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At least 469 records · Page 26Linked to original sources
USGS2013

Ecological prediction with nonlinear multivariate time-frequency functional data models

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Lower Missouri River↗
USGS2008

Some guidelines for helping natural resources adapt to climate change

The changes occurring in mountain regions are an epitome of climate change. The dramatic shrinkage of major glaciers over the past century – and especially in the last 30 years – is one of several iconic images that have come to symbolize climate change. Climate creates the context for ecosystems, and climate variables strongly influence the structure, composition, and processes that characterize distinct ecosystems. Climate change, therefore, is having direct and indirect effects on species attributes, ecological interactions, and ecosystem processes. Because changes in the climate system will continue regardless of emissions mitigation, management strategies to enhance the resilience of ecosystems will become increasingly important. It is essential that management responses to climate change proceed using the best available science despite uncertainties associated with the future path of climate change, the response of ecosystems to climate effects, and the effects of management. Given these uncertainties, management adaptation will require flexibility to reflect our growing understanding of climate change impacts and management effectiveness.

IHDP Update↗
USGS2016

The role of habitat filtering in the leaf economics spectrum and plant susceptibility to pathogen infection

1.The Leaf Economics Spectrum (LES) describes global covariation in the traits of plant leaves. The LES is thought to arise from biophysical constraints and habitat filtering (ecological selection against unfit trait combinations along environmental gradients). However, the role of habitat filtering in generating the LES has not been tested experimentally. 2.If the process of habitat filtering plays a role in generating the LES, the LES could weaken in communities that have yet to be filtered by the current environment, for example after abiotic environmental change. LES traits are commonly used to predict community and ecosystem processes, and if the LES weakens in unfiltered communities, LES-based models may no longer apply. 3.In the greenhouse, we experimentally simulated three stages of habitat filtering in response to abiotic change: from unfiltered, to semi-filtered, to completely filtered communities. In each stage, we quantified the strength of the LES and assessed the accuracy of trait-based models of an important ecological process, pathogen infection. 4.The strength of the LES increased with the completeness of habitat filtering, as did the accuracy of trait-based models of plant susceptibility to pathogen infection. 5. Synthesis . Our results suggest that habitat filtering plays a fundamental role in strengthening the trait correlations of the LES, and that trait-based models may be less accurate when communities have not been filtered by the current environment, for example, following rapid environmental change.

Journal of Ecology↗
USGS2015

Assessing local population vulnerability to wind energy development with branching process models: an application to wind energy development

Quantifying the impact of anthropogenic development on local populations is important for conservation biology and wildlife management. However, these local populations are often subject to demographic stochasticity because of their small population size. Traditional modeling efforts such as population projection matrices do not consider this source of variation whereas individual-based models, which include demographic stochasticity, are computationally intense and lack analytical tractability. One compromise between approaches is branching process models because they accommodate demographic stochasticity and are easily calculated. These models are known within some sub-fields of probability and mathematical ecology but are not often applied in conservation biology and applied ecology. We applied branching process models to quantitatively compare and prioritize species locally vulnerable to the development of wind energy facilities. Specifically, we examined species vulnerability using branching process models for four representative species: A cave bat (a long-lived, low fecundity species), a tree bat (short-lived, moderate fecundity species), a grassland songbird (a short-lived, high fecundity species), and an eagle (a long-lived, slow maturation species). Wind turbine-induced mortality has been observed for all of these species types, raising conservation concerns. We simulated different mortality rates from wind farms while calculating local extinction probabilities. The longer-lived species types (e.g., cave bats and eagles) had much more pronounced transitions from low extinction risk to high extinction risk than short-lived species types (e.g., tree bats and grassland songbirds). High-offspring-producing species types had a much greater variability in baseline risk of extinction than the lower-offspring-producing species types. Long-lived species types may appear stable until a critical level of incidental mortality occurs. After this threshold, the risk of extirpation for a local population may rapidly increase with only minimal increases in wind mortality. Conservation biologists and wildlife managers may need to consider this mortality pattern when issuing take permits and developing monitoring protocols for wind facilities. We also describe how our branching process models may be generalized across a wider range of species for a larger assessment project and then describe how our methods may be applied to other stressors in addition to wind.

Ecosphere↗
USGS2019

Planning for ecological drought: Integrating ecosystem services and vulnerability assessment

As research recognizes the importance of ecological impacts of drought to natural and human communities, drought planning processes need to better incorporate ecological impacts. Drought planning currently recognizes the vulnerability of some ecological impacts from drought (e.g., loss of instream flow affecting fish populations). However, planning often does not identify all the ecological aspects in a landscape that stakeholders value, nor does it examine the extent to which those aspects are vulnerable to drought. One approach for identifying ecological aspects is ecosystem services (ES) -- i.e., the benefits humans receive from nature. To incorporate ecological impacts into drought planning in the Upper Missouri Headwaters region (Montana, USA), we combined ES elicitation using the Common International Classification of Ecosystem Services and a vulnerability assessment using semi-structured interviews. We juxtaposed results from the interviews and the ES elicitation to assess which ES might be vulnerable to drought and which impacts from interviews were associated with losses of ES. While both methods suggested common drought vulnerabilities, each method also suggested drought vulnerabilities not reported using the other method. The ES elicitation produced more detail about services present in the UMH ecosystem today while interviews resulted in more discussion about ecological transformation from future droughts. Results suggest that some combination of open-ended vulnerability assessment methods and ES elicitation using a structured framework can result in greater understanding of ecological drought vulnerability in a given region.

Montana↗
USGS2021

The ecology of river ice

Many of the world's rivers are ice-covered during winter months but increasing evidence indicates that the extent of river ice will shift substantially as winters warm. However, our knowledge of rivers during winter lags far behind that of the growing season, limiting our understanding of how ice loss will affect rivers. Physical, chemical, and biological processes change from headwaters to large rivers; thus, we expect ice processes and resulting effects on the ecology of rivers could also vary with river size, as a result of the associated changes in geomorphology, temperature regimes, and connectivity. To conceptualize these relationships, we review typically disparate literature on ice processes and winter ecology and compare what is known in the smallest and largest rivers. In doing so, we show that our ability to link ice with ecology across river networks is made difficult by a primary focus on ice processes in larger rivers and a lack of study of ecosystem processes during winter. To address some of these gaps, we provide new scenarios of river ice loss and analyses of how the annual importance of winter gross primary productivity (GPP) varies with river size. We show projected ice loss varied with large-scale watershed characteristics such as north-south orientation and that the importance of winter to annual GPP was greatest in the smallest rivers. Finally, we highlight information needed to fill knowledge gaps on winter across river networks and improve our understanding of how rivers may change as climate and ice regimes shift.

JGR Biogeosciences↗
USGS2022

Know what you don't know: Embracing state uncertainty in disease-structured multistate models

Hidden Markov models (HMMs) are broadly applicable hierarchical models that derive their utility from separating state processes from observation processes yielding the data. Multistate models such as mark–recapture and dynamic multistate occupancy models are HMMs frequently used in ecology. In their early formulations, states, such as pathogen infection status, were assumed to be perfectly observed without ambiguity. However, state uncertainty is a pervasive feature of many ecological studies, and multievent models were developed to explicitly account for it. We developed a novel extended multievent mark–recapture model that incorporates state uncertainty at multiple levels of detection. Using a disease-structured example, both false negative and false positive state assignment errors are modelled at two levels of state assignment—the pathogen sampling process and the diagnostic process that samples are subjected to. We additionally describe methods to jointly model infection intensity to integrate heterogeneity in ecological parameters, such as mortality and infection dynamics, and the pathogen detection processes. We provide code to simulate and analyse datasets with various underlying ecological processes and fit our model to a mark–recapture dataset of Mixophyes fleayi (Fleay's barred frog) infected with the amphibian chytrid fungus ( Batrachochytrium dendrobatidis , Bd ). In our case study, we found evidence for various state assignment errors: the sampling protocol performed poorly in detecting Bd , pathogen detection was highly dependent on infection intensity and false positives were non-negligible. Incorporating state uncertainty yielded significantly higher estimates of infection prevalence and 4–5 times lower rates of infection state transitions compared to those obtained from a traditional multistate model. Our results highlight that incorporating state assignment errors improves inference on the ecological process, especially when sensitivity and specificity of the state assignment processes are low. The general model structure can be applied to other HMMs, providing a foundation for modelling state uncertainty in related models. For disease-structured multistate models, we recommend conducting robust design surveys and collecting samples during each capture event to facilitate incorporating pathogen detection errors.

Methods in Ecology and Evolution↗
USGS2012

Species, functional groups, and thresholds in ecological resilience

The cross-scale resilience model states that ecological resilience is generated in part from the distribution of functions within and across scales in a system. Resilience is a measure of a system's ability to remain organized around a particular set of mutually reinforcing processes and structures, known as a regime. We define scale as the geographic extent over which a process operates and the frequency with which a process occurs. Species can be categorized into functional groups that are a link between ecosystem processes and structures and ecological resilience. We applied the cross-scale resilience model to avian species in a grassland ecosystem. A species’ morphology is shaped in part by its interaction with ecological structure and pattern, so animal body mass reflects the spatial and temporal distribution of resources. We used the log-transformed rank-ordered body masses of breeding birds associated with grasslands to identify aggregations and discontinuities in the distribution of those body masses. We assessed cross-scale resilience on the basis of 3 metrics: overall number of functional groups, number of functional groups within an aggregation, and the redundancy of functional groups across aggregations. We assessed how the loss of threatened species would affect cross-scale resilience by removing threatened species from the data set and recalculating values of the 3 metrics. We also determined whether more function was retained than expected after the loss of threatened species by comparing observed loss with simulated random loss in a Monte Carlo process. The observed distribution of function compared with the random simulated loss of function indicated that more functionality in the observed data set was retained than expected. On the basis of our results, we believe an ecosystem with a full complement of species can sustain considerable species losses without affecting the distribution of functions within and across aggregations, although ecological resilience is reduced. We propose that the mechanisms responsible for shaping discontinuous distributions of body mass and the nonrandom distribution of functions may also shape species losses such that local extinctions will be nonrandom with respect to the retention and distribution of functions and that the distribution of function within and across aggregations will be conserved despite extinctions.

Conservation Biology↗
USGS2002

Research plan for lands administered by the U.S. Department of the Interior in the Interior Columbia Basin and Snake River Plateau

This document presents a long-term research strategy designed to address current and future research needs for management of Department of the Interior-administered ecosystems in the Intermountain West. Although the research plan was developed in the context of the Interior Columbia Basin Ecosystem Management Project, the plan addresses many high-priority issues facing land managers throughout the Intermountain West. These issues pose management challenges that may be addressed with applied research both currently and in upcoming decades. Possessing a particular focus on semiarid ecosystems, the plan is a collection of research questions under five categories of research emphases: 1) restoration; 2) rangeland health; 3) aquatic-terrestrial connections; 4) development of monitoring and evaluation protocols; and 5) species and habitats at risk. The goal of the research strategy is to provide ideas for integrating emerging scientific understanding into future management in order to restore and maintain long-term ecosystem health and ecological integrity; provide consistent management direction over broad spatial and temporal scales; emphasize adaptive management over the long term; restore and maintain habitats for plant and animal species; and support economic and social needs of people, without compromising the above goals. Research questions are prioritized into three categories based on the immediacy of their need, feasibility of addressing the question rigorously under varying funding budgets, and magnitude of risk posed by not addressing the issue. The research strategy is intended to support and integrate with existing management efforts and strategies. As such, it melds observational studies with experimental manipulation, treating management actions as experiments whenever feasible. The research strategy focuses on disturbance processes and events that have been the primary drivers of change, to provide a predictive model for future changes. These drivers include fire, nonnative plants, herbivory, roads and associated human influences, and climate change. Whereas management in the western United States has striven to move from an inefficient species-based approach to a habitat-based approach, the plan focuses on ecosystem function and ecological processes as critical measures of habitat response. Because of the large amount and contiguity of public lands in the western United States, the region presents both a compelling opportunity to implement landscape-level science and a challenge to underst

Information and Technology Report↗
USGS2004

Complex trophic interactions in kelp forest ecosystems

The distributions and abundances of species and populations change almost continuously. Understanding the processes responsible is perhaps ecology’s most fundamental challenge. Kelp-forest ecosystems in southwest Alaska have undergone several phase shifts between alga- and herbivore-dominated states in recent decades. Overhunting and recovery of sea otters caused the earlier shifts. Studies focusing on these changes demonstrate the importance of top-down forcing processes, a variety of indirect food-web interactions associated with the otter-urchin-kelp trophic cascade, and the role of food-chain length in the coevolution of defense and resistance in plants and their herbivores. This system unexpectedly shifted back to an herbivore-dominated state during the 1990s, because of a sea-otter population collapse that apparently was driven by increased predation by killer whales. Reasons for this change remain uncertain but seem to be linked to the whole-sale collapse of marine mammals in the North Pacific Ocean and southern Bering Sea. We hypothesize that killer whales sequentially "fished down" pinniped and sea-otter populations after their earlier prey, the great whales, were decimated by commercial whaling. The dynamics of kelp forests in southwest Alaska thus appears to have been influenced by an ecological chain reaction that encompassed numerous species and large scales of space and time.

Bulletin of Marine Science↗
USGS2018

On the development of a magnetic susceptibility‐based tracer for aeolian sediment transport research

Aeolian processes — the erosion, transport, and deposition of sediment by wind — play important geomorphological and ecological roles in drylands. These processes are known to impact the spatial patterns of soil, nutrients, plant‐available water, and vegetation in many dryland ecosystems. Tracers, such as rare earth elements and stable isotopes have been successfully used to quantify the transport and redistribution of sediment by aeolian processes in these ecosystems. However, many of the existing tracer techniques are labor‐intensive and cost‐prohibitive, and hence simpler alternative approaches are needed to track aeolian redistribution of sediments. To address this methodological gap, we test the applicability of a novel metal tracer‐based methodology for estimating post‐fire aeolian sediment redistribution, using spatio‐temporal measurements of low‐field magnetic susceptibility (MS). We applied magnetic metal tracers on soil microsites beneath shrub vegetation in recently burned and control treatments in a heterogeneous landscape in the Chihuahuan desert (New Mexico, USA). Our results indicate a spatially homogeneous distribution of the magnetic tracers on the landscape after post‐burn wind erosion events. MS decreased after wind erosion events on the burned shrub microsites, indicating that these areas functioned as sediment sources following the wildfire, whereas they are known to be sediment sinks in the undisturbed (e.g., not recently burned) ecosystem. This experiment represents the first step toward the development of a cost‐effective and non‐destructive tracer‐based approach to estimate the transport and redistribution of sediment by aeolian processes.

Earth Surface Processes and Landforms↗
USGS2015

Community ecology in a changing environment: Perspectives from the Quaternary

Community ecology and paleoecology are both concerned with the composition and structure of biotic assemblages but are largely disconnected. Community ecology focuses on existing species assemblages and recently has begun to integrate history (phylogeny and continental or intercontinental dispersal) to constrain community processes. This division has left a “missing middle”: Ecological and environmental processes occurring on timescales from decades to millennia are not yet fully incorporated into community ecology. Quaternary paleoecology has a wealth of data documenting ecological dynamics at these timescales, and both fields can benefit from greater interaction and articulation. We discuss ecological insights revealed by Quaternary terrestrial records, suggest foundations for bridging between the disciplines, and identify topics where the disciplines can engage to mutual benefit.

PNAS↗
USGS2019

Quantifying trends and uncertainty in prehistoric forest composition

Forest ecosystems in eastern North America were in flux over the last several thousand years, well before Euro-American land clearance and the 20th-century onset of anthropogenic climate change. However, the magnitude and uncertainty of prehistoric vegetation change have been difficult to quantify because of the multiple ecological, dispersal, and sedimentary processes that govern the relationship between forest composition and fossil pollen assemblages. Here we extend STEPPS, a Bayesian hierarchical spatio-temporal pollen-vegetation model, to estimate changes in forest composition in the upper Midwestern United States from about 2000 to 200 years ago. Using this approach, we identify areas of statistically and ecologically significant change. Between 2000 and 200 years ago, forest composition significantly changed across broad regions of north-central Wisconsin and Minnesota. Rates of compositional change varied spatially, and can be linked to previously reported events. The single largest change is the infilling of Tsuga canadensis in northern Wisconsin over the past 2000 years. Despite this range in-filling, the range limit of T. canadensis was largely stable, with modest expansion westward. The regional ecotone between temperate hardwood forests and northern mixed hardwood/conifer forests shifted southwestward by 15-20 km in Minnesota and Northwestern Wisconsin. Fraxinus, Ulmus, and other mesic hardwoods expanded in the Big Woods region of southern Minnesota. However, some areas showed no significant change, suggesting high complexity in the spatiotemporal patterns of past forest dynamics. The increasing density of paleoecological data networks and advances in statistical modeling approaches now enables the confident detection of subtle but significant changes in forest composition over the last 2000 years.

Minnesota, Wisconsin↗
USGS2017

Complex networks of functional connectivity in a wetland reconnected to its floodplain

Disturbances such as fire or flood, in addition to changing the local magnitude of ecological, hydrological, or biogeochemical processes, can also change their functional connectivity—how those processes interact in space. Complex networks offer promise for quantifying functional connectivity in watersheds. The approach resolves connections between nodes in space based on statistical similarities in perturbation signals (derived from solute time series) and is sensitive to a wider range of timescales than traditional mass-balance modeling. We use this approach to test hypotheses about how fire and flood impact ecological and biogeochemical dynamics in a wetland (Everglades, FL, USA) that was reconnected to its floodplain. Reintroduction of flow pulses after decades of separation by levees fundamentally reconfigured functional connectivity networks. The most pronounced expansion was that of the calcium network, which reflects periphyton dynamics and may represent an indirect influence of elevated nutrients, despite the comparatively smaller observed expansion of phosphorus networks. With respect to several solutes, periphyton acted as a “biotic filter,” shifting perturbations in water-quality signals to different timescales through slow but persistent transformations of the biotic community. The complex-networks approach also revealed portions of the landscape that operate in fundamentally different regimes with respect to dissolved oxygen, separated by a threshold in flow velocity of 1.2 cm/s, and suggested that complete removal of canals may be needed to restore connectivity with respect to biogeochemical processes. Fire reconfigured functional connectivity networks in a manner that reflected localized burn severity, but had a larger effect on the magnitude of solute concentrations.

Florida↗
USGS2015

A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

Hydrology and Earth System Sciences↗
USGS2010

Environmental controls of wood entrapment in upper Midwestern streams

Wood deposited in streams provides a wide variety of ecosystem functions, including enhancing habitat for key species in stream food webs, increasing geomorphic and hydraulic heterogeneity and retaining organic matter. Given the strong role that wood plays in streams, factors that influence wood inputs, retention and transport are critical to stream ecology. Wood entrapment, the process of wood coming to rest after being swept downstream at least 10 m, is poorly understood, yet important for predicting stream function and success of restoration efforts. Data on entrapment were collected for a wide range of natural wood pieces ( n = 344), stream geomorphology and hydraulic conditions in nine streams along the north shore of Lake Superior in Minnesota. Locations of pieces were determined in summer 2007 and again following an overbank stormflow event in fall 2007. The ratio of piece length to effective stream width (length ratio) and the weight of the piece were important in a multiple logistic regression model that explained 25% of the variance in wood entrapment. Entrapment remains difficult to predict in natural streams, and often may simply occur wherever wood pieces are located when high water recedes. However, this study can inform stream modifications to discourage entrapment at road crossings or other infrastructure by applying the model formula to estimate the effective width required to pass particular wood pieces. Conversely, these results could also be used to determine conditions (e.g. pre-existing large, stable pieces) that encourage entrapment where wood is valued for ecological functions.

Minnesota↗
USGS2018

Running on empty: Recharge dynamics from animal movement data

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion ( Puma concolor ; in Colorado, USA) and African buffalo ( Syncerus caffer ; in Kruger National Park, South Africa) recharge dynamics.

Ecology Letters↗
USGS2015

Understanding protected area resilience: a multi-scale, social-ecological approach

Protected areas (PAs) remain central to the conservation of biodiversity. Classical PAs were conceived as areas that would be set aside to maintain a natural state with minimal human influence. However, global environmental change and growing cross-scale anthropogenic influences mean that PAs can no longer be thought of as ecological islands that function independently of the broader social-ecological system in which they are located. For PAs to be resilient (and to contribute to broader social-ecological resilience), they must be able to adapt to changing social and ecological conditions over time in a way that supports the long-term persistence of populations, communities, and ecosystems of conservation concern. We extend Ostrom's social-ecological systems framework to consider the long-term persistence of PAs, as a form of land use embedded in social-ecological systems, with important cross-scale feedbacks. Most notably, we highlight the cross-scale influences and feedbacks on PAs that exist from the local to the global scale, contextualizing PAs within multi-scale social-ecological functional landscapes. Such functional landscapes are integral to understand and manage individual PAs for long-term sustainability. We illustrate our conceptual contribution with three case studies that highlight cross-scale feedbacks and social-ecological interactions in the functioning of PAs and in relation to regional resilience. Our analysis suggests that while ecological, economic, and social processes are often directly relevant to PAs at finer scales, at broader scales, the dominant processes that shape and alter PA resilience are primarily social and economic.

Ecological Applications↗