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At least 541 records · Page 30Linked to original sources
USGS2018

A guide to calculating habitat-quality metrics to inform conservation of highly mobile species

Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations. Considerations for Resource Managers Management objectives, proposed actions, data availability and quality, and model assumptions are all relevant considerations when applying and interpreting habitat-quality metrics. Graph-based metrics answer questions related to habitat centrality and connectivity, are suitable for populations with any movement pattern, quantify basic spatial and temporal patterns of occupancy and movement, and require the least data. Occupancy-based metrics answer questions about likelihood of persistence or colonization, are suitable for populations that undergo localized extinctions, quantify spatial and temporal patterns of occupancy and movement, and require a moderate amount of data. Demographic-based metrics answer questions about relative or absolute population size, are suitable for populations with any movement pattern, quantify demographic processes and population dynamics, and require the most data. More real-world examples applying occupancy-based, agent-based, and continuous-based metrics to seasonally migratory species are needed to better understand challenges and opportunities for applying these metrics more broadly.

Natural Resource Modeling↗
USGS2025

Bridging theory and practice to inform seed selection for restoration

Introduction Land managers often face the critical decision of what plant materials to select for ecological restoration. Selection depends on factors that span ecological conditions and human interventions in the restoration process, which can strongly influence the recovery of a degraded ecosystem. Objectives To improve the seed selection process, we compared scientific literature and guidance from five federal agencies to bridge seed selection “theory” and “practice” in the interior western and central United States. Methods We extracted recurring themes and keywords associated with abiotic, biotic, land management, and producer practices that influence seed selection and analyzed their proportional use between agency guidance and scientific literature. Results We identified significant overlap between key concepts in guidance and literature, highlighting the interconnectedness between science and management. However, nuanced patterns emerged across seed selection themes, including more focus in the literature on local adaptation and genetic structure, ramifications of introducing gene flow and artificial selection during plant production, and provenancing strategies to address changing climatic conditions. In contrast, agency guidance focused on genetically appropriate and environmentally suitable seed selection and practical concerns, including seed cost, availability, and diversity. Seed selection studies in the literature were concentrated in the Great Basin and Colorado Plateau, scattered in the Great Plains, and were largely experimental. Conclusions Our review suggests new opportunities for co-production of science and decision-making frameworks among researchers, land managers, and seed producers to inform seed selection guidance for restoration.

Restoration Ecology↗
USGS2002

Geographic information systems compilation of geophysical, geologic, and tectonic data for the Bering Shelf, Chukchi Sea, Arctic margin, and adjacent landmasses

The accompanying CD-ROM contains a compilation of geophysical, geologic, and tectonic data for the Bering Shelf, the Chukchi Sea, the Arctic margin, and adjacent landmasses. These data sets focus on Alaska, the Russian Far East, and the continental shelves that link these two landmasses. For compatibility with other available geographic information system (GIS) products, our GIS compilation extends from 120°E to 115°W, and from 40°N to 80°N. This area encompasses the region from the modern Paciµc plate boundary of the Japan, Kurile, and Aleutian subduction zones, the Queen Charlotte transform fault, and the Cascadia subduction zone (in the south) to the continent-ocean transition from the Eurasian and North American continents to the Arctic Ocean (in the north); and from the diffuse Eurasian–North American plate boundary, including the probable Okhotsk plate (in the west) to the Alaskan-Canadian Cordilleran fold belt (in the east). The CD-ROM comprises thematic layers of spatial data sets for topography, gravity µeld, magnetic µeld, earthquakes, volcanoes, geology, tectonostratigraphic terranes, and cultural reference features, and also includes metadata (data about the data) for all these data sets. The spatial data sets can be viewed, analyzed, and plotted with commercial GIS software (ArcView and ARC/Info) or through a freeware program (ArcExplorer) that is included on this CD-ROM. This GIS compilation provides data for studies of the Mesozoic and Cenozoic collisional and accretionary tectonics that assembled this continental crust and of the neotectonics of active and passive plate margins in this region, and for constructing and interpreting geophysical, geologic, and tectonic models of the region.

Alaska↗
USGS2024

Incorporating life history diversity in an integrated population model to inform viability analysis

Life history diversity can significantly affect population dynamics and effects of management actions. For instance, variation in individual responses to environmental variability can reduce extirpation risk to populations, as the portfolio effect dampens temporal variability in abundance. Moreover, differences in habitat use may cause individuals to respond differently to habitat management and climate variability. To explore the role of life history diversity in population trajectories, population models need to incorporate within-population variation. Integrated population modeling (IPM) is a population modeling approach that offers several advantages for sharing information and propagating uncertainty across datasets. In this study, we developed an IPM for an endangered population of Chinook salmon ( Oncorhynchus tshawytscha ) in the Wenatchee River, Washington, USA, that accounts for diversity in juvenile life histories, spawning location, and return age. Our analysis revealed that diversity in the age of juvenile emigration from natal streams had a portfolio effect, resulting in a 20% reduction in year-to-year variability in adult abundance in population projections. Our population viability analysis suggests that management interventions may be necessary to meet recovery goals, and our model should be useful for simulating the outcomes of proposed actions.

Washington↗
USGS2017

Mapping informal small-scale mining features in a data-sparse tropical environment with a small UAS

This study evaluates the use of a small unmanned aerial system (UAS) to collect imagery over artisanal mining sites in West Africa. The purpose of this study is to consider how very high-resolution imagery and digital surface models (DSMs) derived from structure-from-motion (SfM) photogrammetric techniques from a small UAS can fill the gap in geospatial data collection between satellite imagery and data gathered during field work to map and monitor informal mining sites in tropical environments. The study compares both wide-angle and narrow field of view camera systems in the collection and analysis of high-resolution orthoimages and DSMs of artisanal mining pits. The results of the study indicate that UAS imagery and SfM photogrammetric techniques permit DSMs to be produced with a high degree of precision and relative accuracy, but highlight the challenges of mapping small artisanal mining pits in remote and data sparse terrain.

Journal of Unmanned Vehicle Systems↗
USGS2006

Improving data analysis in herpetology: Using Akaike's information criterion (AIC) to assess the strength of biological hypotheses

In ecology, researchers frequently use observational studies to explain a given pattern, such as the number of individuals in a habitat patch, with a large number of explanatory (i.e., independent) variables. To elucidate such relationships, ecologists have long relied on hypothesis testing to include or exclude variables in regression models, although the conclusions often depend on the approach used (e.g., forward, backward, stepwise selection). Though better tools have surfaced in the mid 1970's, they are still underutilized in certain fields, particularly in herpetology. This is the case of the Akaike information criterion (AIC) which is remarkably superior in model selection (i.e., variable selection) than hypothesis-based approaches. It is simple to compute and easy to understand, but more importantly, for a given data set, it provides a measure of the strength of evidence for each model that represents a plausible biological hypothesis relative to the entire set of models considered. Using this approach, one can then compute a weighted average of the estimate and standard error for any given variable of interest across all the models considered. This procedure, termed model-averaging or multimodel inference, yields precise and robust estimates. In this paper, I illustrate the use of the AIC in model selection and inference, as well as the interpretation of results analysed in this framework with two real herpetological data sets. The AIC and measures derived from it is should be routinely adopted by herpetologists. ?? Koninklijke Brill NV 2006.

Amphibia-Reptilia↗
USGS2019

Advancing barrier island habitat mapping using landscape position information

Barrier islands are dynamic ecosystems that change gradually from coastal processes, including currents and tides, and rapidly from episodic events, such as storms. These islands provide many important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. Habitat maps, developed by scientists, provide a critical tool for monitoring changes to these dynamic ecosystems. Barrier island monitoring often requires custom habitat maps due to several factors, including island size and the classification of unique geomorphology-based habitats, such as beach, dune, and barrier flats. In this study, we reviewed barrier-island-specific habitat mapping efforts and highlighted common habitat class types, source data, and mapping approaches. We also developed a framework for mapping geomorphology-based barrier island habitats using a rule-based, geographic object-based image analysis approach, which included the use of field data, tide data, high-resolution orthophotography, and lidar data. This framework integrates several barrier island mapping advancements with regard to the use of landscape position information for automated dune extraction and the use of Monte Carlo analyses for the treatment of elevation uncertainty for elevation-dependent habitats. Specifically, we used the uncertainty analyses to refine automated dune delineation based on elevation relative to extreme storm water levels and to increase the accuracy of intertidal and supratidal/upland habitat delineation. We found that dune extraction results were enhanced when elevation relative to storm water levels and visual interpretation were also applied. This framework could also be applied to beach–dune systems found along a mainland.

Alabama↗
USGS2025

Lessons in business recovery following the 2023 Kahramanmaraş earthquake sequence, Türkiye informed by women entrepreneurs

On 6 February 2023, Southern Türkiye was hit by devastating earthquakes, directly affecting over 14 million people in 11 cities, causing more than 50,000 deaths and the destruction of more than 800,000 buildings. This article goes beyond the physical damage imposed by the catastrophe to discuss the effects of the earthquakes on the operations of women-owned businesses. The mixed-method study with entrepreneurs belonging to a women’s business association operating in a moderately disrupted part of the region explores their struggles and recovery expectations. Thirty-five questionnaires were analyzed to identify the reasons for business closure, challenges, and needs faced in the post-disaster period and their recovery strategies. In addition, 23 entrepreneurs participated in roundtable discussions to provide a broader context to their responses to survey topics as well as lessons learned. Across both the survey and roundtables, while many respondents reported minor physical damage to their building, they also experienced financial and personal challenges from disruption to equipment, infrastructure, services, supply chains, institutional decisions, employee well-being, and customer base. Many used their business resources and personal savings to assist employees and others in the community. The women entrepreneurs often felt their recovery needs were ignored by government and private relief organizations and encountered barriers to receiving assistance from public and private institutions. Organizing together as women in business, even informally, provided mutual support during the crisis and recovery periods and catalyzed their role in support of their communities. The results illuminate functional community recovery as a balance of recovery of built infrastructure functionality and recovery of the broader social and economic fabric of the community.

southern Turkey↗
USGS2016

State-dependent resource harvesting with lagged information about system states

Markov decision processes (MDPs), which involve a temporal sequence of actions conditioned on the state of the managed system, are increasingly being applied in natural resource management. This study focuses on the modification of a traditional MDP to account for those cases in which an action must be chosen after a significant time lag in observing system state, but just prior to a new observation. In order to calculate an optimal decision policy under these conditions, possible actions must be conditioned on the previous observed system state and action taken. We show how to solve these problems when the state transition structure is known and when it is uncertain. Our focus is on the latter case, and we show how actions must be conditioned not only on the previous system state and action, but on the probabilities associated with alternative models of system dynamics. To demonstrate this framework, we calculated and simulated optimal, adaptive policies for MDPs with lagged states for the problem of deciding annual harvest regulations for mallards (Anas platyrhynchos) in the United States. In this particular example, changes in harvest policy induced by the use of lagged information about system state were sufficient to maintain expected management performance (e.g. population size, harvest) even in the face of an uncertain system state at the time of a decision.

PLoS ONE↗
USGS2020

Combining genetic and demographic monitoring better informs conservation of an endangered urban snake

Conversion and fragmentation of wildlife habitat often leads to smaller and isolated populations and can reduce a species’ ability to disperse across the landscape. As a consequence, genetic drift can quickly lower genetic variation and increase vulnerability to extirpation. For species of conservation concern, quantification of population size and connectivity can clarify the influence of genetic drift in local populations and provides important information for conservation management and recovery strategies. Here, we used genome-wide single nucleotide polymorphism (SNP) data and capture-mark-recapture methods to evaluate the genetic diversity and demography within seven focal sites of the endangered San Francisco gartersnake ( Thamnophis sirtalis tetrataenia ), a species affected by alteration and isolation of wetland habitats throughout its distribution. The primary goals were to determine the population structure and degree of genetic isolation among T . s . tetrataenia populations and estimate effective size and population abundance within sites to better understand the present and future importance of genetic drift. We also used temporally sampled datasets to examine the magnitude of genetic change over time. We found moderate population genetic structure throughout the San Francisco Peninsula that partitions sites into northern and southern regional clusters. Point estimates of both effective size and population abundance were generally small (≤ 100) for a majority of the sites, and estimates were particularly low in the northern populations. Genetic analyses of temporal datasets indicated an increase in genetic differentiation, especially for the most geographically isolated sites, and decreased genetic diversity over time in at least one site (Pacifica). Our results suggest that drift-mediated processes as a function of small population size and reduced connectivity from neighboring populations may decrease diversity and increase differentiation. Improving genetic diversity and connectivity among T . s . tetrataenia populations could promote persistence of this endangered snake.

California↗
USGS2022

Modeling protected species distributions and habitats to inform siting and management of pioneering ocean industries: A case study for Gulf of Mexico aquaculture

Marine Spatial Planning (MSP) provides a process that uses spatial data and models to evaluate environmental, social, economic, cultural, and management trade-offs when siting (i.e., strategically locating) ocean industries. Aquaculture is the fastest-growing food sector in the world. The United States (U.S.) has substantial opportunity for offshore aquaculture development given the size of its exclusive economic zone, habitat diversity, and variety of candidate species for cultivation. However, promising aquaculture areas overlap many protected species habitats. Aquaculture siting surveys, construction, operations, and decommissioning can alter protected species habitat and behavior. Additionally, aquaculture-associated vessel activity, underwater noise, and physical interactions between protected species and farms can increase the risk of injury and mortality. In 2020, the U.S. Gulf of Mexico was identified as one of the first regions to be evaluated for offshore aquaculture opportunities as directed by a Presidential Executive Order. We developed a transparent and repeatable method to identify aquaculture opportunity areas (AOAs) with the least conflict with protected species. First, we developed a generalized scoring approach for protected species that captures their vulnerability to adverse effects from anthropogenic activities using conservation status and demographic information. Next, we applied this approach to data layers for eight species listed under the Endangered Species Act, including five species of sea turtles, Rice’s whale, smalltooth sawfish, and giant manta ray. Next, we evaluated four methods for mathematically combining scores (i.e., Arithmetic mean, Geometric mean, Product, Lowest Scoring layer) to generate a combined protected species data layer. The Product approach provided the most logical ordering of, and the greatest contrast in, site suitability scores. Finally, we integrated the combined protected species data layer into a multi-criteria decision-making modeling framework for MSP. This process identified AOAs with reduced potential for protected species conflict. These modeling methods are transferable to other regions, to other sensitive or protected species, and for spatial planning for other ocean-uses.

PLoS ONE↗
USGS2024

Predicting the spatial distribution of wintering golden eagles to inform full annual cycle conservation in western North America

Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species’ habitat preferences vary among seasons, age-classes, geographic regions, or other factors. Conservation of golden eagles ( Aquila chrysaetos ) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated–winter–and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult “floaters”, and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2% contribution), vegetation and landcover (27.9%), topography (14%), climate and weather (9.4%), and ecoregion (8.7%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10% quantile) occurred on private lands (55%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33%), but higher concentration of high-use habitat than expected for their area (1.5–1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.

PLoS ONE↗
USGS2025

A partner-driven decision support model to inform the reintroduction of bull trout

Assessments of species reintroductions involve a series of complex decisions that include human perspectives and ecological contexts. Here, we present a reintroduction assessment involving bull trout ( Salvelinus confluentus ) using a structured decision-making process. We approached this assessment by engaging partners representing public utilities, government agencies, and Tribes with shared interests in a potential reintroduction. These individuals identified objectives, decision alternatives, and ecological scenarios that were incorporated into a co-produced simulation-based model of potential reintroduction outcomes. The model included mathematical representations of habitat availability, life history expression, and assumptions regarding constraints on potential bull trout populations. Within each recipient stream, partners chose to explore a wide range of decision alternatives and simulated scenarios affecting reintroduction success. Results suggested that 1) reintroductions using eggs or adults were most optimal, 2) adding more individuals resulted in diminishing returns, 3) access to migratory habitat could improve success, and 4) the diversity of opportunities for life history expression led to improved reintroduction opportunities. In addition, modeled scenarios indicated some recipient streams consistently produced lower abundance of reintroduced bull trout. This work contributes a novel example to a growing portfolio of reintroduction assessments that may inform future conservation for bull trout and many other species facing similar challenges.

Washington↗
USGS2024

Improving how science informs policy within the Ecosystem Approach

Science is fundamental to sound policies, particularly when it comes to implementing an Ecosystem Approach. Science can and should inform nearly all facets of an Ecosystem Approach, yet challenges remain to realizing this goal. To help identify and better understand these challenges we used a qualitative comparative case study approach to identify and characterize the challenges and successes of implementing a science-driven Ecosystem Approach in the Laurentian Great Lakes. These case studies include delisting of Areas of Concern, improving coastal resilience, and addressing declining offshore lake productivity. These case studies were selected because they provide a set of very different, yet complementary, cases for assessing implementation, as well as the factors influencing the science-policy exchange. Through this comparative study, we identified a diverse set of challenges and successes, that were both systemic and case specific. Emerging from this comparative assessment were principles and enabling conditions (e.g. scale, governance, shared goals) we believe are critical to consider when establishing or improving a science-driven Ecosystem Approach.

Aquatic Ecosystem Health & Management↗
USGS2015

Valuing geospatial information: Using the contingent valuation method to estimate the economic benefits of Landsat satellite imagery

While the U.S. government does not charge for downloading Landsat images, the images have value to users. This paper demonstrates a method that can value Landsat and other imagery to users. A survey of downloaders of Landsat images found: (a) established US users have a mean value of $912 USD per scene; (b) new US users and users returning when imagery became free have a mean value of $367 USD per scene. Total US user benefits for the 2.38 million scenes downloaded is $1.8 billion USD. While these benefits indicate a high willingness-to-pay among many Landsat downloaders, it would be economically inefficient for the US government to charge for Landsat imagery. Charging a price of $100 USD a scene would result in an efficiency loss of $37.5 million a year. This economic information should be useful to policy-makers who must decide about the future of this and similar remote sensing programs.

Photogrammetric Engineering and Remote Sensing↗
USGS2011

Top 40 priorities for science to inform conservation and management policy in the United States

To maximize the utility of research to decisionmaking, especially given limited financial resources, scientists must set priorities for their efforts. We present a list of the top 40 high-priority, multidisciplinary research questions directed toward informing some of the most important current and future decisions about management of species, communities, and ecological processes in the United States. The questions were generated by an open, inclusive process that included personal interviews with decisionmakers, broad solicitation of research needs from scientists and policymakers, and an intensive workshop that included scientifically oriented individuals responsible for managing and developing policy related to natural resources. The process differed from previous efforts to set priorities for conservation research in its focus on the engagement of decisionmakers in addition to researchers. The research priorities emphasized the importance of addressing societal context and exploration of trade-offs among alternative policies and actions, as well as more traditional questions related to ecological processes and functions.

BioScience↗
USGS2003

Improving size estimates of open animal populations by incorporating information on age

Around the world, a great deal of effort is expended each year to estimate the sizes of wild animal populations. Unfortunately, population size has proven to be one of the most intractable parameters to estimate. The capture-recapture estimation models most commonly used (of the Jolly-Seber type) are complicated and require numerous, sometimes questionable, assumptions. The derived estimates usually have large variances and lack consistency over time. In capture–recapture studies of long-lived animals, the ages of captured animals can often be determined with great accuracy and relative ease. We show how to incorporate age information into size estimates for open populations, where the size changes through births, deaths, immigration, and emigration. The proposed method allows more precise estimates of population size than the usual models, and it can provide these estimates from two sample occasions rather than the three usually required. Moreover, this method does not require specialized programs for capture-recapture data; researchers can derive their estimates using the logistic regression module in any standard statistical package.

BioScience↗
USGS2004

The Global Invasive Species Information Network: What's in it for you?

A well-known article in BioScience — probably the most widely cited scientific study on invasive species in recent years—calculated the annual cost of invasive species in the United States alone at $138 billion per year (Pimentel et al. 2000). The total annual cost of invasive species to human societies worldwide can therefore be estimated to be in the hundreds of billions of dollars, including the costs of control, detrimental effects on human health, and losses in agricultural production and ecosystem services. This enormous sum far exceeds the combined annual cost of all natural disasters (Munich Re Group 2004), making the problem of invasive species in both agricultural and natural ecosystems a high-priority issue. But there is hope for counteracting the invasive species challenge, and much of that hope stems from new strategies being developed for managing information about invasive species and their effects.

BioScience↗