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At least 91 records · Page 5Linked to original sources
USGS2013

Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts

Regression equations were developed for estimating bankfull geometry—width, mean depth, cross-sectional area—and discharge for streams in Massachusetts. The equations provide water-resource and conservation managers with methods for estimating bankfull characteristics at specific stream sites in Massachusetts. This information can be used for the adminstration of the Commonwealth of Massachusetts Rivers Protection Act of 1996, which establishes a protected riverfront area extending from the mean annual high-water line corresponding to the elevation of bankfull discharge along each side of a perennial stream. Additionally, information on bankfull channel geometry and discharge are important to Federal, State, and local government agencies and private organizations involved in stream assessment and restoration projects. Regression equations are based on data from stream surveys at 33 sites (32 streamgages and 1 crest-stage gage operated by the U.S. Geological Survey) in and near Massachusetts. Drainage areas of the 33 sites ranged from 0.60 to 329 square miles (mi2). At 27 of the 33 sites, field data were collected and analyses were done to determine bankfull channel geometry and discharge as part of the present study. For 6 of the 33 sites, data on bankfull channel geometry and discharge were compiled from other studies done by the U.S. Geological Survey, Natural Resources Conservation Service of the U.S. Department of Agriculture, and the Vermont Department of Environmental Conservation. Similar techniques were used for field data collection and analysis for bankfull channel geometry and discharge at all 33 sites. Recurrence intervals of the bankfull discharge, which represent the frequency with which a stream fills its channel, averaged 1.53 years (median value 1.34 years) at the 33 sites. Simple regression equations were developed for bankfull width, mean depth, cross-sectional area, and discharge using drainage area, which is the most significant explanatory variable in estimating these bankfull characteristics. The use of drainage area as an explanatory variable is also the most commonly published method for estimating these bankfull characteristics. Regional curves (graphic plots) of bankfull channel geometry and discharge by drainage area are presented. The regional curves are based on the simple regression equations and can be used to estimate bankfull characteristics from drainage area. Multiple regression analysis, which includes basin characteristics in addition to drainage area, also was used to develop equations. Variability in bankfull width, mean depth, cross-sectional area, and discharge was more fully explained by the multiple regression equations that include mean-basin slope and drainage area than was explained by equations based on drainage area alone. The Massachusetts regional curves and equations developed in this study are similar, in terms of values of slopes and intercepts, to those developed for other parts of the northeastern United States. Limitations associated with site selection and development of the equations resulted in some constraints for the application of equations and regional curves presented in this report. The curves and equations are applicable to stream sites that have (1) less than about 25 percent of their drainage basin area occupied by urban land use (commercial, industrial, transportation, and high-density residential), (2) little to no streamflow regulation, especially from flood-control structures, (3) drainage basin areas greater than 0.60 mi2 and less than 329 mi2, and (4) a mean basin slope greater than 2.2 percent and less than 23.9 percent. The equations may not be applicable where streams flow through extensive wetlands. The equations also may not apply in areas of Cape Cod and the Islands and the area of southeastern Massachusetts close to Cape Cod with extensive areas of coarse-grained glacial deposits where none of the study sites are located. Regardless of the setting, the regression equations are not intended for use as the sole method of estimating bankfull characteristics; however, they may supplement field identification of the bankfull channel when used in conjunction with field verified bankfull indicators, flood-frequency analysis, or other supporting evidence.

Massachusetts↗
USGS2015

Biodiversity influences plant productivity through niche–efficiency

The loss of biodiversity is threatening ecosystem productivity and services worldwide, spurring efforts to quantify its effects on the functioning of natural ecosystems. Previous research has focused on the positive role of biodiversity on resource acquisition (i.e., niche complementarity), but a lack of study on resource utilization efficiency, a link between resource and productivity, has rendered it difficult to quantify the biodiversity–ecosystem functioning relationship. Here we demonstrate that biodiversity loss reduces plant productivity, other things held constant, through theory, empirical evidence, and simulations under gradually relaxed assumptions. We developed a theoretical model named niche–efficiency to integrate niche complementarity and a heretofore-ignored mechanism of diminishing marginal productivity in quantifying the effects of biodiversity loss on plant productivity. Based on niche–efficiency, we created a relative productivity metric and a productivity impact index (PII) to assist in biological conservation and resource management. Relative productivity provides a standardized measure of the influence of biodiversity on individual productivity, and PII is a functionally based taxonomic index to assess individual species’ inherent value in maintaining current ecosystem productivity. Empirical evidence from the Alaska boreal forest suggests that every 1% reduction in overall plant diversity could render an average of 0.23% decline in individual tree productivity. Out of the 283 plant species of the region, we found that large woody plants generally have greater PII values than other species. This theoretical model would facilitate the integration of biological conservation in the international campaign against several pressing global issues involving energy use, climate change, and poverty.

Proceedings of the National Academy of Sciences of↗
USGS2021

Using landscape metrics to characterize towns along an urban-rural gradient

Context Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation. Objectives We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability. Methods We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation. Results The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient. Conclusions Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Connecticut. Maine, Massachusetts, New Hampshire, ↗
USGS2015

Jaguar critical habitat designation causes concern for Southwestern ranchers

The designation of jaguar critical habitat in April 2014 in southern Arizona and southwestern New Mexico created concern for livestock ranchers in the region. We interviewed ranchers to understand their concerns with the jaguar critical habitat designation and their attitudes toward jaguars, wildlife conservation, and resource management in general. Ranchers we interviewed were concerned about direct impacts of designated critical habitat on ranching, as well as possible alternative agendas of critical habitat advocates and issues specific to the borderlands region. The ranchers were less concerned about the presence of jaguars but were more concerned about possible limiting effects of the Endangered Species Act (ESA), distrust of government entities, and litigious environmental groups. To maximize effectiveness, government agencies should work to foster trust in the ranching community, be cognizant of sensitive issues specific to the region that may challenge endangered species conservation goals, recognize the opportunity to work with ranchers for endangered species management, and provide outreach about implications of the ESA.

Rangelands↗
USGS2024

Realizing the potential of eDNA biodiversity monitoring tools in the marine environment with application to offshore renewable energy

The U.S. Geological Survey (USGS) researches the biological diversity and distribution of species to support management, conservation, and resource use decisions. USGS scientists advance detection and monitoring technologies to assess changes in fish and wildlife populations, biodiversity, and the health of ecosystems. The United States is planning to install 30 gigawatts of offshore marine and wind energy by 2030. However, the effects on fish and wildlife and their habitats are not well understood. The USGS is a leader in the field of eDNA technologies and has helped advance robotic eDNA samplers, has extensive experience working in the offshore environment, and has developed novel and actionable statistical methods and standards for eDNA monitoring applications. This fact sheet presents key eDNA research and development advances needed for realizing the potential of eDNA biodiversity monitoring tools in the marine environment and applying eDNA monitoring to offshore renewable energy development. New and cost-effective tools for measuring changes in biodiversity in response to offshore renewable energy development can help to inform natural resource management and project planning and permitting decisions.

Fact Sheet↗
USGS2015

The 3D Elevation Program: summary for Connecticut

Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Connecticut, elevation data are critical for coastal zone management, flood risk management, natural resources conservation, agriculture and precision farming, sea level rise and subsidence, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.

Connecticut↗
USGS2014

Climate-smart conservation: putting adaption principles into practice

Climate change already is having significant impacts on the nation’s species and ecosystems, and these effects are projected to increase considerably over time. As a result, climate change is now a primary lens through which conservation and natural resource management must be viewed. How should we prepare for and respond to the impacts of climate change on wildlife and their habitats? What should we be doing differently in light of these climatic shifts, and what actions continue to make sense? Climate-Smart Conservation: Putting Adaptation Principles into Practice offers guidance for designing and carrying out conservation in the face of a rapidly changing climate. Addressing the growing threats brought about or accentuated by rapid climate change requires a fundamental shift in the practice of natural resource management and conservation. Traditionally, conservationists have focused their efforts on protecting and managing systems to maintain their current state, or to restore degraded systems back to a historical state regarded as more desirable. Conservation planners and practitioners will need to adopt forward-looking goals and implement strategies specifically designed to prepare for and adjust to current and future climatic changes, and the associated impacts on natural systems and human communities—an emerging discipline known as climate change adaptation. The field of climate change adaptation is still in its infancy. Although there is increasing attention focused on the subject, much of the guidance developed to date has been general in nature, concentrating on high-level principles rather than specific actions. It is against this backdrop that this guide was prepared as a means for helping put adaptation principles into practice, and for moving adaptation from planning to action.

Report↗
USGS2021

Stewardship and management of freshwater ecosystems: From Leopold's land ethic to a freshwater ethic

In 1949, Aldo Leopold formalized the concept of the ‘land ethic’, in what emerged as a foundational and transformational way of thinking about natural resource management, biodiversity conservation, and stewardship in terrestrial systems. Yet, the land ethic has inherent linkages to aquatic ecosystems; Leopold himself conducted research on rivers and lakes, and freshwater ecosystems figured widely in his writing. We reflect on the land ethic and other aspects of Leopold's scholarship to identify key messages that provide insight into the stewardship and management of freshwater ecosystems around the globe. We also frame what we call the ‘freshwater ethic’ around Leopold's legacy. Although Leopold could not have envisaged the stressors affecting modern aquatic ecosystems, his core principles remain salient. These apply not only to ecosystem protection, but also to the ethics of modern conservation economics, sustainability, and the protection of natural capital, in which lakes, rivers, and wetlands now figure prominently. We identify key ‘Aldo-inspired’ recommendations for protecting and restoring freshwater ecosystems in the Anthropocene that emanate directly from his writings (e.g. adopt an ecosystem approach, identify win–win–win scenarios, recognize the irreplaceability of wild waters, and strive for freshwater optimism). In an epoch where links between people and nature are becoming more explicit in environmental management, policy, and governance, we suggest that Aldo Leopold's work illustrates how inspirational, seminal thinkers have offered leadership in this domain. We contend that today there is still much that can be learned from Leopold, especially by the next generation of environmental practitioners, to ensure the effective stewardship of our aquatic ecosystems. We submit that the adoption of a freshwater ethic in parallel with Leopold's land ethic will enhance the stewardship of the world's increasingly threatened fresh waters by raising the profile of the plight of fresh waters and identifying enduring actions that, if embraced, will help conserve and restore biodiversity.

Aquatic Conservation: Marine and Freshwater Ecosys↗
USGS2019

Predicting species distributions: unifying model selection and scale optimization for multi-scale occupancy models

Geographic distributions are a basic component of a species’ ecology, and predicting distributions is a fundamental task of conservation and resource management. Reliable prediction depends on identification of appropriate scales of effect for environmental data, and scale-optimization techniques are thus desirable to identify optimal scales for predictor variables. Recent statistical developments have also advanced methods of model selection based explicitly on predictive ability, which differ from commonly-used methods that regulate model structures via anticipated predictive performance. Such methods are beginning to permeate into species distribution models (SDMs), yet there remains no consensus methodology for developing optimally-predictive multi-scale SDMs when covariate data are collected over a range of scales. Thus, we compared the performance of common approaches for scale optimization and model selection in terms of their ability to produce optimally predictive multi-scale Bayesian occupancy models for predicting a species distribution, using models of the breeding distribution for King Rails (Rallus elegans) as a case study. Our results demonstrate sizable gains in predictive performance for hierarchical occupancy models selected explicitly via their ability to predict out-of-sample data using the logarithmic scoring rule, as compared to models selected using information criteria (DIC and WAIC). Information criteria commonly selected individual covariates, as well as scales of effect for those covariates, with suboptimal predictive performance. Performance of models selected using the logarithmic scoring rule was robust across method of scale optimization, which was not true for models selected using DIC and WAIC. Thus, we empirically demonstrate benefits of study designs that enable covariate and scale selection based explicitly on predictive ability. Our results also imply that more careful consideration of what constitutes an optimal scale is warranted in many ecological studies, as the meaning of optimal is not independent of the technique used for scale selection.

Ecosphere↗
USGS2020

Environmental DNA is an effective tool to track recolonizing migratory fish following large‐scale dam removal

Environmental DNA (eDNA) has emerged as a potentially powerful tool for use in conservation and resource management, including for tracking the recolonization dynamics of fish populations. We used eDNA to assess the effectiveness of dam removal to restore fish passage on the Elwha River in Washington State (USA). Using a suite of 11 species‐specific eDNA polymerase chain reaction (PCR) assays, we showed that most targeted anadromous species (five Pacific Salmon species and Pacific Lamprey) were able to pass upstream of both former dam sites. Multiscale occupancy modeling showed that the timing and spatial extent of recolonization differed among species during the four years of post‐dam removal monitoring. More abundant species like Chinook Salmon and Coho Salmon migrated farther into the upper portions of the watershed than less abundant species like Pink Salmon and Chum Salmon. Sampling also allowed assessment of potamodromous fish species. Bull Trout and Rainbow Trout, ubiquitous species in the watershed, were detected at all sampling locations. Environmental DNA from Brook Trout, a non‐native species isolated between the dams prior to dam removal, was detected downstream of Elwha dam but rarely upstream of the Glines Canyon Dam suggested that the species has not expanded its range appreciably in the watershed following dam removal. We found that eDNA was an effective tool to assess the response of fish populations to large‐scale dam removal on the Elwha River.

Environmental DNA↗
USGS2021

Ontogeny of eDNA shedding during early development in Chinook Salmon (Oncorhynchus tshawytscha)

Knowledge of the timing of major life history events in aquatic species is important for informing conservation and resource management planning. Accordingly, surveys of environmental DNA (eDNA) have been performed to determine the efficacy of eDNA for providing information on life history events, primarily focusing on the timing of events associated with spawning, and these studies have proved successful. However, spawning represents only one part of the life history, and therefore, information on eDNA shedding during other life history stages is needed to fill gaps in knowledge. Here, we explored eDNA shedding during early life history (from fertilized eggs until near yolk sac absorption) in Chinook Salmon ( Oncorhynchus tshawytscha ) at three biomasses in a laboratory environment. We found that fertilized eggs shed little eDNA prior to hatching. Hatching coincided with a spike in eDNA, and we observed a significant and positive relationship between eDNA concentration and the number of hatched eggs. The concentration of eDNA shed by larvae after hatching was not consistent across post-hatch sampling days, suggesting developmental and behavioral changes associated with larval ontogeny may affect eDNA shedding rate. These results indicate that eDNA data may be used to identify hatch timing and verify successful reproduction in oviparous aquatic fishes. The application of eDNA to early life history broadens the capacity of eDNA-based methods for assessing population status and trends.

Environmental DNA↗
USGS2021

How does climate change affect emergent properties of aquatic ecosystems?

Emergent properties of ecosystems are community attributes, such as structure and function, that arise from connections and interactions (e.g., predator–prey, competition) among populations, species, or assemblages that, when viewed together, provide a holistic representation that is more than the sum of its individual parts. Climate change is altering emergent properties of aquatic ecosystems through component responses, a combination of shifts in species range, phenology, distribution, and productivity, which lead to novel ecosystems that have no historical analog. The reshuffling, restructuring, and rewiring of aquatic ecosystems due to climate impacts are of high concern for natural resource management and conservation as these changes can lead to species extinctions and reductions in ecosystem services. Overall, we found that substantial progress has been made to advance our understanding of how climate change is affecting emergent properties of aquatic ecosystems. However, responses are incredibly complex, and high uncertainty remains for how systems will reorganize and function over the coming decades. This cross‐system perspective summarizes the state of knowledge of climate‐driven emergent properties in aquatic habitats with case studies that highlight mechanisms of change, observed or anticipated outcomes, as well as insights into confounding non‐climate effects, research tools, and management approaches to advance the field.

Fisheries↗
USGS2005

Topographic, bioclimatic, and vegetation characteristics of three ecoregion classification systems in North America: Comparisons along continent-wide transects

Ecoregion classification systems are increasingly used for policy and management decisions, particularly among conservation and natural resource managers. A number of ecoregion classification systems are currently available, with each system defining ecoregions using different classification methods and different types of data. As a result, each classification system describes a unique set of ecoregions. To help potential users choose the most appropriate ecoregion system for their particular application, we used three latitudinal transects across North America to compare the boundaries and environmental characteristics of three ecoregion classification systems [Ku??chler, World Wildlife Fund (WWF), and Bailey]. A variety of variables were used to evaluate the three systems, including woody plant species richness, normalized difference in vegetation index (NDVI), and bioclimatic variables (e.g., mean temperature of the coldest month) along each transect. Our results are dominated by geographic patterns in temperature, which are generally aligned north-south, and in moisture, which are generally aligned east-west. In the west, the dramatic changes in physiography, climate, and vegetation impose stronger controls on ecoregion boundaries than in the east. The Ku??chler system has the greatest number of ecoregions on all three transects, but does not necessarily have the highest degree of internal consistency within its ecoregions with regard to the bioclimatic and species richness data. In general, the WWF system appears to track climatic and floristic variables the best of the three systems, but not in all regions on all transects. ?? 2005 Springer Science+Business Media, Inc.

Environmental Management↗
USGS2008

Spatially explicit decision support for selecting translocation areas for Mojave desert tortoises

Spatially explicit decision support systems are assuming an increasing role in natural resource and conservation management. In order for these systems to be successful, however, they must address real-world management problems with input from both the scientific and management communities. The National Training Center at Fort Irwin, California, has expanded its training area, encroaching U.S. Fish and Wildlife Service critical habitat set aside for the Mojave desert tortoise ( Gopherus agassizii ), a federally threatened species. Of all the mitigation measures proposed to offset expansion, the most challenging to implement was the selection of areas most feasible for tortoise translocation. We developed an objective, open, scientifically defensible spatially explicit decision support system to evaluate translocation potential within the Western Mojave Recovery Unit for tortoise populations under imminent threat from military expansion. Using up to a total of 10 biological, anthropogenic, and/or logistical criteria, seven alternative translocation scenarios were developed. The final translocation model was a consensus model between the seven scenarios. Within the final model, six potential translocation areas were identified.

Biodiversity and Conservation↗
USGS2013

Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services

Recent ecosystem services research has highlighted the importance of spatial connectivity between ecosystems and their beneficiaries. Despite this need, a systematic approach to ecosystem service flow quantification has not yet emerged. In this article, we present such an approach, which we formalize as a class of agent-based models termed “Service Path Attribution Networks” (SPANs). These models, developed as part of the Artificial Intelligence for Ecosystem Services (ARIES) project, expand on ecosystem services classification terminology introduced by other authors. Conceptual elements needed to support flow modeling include a service's rivalness, its flow routing type (e.g., through hydrologic or transportation networks, lines of sight, or other approaches), and whether the benefit is supplied by an ecosystem's provision of a beneficial flow to people or by absorption of a detrimental flow before it reaches them. We describe our implementation of the SPAN framework for five ecosystem services and discuss how to generalize the approach to additional services. SPAN model outputs include maps of ecosystem service provision, use, depletion, and flows under theoretical, possible, actual, inaccessible, and blocked conditions. We highlight how these different ecosystem service flow maps could be used to support various types of decision making for conservation and resource management planning.

Ecosystem Services↗
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↗
USGS2013

Future distribution of tundra refugia in northern Alaska

Climate change in the Arctic is a growing concern for natural resource conservation and management as a result of accelerated warming and associated shifts in the distribution and abundance of northern species. We introduce a predictive framework for assessing the future extent of Arctic tundra and boreal biomes in northern Alaska. We use geo-referenced museum specimens to predict the velocity of distributional change into the next century and compare predicted tundra refugial areas with current land-use. The reliability of predicted distributions, including differences between fundamental and realized niches, for two groups of species is strengthened by fossils and genetic signatures of demographic shifts. Evolutionary responses to environmental change through the late Quaternary are generally consistent with past distribution models. Predicted future refugia overlap managed areas and indicate potential hotspots for tundra diversity. To effectively assess future refugia, variable responses among closely related species to climate change warrants careful consideration of both evolutionary and ecological histories.

Alaska↗
USGS2021

A science agenda to inform natural resource management decisions in an era of ecological transformation

Earth is experiencing widespread ecological transformation in terrestrial, freshwater, and marine ecosystems that is attributable to directional environmental changes, especially intensifying climate change. To better steward ecosystems facing unprecedented and lasting change, a new management paradigm is forming, supported by a decision-oriented framework that presents three distinct management choices: resist, accept, or direct the ecological trajectory. To make these choices strategically, managers seek to understand the nature of the transformation that could occur if change is accepted while identifying opportunities to intervene to resist or direct change. In this article, we seek to inspire a research agenda for transformation science that is focused on ecological and social science and based on five central questions that align with the resist–accept–direct (RAD) framework. Development of transformation science is needed to apply the RAD framework and support natural resource management and conservation on our rapidly changing planet.

BioScience↗