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At least 19 recordsLinked to original sources
USGS2021

Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes

Regeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush ( Artemisia tridentata ) after disturbances including fire-invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long-lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range-wide big sagebrush regeneration responses in natural vegetation (process-based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model). The process-based model suggested substantial geographic variation in long-term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression-based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long-term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re-creating conditions of uninvaded, unburned natural big sagebrush vegetation for post-fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire-invasive annual grass cycle.

Ecosphere↗
USGS2015

Equation-free modeling unravels the behavior of complex ecological systems

Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.

PNAS↗
USGS2020

Hierarchical computing for hierarchical models in ecology

Bayesian hierarchical models allow ecologists to account for uncertainty and make inference at multiple scales. However, hierarchical models are often computationally intensive to fit, especially with large datasets, and researchers face trade-offs between capturing ecological complexity in statistical models and implementing these models. We present a recursive Bayesian computing (RB) method that can be used to fit Bayesian models efficiently in sequential MCMC stages to ease computation and streamline hierarchical inference. We also introduce transformation-assisted RB (TARB) to create unsupervised MCMC algorithms and improve interpretability of parameters. We demonstrate TARB by fitting a hierarchical animal movement model to obtain inference about individual- and population-level migratory characteristics. Our recursive procedure reduced computation time for fitting our hierarchical movement model by half compared to fitting the model with a single MCMC algorithm. We obtained the same inference fitting our model using TARB as we obtained fitting the model with a single algorithm. For complex ecological statistical models, like those for animal movement, multi-species systems, or large spatial and temporal scales, the computational demands of fitting models with conventional computing techniques can limit model specification, thus hindering scientific discovery. Transformation-assisted RB is one of the most accessible methods for reducing these limitations, enabling us to implement new statistical models and advance our understanding of complex ecological phenomena.

Article↗
USGS2016

Environmental change makes robust ecological networks fragile

Complex ecological networks appear robust to primary extinctions, possibly due to consumers’ tendency to specialize on dependable (available and persistent) resources. However, modifications to the conditions under which the network has evolved might alter resource dependability. Here, we ask whether adaptation to historical conditions can increase community robustness, and whether such robustness can protect communities from collapse when conditions change. Using artificial life simulations, we first evolved digital consumer-resource networks that we subsequently subjected to rapid environmental change. We then investigated how empirical host–parasite networks would respond to historical, random and expected extinction sequences. In both the cases, networks were far more robust to historical conditions than new ones, suggesting that new environmental challenges, as expected under global change, might collapse otherwise robust natural ecosystems.

Nature Communications↗
USGS2017

Detecting spatial ontogenetic niche shifts in complex dendritic ecological networks

Ontogenetic niche shifts (ONS) are important drivers of population and community dynamics, but they can be difficult to identify for species with prolonged larval or juvenile stages, or for species that inhabit continuous habitats. Most studies of ONS focus on single transitions among discrete habitat patches at local scales. However, for species with long larval or juvenile periods, affinity for particular locations within connected habitat networks may differ among cohorts. The resulting spatial patterns of distribution can result from a combination of landscape-scale habitat structure, position of a habitat patch within a network, and local habitat characteristics—all of which may interact and change as individuals grow. We estimated such spatial ONS for spring salamanders ( Gyrinophilus porphyriticus ), which have a larval period that can last 4 years or more. Using mixture models to identify larval cohorts from size frequency data, we fit occupancy models for each age class using two measures of the branching structure of stream networks and three measures of stream network position. Larval salamander cohorts showed different preferences for the position of a site within the stream network, and the strength of these responses depended on the basin-wide spatial structure of the stream network. The isolation of a site had a stronger effect on occupancy in watersheds with more isolated headwater streams, while the catchment area, which is associated with gradients in stream habitat, had a stronger effect on occupancy in watersheds with more paired headwater streams. Our results show that considering the spatial structure of habitat networks can provide new insights on ONS in long-lived species.

Virginia↗
USGS2019

Introduction: Defining and interpreting ecological disturbances

Within the field of ecology, disturbance can be defined as a physical force, agent, or process, either abiotic or biotic, causing a perturbation or stress, to an ecological component or system, relative to a specified reference state and/or system. Disturbance drive ecosystems, and our understanding of how disturbances interact with biological diversity and scales of space, time, and ecological complexity, have matured over a century of advancement in ecology since early ideas of perturbations and community organization were first formalized. Throughout this book, we approach a set of unifying framing questions for disturbance ecology, including: How can disturbances be categorized in meaningful ways? How do we address scale in disturbance ecology? How does geographic context influence ecological consequences of disturbance, in the near and longer terms? In this introductory chapter, we provide an overview of disturbance ecology and the related topics of diversity and scale that are fundamental to understanding the dynamics of perturbed ecosystems. Subsequently, we outline recent advances in disturbance ecology, which have facilitated greater understanding about dynamic systems and context dependencies. These, in turn, have provided richer insights into the complex manner in which ecosystems change under stress. We survey analytical and methodological advances that are expanding the data flows available to inform disturbance ecology as well as the statistical tools available to investigate disturbance dynamics and ecosystem structure and function. Finally, we lay out four core themes threaded through the remainder of the book: (1) fundamental mechanisms related to ecological theory drive complex system behaviors, including the existence of thresholds; (2) dynamics of ecological disturbance are context-dependent and can be unpredictable; (3) antecedent conditions and the legacies of past disturbances influence contemporary ecosystem dynamics; and (4) natural and anthropogenic disturbances interact in complex ways. Summaries are provided for each of the book’s remaining chapters, highlighting how that material relates to these four core themes. In sum, in this introductory chapter we seek to set a foundation for concepts to ground the remainder of the book. By highlighting constraints in past research and identifying research frontiers, we hope to provide a path forward for advancements in disturbance ecology.

Book chapter↗
USGS2006

Ecological characteristics of coral patch reefs at Midway Atoll, Northwestern Hawaiian Islands

Ecological aspects of coral patch reefs were studied from 1981 to 1985 in Welles Harbor, Midway Atoll. Water temperatures varied from 17??C in February to 28??C in August. Sizes of reefs studied were described by mean area (59 m2), mean volume (52 m3), vertical relief (<1 m), and inter-reef isolation (100 m). Considerable temporal change in reef size occurred due to large winter swells shifting bottom sand. Six common species accounted for 70% of all individual fish visually censused over 4 years. Overall fish assemblage composition ranged from 11 to 46 fish/10 m2, from 3 to 14 species. Numerical abundance and species richness for all fish (pooled) strongly correlated with physical reef substrate characteristics of area, volume, and vertical relief during summer. Species diversity (H') was not correlated with the substrate variables, suggesting similarity in the structure of fish communities among different sizes of patch reefs. Daily surveillance for presence of large transient taxa suggested that visits by sharks, large jacks, monk seals, sea turtles, and dolphins were infrequent. Density estimates were made for all conspicuous invertebrate megafauna during initial and final assessments. Six common taxa provided 90% of these counts; nearly half were sea urchins. Percent cover also was recorded for coral and algal species on the patch reefs. Cover by live coral was low (about 7%) and dominated by a few species. Mean algal cover ranged from 32 to 77%. Such information on ecological characteristics of reefs may aid in understanding complex ecological processes and provides an earlier reference for current ecosystem studies.

Atoll Research Bulletin↗
USGS2026

At the leading edge: Advancing and bridging the science and management of range-shifting species

Climate-mediated shifts in species distributions are reshaping ecosystems worldwide, creating major challenges for conservation and resource management. These range shifts have far-reaching ecological and socio-economic consequences, requiring managers to address complex ecological dynamics while navigating diverse regulatory and value systems. Despite growing attention, key gaps remain in supporting management, from improved understanding of the mechanisms of range shifts, to evaluating the effectiveness of climate adaptation strategies, and tailoring science to the institutional and social contexts of decision-making. Central challenges include scaling processes across space, time, and organizational levels, and reconciling mismatches between biogeographical and management scales. Progress will depend on more comprehensive datasets to assess outcomes across taxa and regions, stronger cross-jurisdictional cooperation, and decision frameworks that integrate uncertainty alongside multiple value systems. Addressing these gaps is essential to make research more actionable and to enable successful management of species redistribution.

BioScience↗
USGS2002

A reservoir landscape for age-0 largemouth bass

Landscape ecology is concerned with how ecological processes are affected by spatial patterns. Identification of heterogeneity in littoral zones has expanded the conceptual framework of aquatic landscapes. Long-term study of a reservoir largemouth bass population indicated that the amount and arrangement of habitat regulated the population processes. The distribution of age-0 largemouth bass was quantified in relation to littoral habitat and relations between landscape features and population parameters on scales from embayment to microhabitat were determined. At the embayment scale, shoreline slope and amount of gravel substratum predicted fivefold variability in abundance among four reservoir embayments. Within an embayment, these habitat features explained between 37 and 88 percent of variation in shoreline distribution of age-0 largemouth bass. At the microhabitat scale, age-0 largemouth bass exhibited patchy distributions in relation to gravel substratum at 40 percent of sites. These results indicate that the landscape scale domain for young largemouth bass is large; whereas, specific patterns explained processes across multiple scales. Distributions of age-0 largemouth bass in relation to habitat, however, were apparent on a fine scale (10 m) and these data, coupled with limited movement behavior of young largemouth bass, indicate that the ecological neighborhood of this life stage is small. Our data also suggested that some habitats may be source habitats because embayments with hypothesized higher source/sink ratios were more productive. Although patch arrangement critical to young largemouth bass ecology was not quantified, it was apparent that embayments with more complex habitats likely provided the extent of the landscape for age-0 largemouth bass in Jordan Lake. Identification of scale of patchiness (of fish distributions and habitats) for this life stage will assist in making inferences regarding complex ecological processes that can affect year-class productivity on multiple scales. ?? 2002 by the American Fisheries Society.

American Fisheries Society Symposium↗
USGS2019

Complexities, context, and new information about the Elwha River

Recently, Hand et al. (2018) discussed the socio- ecological complexities surround-ing natural resource policy, science, and management in the Columbia River Basin, using a case study of dam removal on the Elwha River in Washington State (WebFigure 1a). We feel compelled to provide additional historical context and correct some of the information provided by Hand et al. about the Elwha. The his-toric removals of the two Elwha River dams – a long- anticipated project that was decades in the making – have been touted by some as an environmental success story following the project’s completion in 2014. As with any complex endeavor, critical analyses and lessons learned continue to emerge, and will likely benefit future projects.

Washington↗
USGS2013

Strategies for fitting nonlinear ecological models in R, AD Model Builder, and BUGS

1. Ecologists often use nonlinear fitting techniques to estimate the parameters of complex ecological models, with attendant frustration. This paper compares three open-source model fitting tools and discusses general strategies for defining and fitting models. 2. R is convenient and (relatively) easy to learn, AD Model Builder is fast and robust but comes with a steep learning curve, while BUGS provides the greatest flexibility at the price of speed. 3. Our model-fitting suggestions range from general cultural advice (where possible, use the tools and models that are most common in your subfield) to specific suggestions about how to change the mathematical description of models to make them more amenable to parameter estimation. 4. A companion web site (https://groups.nceas.ucsb.edu/nonlinear-modeling/projects) presents detailed examples of application of the three tools to a variety of typical ecological estimation problems; each example links both to a detailed project report and to full source code and data.

Methods in Ecology and Evolution↗
USGS2022

Toward improved prediction of streamflow effects on freshwater fishes

Understanding the effects of hydrology on fish populations is essential to managing for native fish conservation. However, despite decades of research illustrating streamflow influences on fish habitat, reproduction and survival, biologists remain challenged when tasked with predicting how fish populations will respond to changes in flow regimes. This uncertainty stems from insufficient understanding of the context-dependent mechanisms underlying fish responses to, for example, periods of reduced flow or altered frequency of high-flow events. We aim to address this gap by drawing on previous research to hypothesize mechanisms by which low- and high-flows influence fish populations and communities, identifying challenges that stem from data limitations and ecological complexity, and outlining research directions that can advance an empirical basis for prediction. Focusing flow-ecology research on testing and refining mechanistic hypotheses can help narrow management uncertainties and better support species conservation in changing flow regimes.

Fisheries Magazine↗
USGS2002

Artificial intelligence based decision support for trumpeter swan management

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

Idaho, Montana, Utah, Wyoming↗
USGS2024

Large-scale dam removal and ecosystem restoration

Rivers underpin vital ecosystems that support aquatic and terrestrial biodiversity and many ecosystem services, including food, water, culture, and recreation ( Dudgeon et al. 2006 ). After centuries of building dams on rivers across the world, river restoration via dam removal is receiving increased public attention, financial investment, and scientific study because of various issues of regarding dam infrastructure, such as obsolescence, sedimentation, and ecosystem degradation ( Duda and Bellmore, 2022 ; East and Grant, 2023 ). Most dam removal projects to date have focused on smaller structures, but larger structures > 10 m tall have also started to be removed in increasing numbers. Recent estimates suggest that only a small fraction of all dam removals have been scientifically studied, with most focused on small dams and short time scales ( Bellmore et al., 2016 ). Understanding the outcomes of large dam removal, where case studies are much more limited, depends on sustained research and monitoring efforts aimed at understanding restoration processes over large spatial and temporal scales ( Figure 1 ). The ecological and socio-ecological study of large dam removal represents a new frontier in dam removal research: projects are larger, more recent, and provide an opportunity to understand the complex ecological changes and impacts to humans that occur with these transformative restoration projects.

Frontiers in Ecology and Evolution↗
USGS2023

Using taxa-based approaches to delineate stream macroinvertebrate assemblage responses to stressor gradients in modified alluvial agroecosystems

Alluvial plain landscapes are some of the most agriculturally productive lands in the world but often have modified stream ecosystems due to cultivation history. This context requires consideration when establishing water quality management goals. We analyzed state water quality databases to demonstrate that Mississippi Alluvial Plain (MAP) ecoregion streams have elevated specific conductivity (SC) and nutrients and lower macroinvertebrate local and regional taxa pools compared to streams in other ecoregions, potentially reducing the efficacy of traditional biomonitoring approaches within the region. To overcome these challenges, we used threshold indicator taxa analysis (TITAN) to compare macroinvertebrate assemblage responses to water quality gradients among ecoregions in Mississippi. We identified individual taxa and assemblage-level responses to increasing water quality degradation in MAP streams. Observed responses occurred at higher concentrations for SC, total organic carbon (TOC) and total phosphorus (TP), but not total nitrogen (TN) relative to other ecoregions. These responses appeared to be driven by a large proportion of indicator taxa considered tolerant or unresponsive in other ecoregions, responding negatively to increasing water quality stressors in MAP streams. Our observed assemblage-level stressor responses to WQ gradients in MAP streams demonstrate shifting tolerance in highly altered ecosystems may require adjustments to recovery expectations but also provide useful measures for monitoring improvements in regional water quality. For example, our observed macroinvertebrate assemblage response to increasing TP identified a management goal similar to guidance based on distributional analysis of water quality data within the MAP ecoregion (0.11 vs 0.128 mg L−1) and thus provide some biological basis for previously identified nutrient goals for the region. Our approach can guide and monitor success of nutrient reduction efforts in MAP watersheds and other alluvial plain agroecosystems where reference conditions do not exist, and local and regional taxa pools are less diverse and may not support full recovery of ecological assemblages. While our results are promising, they should also be compared with more sensitive and less habitat-limited biological assemblages (e.g., algae or bacteria) to better understand complex ecological responses to best management practices designed to increase sustainability of high production agricultural regions.

Mississippi↗
USGS2022

Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: A global analysis

Background Billions of people living in poverty are at risk of environmentally mediated infectious diseases—that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone. Methods We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries. Findings We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities. Interpretation The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. Funding Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.

The Lancet Planetary Health↗
USGS2015

Management applications of discontinuity theory

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

Journal of Applied Ecology↗
USGS2026

Socio-ecological impacts of the 2025 Los Angeles urban fires on communities, neighborhoods, and homes

Human settlements are increasingly being impacted by urban fires initiated by wildfires. Metrics such as area burned and number of structures destroyed are important, but research often overlooks the socio-ecological complexity of urban fires. We study the impacts of the 2025 Los Angeles fires on two communities at the neighborhood and residential parcel scales. Geospatial analyses and econometric modeling explore the relationships between urban morphology, socio-demographic factors, and home destruction. Here we show that socio-ecological characteristics and scale are key in parsing the dynamics of urban fires. Also, new socio-demographic populations are being affected and urban morphology metrics are more important than vegetation cover. Despite parallels with 19 th and early 20 th century urban conflagrations, understanding these re-emerging urban fires requires transdisciplinary approaches and unique metrics. Investigating the socio-ecological scales and dynamics of urban fires provides a valuable next step towards understanding and adapting to the risk associated with these disasters.

California↗