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At least 397 records · Page 22Linked to original sources
USGS2003

A strategy for mapping mid-scale existing vegetation in support of national fire fuel assessment

Geospatial distribution of natural vegetation is among the very important environmental parameters required for applications ranging from global climate change to monitoring of natural hazards, monitoring of ecosystem vitality, and fire management practices. Increasingly sophisticated applications require vegetation datasets to cover large areas at a suitable scale and provide sufficiently detailed information. In this paper, we describe a research effort to develop a remote sensing methodology capable of producing 30-meter resolution, wall-to-wall coverage of existing vegetation types and structure variables in support of a multi-agency fire fuels and fire risks assessment project. Success of this remote sensing research effort is dependent on improved sensor and data qualities, a thorough understanding of regional and local vegetation ecology, successful integration of remote sensing with a large amount of field plot data, and flexible mapping algorithms. Preliminary results produced in the Wasatch Range and Uinta Mountains of central Utah include 28 vegetation types with an overall accuracy of 60% (average by life forms), percent canopy density (sub-pixel density) of forest, shrub, and herbaceous cover (correlation coefficient of 89, 60, and 55% respectively), and average top canopy height of forest, shrub, and herbaceous cover (correlation coefficient of 73, 50, 20% respectively). Techniques to improve the first-round results are discussed, including refinements of mapping models and use of relevant environmental gradients and potential vegetation classification associated with actual vegetation types.

Conference Paper↗
USGS2011

Accounting for the ecosystem services of migratory species: Quantifying migration support and spatial subsidies

Migratory species support ecosystem process and function in multiple areas, establishing ecological linkages between their different habitats. As they travel, migratory species also provide ecosystem services to people in many different locations. Previous research suggests there may be spatial mismatches between locations where humans use services and the ecosystems that produce them. This occurs with migratory species, between the areas that most support the species' population viability – and hence their long-term ability to provide services – and the locations where species provide the most ecosystem services. This paper presents a conceptual framework for estimating how much a particular location supports the provision of ecosystem services in other locations, and for estimating the extent to which local benefits are dependent upon other locations. We also describe a method for estimating the net payment, or subsidy, owed by or to a location that balances benefits received and support provided by locations throughout the migratory range of multiple species. The ability to quantify these spatial subsidies could provide a foundation for the establishment of markets that incentivize cross-jurisdictional cooperative management of migratory species. It could also provide a mechanism for resolving conflicts over the sustainable and equitable allocation of exploited migratory species.

Ecological Economics↗
USGS2026

Ecology of reintroduced Rocky Mountain bighorn sheep in Dinosaur National Monument

Translocations have been widely used to restore and conserve bighorn sheep ( Ovis canadensis ) populations in North America. Some translocations have been successful, but many populations remain small and genetically isolated. Population structure can influence the viability and long-term success of reintroductions. Social ungulates often function as interconnected subpopulations (metapopulations); however, few studies evaluate subpopulation sizes, connectivity, and genetic diversity within metapopulations. To address this gap, we conducted a comprehensive study of a reintroduced Rocky Mountain bighorn sheep ( Ovis canadensis canadensis ) population in Dinosaur National Monument in Colorado and Utah, USA, between 2006–2020. We analyzed global positioning system (GPS) radio-collar data, genetic samples, and results of health testing to evaluate abundance, distribution, genetic structure and diversity, habitat use, movement and connectivity, and presence of or exposure to respiratory pathogens. We integrated these analyses to evaluate the outcomes of a reintroduction effort that began in 1952, over 70 years ago, and to inform management decisions in Dinosaur National Monument. We also provide a framework for evaluating metapopulation processes, including a non-invasive approach that links genetic structure with Bayesian spatial capture-recapture analyses to estimate subpopulation sizes. Despite models indicating continuous suitable habitat, we found a spatially structured population with at least 4 subpopulations with constrained connectivity. Evidence from step selection and density analyses suggested that movement among subpopulations may be limited by semi-permeable barriers including rivers and human disturbance, which could contribute to maintenance of spatial structure over time. In 2006, antibody to Mycoplasma ovipneumoniae was detected in all geographically and genetically distinct subpopulations. Widespread clinical signs of disease and a confirmed exposure to M. ovipneumoniae in 2019 indicate a long-term disease challenge. Proximity to domestic sheep creates repeated opportunities for introduction of new M. ovipneumoniae strains. We estimated abundance in 2019 at 109 (95% CrI = 87–133), composed of subpopulations ranging from 18–39 animals (95% CrIs from 11–50). Genetic diversity was relatively high compared to other reintroduced and native Rocky Mountain bighorn sheep populations, which is likely a consequence of multiple translocations from different sources. Three of 4 subpopulation centers generally aligned with the locations of original translocation release sites. Persistence in the presence of pathogens may be facilitated by metapopulation structure and moderately high genetic diversity. Conversely, metapopulation structure can also facilitate pathogen persistence. Our approach offers a path to advance understanding of the population ecology of reintroduced bighorn sheep and can inform effective conservation and management of their populations.

Colorado, Wyoming↗
USGS2017

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae , an agent responsible for bighorn sheep pneumonia. We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs. Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae , our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.

Journal of Animal Ecology↗
USGS2013

Wyoming Basin Rapid Ecoregional Assessment

The overall goal of the Wyoming Basin Rapid Ecoregional Assessment (REA) is to provide information that supports regional planning and analysis for the management of ecological resources. The REA provides an assessment of baseline ecological conditions, an evaluation of current risks from drivers of ecosystem change (including energy development, fire, and invasive species), and a predictive capacity for evaluating future risks (including climate change). Additionally, the REA may be used for identifying priority areas for conservation or restoration and for assessing cumulative effects of multiple land uses. The Wyoming Basin REA will address Management Questions developed by the Bureau of Land Management and other agency partners for 8 major biomes and 19 species or species assemblages. The maps developed for addressing Management Questions will be integrated into overall maps of landscape-level ecological values and risks. The maps can be used to address the goals of the REA at a number of levels: for individual species, species assemblages, aquatic and terrestrial systems, and for the entire ecoregion. This allows flexibility in how the products of the REA are compiled to inform planning and management actions across a broad range of spatial scales.

Colorado;Idaho;Montana;Utah;Wyoming↗
USGS2014

Maintaining resilience in the face of climate change

Climate change, when combined with more conventional stress from human exploitation, calls into question the capacity of both existing ecological communities and resource management institutions to experience disturbances while substantially retaining their same functions and identities (Zellmer and Gunderson 2009; Ruhl 2011). In other words, the physical and biological effects of climate change raise fundamental challenges to the resilience of natural ecosystems (Gunderson and Holling 2002). Perhaps more importantly, the projected scope of ecological shifts from global climate change-and uncertainty about such changes-significantly stresses the capacity of legal institutions to manage ecosystem change (Camacho 2009). Existing governmental institutions lack the adaptive capacity to manage such substantial changes to ecological and legal systems. In particular, regulators and managers lack information about ecological effects and alternative management strategies for managing the effects of climate change (Karkkainen 2008; Camacho 2009), as well as the institutional infrastructure for obtaining such information (Peters 2008). A number of recent initiatives have been proposed to address the effects of climate change on ecological systems. However, these nascent programs do not fully meet the needs for developing adaptive capacity. A federal, publicly accessible, and system-wide portal and clearinghouse will help regulators at all levels of government manage the effects and uncertainty from climate change (DiMento and Ingram 2005; Farber 2007). Such an information infrastructure, combined with a range of incentives that encourage regulators to engage in adaptive management and programmatic adjustment over time (Baron et al. 2009), will help governmental and private institutions become more resilient and capable of managing the physical and human institutional effects of changing climate (Camacho 2009).

Book chapter↗
USGS2007

Invasive plants and their ecological strategies: Prediction and explanation of woody plant invasion in New England

Effective management of introduced species requires the early identification of species that pose a significant threat of becoming invasive. To better understand the invasive ecology of species in New England, USA, we compiled a character data set with which to compare non-native species that are known invaders to non-native species that are not currently known to be invasive. In contrast to previous biological trait-based models, we employed a Bayesian hierarchical analysis to identify sets of plant traits associated with invasiveness for each of three growth forms (vines, shrubs, and trees). The resulting models identify a suite of 'invasive traits' highlighting the ecology associated with invasiveness for each of three growth forms. The most effective predictors of invasiveness that emerged from our model were 'invasive elsewhere', 'fast growth rate', 'native latitudinal range', and 'growth form'. The contrast among growth forms was pronounced. For example, 'wind dispersal' was positively correlated with invasiveness in trees, but negatively correlated in shrubs and vines. The predictive model was able to correctly classify invasive plants 67% of the time (22/33), and non-invasive plants 95% of the time (204/215). A number of potential future invasive species in New England that deserve management consideration were identified. ?? 2007 The Authors.

Diversity and Distributions↗
USGS2020

Efficient mammal biodiversity surveys for ecological restoration monitoring

Efficient biodiversity surveys are critical for successful restoration monitoring and management. We studied the effect of varying sampling effort on the observed species richness of surveys of small mammals (trapping transects), bats (passive acoustic detection), and medium to large mammals (trail cameras). Field studies provided mammalian biodiversity data for 4 bottomland hardwood restoration sites in northeastern Indiana. Subsampled data were used to simulate monitoring surveys with a range of levels of effort. We then used hierarchical Bayesian nonlinear mixed models to analyze how different components of sampling effort affected observed species richness, a key monitoring outcome. We found that observed small mammal richness increased with the increased number of transects in a survey, while observed bat and medium to large mammal richness increased with the increased duration of sampling. Variation between sites was important for the observed richness of small mammals and bats but not for medium to large mammals. The key driver of richness observed in simulated surveys was related to the spatial scale at which target fauna interact with the habitat, with decreasing richness accompanied by a greater spatial scale of animal–habitat interactions. Our findings suggest taxon-specific recommendations for efficiently quantifying the mammalian diversity of managed sites.

Indiana↗
USGS2019

Interactive effects of severe drought and grazing on the life history cycle of a bioindicator species on the edge of its range

Recurring drought and grazing are ecological drivers of semi-arid grasslands on the Southern High Plains, USA; however, ecological drivers are currently undergoing human-induced alterations, which likely have implications for wildlife. We used the lesser prairie-chicken (Tympanuchus pallidicinctus), an iconic grouse species that exhibits a boom-bust life history strategy, on the Southern High Plains, USA, as a bioindicator of main and interactive effects of severe drought and grazing. This region encompasses the southern and westernmost part of the lesser prairie-chicken range and experienced the worst drought on record in 2011. We surveyed lesser prairie-chicken leks (i.e., communal breeding grounds) across 12 years that represented 7 years before the 2011 drought ("pre-drought") and 4 years during and following the 2011 drought ("post-drought"). Grazing was annually managed with the objective of achieving ≤50% utilization of above-ground vegetation biomass. We used lek (n = 49) count data and covariates of weather and managed grazing to: 1) estimate long-term lesser prairie-chicken abundance and compare abundance pre-drought and post-drought; 2) examine annually the influence of drought (modified Palmer Drought Index), temperature, the number of days with maximum temperature >75th percentile, and precipitation on long-term lesser prairie-chicken survival and recruitment; and 3) assess and compare the influence of grazing on lesser prairie-chickens pre-drought and post-drought. Lesser prairie-chicken abundance was nearly 7 times greater pre-drought than post-drought, and population declines were attributed to decreased survival and recruitment. The number of days with temperature >75th percentile had the greatest effect, particularly on recruitment. The population exhibited a substantial bust during 2011 and 2012 without a boom to recover in 4 post-drought years. Adaptive grazing positively influenced the population pre-drought, but had no effects post-drought. Results suggest that the severe drought in 2011 may have been beyond the range of environmental conditions to which lesser prairie-chickens, and likely other species, have adapted. Land management practices, such as grazing, should remain adaptive to ensure potential negative influences to all species are avoided. Increasing habitat quantity and quality by reducing habitat loss and fragmentation likely will increase resiliency of the ecosystem and individual species.

Southern High Plains↗
USGS2022

Defining biologically relevant and hierarchically nested population units to inform wildlife management

Wildlife populations are increasingly affected by natural and anthropogenic changes that negatively alter biotic and abiotic processes at multiple spatiotemporal scales and therefore require increased wildlife management and conservation efforts. However, wildlife management boundaries frequently lack biological context and mechanisms to assess demographic data across the multiple spatiotemporal scales influencing populations. To address these limitations, we developed a novel approach to define biologically relevant subpopulations of hierarchically nested population levels that could facilitate managing and conserving wildlife populations and habitats. Our approach relied on the Spatial “K”luster Analysis by Tree Edge Removal clustering algorithm, which we applied in an agglomerative manner (bottom-to-top). We modified the clustering algorithm using a workflow and population structure tiers from least-cost paths, which captured biological inferences of habitat conditions (functional connectivity), dispersal capabilities (potential connectivity), genetic information, and functional processes affecting movements. The approach uniquely included context of habitat resources (biotic and abiotic) summarized at multiple spatial scales surrounding locations with breeding site fidelity and constraint-based rules (number of sites grouped and population structure tiers). We applied our approach to greater sage-grouse ( Centrocercus urophasianus ), a species of conservation concern, across their range within the western United States. This case study produced 13 hierarchically nested population levels (akin to cluster levels, each representing a collection of subpopulations of an increasing number of breeding sites). These closely approximated population closure at finer ecological scales (smaller subpopulation extents with fewer breeding sites; cluster levels ≥2), where >92% of individual sage-grouse's time occurred within their home cluster. With available population monitoring data, our approaches can support the investigation of factors affecting population dynamics at multiple scales and assist managers with making informed, targeted, and cost-effective decisions within an adaptive management framework. Importantly, our approach provides the flexibility of including species-relevant context, thereby supporting other wildlife characterized by site fidelity.

Ecology and Evolution↗
USGS2016

Are we working towards global research priorities for management and conservation of sea turtles?

In 2010, an international group of 35 sea turtle researchers refined an initial list of more than 200 research questions into 20 metaquestions that were considered key for management and conservation of sea turtles. These were classified under 5 categories: reproductive biology, biogeography, population ecology, threats and conservation strategies. To obtain a picture of how research is being focused towards these key questions, we undertook a systematic review of the peer-reviewed literature (2014 and 2015) attributing papers to the original 20 questions. In total, we reviewed 605 articles in full and from these 355 (59%) were judged to substantively address the 20 key questions, with others focusing on basic science and monitoring. Progress to answering the 20 questions was not uniform, and there were biases regarding focal turtle species, geographic scope and publication outlet. Whilst it offers some meaningful indications as to effort, quantifying peer-reviewed literature output is obviously not the only, and possibly not the best, metric for understanding progress towards informing key conservation and management goals. Along with the literature review, an international group based on the original project consortium was assigned to critically summarise recent progress towards answering each of the 20 questions. We found that significant research is being expended towards global priorities for management and conservation of sea turtles. Although highly variable, there has been significant progress in all the key questions identified in 2010. Undertaking this critical review has highlighted that it may be timely to undertake one or more new prioritizing exercises. For this to have maximal benefit we make a range of recommendations for its execution. These include a far greater engagement with social sciences, widening the pool of contributors and focussing the questions, perhaps disaggregating ecology and conservation.

Endangered Species Research↗
USGS2017

Network analysis of a regional fishery: Implications for management of natural resources, and recruitment and retention of anglers

Angler groups and water-body types interact to create a complex social-ecological system. Network analysis could inform detailed mechanistic models on, and provide managers better information about, basic patterns of fishing activity. Differences in behavior and reservoir selection among angler groups in a regional fishery, the Salt Valley fishery in southeastern Nebraska, USA, were assessed using a combination of cluster and network analyses. The four angler groups assessed ranged from less active, unskilled anglers (group One) to highly active, very skilled anglers (group Four). Reservoir use patterns and the resulting network communities of these four angler groups differed; the number of reservoir communities for these groups ranged from two to three and appeared to be driven by reservoir location (group One), reservoir size and its associated attributes (groups Two and Four), or an interaction between reservoir size and location (group Three). Network analysis is a useful tool to describe differences in participation among angler groups within a regional fishery, and provides new insights about possible recruitment of anglers. For example, group One anglers fished reservoirs closer to home and had a greater probability of dropping out if local reservoir access were restricted.

Fisheries Research↗
USGS2017

Skagit River coho salmon life history model—Users’ guide

Natural resource management is conducted in the context of multiple anthropogenic stressors and is further challenged owing to changing climate. Experiments to determine the effects of climate change on complex ecological systems are nearly impossible. However, using a simulation model to synthesize current understanding of key ecological processes through the life cycle of a fish population can provide a platform for exploring potential effects of and management responses to changing conditions. Potential climate-change scenarios can be imposed, responses can be observed, and the effectiveness of potential actions can be evaluated. This approach is limited owing to future conditions likely deviating in range and timing from conditions used to create the model so that the model is expected to become obsolete. In the meantime, however, the modeling process explicitly states assumptions, clarifies information gaps, and provides a means to better understand which relationships are robust and which are vulnerable to changing climate by observing whether and why model output diverges from actual observations through time. The purpose of the model described herein is to provide such a decision-support tool regarding coho ( Oncorhynchus kisutch ) salmon for the Sauk-Suiattle Indian Tribe of Washington State. The Skagit coho salmon model is implemented in a system dynamics format and has three primary stocks—(1) predicted smolts, (2) realized smolts, and (3) escapement. “Predicted smolts” are the number of smolts expected based on the number of spawners in any year and the Ricker production curve. Pink salmon ( Oncorhynchus gorbuscha ) return to the Skagit River in odd years, and when they overlap with juvenile rearing coho salmon, coho smolt production is substantially higher than in non-pink years. Therefore, the model uses alternative Ricker equations to predict smolts depending on whether their juvenile year was a pink or non-pink year. The stock “realized smolts” is calculated based on the expected effect of streamflow conditions to alter the productivity predicted by the Ricker curve. Adverse conditions include scouring flow events that occur when redds are present; high-flow events during winter on juveniles, which can cause fish displacement and adverse water turbidity; and extremely low flows in summer. The stock “escapement” represents the fish remaining after accounting for ocean mortality and harvest. Ocean mortality has been linked with indices of ocean conditions, which are related to ocean biological productivity. Ocean survival also may have a density-dependent component such that lower survival is associated with higher numbers of smolts. The model allows the user to change certain model parameters and inputs, and choose among alternative predictors for certain modeled relations.

Washington↗
USGS2025

The value of reducing uncertainties to support the management of a high‐elevation endemic salamander

Many salamander populations are declining, and methods to determine how best to allocate limited resources to slow or reverse these declines could support land managers in their decision‐making processes. Multiple types of uncertainty may delay management decisions, including when (1) knowledge of a species' ecology is incomplete, (2) climate change effects on environmental covariates are uncertain, and (3) the efficacy of management alternatives is unknown. For management decisions, a value‐of‐information analysis can identify which uncertainties are critical to reduce in order to identify an optimal strategy from a set of possible management actions. If the same management action is optimal across the full range of uncertainties, then resources for research can be redirected toward active management. Using value‐of‐information analyses, we examine the effect of uncertainty on identifying optimal management to maximize the future expected occupancy of Plethodon shenandoah , a Federally Endangered high‐elevation endemic salamander that is threatened by climate change. Out of 11 management actions proposed by National Park Service managers, those that increase environmental moisture are expected to maximize occupancy, and we find that the selection of this action is robust to all the identified uncertainties. We show that, even in systems with multiple sources of large uncertainty, value of information analyses discriminate among investments in species management.

Ecosphere↗
USGS2021

Widespread use of the nitrification inhibitor nitrapyrin: Assessing benefits and costs to agriculture, ecosystems, and environmental health

Agricultural production and associated applications of nitrogen (N) fertilizers have increased dramatically in the last century, and current projections to 2050 show that demands will continue to increase as the human population grows. Applied in both organic and inorganic fertilizer forms, N is an essential nutrient in crop productivity. Increased fertilizer applications, however, create the potential for more N loss before plant uptake. One strategy for minimizing N loss is the use of enhanced efficiency fertilizers, fortified with a nitrification inhibitor, such as nitrapyrin. In soils and water, nitrapyrin inhibits the activity of ammonia monooxygenase, a microbial enzyme that catalyzes the first step of nitrification from ammonium to nitrite. Potential benefits of using nitrification inhibitors range from reduced nitrate leaching and nitrous oxide emissions to increased crop yield. The extent of these benefits, however, depends on environmental conditions and management practices. Thus, such benefits are not always realized. Additionally, nitrapyrin has been shown to transport off-field, and it is unknown what effects environmental nitrapyrin could have on nontarget organisms and the ecological nitrogen cycle. Here, we review the agronomic and environmental benefits and costs of nitrapyrin use and present a series of research questions and considerations to be addressed with future nitrification inhibitor research.

Environmental Science and Technology↗
USGS2024

Biogeochemical and community ecology responses to the wetting of non-perennial streams

Transitions between dry and wet hydrologic states are the defining characteristic of non-perennial rivers and streams, which constitute the majority of the global river network. Although past work has focused on stream drying characteristics, there has been less focus on how hydrology, ecology and biogeochemistry respond and interact during stream wetting. Wetting mechanisms are highly variable and can range from dramatic floods and debris flows to gradual saturation by upwelling groundwater. This variation in wetting affects ecological and biogeochemical functions, including nutrient processing, sediment transport and the assembly of biotic communities. Here we synthesize evidence describing the hydrological mechanisms underpinning different types of wetting regimes, the associated biogeochemical and organismal responses, and the potential scientific and management implications for downstream ecosystems. This combined multidisciplinary understanding of wetting dynamics in non-perennial streams will be key to predicting and managing for the effects of climate change on non-perennial ecosystems.

Nature Water↗
USGS2017

Using object-based image analysis to conduct high-resolution conifer extraction at regional spatial scales

The distribution and abundance of pinyon ( Pinus monophylla ) and juniper ( Juniperus osteosperma, J. occidentalis ) trees (hereinafter, "pinyon-juniper") in sagebrush ( Artemisia spp.) ecosystems of the Great Basin in the Western United States has increased substantially since the late 1800s. Distributional expansion and infill of pinyon-juniper into sagebrush ecosystems threatens the ecological function and economic viability of these ecosystems within the Great Basin, and is now a major contemporary challenge facing land and wildlife managers. Particularly, pinyon-juniper encroachment into intact sagebrush ecosystems has been identified as a primary threat facing populations of greater sage-grouse ( Centrocercus urophasianus ; hereinafter, "sage-grouse"), which is a sagebrush obligate species. Even seemingly innocuous scatterings of isolated pinyon-juniper in an otherwise intact sagebrush landscape can negatively affect survival and reproduction of sage-grouse. Therefore, accurate and high-resolution maps of pinyon-juniper distribution and abundance (indexed by canopy cover) across broad geographic extents would help guide land management decisions that better target areas for pinyon-juniper removal projects (for example, fuel reduction, habitat improvement for sage-grouse, and other sagebrush species) and facilitate science that further quantifies ecological effects of pinyon-juniper encroachment on sage-grouse populations and sagebrush ecosystem processes . Hence, we mapped pinyon-juniper (referred to as conifers for actual mapping) at a 1 × 1-meter (m) high resolution across the entire range of previously mapped sage-grouse habitat in Nevada and northeastern California. We used digital orthophoto quad tiles from National Agriculture Imagery Program (2010, 2013) as base imagery, and then classified conifers using automated feature extraction methodology with the program Feature Analyst ™ . This method relies on machine learning algorithms that extract features from imagery based on their spectral and spatial signatures. We classified conifers in 6,230 tiles and then tested for errors of omission and commission using confusion matrices. Accuracy ranged from 79.1 to 96.8, with an overall accuracy of 84.3 percent across all mapped areas. An estimated accuracy coefficient (kappa) indicated substantial to nearly perfect agreement, which varied across mapped areas. For this mapping process across the entire mapping extent, four sets of products are available at https://doi.org/10.5066/F7348HVC , including (1) a shapefile representing accuracy results linked to mapping subunits; (2) binary rasters representing conifer presence or absence at a 1 × 1 m resolution; (3) a 30 × 30 m resolution raster representing percentages of conifer canopy cover within each cell from 0 to 100; and (4) 1 × 1 m resolution canopy cover classification rasters derived from a 50-m-radius moving window analysis. The latter two products can be reclassified in a geographic information system (GIS) into user-specified bins to meet different objectives, which include approximations for phases of encroachment. These products complement, and in some cases improve upon, existing conifer maps in the Western United States, and will help facilitate sage-grouse habitat management and sagebrush ecosystem restoration.

California, Nevada↗
USGS2017

Full annual cycle climate change vulnerability assessment for migratory birds

Climate change is a serious challenge faced by all plant and animal species. Climate change vulnerability assessments (CCVAs) are one method to assess risk and are increasingly used as a tool to inform management plans. Migratory animals move across regions and continents during their annual cycles where they are exposed to diverse climatic conditions. Climate change during any period and in any region of the annual cycle could influence survival, reproduction, or the cues used to optimize timing of migration. Therefore, CCVAs for migratory animals best estimate risk when they include climate exposure during the entire annual cycle. We developed a CCVA incorporating the full annual cycle and applied this method to 46 species of migratory birds breeding in the Upper Midwest and Great Lakes (UMGL) region of the United States. Our methodology included background risk, climate change exposure × climate sensitivity, adaptive capacity to climate change, and indirect effects of climate change. We compiled information about migratory connectivity between breeding and stationary non-breeding areas using literature searches and U.S. Geological Survey banding and re-encounter data. Climate change exposure (temperature and moisture) was assessed using UMGL breeding season climate and winter climate from non-breeding regions for each species. Where possible, we focused on non-breeding regions known to be linked through migratory connectivity. We ranked 10 species as highly vulnerable to climate change and two as having low vulnerability. The remaining 34 species were ranked as moderately vulnerable. In general, including non-breeding data provided more robust results that were highly individualistic by species. Two species were found to be highly vulnerable throughout their annual cycle. Projected drying will have the greatest effect during the non-breeding season for species overwintering in Mexico and the Caribbean. Projected temperature increases will have the greatest effect during the breeding season in UMGL as well as during the non-breeding season for species overwintering in South America. We provide a model for adaptive management of migratory animals in the face of projected climate change, including identification of priority species, research needs, and regions within non-breeding ranges for potential conservation partnerships.

Ecological Applications↗