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At least 1,729 records · Page 96Linked to original sources
USGS2020

Ecological interfaces between land and flowing water: Themes and trends in riparian research and management

This paper provides an overview of past, present and future themes for research and management of riparian zones, often relating to papers within this Wetlands Special Feature. Riparian research expanded in the United States around 1980 with themes that recognized (1) damage from excessive livestock, or (2) damage from river damming and diversion, and (3) the beneficial capacity of riparian buffers to intercept and assimilate nutrients and other water contaminants. Research expanded globally in the 1990s, with themes including (4) plant life history requirements and (5) reliance on fluvial geomorphic dynamics that enable riparian rejuvenation. Resource managers recognized that riparian areas provide (6) rich wildlife habitats (7) along with valued ecosystem services, (8) which encouraged conservation and restoration initiatives, (9) including environmental flow regimes. Floodplains are (10) vulnerable to invasive plants and management has included biocontrol such as for Tamarix in the American Southwest. Into the twenty-first century, (11) climate change is advancing, and riparian ecosystems may be especially impacted due to the compound challenges from increasing water demand and declining summer flows. As an emerging opportunity, (12) while reservoirs submerge floodplain vegetation, reservoir deltas may support compensatory riparian wetlands. (13) Studies increasingly utilize remote sensing tools including satellite imagery, LiDAR and unmanned aircraft systems, and (14) the coordination of large data sets invites digital ecology, including artificial intelligence and machine learning. Since riparian zones are centres for human activities, (15) there are opportunities for citizen science, social media and internet applications, which will increasingly democratize riparian research and management.

Wetlands↗
USGS2022

Drones and bathymetry show the importance of optimal water depth for nest placement within breeding colonies of Western and Clark’s grebes

Habitat selection involves a series of decisions that are arguably the most important decisions that animals make and these decisions occur at multiple hierarchical spatial scales. Colonial-nesting birds face a unique challenge when selecting a nest site because each bird’s choices are severely constrained by other birds within their breeding colony. Individuals must seek out optimum nesting locations within the constraint of the colony’s geographic location. We investigated how water depth and proximity to open water affected 4th-order nest-site selection of Western and Clark’s Grebes ( Aechmophorus occidentalis, Aechmophorus clarkii ), colonial nesting waterbirds that have declined in abundance across their range. We used an orthomosiac that we created from ~ 500 aerial drone images of a large breeding colony to construct a Resource Selection Function to describe microhabitat features that influence nest-site placement within the colony footprint. Grebes preferred to nest in portions of the colony with intermediate water depths (40-80 cm during nest construction) and they preferred to nest in portions of the colony furthest from open water. Understanding how individual birds make use of available microhabitat features within the footprint of their breeding colony can help inform conservation efforts of colonial-nesting birds, particularly for species that nest in wetland habitats whose water levels are managed for human use.

Idaho↗
USGS2023

Predicting inundation dynamics and hydroperiods of small, isolated wetlands using a machine learning approach

The duration of inundation or saturation (i.e., hydroperiod) controls many wetland functions. In particular, it is a key determinant of whether a wetland will provide suitable breeding habitat for amphibians and other taxa that often have specific hydrologic requirements. Yet, scientists and land managers often are challenged by a lack of sufficient monitoring data to enable the understanding of the wetting and drying dynamics of small depressional wetlands. In this study, we present and evaluate an approach to predict daily inundation dynamics using a large wetland water-level dataset and a random forest algorithm. We relied on predictor variables that described characteristics of basin morphology of each wetland and atmospheric water budget estimates over various antecedent periods. These predictor variables were derived from datasets available over the conterminous United States making this approach potentially extendable to other locations. Model performance was evaluated using two metrics, median hydroperiod and the proportion of correctly classified days. We found that models performed well overall with a median balanced accuracy of 83% on validation data. Median hydroperiod was predicted most accurately for wetlands that were infrequently inundated and least accurate for permanent wetlands. The proportion of inundated days was predicted most accurately in permanent wetlands (99%) followed by frequently inundated wetlands (98%) and infrequently inundated wetlands (93%). This modeling approach provided accurate estimates of inundation and could be useful in other depressional wetlands where the primary water flux occurs with the atmosphere and basin morphology is a critical control on wetland inundation and hydroperiods.

Florida↗
USGS2023

Practical guide to measuring wetland carbon pools and fluxes

Wetlands cover a small portion of the world, but have disproportionate influence on global carbon (C) sequestration, carbon dioxide and methane emissions, and aquatic C fluxes. However, the underlying biogeochemical processes that affect wetland C pools and fluxes are complex and dynamic, making measurements of wetland C challenging. Over decades of research, many observational, experimental, and analytical approaches have been developed to understand and quantify pools and fluxes of wetland C. Sampling approaches range in their representation of wetland C from short to long timeframes and local to landscape spatial scales. This review summarizes common and cutting-edge methodological approaches for quantifying wetland C pools and fluxes. We first define each of the major C pools and fluxes and provide rationale for their importance to wetland C dynamics. For each approach, we clarify what component of wetland C is measured and its spatial and temporal representativeness and constraints. We describe practical considerations for each approach, such as where and when an approach is typically used, who can conduct the measurements (expertise, training requirements), and how approaches are conducted, including considerations on equipment complexity and costs. Finally, we review key covariates and ancillary measurements that enhance the interpretation of findings and facilitate model development. The protocols that we describe to measure soil, water, vegetation, and gases are also relevant for related disciplines such as ecology. Improved quality and consistency of data collection and reporting across studies will help reduce global uncertainties and develop management strategies to use wetlands as nature-based climate solutions.

Wetlands↗
USGS2025

Factors regulating the potential for freshwater mineral soil wetlands to function as natural climate solutions

There are increasing global efforts and initiatives aiming to tackle climate change and mitigate its impacts via natural climate solutions (NCS). Wetlands have been considered effective NCS given their capacity to sequester and retain atmospheric carbon dioxide (CO 2 ) while also providing a myriad of other ecosystem functions that can assist in mitigating the impacts of climate change. However, wetlands have a dual impact on climate, influencing the atmospheric concentrations of both CO 2 and methane (CH 4 ). The cooling effect associated with wetland CO 2 sequestration can be counterbalanced by the warming effect caused by CH 4 emissions from wetlands. The relative ability of wetlands to sequester CO 2 versus emit CH 4 is dependent on a suite of interacting physical, chemical, and biological factors, making it difficult to determine if/which wetlands are considered important NCS. The fact that wetlands are embedded in landscapes with surface and subsurface hydrological connections to other wetlands (i.e., wetlandscapes) that flow over and through geochemically active soils and sediments adds a new layer of complexity and poses further challenges to understanding wetland carbon sequestration and greenhouse gas fluxes at large spatial scales. Our review demonstrates how additional scientific advances are required to understand the driving mechanisms associated with wetland carbon cycling under different environmental conditions. It is vital to understand wetland functionality at both wetland and wetlandscape scales to effectively implement wetlands as NCS to maximize ecological, social, and economic benefits.

Wetlands↗
USGS2026

From model to action: Identifying the gaps in coastal marsh models for decision making

Coastal salt marsh modeling projects are designed to answer questions about where salt marshes may migrate, how they can migrate, and how they will be impacted by changing water levels. While this information is vital for climate-resilient marsh conservation, translating these findings into actionable results remains a challenge. The authors examined the actionability of marsh modeling efforts in the United States by analyzing data collected from semi-structured interviews of marsh model users ( n = 24) across two ongoing projects along the U.S. East Coast and the Gulf of America (Gulf of Mexico). By qualitatively analyzing the interview data, the authors found that the tasks of practitioners who use coastal marsh model outputs fall into three major themes: (1) marsh restoration, (2) planning with uncertainty, and (3) conserving habitat for marsh-reliant species. For each of these themes, the authors identify unmet needs, including high spatial resolution information for local planning, accessible descriptions of uncertainty to increase user confidence, and the incorporation of human dimensions data (e.g., human alterations to the landscape such as impoundments and culverts) for a comprehensive understanding of the coastal salt marsh. Marsh modeling projects should strategize how to fulfil these unmet user needs so that marsh modeling outputs can better support decisions related to marsh conservation and restoration.

Gulf of America, United States East Coast↗
USGS2017

The Bayesian group lasso for confounded spatial data

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Journal of Agricultural, Biological, and Environme↗
USGS2017

Imputation approaches for animal movement modeling

The analysis of telemetry data is common in animal ecological studies. While the collection of telemetry data for individual animals has improved dramatically, the methods to properly account for inherent uncertainties (e.g., measurement error, dependence, barriers to movement) have lagged behind. Still, many new statistical approaches have been developed to infer unknown quantities affecting animal movement or predict movement based on telemetry data. Hierarchical statistical models are useful to account for some of the aforementioned uncertainties, as well as provide population-level inference, but they often come with an increased computational burden. For certain types of statistical models, it is straightforward to provide inference if the latent true animal trajectory is known, but challenging otherwise. In these cases, approaches related to multiple imputation have been employed to account for the uncertainty associated with our knowledge of the latent trajectory. Despite the increasing use of imputation approaches for modeling animal movement, the general sensitivity and accuracy of these methods have not been explored in detail. We provide an introduction to animal movement modeling and describe how imputation approaches may be helpful for certain types of models. We also assess the performance of imputation approaches in two simulation studies. Our simulation studies suggests that inference for model parameters directly related to the location of an individual may be more accurate than inference for parameters associated with higher-order processes such as velocity or acceleration. Finally, we apply these methods to analyze a telemetry data set involving northern fur seals ( Callorhinus ursinus ) in the Bering Sea. Supplementary materials accompanying this paper appear online.

Journal of Agricultural, Biological, and Environme↗
USGS2024

Joint spatial modeling bridges the gap between disparate disease surveillance and population monitoring efforts informing conservation of at-risk bat species

White-Nose Syndrome (WNS) is a wildlife disease that has decimated hibernating bats since its introduction in North America in 2006. As the disease spreads westward, assessing the potentially differential impact of the disease on western bat species is an urgent conservation need. The statistical challenge is that the disease surveillance and species response monitoring data are not co-located, available at different spatial resolutions, non-Gaussian, and subject to observation error requiring a novel extension to spatially misaligned regression models for analysis. Previous work motivated by epidemiology applications has proposed two-step approaches that overcome the spatial misalignment while intentionally preventing the human health outcome from informing estimation of exposure. In our application, the impacted animals contribute to spreading the fungus that causes WNS, motivating development of a joint framework that exploits the known biological relationship. We introduce a Bayesian, joint spatial modeling framework that provides inferences about the impact of WNS on measures of relative bat activity and accounts for the uncertainty in estimation of WNS presence at non-surveyed locations. Our simulations demonstrate that the joint model produced more precise estimates of disease occurrence and unbiased estimates of the association between disease presence and the count response relative to competing two-step approaches. Our statistical framework provides a solution that leverages disparate monitoring activities and informs species conservation across large landscapes. Stan code and documentation are provided to facilitate access and adaptation for other wildlife disease applications.

Journal of Agricultural, Biological and Environmen↗
USGS2018

Ecosystem service flows from a migratory species: Spatial subsidies of the northern pintail

Migratory species provide important benefits to society, but their cross-border conservation poses serious challenges. By quantifying the economic value of ecosystem services (ESs) provided across a species’ range and ecological data on a species’ habitat dependence, we estimate spatial subsidies —how different regions support ESs provided by a species across its range. We illustrate this method for migratory northern pintail ducks in North America. Pintails support over \$101 million USD annually in recreational hunting and viewing and subsistence hunting in the U.S. and Canada. Pintail breeding regions provide nearly \$30 million in subsidies to wintering regions, with the “Prairie Pothole” region supplying over \$24 million in annual benefits to other regions. This information can be used to inform conservation funding allocation among migratory regions and nations on which the pintail depends. We thus illustrate a transferrable method to quantify migratory species-derived ESs and provide information to aid in their transboundary conservation.

Ambio↗
USGS2016

Nutrients in the nexus

Synthetic nitrogen (N) fertilizer has enabled modern agriculture to greatly improve human nutrition during the twentieth century, but it has also created unintended human health and environmental pollution challenges for the twenty-first century. Averaged globally, about half of the fertilizer-N applied to farms is removed with the crops, while the other half remains in the soil or is lost from farmers’ fields, resulting in water and air pollution. As human population continues to grow and food security improves in the developing world, the dual development goals of producing more nutritious food with low pollution will require both technological and socio-economic innovations in agriculture. Two case studies presented here, one in sub-Saharan Africa and the other in Midwestern United States, demonstrate how management of nutrients, water, and energy is inextricably linked in both small-scale and large-scale food production, and that science-based solutions to improve the efficiency of nutrient use can optimize food production while minimizing pollution. To achieve the needed large increases in nutrient use efficiency, however, technological developments must be accompanied by policies that recognize the complex economic and social factors affecting farmer decision-making and national policy priorities. Farmers need access to affordable nutrient supplies and support information, and the costs of improving efficiencies and avoiding pollution may need to be shared by society through innovative policies. Success will require interdisciplinary partnerships across public and private sectors, including farmers, private sector crop advisors, commodity supply chains, government agencies, university research and extension, and consumers.

Journal of Environmental Studies and Sciences↗
USGS2018

Drought and fire in the western USA: Is climate attribution enough?

Purpose of Review I sought to review the contributions of recent literature and prior foundational papers to our understanding of drought and fire. In this review, I summarize recent literature on drought and fire in the western USA and discuss research directions that may increase the utility of that body of work for twenty-first century application. I then describe gaps in the synthetic knowledge of drought-driven fire in managed ecosystems and use concepts from use-inspired research to describe potentially useful extensions of current work. Recent Findings Fire responses to climate, and specifically various kinds of drought, are clear, but vary widely with fuel responses to surplus water and drought at different timescales. Ecological and physical factors interact with human management and ignitions to create fire regime and landscape trajectories that challenge prediction. Summary The mechanisms by which the climate system affects regional droughts and how they translate to fire in the western USA need more attention to accelerate both forecasting and adaptation. However, projections of future fire activity under climate change will require integrated advances on both fronts to achieve decision-relevant modeling. Concepts from transdisciplinary research and coupled human-natural systems can help frame strategic work to address fire in a changing world.

Current Climate Change Reports↗
USGS2026

Tidal forested wetlands can be incorporated into blue carbon conservation and restoration strategies

Purpose of Review Blue carbon is an important concept for environmental policy. Blue carbon strategies (conservation and restoration for carbon gain) have been primarily implemented with mangroves, though are likely to be suitable for other tidal forested wetlands. Here, we discuss the expanding definition of blue carbon encompassing all tidal forested wetlands, synthesize ecological and carbon sink knowledge of tidal forested wetlands, and reflect on key actions in mangrove blue carbon research and implementation that could be applied to other tidal forested wetlands. Recent Findings Conceptually, the blue carbon concept has now expanded beyond traditional coastal vegetated ecosystems to include all tidal wetlands, including tidal forested wetlands. Emerging data on carbon sequestration, emissions, and budgets from around the world now show that many tidal forested wetland ecosystems are carbon sinks at a magnitude similar to mangroves. At the global scale, mangroves have become incorporated into blue carbon strategies rapidly compared to other tidal forested wetlands, facilitated by agenda-setting papers, adequate data addressing concerns on emissions and permanence, the availability of global maps, a clear ecosystem definition, clear accounting and policy frameworks, and international stakeholders who acted as high profile ecosystem advocates, alongside long-term capacity building efforts. This provides a roadmap for implementation in other tidal forested wetlands. Summary Tidal forested wetlands other than mangroves have high potential for blue carbon management. Many tidal forested wetlands share biophysical similarities with mangroves, carbon stocks can be similar, and methane emissions are often no higher. An increasing evidence base, challenging assumptions around greenhouse gas fluxes, and robust engagement with policy actors and frameworks, could increase the use of blue carbon for tidal forested wetland conservation and restoration.

Current Forestry Reports↗
USGS2017

Integrating spatially explicit representations of landscape perceptions into land change research

Purpose of Review Human perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research. Recent Findings Mapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models. Summary Challenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

Current Landscape Ecology Reports↗
USGS2019

Selecting a landscape model for natural resource management applications

Purpose of Review: Climate change and associated ecological impacts have challenged many conventional, observation-based approaches for predicting ecosystem and landscape responses to natural resource management. Complex spatial ecological models provide powerful, flexible tools which managers and others can use to make inferences about management impacts on future, no-analog landscape conditions. However, land managers who wish to use ecosystem and landscape models for natural resource applications are faced with the difficult task of deciding among many models that differ in important ways. Here, we summarize a process to aid managers in the selection of an appropriate model for natural resource management. Recent Findings: To guide management planning, scientifically credible information on how landscapes will respond to management actions under changing climate is required. Landscape models are increasingly used in a management context to evaluate of impacts of changing climate and interacting stressors on ecosystems and to test effects of alternative management options on desired conditions. However, the wide range of available models makes selection of appropriate and viable models a complex process. Summary: We present a series of preliminary steps to define critical scales of time, space, and ecological organization to guide an experimental design for a modeling project and then list a set of criteria for selecting a landscape or ecological model. Material presented includes the preliminary steps (crafting modeling objective, designing modeling project), organizational concerns (resources available, expertise on hand, timelines), and modeling details (complexity, design, documentation) of model selection.

Current Landscape Ecology Reports↗
USGS2019

Landscape connectivity planning for adaptation to future climate and land-use change

Purpose of Review We examined recent literature on promoting habitat connectivity in the context of climate change (CC) and land-use change (LUC). These two global change forcings have wide-reaching ecological effects that are projected to worsen in the future. Improving connectivity is a common adaptation strategy, but CC and LUC can also degrade planned connections, potentially reducing their effectiveness. We synthesize advances in connectivity design approaches, identify challenges confronted by researchers and practitioners, and offer suggestions for future research. Recent Findings Recent studies incorporated future CC into connectivity design more often than LUC and rarely considered the two drivers jointly. When considering CC, most studies have focused on relatively broad spatial and temporal extents and have included either species-based targets or coarse-filter targets like geodiversity and climate gradients. High levels of uncertainty about future LUC and lack of consistent, readily available model simulations are likely hindering its inclusion in connectivity modeling. This high degree of uncertainty extends to efforts to jointly consider future CC and LUC. Summary We argue that successful promotion of connectivity as a means to adapt to CC and LUC will depend on (1) the velocity of CC, (2) the velocity of LUC, and (3) the degree of existing landscape fragmentation. We present a new conceptual framework to assist in identifying connectivity networks given these three factors. Given the high uncertainty associated with future CC and LUC, incorporating insights from decision science into connectivity planning will facilitate the development of more robust adaptation strategies.

Current Landscape Ecology Reports↗
USGS2020

Forecasting, detecting, and tracking volcanic eruptions from space

Satellite monitoring of volcanic activity typically includes four primary observations: (1) deformation and surface change, (2) gas emissions, (3) thermal anomalies, and (4) ash plumes. These phenomena are imaged by remote sensing data that span the electromagnetic spectrum, from microwave to ultraviolet energy and including visible and infrared wavelengths. The primary uses of satellite data in volcanology are forecasting, detecting, and tracking eruptive activity. Eruptions are often preceded by a number of indicators that are detectable from space, including surface deformation, subtle increases in surface temperature, and elevated gas emissions. The first indications of eruption, especially at remote volcanoes, are often identified in satellite data by strong thermal anomalies and/or the presence of ash and gas in the atmosphere, the recognition of which can be automated for rapid eruption detection. Once an eruption is in progress, space-based imagery of all types can track activity over time, providing information on the emplacement of volcanic deposits, the presence and character of ash plumes, and potential changes in the character of the eruption, all of which aid hazards assessment. Activity at Agung volcano, Indonesia, during 2017–2019, offers an excellent example of the importance of remote sensing datasets for forecasting, detecting, and tracking eruptions. Challenges to exploiting current and future satellite data include ensuring regular acquisitions over active volcanoes and developing tools for automated analysis of the massive volume of imagery for volcano-related signals.

Remote Sensing in Earth Systems Sciences↗
USGS2022

Manatee population traits elucidated through photo-identification

Data on the demography and distribution of wildlife populations are important for informing conservation and management decisions; however, determination of life history traits and population trends often are elusive. All four extant species in the order Sirenia are deemed vulnerable to extinction; therefore, determining the demography and distribution for populations worldwide is crucial. Aerial surveys, radio-tagging and tracking, genetic sampling and analyses, health assessments, carcass examination, and photographic documentation are all techniques used to study sirenian populations. A 40 +-year computer-aided catalog of images and demography data collected on Florida manatees enables searches of individuals by descriptions of feature (scar) types and has enabled estimates of annual survival and reproductive rates, documented extra-limital movements, and advanced modeling designs. Photography is discussed as a method for the documentation of unique and acquired features specifically on Florida manatees. By means of these features, individual Florida manatees have been re-identified as far from their established range as Cape Cod, Massachusetts, Houston, Texas, and in Cuba, The Bahamas, and Mexico. The length of gestation (11–13 months) and calf dependency (1–3 years), and potential longevity in the wild (> 50 years), have been verified. To meet the challenge of an increasing number of images collected with the advent of digital photography, there has been an increasing interest and potential for new techniques to assist with individual identification. Several researchers are utilizing drones and artificial intelligence to find, photograph, and streamline the individual identification of sirenians as well as other marine mammal species. New techniques have potential to simplify the photographic identification of Florida manatees. Photographic documentation could be a model for demographic and distribution research of sirenian populations outside of Florida and as a tool to monitor the viability of sirenian populations, particularly as threats emerge due to anthropogenic pressures and global climate change.

Mammalian Biology↗