Search USGS⌕ Search

SEARCH · Search USGS

Results for “Ecological Processes”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4Linked to original sources
USGS2025

Mapping ecological states in the upper Colorado River basin: Implications for fire management

Spatially explicit information on ecosystem dynamics that offers a mechanistic understanding of ecological processes can benefit environmental management. Broad-scale maps based on state-and-transition models provide valuable insight into transitions among ecological states resulting from specific drivers within areas sharing similar climatic and edaphic characteristics ecological sites (ES). We aimed to quantify ecological dynamics of two ES groups in the Upper Colorado River Basin from 1986 to 2022 through annual maps of ecological states and assess potential drivers of observed state change. This region comprises important sagebrush shrublands and pinyon-juniper woodlands affected by non-native annual grass invasion, wildfires, and drought-induced tree mortality. Using field-based and remote sensing data, we modeled vegetation states using random forest models and mapped the states annually from 1986 to 2022. To demonstrate the utility of the state maps for monitoring and management, we used this time series of maps to investigate the influences of fire and drought on state occurrence. Our findings revealed a statistically significant increase in states invaded by non-native annual species (Invaded state), which replaced Grassland and Shrubland states, while Shrubland states decreased significantly, transitioning to invaded and Woodland states. Invaded states had the highest likelihood of burning, followed by Woodlands. Drought was associated with increased area of Grassland and Bare states, but with decreased area of invaded and Shrubland states. These results indicate an accelerating fire cycle is potentially leading to ongoing regional environmental degradation. Despite increasing drought conditions during the study period, the invaded states continued to increase in area, indicating additional underlying mechanisms. Our reproducible, broad-scale, ecologically-driven state mapping process enhances understanding of how drought, fire, and invasion by non-native plants can transform semiarid landscapes of the western USA.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2020

Methylmercury exposure in wildlife: A review of the ecological and physiological processes affecting contaminant concentrations and their interpretation

Exposure to methylmercury (MeHg) can result in detrimental health effects in wildlife. With advances in ecological indicators and analytical techniques for measurement of MeHg in a variety of tissues, numerous processes have been identified that can influence MeHg concentrations in wildlife. This review presents a synthesis of theoretical principals and applied information for measuring MeHg exposure and interpreting MeHg concentrations in wildlife. Mercury concentrations in wildlife are the net result of ecological processes influencing dietary exposure combined with physiological processes that regulate assimilation, transformation, and elimination. Therefore, consideration of both physiological and ecological processes should be integrated when formulating biomonitoring strategies. Ecological indicators, particularly stable isotopes of carbon, nitrogen, and sulfur, compound-specific stable isotopes, and fatty acids, can be effective tools to evaluate dietary MeHg exposure. Animal species differ in their physiological capacity for MeHg elimination, and animal tissues can be inert or physiologically active, act as sites of storage, transformation, or excretion of MeHg, and vary in the timing of MeHg exposure they represent. Biological influences such as age, sex, maternal transfer, and growth or fasting are also relevant for interpretation of tissue MeHg concentrations. Wildlife tissues that represent current or near-term bioaccumulation and in which MeHg is the predominant mercury species (such as blood and eggs) are most effective for biomonitoring ecosystems and understanding landscape drivers of MeHg exposure. Further research is suggested to critically evaluate the use of keratinized external tissues to measure MeHg bioaccumulation, particularly for less-well studied wildlife such as reptiles and terrestrial mammals. Suggested methods are provided to effectively use wildlife for quantifying patterns and drivers of MeHg bioaccumulation over time and space, as well as for assessing the potential risk and toxicological effects of MeHg on wildlife.

Science of the Total Environment↗
USGS2009

The ecology of dust

Wind erosion and associated dust emissions play a fundamental role in many ecological processes and provide important biogeochemical connectivity at scales ranging from individual plants up to the entire globe. Yet, most ecological studies do not explicitly consider dust‐driven processes, perhaps because most relevant research on aeolian (wind‐driven) processes has been presented in a geosciences rather than an ecological context. To bridge this disciplinary gap, we provide a general overview of the ecological importance of dust, examine complex interactions between wind erosion and ecosystem dynamics from the scale of plants and surrounding space to regional and global scales, and highlight specific examples of how disturbance affects these interactions and their consequences. It is likely that changes in climate and intensification of land use will lead to increased dust production from many drylands. To address these issues, environmental scientists, land managers, and policy makers need to consider wind erosion and dust emissions more explicitly in resource management decisions.

Frontiers in Ecology and the Environment↗
USGS2024

2023-2024 Coastal sage scrub and chaparral community monitoring for western San Diego County

Western San Diego County is dominated by shrublands supporting biologically diverse native plant and animal communities. Widespread urbanization has led to regional habitat loss and fragmentation, and many species in these shrubland communities are rare, threatened, or endangered. Large-scale, multiple-species conservation planning has resulted in a regional preserve system that focuses on these shrubland communities. Several large-scale threats are leading to type conversion from shrub-dominated to non-native invasive annual grass-dominated vegetation. To understand the changes that are occurring to native shrublands, we have developed a vegetation monitoring program with several components at multiple spatial scales, focused on quantifying coastal sage scrub (CSS) and chaparral vegetation community characteristics. Several drivers of change associated with type conversion of native shrubland to non-native annual grassland have been identified by previous research including increasing fire frequency, nitrogen deposition from air pollution, and prolonged and intense drought associated with changing climate. Loss of ecological integrity indices have been proposed as useful measures of the threat of degradation and type conversion of shrublands in San Diego County. For this study, ecological integrity is defined as a system’s ability to maintain species’ relationships and functions comparable to natural habitat in the region. Previous studies have identified the percent cover of invasive non-native annual grasses as a proxy for overall ecological degradation (loss of integrity) that is consistent across native taxonomic groups. Increased cover of non-native grass is associated with lower integrity of the shrubland vegetation community as shrub-associated plant and animal species are replaced by species preferring grassy and disturbed habitats. The objectives of this CSS and chaparral vegetation community monitoring plan are to: 1) Determine the distribution, composition, structure, and integrity of CSS and chaparral vegetation communities on conserved lands in western San Diego County, 2) Identify whether these attributes of the vegetation communities are changing over time, and 3) Evaluate relationships of known drivers of change (threats) and environmental factors in association with changes in vegetation community attributes. The CSS and chaparral vegetation community monitoring program is divided into four components: 1) vegetation mapping, 2) GIS/remote sensing office analysis of landscape-scale data, 3) permanent field plots using Unmanned Aerial Systems (UAS) and field data collections, and 4) animal and target species surveys and rapid assessment protocols. The first component, which is not detailed in this vegetation monitoring plan, aims to map vegetation communities every 10-15 years based on a classification developed for western San Diego County. High resolution aerial imagery will be used to update the 2012 vegetation map and expand it across the entire study area. The second component uses remote sensing models to annually track ecological integrity of shrublands across the study area and will include a map of areas of change and areas of stability over several decades. These landscape-scale integrity classifications will be used to analyze ecological processes, threats, and abiotic factors relative to changes to shrubland ecological integrity over time and space. The third component includes field surveys of 100 permanent plots across areas historically mapped as shrublands. Surveys in the 1930s mapped vegetation types using plot data. By using this historical classification map, we included areas that have already type-converted from shrubland to non-native annual grassland. The plots were split between CSS (55 plots) and chaparral (45 plots) and stratified into four geographical eco-subregions to guarantee coverage over small patches of habitat along the heavily developed coast. Surveys will include the collection of UAS imagery at a very high resolution. Species-level identifications will be made from the imagery based on a plant list compiled of all species detected in the plot during a thorough field survey by botanists, combined with geo-referenced samples of plant species locations. In addition, herbaceous cover will be estimated in the field using nine 1-m diameter circles (one per subplot) to obtain ocular estimates of cover for each plant species within the circle frame. Soil samples will be collected and analyzed for important element compositions. These data will be analyzed to evaluate plot-level ecological integrity based on species composition and cover. Repeated monitoring will allow evaluation of changes in vegetation attributes over time with known drivers or threats and other environmental factors. In addition, analyses will focus on indicator species and various measures of biological diversity for the vegetation communities. Finally, animal species and rare plants will be assessed using either taxa-based rapid assessment protocols or specialized species-specific protocols for rarer species. The purpose of these assessments is to document the status, habitat, and threat covariates of specific species and confirm the species composition and diversity of animal taxonomic groups (e.g., pollinators). Diversity and abundance of animal species at vegetation plots will be used to refine measures and thresholds of ecological integrity. Rapid assessment protocols for animal taxonomic groups can include multiple detection methods such as, camera traps, cover boards, and bird point counts. Pollinators will be monitored at plots using a protocol currently being developed in conjunction with but separately from this plan. Target rare plant species will be monitored using the regional Inspect and Manage (IMG) protocol that measures the status of rare plant occurrences and habitat and threat covariates over time. Species-specific animal survey methods will be refined as these species are prioritized for future monitoring. The goal of this monitoring program is to classify CSS and chaparral vegetation community integrity, identify areas of degradation across western San Diego County, and characterize drivers, and environmental factors associated with loss of ecological integrity. A combination of vegetation mapping, landscape-scale remote sensing, and field plots will be used to address all the aspects of our research questions. Data compiled and collected will be available to conservation partners to help inform future management decisions.

California↗
USGS2005

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Environmetrics↗
USGS2018

Integrating animal movement with habitat suitability for estimating dynamic migratory connectivity

Context High-resolution animal movement data are becoming increasingly available, yet having a multitude of empirical trajectories alone does not allow us to easily predict animal movement. To answer ecological and evolutionary questions at a population level, quantitative estimates of a species’ potential to link patches or populations are of importance. Objectives We introduce an approach that combines movement-informed simulated trajectories with an environment-informed estimate of the trajectories’ plausibility to derive connectivity. Using the example of bar-headed geese we estimated migratory connectivity at a landscape level throughout the annual cycle in their native range. Methods We used tracking data of bar-headed geese to develop a multi-state movement model and to estimate temporally explicit habitat suitability within the species’ range. We simulated migratory movements between range fragments, and calculated a measure we called route viability. The results are compared to expectations derived from published literature. Results Simulated migrations matched empirical trajectories in key characteristics such as stopover duration. The viability of the simulated trajectories was similar to that of the empirical trajectories. We found that, overall, the migratory connectivity was higher within the breeding than in wintering areas, corroborating previous findings for this species. Conclusions We show how empirical tracking data and environmental information can be fused for meaningful predictions of animal movements throughout the year and even outside the spatial range of the available data. Beyond predicting migratory connectivity, our framework will prove useful for modelling ecological processes facilitated by animal movement, such as seed dispersal or disease ecology.

Landscape Ecology↗
USGS2014

Quantifying and valuing ecosystem services: An application of ARIES to the San Pedro River basin, USA

A large body of research exists that identifies and values ecosystem services - the benefits that ecosystems provide to humans (MA, 2005) - and their underlying ecological processes. However, the development of software decision support tools that integrate ecology, economics and geography that can be independently used within the public, private, academic and NGO sectors is a more recent phenomenon (Ruhl et al., 2007; Daily et al., 2009). Spurred by growing demand for more sophisticated analysis of the social and economic consequences of land management decisions, the US Department of Interior - Bureau of Land Management (BLM) launched a pilot project with the US Geological Survey (USGS) to assess the usefulness and feasibility of ecosystem service assessment and valuation tools to provide inputs to decision-making. The project analysed ecosystem services in the US portion of the San Pedro River watershed, which includes the BLM-managed San Pedro Riparian National Conservation Area (SPRNCA), to improve the understanding of complex social and ecological relationships that transcend administrative divisions. The BLM manages some 99 million hectares, primarily in the western United States, and 283 million hectares of sub-surface mineral estate. BLM's multiple-use mission requires that it appropriately balance non-extractive uses such as habitat conservation, recreation and archaeological heritage protection and the extractive use of resources such as timber, oil and gas, coal, uranium, and other minerals.

Arizona↗
USGS2015

Predictive modelling of habitat use by marine predators with respect to the abundance and depth distribution of pelagic prey

Understanding the ecological processes that underpin species distribution patterns is a fundamental goal in spatial ecology. However, developing predictive models of habitat use is challenging for species that forage in marine environments, as both predators and prey are often highly mobile and difficult to monitor. Consequently, few studies have developed resource selection functions for marine predators based directly on the abundance and distribution of their prey. We analysed contemporaneous data on the diving locations of two seabird species, the shallow-diving Peruvian Booby ( Sula variegata ) and deeper diving Guanay Cormorant ( Phalacrocorax bougainvilliorum ), and the abundance and depth distribution of their main prey, Peruvian anchoveta ( Engraulis ringens ). Based on this unique data set, we developed resource selection functions to test the hypothesis that the probability of seabird diving behaviour at a given location is a function of the relative abundance of prey in the upper water column. For both species, we show that the probability of diving behaviour is mostly explained by the distribution of prey at shallow depths. While the probability of diving behaviour increases sharply with prey abundance at relatively low levels of abundance, support for including abundance in addition to the depth distribution of prey is weak, suggesting that prey abundance was not a major factor determining the location of diving behaviour during the study period. The study thus highlights the importance of the depth distribution of prey for two species of seabird with different diving capabilities. The results complement previous research that points towards the importance of oceanographic processes that enhance the accessibility of prey to seabirds. The implications are that locations where prey is predictably found at accessible depths may be more important for surface foragers, such as seabirds, than locations where prey is predictably abundant. Analysis of the relative importance of abundance and accessibility is essential for the design and evaluation of effective management responses to reduced prey availability for seabirds and other top predators in marine systems.

Gulf of Guinea↗
USGS2016

Evaluation of downscaled, gridded climate data for the conterminous United States

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Ecological Applications↗
USGS2021

From site to system: Approaches for producing system-wide estimates of fish habitat in large rivers

Worldwide, many productive rivers are dam-regulated and rely on flow management strategies that must balance support of ecological processes with human water use. One component of evaluating this balance is to understand ecological consequences of alternative flow management strategies, which has often been accomplished by coupling population dynamics models with models that relate streamflow to habitat availability and quality. Numerous methods assign habitat availability to locations within a river basin: These include fine-scale field-measured values that are extrapolated to other locations within the basin having similar physical characteristics or equation-driven values created by functions of model-predicted values of physical characteristics. The array of options for creating habitat models is evolving rapidly as high-resolution remote-sensing data becomes more accessible and computational capacity improves. Our objective was to identify trade-offs among approaches that assign habitat relationships to large rivers and to create a decision support tool to supplement choices of extent and granularity. Using a selection of case studies that represent a breadth of scales and diverse trade-offs, we demonstrate the need for a transparent process of data evaluation and assessment to determine the appropriate fit for model scope or context that best supports management needs and recognize sources of uncertainty. The structured approach proposed here aims at improving future model development and refine population dynamics models that inform the management of rivers.

River Research and Applications↗
USGS2025

A comparison of deep-sea coral and sponge species distribution models and the impact of ocean currents in the Southern California Bight

Deep-sea corals and sponges (DSCS) are signature taxa of deep-water habitats, but ecological mechanisms that drive their geographic distributions can be difficult to uncover due to the challenges of surveying deep-water ecosystems and limited oceanographic data. A comparison of species distribution models was made for three DSCS ( Antipathes dendochristos, Plumarella longispina, and an unidentified sponge morphotype known as Porifera #2), two of which are associated with young-of-the-year and adult rockfish taxa ( Sebastes spp.). Models were built using generalized additive models (GAMs) that accounted for spatial autocorrelation. These models were compared to Maxent models, a commonly used method. All models utilized bathymetrically derived variables (including depth, slope, and Bathymetric Position Index) and output from a coupled physical-biogeochemical ocean model (including current direction and magnitude, food abundance, and dissolved oxygen). Direction of benthic ocean currents played an important role in predictions, pointing to large-scale ecological processes that may determine presence of DSCS. GAMs outperformed Maxent models and predicted more ecologically interpretable patterns. Additionally we quantified the predicted amount of suitable habitat that is currently located within some protected areas of the Southern California Bight and show that many hot spots occur outside protected areas. Given the importance of DSCS for multiple demersal fish species of commercial or conservation concerns, this research provides valuable information that natural resource managers can use as a tool in the Southern California Bight.

California↗
USGS2013

Mapping behavioral landscapes for animal movement: a finite mixture modeling approach

Because of its role in many ecological processes, movement of animals in response to landscape features is an important subject in ecology and conservation biology. In this paper, we develop models of animal movement in relation to objects or fields in a landscape. We take a finite mixture modeling approach in which the component densities are conceptually related to different choices for movement in response to a landscape feature, and the mixing proportions are related to the probability of selecting each response as a function of one or more covariates. We combine particle swarm optimization and an Expectation-Maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. We use this approach to analyze data for movement of three bobcats in relation to urban areas in southern California, USA. A behavioral interpretation of the models revealed similarities and differences in bobcat movement response to urbanization. All three bobcats avoided urbanization by moving either parallel to urban boundaries or toward less urban areas as the proportion of urban land cover in the surrounding area increased. However, one bobcat, a male with a dispersal-like large-scale movement pattern, avoided urbanization at lower densities and responded strictly by moving parallel to the urban edge. The other two bobcats, which were both residents and occupied similar geographic areas, avoided urban areas using a combination of movements parallel to the urban edge and movement toward areas of less urbanization. However, the resident female appeared to exhibit greater repulsion at lower levels of urbanization than the resident male, consistent with empirical observations of bobcats in southern California. Using the parameterized finite mixture models, we mapped behavioral states to geographic space, creating a representation of a behavioral landscape. This approach can provide guidance for conservation planning based on analysis of animal movement data using statistical models, thereby linking connectivity evaluations to empirical data.

Ecological Applications↗
USGS2022

The socioecology of fear: A critical geographical consideration of human-wolf-livestock conflict

Animal fear can be an important driver of ecological community structure: predators affect prey not only through predation, but by inducing changes in behavior and distribution—a phenomenon evocatively called the “ecology of fear.” The return of wolves to the western United States is a notable instance of such dynamics, yet plays out in a complex socio-ecological system where efforts to mitigate impacts on livestock rely on manipulating wolves’ fear of people. Examining Washington state’s efforts to affect wolf behavior to reduce livestock predation, we argue that this approach to coexistence with wolves is predicated on relations of fear: people, livestock, and wolves can arguably share landscapes with minimal conflict, as long as wolves are adequately afraid. We introduce the “socioecology of fear” as an interdisciplinary framework for examining the interwoven social and ecological processes of human-wildlife conflict management. Beyond frequently-voiced ideas about wolves’ “innate” fear, we examine how fear is (re)produced through human-wolf interactions and deeply shaped by human social processes. We contribute to the Critical Physical Geography project by integrating critical social analysis with ecological theory, conducted through collaborative interdisciplinary dialogue. Such integrative practice is essential for understanding the complex challenges of managing wildlife in the Anthropocene.

Washington↗
USGS2006

Use of Numerical Simulations in Surface-Water Studies by the U.S. Geological Survey in Missouri

Numerical simulations of surface-water systems can be a useful tool to predict and understand a variety of physical, chemical, and ecological processes. A number of applications have been conducted by the U.S. Geological Survey Missouri Water Science Center in conjunction with ecological and flood studies in Missouri. Numerical simulations can provide a physically based method to predict natural processes in situations where it is impractical to measure the results directly as a result of cost, time, or infrequent occurrence. Numerical simulations provide a means of analyzing 'What if?' scenarios. For example, a simulation can be used to estimate the effects of reservoirs in a basin on the timing and magnitude of downstream streamflows. Simulations also may provide a better understanding of a complex process, such as sediment transport and deposition during a large flood. Alternatively, numerical simulations can be used to quantify aquatic habitat that is defined by the hydraulic (depth and velocity) characteristics of streamflow. This report provides information on recent applications of numerical simulations of hydraulic, floodplain, and watershed processes.

Fact Sheet↗
USGS2017

Decadal declines in avian herbivore reproduction: density-dependent nutrition and phenological mismatch in the Arctic

A full understanding of population dynamics depends not only on estimation of mechanistic contributions of recruitment and survival, but also knowledge about the ecological processes that drive each of these vital rates. The process of recruitment in particular may be protracted over several years, and can depend on numerous ecological complexities until sexually mature adulthood is attained. We addressed long-term declines (23 breeding seasons, 1992–2014) in the per capita production of young by both Ross's Geese ( Chen rossii ) and Lesser Snow Geese ( Chen caerulescens caerulescens ) nesting at Karrak Lake in Canada's central Arctic. During this period, there was a contemporaneous increase from 0.4 to 1.1 million adults nesting at this colony. We evaluated whether (1) density-dependent nutritional deficiencies of pre-breeding females or (2) phenological mismatch between peak gosling hatch and peak forage quality, inferred from NDVI on the brood-rearing areas, may have been behind decadal declines in the per capita production of goslings. We found that, in years when pre-breeding females arrived to the nesting grounds with diminished nutrient reserves, the proportional composition of young during brood-rearing was reduced for both species. Furthermore, increased mismatch between peak gosling hatch and peak forage quality contributed additively to further declines in gosling production, in addition to declines caused by delayed nesting with associated subsequent negative effects on clutch size and nest success. The degree of mismatch increased over the course of our study because of advanced vegetation phenology without a corresponding advance in Goose nesting phenology. Vegetation phenology was significantly earlier in years with warm surface air temperatures measured in spring (i.e., 25 May–30 June). We suggest that both increased phenological mismatch and reduced nutritional condition of arriving females were behind declines in population-level recruitment, leading to the recent attenuation in population growth of Snow Geese.

Ecology↗
USGS2022

Estuarine Geomorphology, Circulation, and Mixing

To understand the processes affecting the distribution and cycles of particulates, pollutants, nutrients, and organisms in estuaries, it is insufficient to focus solely on the biological and chemical aspects of the processes. Water sources and movements (e.g. evaporation, precipitation, riverine discharge, submarine ground water discharge, wetland hydrology, and tidal exchange) as well as other hydrodynamic aspects of coastal systems, including circulation patterns, stratification, mixing and flushing, must also be considered. When hydrodynamic changes occur quickly relative to biological, geological, and chemical transformations, they become the dominant controlling factors of many ecological processes in estuaries (Officer 1980), and it is now widely recognized that a thorough understanding of the marine estuarine ecology requires comprehensive knowledge and integration of physical processes affecting the system. Using the terminology of a shallow-water oceanographer, this chapter aims to organize, classify, and describe some of these important physical characteristics and processes.

Book chapter↗
USGS2018

Adaptive management of animal populations with significant unknowns and uncertainties: A case study

Conservation and management decision making in natural resources is challenging due to numerous uncertainties and unknowns, especially relating to understanding system dynamics. Adaptive resource management (ARM) is a formal process to making logical and transparent recurrent decisions when there are uncertainties about system dynamics. Despite wide recognition and calls for implementing adaptive natural resource management, applications remain limited. More common is a reactive approach to decision making, which ignores future system dynamics. This contrasts with ARM, which anticipates future dynamics of ecological process and management actions using a model-based framework. Practitioners may be reluctant to adopt ARM because of the dearth of comparative evaluations between ARM and more common approaches to making decisions. We compared the probability of meeting management objectives when managing a population under both types of decision frameworks, specifically in relation to typical uncertainties and unknowns. We use a population of Sandhill Cranes as our case study. We evaluate each decision process under varying levels of monitoring and ecological uncertainty, where the true underlying population dynamics followed a stochastic age-structured population model with environmentally driven vital rate density dependence. We found that the ARM framework outperformed the currently employed reactive decision framework to manage Sandhill Cranes in meeting the population objective across an array of scenarios. This was even the case when the candidate set of population models contained only naïve representations of the true population process. Under the reactive decision framework, we found little improvement in meeting the population objective even if monitoring uncertainty was eliminated. In contrast, if the population was monitored without error within the ARM framework, the population objective was always maintained, regardless of the population models considered. Contrary to expectation, we found that age-specific optimal harvest decisions are not always necessary to meet a population objective when population dynamics are age structured. Population managers can decrease risks and gain transparency and flexibility in management by adopting an ARM framework. If population monitoring data has high sampling variation and/or limited empirical knowledge is available for constructing mechanistic population models, ARM model sets should consider a range of mechanistic, descriptive, and predictive model types.

Ecological Applications↗
USGS2017

Dam removal: Listening in

Dam removal is widely used as an approach for river restoration in the United States. The increase in dam removals—particularly large dams—and associated dam-removal studies over the last few decades motivated a working group at the USGS John Wesley Powell Center for Analysis and Synthesis to review and synthesize available studies of dam removals and their findings. Based on dam removals thus far, some general conclusions have emerged: (1) physical responses are typically fast, with the rate of sediment erosion largely dependent on sediment characteristics and dam-removal strategy; (2) ecological responses to dam removal differ among the affected upstream, downstream, and reservoir reaches; (3) dam removal tends to quickly reestablish connectivity, restoring the movement of material and organisms between upstream and downstream river reaches; (4) geographic context, river history, and land use significantly influence river restoration trajectories and recovery potential because they control broader physical and ecological processes and conditions; and (5) quantitative modeling capability is improving, particularly for physical and broad-scale ecological effects, and gives managers information needed to understand and predict long-term effects of dam removal on riverine ecosystems. Although these studies collectively enhance our understanding of how riverine ecosystems respond to dam removal, knowledge gaps remain because most studies have been short (< 5 years) and do not adequately represent the diversity of dam types, watershed conditions, and dam-removal methods in the U.S.

Water Resources Research↗