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USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗

USGS2025

Does habitat or climate change drive species range shifts?

A primary prediction of climate change ecology is that species will track their climate niche poleward and upslope. However, studies have shown species responding in surprising ways. In this study, we aim to understand the impact of global change on species ranges by considering both climate and habitat changes. Using occupancy analysis of acoustic survey data in the mountains of the northeastern United States, we tested specific predictions of range responses to warming (shifting upslope), precipitation change (shifting downslope), and forest composition change (shifting downslope). We found that American red squirrels Tamiasciurus hudsonicus , key nodes in northern North American food webs, are not tracking increasing temperatures upslope, despite substantial warming in recent decades. Structural equation modeling indicates that red squirrel abundance is primarily influenced by red-spruce forest cover, which has shifted downslope with recovery from historical logging and acid deposition. Accounting for the multiple dimensions of global change will enable better predictions and more effective conservation strategies.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2020

Conservation genomics in a changing arctic

Although logistically challenging to study, the Arctic is a bellwether for global change and is becoming a model for questions pertinent to the persistence of biodiversity. Disruption of Arctic ecosystems is accelerating, with impacts ranging from mixing of biotic communities to individual behavioral responses. Understanding these changes is crucial for conservation and sustainable economic development. Genomic approaches are providing transformative insights into biotic responses to environmental change, but have seen limited application in the Arctic due to a series of limitations. To meet the promise of genome analyses, we urge rigorous development of biorepositories from high latitudes to provide essential libraries to improve the conservation, monitoring, and management of Arctic ecosystems through genomic approaches.

Trends in Ecology and Evolution↗

USGS2006

Planning for robust reserve networks using uncertainty analysis

Planning land-use for biodiversity conservation frequently involves computer-assisted reserve selection algorithms. Typically such algorithms operate on matrices of species presence?absence in sites, or on species-specific distributions of model predicted probabilities of occurrence in grid cells. There are practically always errors in input data?erroneous species presence?absence data, structural and parametric uncertainty in predictive habitat models, and lack of correspondence between temporal presence and long-run persistence. Despite these uncertainties, typical reserve selection methods proceed as if there is no uncertainty in the data or models. Having two conservation options of apparently equal biological value, one would prefer the option whose value is relatively insensitive to errors in planning inputs. In this work we show how uncertainty analysis for reserve planning can be implemented within a framework of information-gap decision theory, generating reserve designs that are robust to uncertainty. Consideration of uncertainty involves modifications to the typical objective functions used in reserve selection. Search for robust-optimal reserve structures can still be implemented via typical reserve selection optimization techniques, including stepwise heuristics, integer-programming and stochastic global search.

Ecological Modelling↗

USGS2021

Mapping out a future for ungulate migrations

Migration of ungulates (hooved mammals) is a fundamental ecological process that promotes abundant herds, whose effects cascade up and down terrestrial food webs. Migratory ungulates provide the prey base that maintains large carnivore and scavenger populations and underpins terrestrial biodiversity (fig. S1). When ungulates move in large aggregations, their hooves, feces, and urine create conditions that facilitate distinct biotic communities. The migrations of ungulates have sustained humans for thousands of years, forming tight cultural links among Indigenous people and local communities. Yet ungulate migrations are disappearing at an alarming rate ( 1 ). Efforts by wildlife managers and conservationists are thwarted by a singular challenge: Most ungulate migrations have never been mapped in sufficient detail to guide effective conservation. Without a strategic and collaborative effort, many of the world's great migrations will continue to be truncated, severed, or lost in the coming decades. Fortunately, a combination of animal tracking datasets, historical records, and local and Indigenous knowledge can form the basis for a global atlas of migrations, designed to support conservation action and policy at local, national, and international levels.

Science↗

USGS1998

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Information and Technology Report↗

USGS2018

Using the value of information to improve conservation decision making

Conservation decisions are challenging, not only because they often involve difficult conflicts among outcomes that people value, but because our understanding of the natural world and our effects on it is fraught with uncertainty. Value of Information (VoI) methods provide an approach for understanding and managing uncertainty from the standpoint of the decision maker. These methods are commonly used in other fields (e.g., economics, public health) and are increasingly used in biodiversity conservation. This decision analytical approach can identify the best management alternative to select where the effectiveness of interventions is uncertain, and can help to decide when to act and when to delay action until after further research. We review the use of VoI in the environmental domain, reflect on the need for greater uptake of VoI, particularly for strategic conservation planning, and suggest promising areas for new research. We also suggest common reporting standards as a means of increasing the leverage of this powerful tool. The environmental science, ecology and biodiversity categories of the Web of Knowledge were searched using the terms ‘Value of Information,’ ‘Expected Value of Perfect Information,’ and the abbreviation ‘EVPI.’ Google Scholar was searched with the same terms, and additionally the terms decision and biology, biodiversity conservation, fish, or ecology. We identified 1225 papers from these searches. Included studies were limited to those that show an application of VoI in biodiversity conservation rather than simply describing the method. All examples of use of VOI were summarised regarding the application of VoI, the management objectives, the uncertainties, models used, how the objectives were measured, and the type of VoI. While the use of VoI appears to be on the increase in biodiversity conservation, the reporting of results is highly variable, which can make it difficult to understand the decision context and which uncertainties were considered. Moreover, it was unclear if, and how, the papers informed management and policy interventions, which is why we suggest a range of reporting standards that would aid the use of VoI. The use of VoI in conservation settings is at an early stage. There are opportunities for broader applications, not only for species-focussed management problems, but also for setting local or global research priorities for biodiversity conservation, making funding decisions, or designing or improving protected area networks and management. The long-term benefits of applying VoI methods to biodiversity conservation include a more structured and decision-focused allocation of resources to research.

Biological Reviews↗

USGS2025

Wet meadow regeneration through restoration of biophysical feedbacks

Wet meadows are globally significant ecosystems that provide critical hydrological, ecological, and biogeochemical functions, yet their extent has declined dramatically due to land use changes and hydrologic alteration. These sedge-dominated wetlands exist at the drier end of the wetland gradient, maintained by shallow groundwater and periodic inundation. This paper is a global synthesis of the ecological, geomorphic, and hydrological dynamics of wet meadows, with an emphasis on alluvial systems, to inform effective restoration strategies. We compare wet meadows to other wetlands, classify them into palustrine, lacustrine, and alluvial types, then focus on alluvial wet meadows and discuss how their formation and persistence depend on ground and surface water interactions, sediment deposition and flow obstructions, all mediated by biological processes. In particular, we highlight the role of hydric graminoids in resisting erosion and maintaining soil cohesion, how beaver promote meadow persistence, and the significance of wet meadows as carbon sinks. We also present stratigraphic evidence demonstrating that incision, often triggered by anthropogenic activity or changing climate, is the primary mechanism of alluvial wet meadow degradation, resulting in water table decline and shifts in vegetation composition. Restoration requires reversing these incisional processes through techniques that elevate water tables, disperse flow and retain sediment—methods traditionally associated with either soil conservation or stream restoration. These include nature-based solutions that create obstructions such as beaver dams and their analogues, rock and wood-based obstructions and incision trench or gully filling and grading. Given their multifunctional value—including but not limited to flood attenuation, biodiversity support, and carbon sequestration—wet meadows warrant a focused restoration framework. This review advocates for a valley-floor scale restoration paradigm that integrates hydrological reconnection, sediment retention, and biological reinforcement to ensure long-term resilience of these systems in the face of changing climate and land use pressures.

Frontiers in Environmental Science↗

USGS2011

Ecoregional-scale monitoring within conservation areas, in a rapidly changing climate

Long-term monitoring of ecological systems can prove invaluable for resource management and conservation. Such monitoring can: (1) detect instances of long-term trend (either improvement or deterioration) in monitored resources, thus providing an early-warning indication of system change to resource managers; (2) inform management decisions and help assess the effects of management actions, as well as anthropogenic and natural disturbances; and (3) provide the grist for supplemental research on mechanisms of system dynamics and cause-effect relationships (Fancy et al., 2009). Such monitoring additionally provides a snapshot of the status of monitored resources during each sampling cycle, and helps assess whether legal standards and regulations are being met. Until the last 1-2 decades, tracking and understanding changes in condition of natural resources across broad spatial extents have been infrequently attempted. Several factors, however, are facilitating the achievement of such broad-scale investigation and monitoring. These include increasing awareness of the importance of landscape context, greater prevalence of regional and global environmental stressors, and the rise of landscape-scale programs designed to manage and monitor biological systems. Such programs include the US Forest Service's Forest Inventory and Analysis (FIA) Program (Moser et al., 2008), Canada's National Forest Inventory, the 3Q Programme for monitoring agricultural landscapes of Norway (Dramstad et al., 2002), and the emerging (US) Landscape Conservation Cooperatives (USDOI Secretarial Order 3289, 2009; Anonymous, 2011). This Special Section explores the underlying design considerations, as well as many pragmatic aspects associated with program implementation and interpretation of results from broad-scale monitoring systems, particularly within the constraints of high-latitude contexts (e.g., low road density, short field season, dramatic fluctuations in temperature). Although Alaska is the focus of most papers in this Special Section, we posit that many of the issues that characterize the remote, relatively undisturbed ecosystems of high northern latitudes are widespread and thus applicable to natural-resource management and conservation across northern portions of the Holarctic ecozone and indeed anywhere broad-scale monitoring is contemplated.

Biological Conservation↗

USGS2014

Downscaled climate projections for the Southeast United States: evaluation and use for ecological applications

Climate change is likely to have many effects on natural ecosystems in the Southeast U.S. The National Climate Assessment Southeast Technical Report (SETR) indicates that natural ecosystems in the Southeast are likely to be affected by warming temperatures, ocean acidification, sea-level rise, and changes in rainfall and evapotranspiration. To better assess these how climate changes could affect multiple sectors, including ecosystems, climatologists have created several downscaled climate projections (or downscaled datasets) that contain information from the global climate models (GCMs) translated to regional or local scales. The process of creating these downscaled datasets, known as downscaling, can be carried out using a broad range of statistical or numerical modeling techniques. The rapid proliferation of techniques that can be used for downscaling and the number of downscaled datasets produced in recent years present many challenges for scientists and decisionmakers in assessing the impact or vulnerability of a given species or ecosystem to climate change. Given the number of available downscaled datasets, how do these model outputs compare to each other? Which variables are available, and are certain downscaled datasets more appropriate for assessing vulnerability of a particular species? Given the desire to use these datasets for impact and vulnerability assessments and the lack of comparison between these datasets, the goal of this report is to synthesize the information available in these downscaled datasets and provide guidance to scientists and natural resource managers with specific interests in ecological modeling and conservation planning related to climate change in the Southeast U.S. This report enables the Southeast Climate Science Center (SECSC) to address an important strategic goal of providing scientific information and guidance that will enable resource managers and other participants in Landscape Conservation Cooperatives to make science-based climate change adaptation decisions.

Open-File Report↗

USGS2007

Population structure and genetic diversity of black redhorse (Moxostoma duquesnei) in a highly fragmented watershed

Dams have the potential to affect population size and connectivity, reduce genetic diversity, and increase genetic differences among isolated riverine fish populations. Previous research has reported adverse effects on the distribution and demographics of black redhorse (Moxostoma duquesnei), a threatened fish species in Canada. However, effects on genetic diversity and population structure are unknown. We used microsatellite DNA markers to assess the number of genetic populations in the Grand River (Ontario) and to test whether dams have resulted in a loss of genetic diversity and increased genetic differentiation among populations. Three hundred and seventy-seven individuals from eight Grand River sites were genotyped at eight microsatellite loci. Measures of genetic diversity were moderately high and not significantly different among populations; strong evidence of recent population bottlenecks was not detected. Pairwise FST and exact tests identified weak (global FST = 0.011) but statistically significant population structure, although little population structuring was detected using either genetic distances or an individual-based clustering method. Neither geographic distance nor the number of intervening dams were correlated with pairwise differences among populations. Tests for regional equilibrium indicate that Grand River populations were either in equilibrium between gene flow and genetic drift or that gene flow is more influential than drift. While studies on other species have identified strong dam-related effects on genetic diversity and population structure, this study suggests that barrier permeability, river fragment length and the ecological characteristics of affected species can counterbalance dam-related effects. ?? 2007 Springer Science+Business Media B.V.

Conservation Genetics↗

USGS2018

International meeting on sarcoptic mange in wildlife, June 2018, Blacksburg, Virginia, USA

Sarcoptic mange is a globally distributed disease caused by the burrowing mite Sarcoptes scabiei , which also causes scabies in humans. A wide and increasing number of wild mammal species are reported to be susceptible to mange; however, the impacts of the disease in wildlife populations, mechanisms involved in its eco-epidemiological dynamics, and risks to public and ecosystem health are still unclear. Major gaps exist concerning S. scabiei host specificity and the mechanisms involved in the different presentations of the disease, which change between individuals and species. Immunological responses to the mite may have a relevant role explaining these different susceptibilities, as these affect the clinical signs, and consequently, the severity of the disease. Recently, some studies have suggested sarcoptic mange as an emerging threat for wildlife, based on several outbreaks with increased severity, geographical expansions, and novel wild hosts affected. Disease ecology experts convened for the “International Meeting on Sarcoptic Mange in Wildlife” on 4–5 June 2018, hosted by the Department of Fish and Wildlife Conservation at Virginia Tech in Blacksburg, Virginia, USA. The meeting had a structure of (i) pre-workshop review; (ii) presentation and discussions; and (iii) identification of priority research questions to understand sarcoptic mange in wildlife. The workgroup concluded that research priorities should be on determining the variation in modes of transmission for S. scabiei in wildlife, factors associated with the variation of disease severity among species, and long-terms effects of the mange in wildlife populations. In this note we summarize the main discussions and research gaps identified by the experts.

Parasites & Vectors↗

USGS2021

Modeling effects of disturbance across life history strategies of stream fishes

A central goal of population ecology is to establish linkages between life history strategy, disturbance, and population dynamics. Globally, disturbance events such as drought and invasive species have dramatically impacted stream fish populations and contributed to sharp declines in freshwater biodiversity. Here, we used RAMAS-Metapop to construct stage-based demographic metapopulation models for stream fishes with periodic, opportunistic, and equilibrium life history strategies and assessed their responses to disturbance scenarios that approximated the effects of invasion, drought, and the additive effects of both disturbances. Our models indicated that populations respond differentially to disturbance based on life history strategy. Equilibrium strategists were best able to deal with simulated invasion. Periodic strategists did well under lower levels of drought, whereas opportunistic strategists outperformed other life histories under extreme seasonal drought. When we modeled additive effects scenarios, these disturbances interacted synergistically, dramatically increasing terminal extinction risk for all three life history strategies. Modeling exercises that examine broad life history categories can help to answer fundamental ecological questions about the relationship between disturbance resilience and life history, as well as help managers to develop generalized conservation strategies when species-specific data are lacking. Our results indicate that life history strategy is a fundamental determinant of population trajectories, and that disturbances can interact synergistically to dramatically impact extinction outcomes.

Oecologia↗

USGS2005

Inventory of the mosses, liverworts, and lichens of Olympic National Park, Washington- Species list

The identification of non-vascular cryptogam species (lichens, mosses, liverworts, and hornworts) is especially challenging because of their small size, their often microscopic or chemical distinguishing features, and their enormous diversity. Consequently, they are a poorly known component of Olympic National Park, despite their ecological and aesthetic importance. This project is the first attempt at a systematic, comprehensive survey of non-vascular cryptogams in the Park and presents the current species list with descriptions of the substrate and vascular vegetation type where they were observed. The authors strove to collect from as many park environments as feasible, and distributed collections along important environmental gradients in different regions of the park using vascular vegetation as an environmental indicator. They also collected opportunistically when interesting habitats or microhabitats were encountered. Finally, the authors updated the nomenclature in the Park’s previous collection of nonvascular plants. This study identified approximately 13,200 bryophyte and lichen species, adding approximately 425 new species to the Olympic National Park Herbarium. These data, combined with select literature reports and personal data from Martin and Karen Hutten, added more than 350 species to the previously documented Olympic Peninsula lichen and bryophyte list. The authors discuss the list in a local, regional, and global context of rarity, as well as cryptogam conservation and further work needed in Olympic National Park. The improved inventory of Olympic National Park cryptogams represented by this project enables Olympic National Park to protect populations of rare and sensitive species, assess the damage caused by illegal harvest, and contribute information to the Bureau of Land Management and U.S. Forest Service Sensitive Species Programs.

Scientific Investigations Report↗

USGS2015

Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities?

Increased land use by polar bears ( Ursus maritimus ) due to climate-change-induced reduction of their sea-ice habitat illustrates the impact of climate change on species distributions and the difficulty of conserving a large, highly specialized carnivore in the face of this global threat. Some authors have suggested that terrestrial food consumption by polar bears will help them withstand sea-ice loss as they are forced to spend increasing amounts of time on land. Here, we evaluate the nutritional needs of polar bears as well as the physiological and environmental constraints that shape their use of terrestrial ecosystems. Only small numbers of polar bears have been documented consuming terrestrial foods even in modest quantities. Over much of the polar bear's range, limited terrestrial food availability supports only low densities of much smaller, resident brown bears ( Ursus arctos ), which use low-quality resources more efficiently and may compete with polar bears in these areas. Where consumption of terrestrial foods has been documented, polar bear body condition and survival rates have declined even as land use has increased. Thus far, observed consumption of terrestrial food by polar bears has been insufficient to offset lost ice-based hunting opportunities but can have ecological consequences for other species. Warming-induced loss of sea ice remains the primary threat faced by polar bears.

Frontiers in Ecology and the Environment↗

USGS2026

Behavioral shifts mask the success of legislation and outreach for endangered species recovery

A fundamental challenge in conservation is assessing the efficacy of recovery actions to optimize endangered species management. Considerable recent attention has focused on effective measures to counter the endangerment of avian scavengers, which have declined worldwide, primarily due to poisoning. One iconic example is efforts to recover the critically endangered California condor ( Gymnogyps californianus ), whose leading cause of death is poisoning from ingesting lead-based ammunition in carcasses. Despite enormous resources expended in California, USA, including implementation of public outreach campaigns and two legislative bans on lead ammunition, lead-related mortality of condors has increased. Here we show that two types of behavioral shifts explain the observed increases in condor lead exposure: wilder foraging and ranging by condors and increased shooting of wild pigs ( Sus scrofa ) by humans. After accounting for these trends, we show that both lead ammunition bans and public outreach efforts have significantly reduced condor blood lead levels in California, lowering mortality. Our analyses uncover a dynamic in which changing ecological conditions mask the true efficacy of legislation and outreach. Given rapid global change, such dynamics are likely operating in many settings, underscoring the importance of comprehensive evaluations of recovery actions, which can be obscured by shifting behaviors and threats.

Baja California, California↗

USGS2024

Milkweed and floral resource availability for monarch butterflies (Danaus plexippus) in the United States

The global decline of pollinators, particularly insects, underscores the importance of enhanced monitoring of their populations and habitats. However, monitoring some pollinator habitat is challenging due to widespread species distributions and shifts in habitat requirements through seasons and life stages. The monarch butterfly ( Danaus plexippus ), a migratory insect pollinator that breeds widely throughout North America, presents a unique case study for testing a sampling framework to overcome these challenges. Monarchs exhibit discrete resource needs across life stages (e.g., larval requirement for milkweed, adult requirement for floral nectar), utilizing many land use types across their extensive geographic range during breeding and migration seasons. The Integrated Monarch Monitoring Program (IMMP) uses a standardized protocol with a generalized random tessellation stratified (GRTS) sampling design to gather spatially balanced and ecologically representative information on monarch habitats within the United States. The IMMP is applicable to various land use types and habitats used by breeding monarchs and may be extended to sites outside of the GRTS design to collect data on non-random sites of interest, such as legacy or conservation sites. Additionally, the IMMP’s modular design and publicly available training allows for broad participation, including involvement from community scientists. Here, we summarize habitat metrics (milkweed and floral resources) across 1,233 sites covering much of the monarch’s breeding range. We examine variation in milkweed density and floral resource availability on probabilistic (random) and non-probabilistic (convenience) samples and among land use types (site types). Additionally, we assess resource availability within core geographies for monarch breeding and migration, specifically within the U.S. Fish and Wildlife Service’s Monarch Conservation Units (western, northern, and southern United States). Milkweed density, floral frequency, and floral richness were higher on non-random sites and in the North region. Among site types, milkweed density was highest on Rights-of-Way and Unclassified Grassland, while floral frequency was lowest on Rights-of-Way. The IMMP represents the first field-based habitat monitoring program of this scale for monarchs, yielding a robust dataset on monarchs and their habitats across their breeding range and offering a framework for surveying the habitat of insect species with diverse habitat requirements or widespread distributions.

Frontiers in Ecology and Evolution↗

USGS2020

Waterfowl occurrence and residence time as indicators of H5 and H7 avian influenza in North American Poultry

Avian inﬂuenza (AI) affects wild aquatic birds and poses hazards to human health, food security, and wildlife conservation globally. Accordingly, there is a recognized need for new methods and tools to help quantify the dynamic interaction between wild bird hosts and commercial poultry. Using satellite-marked waterfowl, we applied Bayesian joint hierarchical modeling to concurrently model species distributions, residency times, migration timing, and disease occurrence probability under an integrated animal movement and disease distribution modeling framework. Our results indicate that migratory waterfowl are positively related to AI occurrence over North America such that as waterfowl occurrence probability or residence time increase at a given location, so too does the chance of a commercial poultry AI outbreak. Analyses also suggest that AI occurrence probability is greatest during our observed waterfowl northward migration, and less during the southward migration. Methodologically, we found that when modeling disparate facets of disease systems at the wildlife-agriculture interface, it is essential that multiscale spatial patterns be addressed to avoid mistakenly inferring a disease process or disease-environment relationship from a pattern evaluated at the improper spatial scale. The study offers important insights into migratory waterfowl ecology and AI disease dynamics that aid in better preparing for future outbreaks.

Scientific Reports↗