneficial for targeted conservation, such as limiting disturbance to potential roost habitat. We also identified areas where additional data would benefit future summer roost modeling efforts. This work provides a first step toward developing multistate inventories of summer roost habitat suitable for implementing effective conservation planning at multiple scales.

Journal of Mammalogy↗

USGS1987

Dynamics of the recovery of the western Lake Erie walleye (Stizostedion vitreum vitreum) stock

After its 1957 collapse under intensive fishing and environmental stresses, the walleye (Stizostedion vitreum vitreum) stock of western Lake Erie remained low throughout the 1960s. A moratorium on both sport and commercial fishing, resulting from the 1970 discovery of mercury concentrations in walleye flesh, provided an opportunity for the development of an international interagency management plan. The quota management plan developed depended on sequential projection of the fishable stock on the basis of estimated annual recruitment and reports of total withdrawals from the stock. The fishery reopened gradually and quota management (including allocation among jurisdictions) was implemented in 1976. The stock, which had been gradually increasing as a result of relatively strong year-classes produced in 1970, 1972, and 1974, responded well to limited exploitation and produced a record year-class in 1977. Quotas were exceeded in 1978-80, but the stock continued to improve to the extent that the recommended rate of exploitation was increased in 1980 and again in 1981. As the population expanded, growth began to decline; the decline became apparent in young-of-the-year in the early 1970s and in older walleyes in the late 1970s. This trend toward progressively slower growth, which continued in the 1977 and subsequent year-classes, was accompanied by an increase in length at sexual maturity and a decrease in the percentage of female walleyes reaching sexual maturity at age III. As a net result of these changes, the proportion of mature females in the stock (an index of stock fecundity) decreased slightly during the interval 1975-84, while the estimated biomass of the standing stock rose from 9 000 to nearly 26 000 t. Both sport and commercial catches increased markedly after 1980 in Lake Erie's central basin.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2026

Characterization and modeling approach for planning restoration strategies in a complex basin affected by acid mine drainage

The management of acid mine drainage (AMD) impacted catchments, such as the Odiel River basin, in southwestern Spain, prioritizes reclamation to meet water resources needs. Assessing water composition across its watercourses is needed to identify major AMD contributors and potentially guide remediation efforts. An equilibrium-based mixing model was developed to simulate AMD pollutant load reductions and estimate the impact of selective restorations on water quality in the Odiel River, particularly at the planned Alcolea Reservoir near its outlet. Sampling under varying flow conditions (average vs. high flow) showed a reduction in acidity transport (from 54.0 to 42.5 ton/day), attributed to greater neutralization effects during high flows. Over 90 % of metal-fluxes originate alone from the Riotinto (73.6 %), Tharsis (14.5 %), and San Telmo (5.00 %) mining districts, among many other mines. While geochemical model estimates fit well with observed data (R 2 = 0.99), some deviations in non-conservative constituents (i.e. pH, Fe and Al) were observed (R 2 = 0.73–0.99), likely due to uncertainties in solubility constants and redox/Fe speciation. After evaluating model reliability, two reduction scenarios (50 % and 100 %) were applied to the three primary sources. Full removal of contamination could subtantially improve impounded reservoir water quality, with pH values of 4.93 and 7.64, and a net acidity between 8.75 and 4.63 mg/L eq. CaCO 3 in both average and high flows, respectively. Such differences may be related to flow regime effects on water quality. However, a 50 % reduction is insufficient to meet drinking or irrigation standards, highlighting the need for full and appropriate reclamation. The model offers a management tool for decision-making in the restoration of the Odiel River basin and could be transferable to similar AMD-affected basins worldwide.

Odiel River basin, southwestern Spain↗

USGS2025

Reliability of satellite-based vegetation maps for planning wildfire-fuel treatments in shrub steppe: Inferences from two contrasting national parks

Protecting habitat threatened by increasing wildfire size and frequency requires identifying the spatial intersection of wildfire behavior and ecological conditions that favor positive management outcomes. In the perennial sagebrush steppe of Western North America, invasions by fire-prone annual grasses are a key concern, and management of them requires reliable maps of vegetation cover, fuels, and wildfire behavior. We compared commonly used, publicly available vegetation cover and fuels maps, specifically the Rangeland Analysis Platform (RAP) and LANDFIRE, with field-based assessments at two U.S. National Parks dominated by sagebrush steppe: City of Rocks National Reserve and Craters of the Moon National Monument and Preserve. Plant-community composition and fuels measured at ∼1700 field locations spanning ∼300,000 ha revealed that 1) RAP generally underestimated each vegetation cover type where the cover was actually abundant, and conversely overestimated cover types where they were actually scarce, and 2) there was considerable disagreement in fuel-bed maps derived from LANDFIRE compared to field observations. As a result, there were substantial discrepancies in the spatial patterning of wildfire behavior estimated from the fire-spread model FLAMMAP when parameterized with LANDFIRE compared to field-based fuel-bed maps created from Random Forests models. Reliable maps of vegetation cover and fuel conditions are needed to help guide fuels and invasive species management, especially given recent increases in pre- and post-fire treatments in arid and semiarid landscapes. The costs associated with poorly informed fuel reduction may greatly exceed the costs of field-based vegetation and fuels inventory to inform effective design of vegetative fuels treatments.

Idaho↗

USGS2022

Reassessing perennial cover as a driver of duck nest survival in the Prairie Pothole Region

Conservation plans designed to sustain North American duck populations prominently feature a key hypothesis stating that the amount of the landscape in perennial cover surrounding upland duck nests positively influences nest survival rates. Recent conflicting research testing this hypothesis creates ambiguity regarding which management actions to pursue and where to prioritize conservation delivery. We compared existing models and new formulations of existing models explaining spatiotemporal variation in nest survival using independent data documenting the fate of >20,000 duck nests within the Drift Prairie, Missouri Coteau, and Prairie Coteau physiographic regions of the United States Prairie Pothole Region during 2002–2018. Our results suggest an inconsistent relationship between perennial cover and survival of upland duck nests, which depended upon physiographic region and current and time-lagged landscape and environmental conditions. The magnitude and direction of how perennial cover correlated with daily nest survival depended on its dominance as a landcover type. A positive relationship existed when perennial cover was a minor component of landcover in all physiographic regions (<30% of a 10.4-km 2 area) and, in the Drift Prairie and Prairie Coteau, when perennial cover was the dominant landcover type (>60%). A constant or negative relationship was predicted at locations of about 30–60% perennial cover. Additionally, environmental conditions (i.e., density of wetlands and estimated gross primary productivity in the previous year) moderated or enhanced the effect of perennial cover on nest survival, depending on physiographic region. Our finding of inconsistency in the relationship between perennial cover and nest survival contradicts the conservation premise that nest survival universally increases linearly when uplands are converted to perennial cover. Promoting policies and management actions designed to increase perennial cover can be expected to be situationally but not consistently associated with higher survival of upland duck nests.

Montana, North Dakota, South Dakota↗

USGS2015

Spatially explicit modeling of blackbird abundance in the Prairie Pothole Region

Knowledge of factors influencing animal abundance is important to wildlife biologists developing management plans. This is especially true for economically important species such as blackbirds (Icteridae), which cause more than $100 million in crop damages annually in the United States. Using data from the North American Breeding Bird Survey, the National Land Cover Dataset, and the National Climatic Data Center, we modeled effects of regional environmental variables on relative abundance of 3 blackbird species (red-winged blackbird, Agelaius phoeniceus ; yellow-headed blackbird, Xanthocephalus xanthocephalus ; common grackle, Quiscalus quiscula ) in the Prairie Pothole Region of the central United States. We evaluated landscape covariates at 3 logarithmically related spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and modeled weather variables at the 100,000-ha scale. We constructed models a priori using information from published habitat associations. We fit models with WinBUGS using Markov chain Monte Carlo techniques. Both landscape and weather variables contributed strongly to predicting blackbird relative abundance (95% credibility interval did not overlap 0). Variables with the strongest associations with blackbird relative abundance were the percentage of wetland area and precipitation amount from the year before bird surveys were conducted. The influence of spatial scale appeared small—models with the same variables expressed at different scales were often in the best model subset. This large-scale study elucidated regional effects of weather and landscape variables, suggesting that management strategies aimed at reducing damages caused by these species should consider the broader landscape, including weather effects, because such factors may outweigh the influence of localized conditions or site-specific management actions. The regional species distributional models we developed for blackbirds provide a tool for understanding these broader landscape effects and guiding wildlife management practices to areas that are optimally beneficial. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Iowa, Minnesotta, Montana, Nebraska, North Dakota↗

USGS2023

A retrospective assessment of fuel break effectiveness for containing rangeland wildfires in the sagebrush biome

Escalated wildfire activity within the western U.S. has widespread societal impacts and long-term consequences for the imperiled sagebrush ( Artemisia spp.) biome. Shifts from historical fire regimes and the interplay between frequent disturbance and invasive annual grasses may initiate permanent state transitions as wildfire frequency outpaces sagebrush communities’ innate capacity to recover. Therefore, wildfire management is at the core of conservation plans for sagebrush ecosystems, especially critical habitat for species of conservation concern such as the greater sage-grouse ( Centrocercus urophasianus ; hereafter sage-grouse). Fuel breaks help facilitate wildfire suppression by modifying behavior through fuels modification and allowing safe access points for containment by firefighters. The Bureau of Land Management has proposed to roughly double the existing fuel break network in the western U.S., centered on the Great Basin. To our knowledge, no broad-scale examination of fuel break effectiveness or the environmental conditions under which fuel breaks are expected to be most effective has been conducted. We performed a retrospective assessment of probability of fuel break contributing to wildfire containment on recorded wildfire and fuel break interactions from 1985 to 2018 within the western U.S. We characterized environmental, fuels, and weather conditions within 500 m of wildfire contact, and within 5 km of the approaching wildfire. We used a binomial mixed model within a Bayesian framework to identify relationships between these variables and fuel break success. Fuel breaks were least successful in areas classified as having low resilience to disturbance and low resistance to invasion, in areas composed of primarily woody fuels, and when operating in high temperature and low precipitation conditions. Fuel breaks were most effective in areas where fine fuels dominated and in areas that were readily accessible. Maintenance history and fuel break type also contributed to the probability of containment. Overall results indicate a complex and sometimes paradoxical relationship between landscape characteristics that promote wildfire spread and those that impact fuel break effectiveness. Finally, we developed predictive maps of fuel break effectiveness by fuel break type to further elucidate these complex relationships and to inform urgently needed fuel break placement and maintenance priorities across the sagebrush biome.

Journal of Environmental Management↗

USGS2016

Using a full annual cycle model to evaluate long-term population viability of the conservation-reliant Kirtland's warbler after successful recovery

Long-term management planning for conservation-reliant migratory songbirds is particularly challenging because habitat quality in different stages and geographic locations of the annual cycle can have direct and carry-over effects that influence the population dynamics. The Neotropical migratory songbird Kirtland's warbler Setophaga kirtlandii (Baird 1852) is listed as endangered under the U.S. Endangered Species Act and Near Threatened under the IUCN Red List. This conservation-reliant species is being considered for U.S. federal delisting because the species has surpassed the designated 1000 breeding pairs recovery threshold since 2001. To help inform the delisting decision and long-term management efforts, we developed a population simulation model for the Kirtland's warbler that incorporated both breeding and wintering grounds habitat dynamics, and projected population viability based on current environmental conditions and potential future management scenarios. Future management scenarios included the continuation of current management conditions, reduced productivity and carrying capacity due to the changes in habitat suitability from the creation of experimental jack pine Pinus banksiana (Lamb.) plantations, and reduced productivity from alteration of the brown-headed cowbird Molothrus ater (Boddaert 1783) removal programme. Linking wintering grounds precipitation to productivity improved the accuracy of the model for replicating past observed population dynamics. Our future simulations indicate that the Kirtland's warbler population is stable under two potential future management scenarios: (i) continuation of current management practices and (ii) spatially restricting cowbird removal to the core breeding area, assuming that cowbirds reduce productivity in the remaining patches by ≤41%. The additional future management scenarios we assessed resulted in population declines. Synthesis and applications . Our study indicates that the Kirtland's warbler population is stable under current management conditions and that the jack pine plantation and cowbird removal programmes continue to be necessary for the long-term persistence of the species. This study represents one of the first attempts to incorporate full annual cycle dynamics into a population viability analysis for a migratory bird, and our results indicate that incorporating wintering grounds dynamics improved the model performance.

Michigan↗

USGS2011

Landscape models of brook trout abundance and distribution in lotic habitat with field validation

Brook trout Salvelinus fontinalis are native fish in decline owing to environmental changes. Predictions of their potential distribution and a better understanding of their relationship to habitat conditions would enhance the management and conservation of this valuable species. We used over 7,800 brook trout observations throughout New York State and georeferenced, multiscale landscape condition data to develop four regionally specific artificial neural network models to predict brook trout abundance in rivers and streams. Land cover data provided a general signature of human activity, but other habitat variables were resistant to anthropogenic changes (i.e., changing on a geological time scale). The resulting models predict the potential for any stream to support brook trout. The models were validated by holding 20% of the data out as a test set and by comparison with additional field collections from a variety of habitat types. The models performed well, explaining more than 90% of data variability. Errors were often associated with small spatial displacements of predicted values. When compared with the additional field collections (39 sites), 92% of the predictions were off by only a single class from the field-observed abundances. Among “least-disturbed” field collection sites, all predictions were correct or off by a single abundance class, except for one where brown trout Salmo trutta were present. Other degrading factors were evident at most sites where brook trout were absent or less abundant than predicted. The most important habitat variables included landscape slope, stream and drainage network sizes, water temperature, and extent of forest cover. Predicted brook trout abundances were applied to all New York streams, providing a synoptic map of the distribution of brook trout habitat potential. These fish models set benchmarks of best potential for streams to support brook trout under broad-scale human influences and can assist with planning and identification of protection or rehabilitation sites.

New York↗

USGS2013

Clarity versus complexity: land-use modeling as a practical tool for decision-makers

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes. LULC modelers have become very adept at creating tools for modeling LULC change, but complicated models and lack of transparency limit their utility for decision-makers. The complicated nature of many LULC models also makes it impractical or even impossible to perform a rigorous analysis of modeling uncertainty. This paper provides a review of land-cover modeling approaches and the issues causes by the complicated nature of models, and provides suggestions to facilitate the increased use of LULC models by decision-makers and other stakeholders. The utility of LULC models themselves can be improved by 1) providing model code and documentation, 2) through the use of scenario frameworks to frame overall uncertainties, 3) improving methods for generalizing key LULC processes most important to stakeholders, and 4) adopting more rigorous standards for validating models and quantifying uncertainty. Communication with decision-makers and other stakeholders can be improved by increasing stakeholder participation in all stages of the modeling process, increasing the transparency of model structure and uncertainties, and developing user-friendly decision-support systems to bridge the link between LULC science and policy. By considering these options, LULC science will be better positioned to support decision-makers and increase real-world application of LULC modeling results.

Journal of Environmental Management↗

USGS2026

When best intentions are not enough - A collaboration between scientists, policymakers, and an agricultural community

Rocky Mountain National Park is a Congressionally mandated Clean Air Act Class I Area, but years of research have documented evidence of biogeochemical and ecological change caused by atmospheric deposition of nitrogen. A coalition of government agencies—National Park Service, the Environmental Protection Agency Region 8, and the State of Colorado—developed the 2007 Nitrogen Deposition Reduction Plan to reduce wet nitrogen deposition to the park from the baseline in 2006 by 50% by 2032. Fifty-four percent of wet nitrogen deposition is ammonium, primarily sourced from industrial cattle and dairy operations east of the park. An Agriculture Subcommittee, meeting with regulatory and management agencies and scientists since 2006, has explored voluntary options to reduce ammonia emissions. Ammonia emissions are unregulated in the U.S. Despite sustained efforts, neither ammonium deposition nor total inorganic nitrogen deposition have declined at the rate determined to reach the targeted value by 2032. In fact, ammonia is increasing over the Front Range agricultural area. Wet nitrogen deposition in 2024 was 2.81 kg N ha −1 yr −1 , 0.61 kg N ha −1 yr −1 higher than targeted in the Nitrogen Deposition Reduction Plan. The collaborative approach between agricultural producers, regulatory entities, and resource managers is not working, but not for lack of effort by all parties. Cattle process nitrogen inefficiently, and while management practices can somewhat reduce the proportion of ammonia emitted from feedlots, with more than one million head of cattle east of Rocky Mountain National Park, large-scale reductions are unlikely. New programs to reduce emissions of nitrogen oxides (46% of wet nitrogen deposition) may reduce nitrogen deposition that is changing park ecosystems. Improved integration of crop and livestock agriculture and valuation of the ecosystem services and economy of Rocky Mountain National Park alongside agricultural value are topics for further discussion. Implications : Nitrogen deposition in precipitation to Rocky Mountain National Park has changed natural ecosystems. To protect its Clean Air Act Class I status a 2007 Nitrogen Deposition Reduction Plan agreed upon by state and federal agencies set a goal to reduce wet nitrogen deposition to the Park by half by 2032. Industrial livestock operations are a large source of nitrogen; an Agriculture Subcommittee explored voluntary options to reduce emissions from cattle. Despite sustained efforts nitrogen deposition has not declined. Further reductions in industry and transportation emissions will be needed reduce nitrogen deposition to Rocky Mountain National Park.

Colorado↗