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At least 1,621 records · Page 90Linked to original sources
USGS2015

Potamochoerus porcus (Artiodactyla: Suidae)

Potamochoerus porcus (Linnaeus, 1758) is a monotypic suid commonly known as the red river hog. It is 1 of 2 species in the genus Potamochoerus and among the smallest and most plesiomorphic (ancestral) of the 8 African suids. This is the brightest colored wild pig species and is identified by its rufous coat and white dorsal crest; spectacled black-and-white facemask; and elongated, leaf-shaped ears that end in terminally drooping tufts of hair. P. porcus lives in damp forests throughout the rainforest belt of western and central Africa; it never ranges far from thick vegetative cover, soft soils, and water. Although P. porcus is commonly harvested for subsistence and urban bushmeat markets, it is considered of “Least Concern” by the International Union for Conservation of Nature and Natural Resources.

Mammalian Species↗
USGS2016

Priodontes maximus (Cingulata: Chlamyphoridae)

Priodontes maximus ( Kerr, 1792 ), called the giant armadillo, is monotypic and by far the largest extant armadillo. Average adult weight is about 30kg (in captivity, as high as 80kg). Its carapace extends about halfway down its sides, making it impossible to curl up tightly. It is dark brown to black dorsally, with a broad light band around the lower part of its carapace. It primarily digs to escape, enhanced by its 20-cm, sickle-shaped nail on its 3rd forefingers. P. maximus is widely distributed in South America but nowhere abundant. It is affected by habitat loss and fragmentation, agriculture, hunting, collection for museum specimens, and illegal animal trafficking. P. maximus is listed as “Vulnerable” by the International Union for Conservation of Nature and Natural Resources.

Mammalian Species↗
USGS2007

Clean coal initiatives in Indiana

Purpose - Indiana is listed among the top ten coal states in the USA and annually mines about 35 million short tons (million tons) of coal from the vast reserves of the US Midwest Illinois Coal Basin. The implementation and commercialization of clean coal technologies is important to the economy of the state and has a significant role in the state's energy plan for increasing the use of the state's natural resources. Coal is a substantial Indiana energy resource and also has stable and relatively low costs, compared with the increasing costs of other major fuels. This indigenous energy source enables the promotion of energy independence. The purpose of this paper is to outline the significance of clean coal projects for achieving this objective. Design/methodology/approach - The paper outlines the clean coal initiatives being taken in Indiana and the research carried out at the Indiana Center for Coal Technology Research. Findings - Clean coal power generation and coal for transportation fuels (coal-to-liquids - CTL) are two major topics being investigated in Indiana. Coking coal, data compilation of the bituminous coal qualities within the Indiana coal beds, reducing dependence on coal imports, and provision of an emissions free environment are important topics to state legislators. Originality/value - Lessons learnt from these projects will be of value to other states and countries.

International Journal of Energy Sector Management↗
USGS1996

Ecosystem management: A decision support GIS approach

This paper describes a new approach using decision support GIS for handling information in ecosystem management. Technical research efforts resulted in specialized spatial decision support systems for wetland restoration planning, wetland permit analysis, and wildlife research and management. These applications are briefly presented to illustrate the usage of the methodology. With its powerful capabilities in information synthesis, analytical visualization, and spatial simulation and modeling, the decision support GIS provided cost-effective technical tools and a conceptual framework for integrating natural resource management with an ecosystem approach.

Conference Paper↗
USGS2006

The future of imaging spectroscopy - Prospective technologies and applications

Spectroscopy has existed for more than three centuries now. Nonetheless, significant scientific advances have been achieved. We discuss the history of spectroscopy in relation to emerging technologies and applications. Advanced focal plane arrays, optical design, and intelligent on-board logic are prime prospective technologies. Scalable approaches in pre-processing of imaging spectrometer data will receive additional focus. Finally, we focus on new applications monitoring transitional ecological zones, where human impact and disturbance have highest impact as well as in monitoring changes in our natural resources and environment We conclude that imaging spectroscopy enables mapping of biophysical and biochemical variables of the Earth's surface and atmospheric composition with unprecedented accuracy.

Conference Paper↗
USGS2007

TerraLook: Providing easy, no-cost access to satellite images for busy people and the technologically disinclined

Access to satellite images has been largely limited to communities with specialized tools and expertise, even though images could also benefit other communities. This situation has resulted in underutilization of the data. TerraLook, which consists of collections of georeferenced JPEG images and an open source toolkit to use them, makes satellite images available to those lacking experience with remote sensing. Users can find, roam, and zoom images, create and display vector overlays, adjust and annotate images so they can be used as a communication vehicle, compare images taken at different times, and perform other activities useful for natural resource management, sustainable development, education, and other activities.

Conference Paper↗
USGS2010

Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

Connecticut, Georgia, Maine, Maryland, Massachuset↗
USGS2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

Functional Ecology↗
USGS2015

Management applications of discontinuity theory

Human impacts on the environment are multifaceted and can occur across distinct spatiotemporal scales. Ecological responses to environmental change are therefore difficult to predict, and entail large degrees of uncertainty. Such uncertainty requires robust tools for management to sustain ecosystem goods and services and maintain resilient ecosystems. We propose an approach based on discontinuity theory that accounts for patterns and processes at distinct spatial and temporal scales, an inherent property of ecological systems. Discontinuity theory has not been applied in natural resource management and could therefore improve ecosystem management because it explicitly accounts for ecological complexity. Synthesis and applications . We highlight the application of discontinuity approaches for meeting management goals. Specifically, discontinuity approaches have significant potential to measure and thus understand the resilience of ecosystems, to objectively identify critical scales of space and time in ecological systems at which human impact might be most severe, to provide warning indicators of regime change, to help predict and understand biological invasions and extinctions and to focus monitoring efforts. Discontinuity theory can complement current approaches, providing a broader paradigm for ecological management and conservation.

Journal of Applied Ecology↗
USGS2018

Integrating encounter theory with decision analysis to evaluate collision risk and determine optimal protection zones for wildlife

1.Better understanding human‐wildlife interactions and their links with management can help improve the design of wildlife protection zones. One example is the problem of wildlife collisions with vehicles or human‐built structures (e.g. power lines, wind farms). In fact, collisions between marine wildlife and watercraft are among the major threats faced by several endangered species of marine mammals. Natural resource managers are therefore interested in finding cost‐effective solutions to mitigate these threats. 2.We combined abundance estimators with encounter rate theory to estimate relative lethal collision risk of the Florida manatee ( Trichechus manatus latirostris ) from watercraft. We first modeled seasonal abundance of watercraft and manatees using a Bayesian analysis of aerial survey count data. We then modeled relative lethal collision risk in space and across seasons. Finally, we applied decision analysis and Linear Integer Programming to determine the optimal design of speed zones in terms of relative risk to manatees and costs to waterway users. We used a Pareto efficient frontier approach to evaluate the performance of alternative zones, which included additional practical considerations (e.g. spatial aggregation of speed zones) in relation to the optimal zone configurations. 3.Under the various relationships for probability of death given strike speed that we considered, the current speed zones reduced the relative lethal collision risk by an average of 51.5% to 70% compared to the scenario in which all speed regulations were removed (i.e. the no‐protection scenario). We identified optimal zones and near‐optimal zones with additional management considerations that improved upon the current zones in terms of cost or relative risk. 4.Policy Implications : Our analytical framework combines encounter rate theory and decision analysis to quantify the effectiveness of speed zones protecting manatees while accounting for uncertainty. Our approach can be used to optimize the design of protection zones intended to reduce conflicts between human waterborne activity and marine mammals. This framework could be extended to address many other problems of human‐wildlife interactions, such as the optimal placement of wind farms to minimize collisions with wildlife or the optimal allocation of ranger effort to mitigate poaching threats.

Journal of Applied Ecology↗
USGS2021

Integrating socioecological suitability with human-wildlife conflict risk: Case study for translocation of a large ungulate

Translocations are essential for re-establishing wildlife populations. As they sometimes fail, it is critical to assess factors that influence their success pre-translocation. Socioecological suitability models (SESMs) integrate social acceptance and ecological suitability to enable identification of areas where wildlife populations will expand, which makes it likely that SESMs will also be useful for predicting translocation success. To inform site selection for potential elk Cervus canadensis reintroduction to north-eastern Minnesota, United States, we developed broadscale maps of social acceptance from surveys of local residents and landowners, animal use equivalence (AUE) from forage measured in the field and empirical conflict risk from geospatial data. Resulting SESMs integrated social acceptance favourability scores, AUE and conflict risk, and weighted SESMs showed the relative influences of acceptance and conflict. Social acceptance was positive for local residents and landowners (mean ≥ 5.4; scale of 1–7). AUE (scaled to an elk home range) ranged between 1 and 9 elk/16 km 2 during winter, and from 14 to 83 elk/16 km 2 during summer. Human–elk conflict risk was low (mean ≤ 0.10; scaled 0–1), increasing from north to south. Geographical distributions differed for social acceptance, AUE and conflict risk, and weighted SESMs revealed unsuitable areas that were otherwise obscured. Synthesis and applications . Integrating human–wildlife conflict risk into SESMs shows where social acceptance of translocated species is likely to erode, even where viewed favourably pre-translocation, to inform translocation planning by highlighting interactions between key factors. Such integrated models supplement existing reintroduction biology frameworks by supporting decision-making and knowledge development. In north-eastern Minnesota, natural resource managers who are considering elk reintroductions are using SESMs reported here to identify where human–elk conflict is unlikely to result in an isolated elk population and where addressing concerns for area residents about conflict risk is essential.

Minnesota↗
USGS2022

Coupling validation effort with in situ bioacoustic data improves estimating relative activity and occupancy for multiple species with cross-species misclassifications

The increasing complexity and pace of ecological change requires natural resource managers to consider entire species assemblages. Acoustic recording units (ARUs) require minimal cost and effort to deploy and inform relative activity, or encounter rates, for multiple species simultaneously. ARU-based surveys require post-processing of the recordings via software algorithms that assign a species label to each recording. The automated classification process can result in cross-species misidentifications that should be accounted for when employing statistical modelling for conservation decision-making. Using simulation and ARU-based detection counts from 17 bat species in British Columbia, Canada, we investigate three strategies for adjusting statistical inference for species misclassification: (a) ‘coupling’ ambiguous and unambiguous detections by validating a subset of survey events post-hoc, (b) using a calibration dataset on the software algorithm's (in)accuracy for species identification or (c) specifying informative Bayesian priors on classification probabilities. We explore the impact of different Bayesian prior specifications for the classification probabilities on posterior estimation. We then consider how the quantity of data validated post-hoc impacts model convergence and resulting inferences for bat species relative activity as related to nightly conditions and yearly site occupancy after accounting for site-level environmental variables. Coupled methods resulted in less bias and uncertainty when estimating relative activity and species classification probabilities relative to calibration approaches. We found that species that were difficult-to-detect and those that were often inaccurately identified by the software required more validation effort than more easily detected and/or identified species. Our results suggest that, when possible, acoustic surveys should rely on coupled validated detection information to account for false-positive detections, rather than uncoupled calibration datasets. However, if the assemblage of interest contains a large number of rarely detected or less prevalent species, an intractable amount of effort may be required, suggesting there are benefits to curating a calibration dataset that is representative of the observation process. Our findings provide insights into the practical challenges associated with statistical analyses of ARU data and possible analytical solutions to support reliable and cost-effective decision-making for wildlife conservation/management in the face of known sources of observation errors.

British Columbia↗
USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗
USGS2022

Considering science needs to deliver actionable science

Conservation practitioners, natural resource managers, and environmental stewards often seek out scientific contributions to inform decision-making. This body of science only becomes actionable when motivated by decision makers considering alternative courses of action. Many in the science community equate addressing stakeholder science needs with delivering actionable science. However, not all efforts to address science needs deliver actionable science, suggesting that the synonymous use of these two constructs (delivering actionable science and addressing science needs) is not trivial. This can be the case when such needs are conveyed by people who neglect decision makers responsible for articulating a priority management concern and for specifying how the anticipated scientific information will aid the decision-making process. We argue that the actors responsible for articulating these science needs and the process used to identify them are decisive factors in the ability to deliver actionable science, stressing the importance of examining the provenance and the determination of science needs. Guided by a desire to enhance communication and cross-literacy between scientists and decision makers, we identified categories of actors who may inappropriately declare science needs (e.g., applied scientists with and without regulatory affiliation, external influencers, reluctant decision makers, agents in place of decision makers, and boundary organization representatives). We also emphasize the importance of, and general approach to, undertaking needs assessments or gap analyses as a means to identify priority science needs. We conclude that basic stipulations to legitimize actionable science, such as the declaration of decisions of interest that motivate science needs and using a robust process to identify priority information gaps, are not always satisfied and require verification. To alleviate these shortcomings, we formulated practical suggestions for consideration by applied scientists, decision makers, research funding entities, and boundary organizations to help foster conditions that lead to science output being truly actionable.

Conservation Biology↗
USGS2024

Advancing at-risk species recovery planning in an era of rapid ecological change with a transparent, flexible, and expert-engaged approach

In the face of unprecedented ecological changes, the conservation community needs strategies to recover species at risk of extinction. On the Island of Maui, we collaborated with species experts and managers to assist with climate-resilient recovery planning for 36 at-risk native plant species by identifying priority areas for the management of recovery populations. To do this, we developed a tailored spatial conservation prioritization (SCP) approach distinguished by its emphasis on transparency, flexibility, and expert (TFE) engagement. Our TFE SCP approach consisted of 2 iterative steps: first, the generation of multiple candidate conservation footprints (i.e., prioritization solutions) with a flexible greedy algorithm that reflects conservation practitioners’ priorities and, second, the selection of an optimal conservation footprint based on the consideration of trade-offs in expert-agreed criteria among footprints. This process maximized buy-in by involving conservation practitioners and experts throughout, from setting goals to reviewing optimization data, defining optimization rules, and designating planning units meaningful to practitioners. We minimized the conservation footprint area necessary to meet recovery goals while incorporating species-specific measures of habitat suitability and climate resilience and retaining species-specific information for guiding recovery efforts. Our approach reduced the overall necessary conservation area by 36%, compared with selecting optimal recovery habitats for each species separately, and still identified high-quality habitat for individual species. Compared with prioritizr (an existing SCP tool), our approach identified a conservation area of equal size but with higher quality habitat. By integrating the strengths of existing techniques in a flexible and transparent design, our approach can address natural resource management constraints and provide outputs suitable for local recovery planning, consequently enhancing engagement and buy-in from conservation practitioners and experts. It demonstrates a step forward in making conservation planning more responsive to real-world complexities and helps reduce barriers to implementation for local conservation practitioners.

Hawaii↗
USGS2025

Bright spots for advancing ecological understanding and conservation decision-making

A lot can be learned by studying bright spots—defined as unexpected positive outcomes. In fields like public health, education, and oncology, identifying factors behind bright spots reveals previously unknown drivers of success that can be replicated elsewhere. This concept is being applied in conservation but is hampered by variations in definitions of bright spots and confusion with hotspots—sites with high absolute values of a metric. We developed a framework to clearly define and distinguish between hotspots (e.g., a wetland with high plant diversity) and bright spots (e.g., a biodiverse wetland in a housing development), which outperform conservation expectations. The framework is an iterative cycle, consisting of setting expectations for relative comparisons, classifying systems into bright, dark, hot, and cold categories, and digging deeper to reveal hidden mechanisms and opportunities for intervention. We drew on examples from diverse fields to demonstrate how our framework can generate new knowledge, identify potential interventions, and inform management priorities. Defining conservation and management expectations, often through predictive models, is essential to understanding drivers of success and fosters hypotheses about overlooked factors. Our framework can enhance ecological understanding, guide interventions, and help prioritize actions in conservation and natural resource management.

Conservation Biology↗
USGS2016

Governance principles for wildlife conservation in the 21st century

Wildlife conservation is losing ground in the U.S. for many reasons. The net effect is declines in species and habitat. To address this trend, the wildlife conservation institution (i.e., all customs, practices, organizations and agencies, policies, and laws with respect to wildlife) must adapt to contemporary social–ecological conditions. Adaptation could be supported by clear guidelines reflecting contemporary expectations for wildlife governance. We combine elements of public trust thinking and good governance to produce a broad set of wildlife governance principles. These principles represent guidance for ecologically and socially responsible wildlife conservation. They address persistent, systemic problems and, if adopted, will bring the institution into line with modern expectations for governance of public natural resources. Implementation will require changes in values, objectives, and processes of the wildlife conservation institution. These changes may be difficult, but promise improved wildlife conservation outcomes and increased support for conservation. We introduce challenges and opportunities associated with the principles, and encourage dialogue about them among scientists, practitioners, and other leaders in U.S. wildlife conservation. The principles alone will not change the course of conservation for the better, but may be necessary for such change to occur.

Conservation Letters↗
USGS2025

Biodiversity on public lands: How community science can help

Species inventories are crucial for conservation but are difficult to assemble and maintain. Bioblitzes, which encourage the public to document biodiversity in a particular area and timeframe, may offer useful information but their integration with other datasets poses challenges. We investigated the potential contribution of bioblitzes to natural resource management using observations from the United States National Park Service (NPS) 2016 Centennial Bioblitz. Through automated cross-referencing over 19,000 iNaturalist “research-grade” observations from 107 national parks with existing park inventory lists, we matched 86% of species documented in the Bioblitz to NPS species lists, based on current taxonomy, and matched another 6% of species using alternative scientific names using our matching process in R. Of the remaining 13.5% that did not match the NPS species lists, we manually found that 84% of the unmatched species were found within the lists or were outside the boundaries of the park, identifying 141 native species that were unrecorded in NPS species lists. Many introduced species were recorded; they were more likely to be documented in parks closer to cities. Parks near cities also drew more participants. Our study shows how public participation, through iNaturalist and bioblitzes, can facilitate biodiversity monitoring across large spatial scales.

Conservation Science and Practice↗