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Representation of ecological systems within the protected areas network of the continental United States

If conservation of biodiversity is the goal, then the protected areas network of the continental US may be one of our best conservation tools for safeguarding ecological systems (i.e., vegetation communities). We evaluated representation of ecological systems in the current protected areas network and found insufficient representation at three vegetation community levels within lower elevations and moderate to high productivity soils. We used national-level data for ecological systems and a protected areas database to explore alternative ways we might be able to increase representation of ecological systems within the continental US. By following one or more of these alternatives it may be possible to increase the representation of ecological systems in the protected areas network both quantitatively (from 10% up to 39%) and geographically and come closer to meeting the suggested Convention on Biological Diversity target of 17% for terrestrial areas. We used the Landscape Conservation Cooperative framework for regional analysis and found that increased conservation on some private and public lands may be important to the conservation of ecological systems in Western US, while increased public-private partnerships may be important in the conservation of ecological systems in Eastern US. We have not assessed the pros and cons of following the national or regional alternatives, but rather present them as possibilities that may be considered and evaluated as decisions are made to increase the representation of ecological systems in the protected areas network across their range of ecological, geographical, and geophysical occurrence in the continental US into the future.

PLoS ONE

Digital mapping of ecological land units using a nationally scalable modeling framework

Ecological site descriptions (ESDs) and associated state-and-transition models (STMs) provide a nationally consistent classification and information system for defining ecological land units for management applications in the United States. Current spatial representations of ESDs, however, occur via soil mapping and are therefore confined to the spatial resolution used to map soils within a survey area. Land management decisions occur across a range of spatial scales and therefore require ecological information that spans similar scales. Digital mapping provides an approach for optimizing the spatial scale of modeling products to best serve decision makers and have the greatest impact in addressing land management concerns. Here, we present a spatial modeling framework for mapping ecological sites using machine learning algorithms, soil survey field observations, soil survey geographic databases, ecological site data, and a suite of remote sensing-based spatial covariates (e.g., hyper-temporal remote sensing, terrain attributes, climate data, land-cover, lithology). Based on the theoretical association between ecological sites and landscape biophysical properties, we hypothesized that the spatial distribution of ecological sites could be predicted using readily available geospatial data. This modeling approach was tested at two study areas within the western United States, representing 6.1 million ha on the Colorado Plateau and 7.5 million ha within the Chihuahuan Desert. Results show our approach was effective in mapping grouped ecological site classes (ESGs), with 10-fold cross-validation accuracies of 70% in the Colorado Plateau based on 1405 point observations across eight expertly-defined ESG classes and 79% in the Chihuahuan Desert based on 2589 point observations across nine expertly-defined ESG classes. Model accuracies were also evaluated using external-validation datasets; resulting in 56 and 44% correct classification for the Colorado Plateau and Chihuahuan Desert, respectively. National coverage of the training and covariate data used in this study provides opportunities for a consistent national-scale mapping effort of ecological sites.

Chihuahuan Desert, Colorado Plateau

Ecological forecasting—21st century science for 21st century management

Natural resource managers are coping with rapid changes in both environmental conditions and ecosystems. Enabled by recent advances in data collection and assimilation, short-term ecological forecasting may be a powerful tool to help resource managers anticipate impending near-term changes in ecosystem conditions or dynamics. Managers may use the information in forecasts to minimize the adverse effects of ecological stressors and optimize the effectiveness of management actions. To explore the potential for ecological forecasting to enhance natural resource management, the U.S. Geological Survey (USGS) convened a workshop titled "Building Capacity for Applied Short-Term Ecological Forecasting" on May 29—31, 2019, with participants from several Federal agencies, including the Bureau of Land Management, the U.S. Fish and Wildlife Service, the National Park Service, and the National Oceanic and Atmospheric Administration as well as all mission areas within the USGS. Participants broadly agreed that short-term ecological forecasting—on the order of days to years into the future—has tremendous potential to improve the quality and timeliness of information available to guide resource management decisions. Participants considered how ecological forecasting could directly affect their agency missions and specified numerous critical tools for addressing natural resource management concerns in the 21st century that could be enhanced by ecological forecasting. Given this breadth of possible applications for forecast products, participants developed a repeatable framework for evaluating potential value of a forecast product for enhancing resource management. Applying that process to a large list of forecast ideas that were developed in a brainstorming session, participants identified a small set of promising forecast products that illustrate the value of ecological forecasting for informing resource management. Workshop outcomes also include insights about important likely obstacles and next steps. In particular, reliable production and delivery of operational ecological forecasts will require a sustained commitment by research agencies, in partnership with resource management agencies, to maintain and improve forecasting tools and capabilities.

Open-File Report

The NEON Ecological Forecasting Challenge

The 21st century continues to be characterized by major changes to the environment and the ecosystem services upon which society depends. Anticipating and responding to these changes requires that scientists explicitly forecast future conditions in real time (Dietze et al . 2018 ). Ecological forecasting, like weather and epidemiological forecasting, involves integrating data and models to generate quantitative predictions of the future state of ecological systems before observations are collected. The iterative cycle of creating forecasts, evaluating them with new observations, updating the models, and then making new forecasts has the potential to accelerate learning across many ecological subdisciplines. This cycle builds on openly available data, often published soon after collection, as is increasingly common in ecological observatory networks, such as the National Ecological Observatory Network (NEON). To accelerate improvements in ecological forecasting, we designed and launched the NEON Ecological Forecasting Challenge (hereafter, “Challenge”) (Figure 1 ), an open platform for the ecological and data science communities to forecast NEON data before they are collected.

Frontiers in Ecology and the Environment

High value of ecological information for river connectivity restoration

Context Efficient restoration of longitudinal river connectivity relies on barrier mitigation prioritization tools that incorporate stream network spatial structure to maximize ecological benefits given limited resources. Typically, ecological benefits of barrier mitigation are measured using proxies such as the amount of accessible riverine habitat. Objectives We developed an optimization approach for barrier mitigation planning which directly incorporates the ecology of managed taxa, and applied it to an urbanizing salmon-bearing watershed in Alaska. Methods A novel river connectivity metric that exploits information on the distribution and movement of managed taxon was embedded into a barrier prioritization framework to identify optimal mitigation actions given limited restoration budgets. The value of ecological information on managed taxa was estimated by comparing costs to achieve restoration targets across alternative barrier prioritization approaches. Results Barrier mitigation solutions informed by life history information outperformed those using only river connectivity proxies, demonstrating high value of ecological information for watershed restoration. In our study area, information on salmon ecology was typically valued at 0.8–1.2 M USD in costs savings to achieve a given benefit level relative to solutions derived only from stream network information, equating to 16–28% of the restoration budget. Conclusions Investing in ecological studies may achieve win–win outcomes of improved understanding of aquatic ecology and greater watershed restoration efficiency.

Alaska

Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities

Context Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial analyses to address ecological questions and are therefore uniquely positioned to advance UAS research for ecological applications. Objectives The review objectives are to: (1) provide background on how UAS are used in landscape ecological studies, (2) identify major advancements and research gaps, and (3) discuss ways to better facilitate the use of UAS in landscape ecology research. Methods We conducted a systematic review based on PRISMA guidelines using key search terms that are unique to landscape ecology research. We reviewed only papers that applied UAS data to investigate questions about ecological patterns, processes, or function. Results We summarize metadata from 161 papers that fit our review criteria. We highlight and discuss major research themes and applications, sensors and data collection techniques, image processing, feature extraction and spatial analysis, image fusion and satellite scaling, and open data and software. Conclusion We observed a diversity of UAS methods, applications, and creative spatial modeling and analysis approaches. Key aspects of UAS research in landscape ecology include modeling wildlife micro-habitats, scaling of ecosystem functions, landscape and geomorphic change detection, integrating UAS with historical aerial and satellite imagery, and novel applications of spatial statistics.

Landscape Ecology

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

Translational invasion ecology: Bridging research and practice to address one of the greatest threats to biodiversity

Effective natural resource management and policy is contingent on information generated by research. Conversely, the applicability of research depends on whether it is responsive to the needs and constraints of resource managers and policy makers. However, many scientific fields including invasion ecology suffer from a disconnect between research and practice. Despite strong socio-political imperatives, evidenced by extensive funding dedicated to addressing invasive species, the pairing of invasion ecology with stakeholder needs to support effective management and policy is lacking. As a potential solution, we propose translational invasion ecology (TIE). As an extension of translational ecology, as a framework to increase collaboration among scientists, practitioners, and policy makers to reduce negative impacts of invasive species. As an extension of translational ecology, TIE is an approach that embodies an intentional and inclusive process in which researchers, stakeholders, and decision makers collaborate to develop and implement ecological research via joint consideration of the ecological, sociological, economic, and/or political contexts in order to improve invasive species management. TIE ideally results in improved outcomes as well as shared benefits between researchers and managers. We delineate the steps of our proposed TIE approach and describe successful examples of ongoing TIE projects from the US and internationally. We suggest practical ways to begin incorporating TIE into research and management practices, including supporting boundary-spanning organizations and activities, expanding networks, sharing translational experiences, and measuring outcomes. We find that there is a need for strengthened boundary spanning, as well as funding and recognition for advancing translational approaches. As climate change and globalization exacerbate invasive species impacts, TIE provides a promising approach to generate actionable ecological research while improving outcomes of invasive species management and policy decisions.

Biological Invasions

Visualizing social-ecological intensities for management of recreation visitors in a multiuse system

Accounting for the variation of visitor conflicts and ecological disturbance of outdoor recreation activities across space and time can cause difficulty for managers seeking to make decisions in social-ecological systems (SESs). We develop a method to quantify and visualize social and ecological intensities resulting from outdoor recreation. We demonstrate the utility of our method at Valentine National Wildlife Refuge, where we conducted onsite surveys for an entire year of recreationists participating in consumptive (i.e., hunting), intermediate-consumptive (i.e., fishing) and nonconsumptive (e.g., hiking) activities. We use survey results and combine them with expert consensus by engaging refuge managers and scientists (i.e., Delphi method) to chart patterns in social (e.g., visitor conflicts) and ecological (e.g., damages to natural resources) intensities across multiple spatial and temporal scales. We highlight unexpected patterns that are revealed by collectively considering multi-activity groups through space and time and combining different survey methods (onsite, Delphi method). Based on the consensus reached using the Delphi method , the consumptive group had the greatest potential for social conflicts and ecological disturbances. Social and ecological intensities (i.e., hotspots) of recreation varied across lake types and seasons, highlighting high-intensity areas and periods on the refuge. Accounting for diverse outdoor recreation activities and coinciding social and ecological intensities will allow managers of SESs the ability to concomitantly preserve ecological resources, prioritize conservation efforts, and minimize visitor conflicts. We demonstrate the utility and ease of use of this technique, which can be implemented by managers and scientists within their respective SES of interest.

Nebraska

At-sea feeding ecology of parasitic lampreys

This paper synthesizes information on the at-sea ecology of ten anadromous lampreys, with emphasis on trophic ecology. The at-sea ecology of these lampreys concerns the juvenile stage, in which growth is most rapid. Anadromous lampreys can be categorized into four groups, based on feeding modalities: 1) scavenger (Caspian lamprey, Caspiomyzon wagneri ); 2) parasite-predator (Pacific lamprey, Entosphenus tridentatus ); 3) predators (western river lamprey, Lampetra ayresii ; European river lamprey, L. fluviatilis ; Arctic lamprey, Lethenteron camtschaticum ; pouched lamprey, Geotria australis ; and Argentinian pouched lamprey, G. macrostoma ); and 4) parasites (sea lamprey, Petromyzon marinus ; Chilean lamprey, Mordacia lapicida ; and short-headed lamprey, M. mordax ). This paper discusses direct evidence for lamprey feeding ecology, as observed through lamprey-induced wounds on hosts and prey, and lamprey attachments on hosts and prey; and indirect evidence for feeding ecology, via analyses of fatty acids, stable isotopes, contaminants, and bioenergetics modelling. A part of the information presented on feeding ecology is from landlocked sea lamprey, and in some instances this information can be generalizable to anadromous populations. For most anadromous lampreys, but particularly for Southern Hemisphere taxa, little is known about their feeding ecology at sea. Duration of the trophic marine phase and habitat use are still subjects of debate. Species identified as lamprey hosts can be demersal or pelagic, possibly reflecting marine habitat preferences. To unlock understanding of the marine phase of anadromous lampreys, direct evidence of feeding ecology should be coupled with natural (i.e., biomarkers) and artificial (e.g., biologgers) markers to identify habitat use, movement patterns and dispersal.

Journal of Great Lakes Research

A synergistic future for AI and ecology

Research in both ecology and AI strives for predictive understanding of complex systems, where nonlinearities arise from multidimensional interactions and feedbacks across multiple scales. After a century of independent, asynchronous advances in computational and ecological research, we foresee a critical need for intentional synergy to meet current societal challenges against the backdrop of global change. These challenges include understanding the unpredictability of systems-level phenomena and resilience dynamics on a rapidly changing planet. Here, we spotlight both the promise and the urgency of a convergence research paradigm between ecology and AI. Ecological systems are a challenge to fully and holistically model, even using the most prominent AI technique today: deep neural networks. Moreover, ecological systems have emergent and resilient behaviors that may inspire new, robust AI architectures and methodologies. We share examples of how challenges in ecological systems modeling would benefit from advances in AI techniques that are themselves inspired by the systems they seek to model. Both fields have inspired each other, albeit indirectly, in an evolution toward this convergence. We emphasize the need for more purposeful synergy to accelerate the understanding of ecological resilience whilst building the resilience currently lacking in modern AI systems, which have been shown to fail at times because of poor generalization in different contexts. Persistent epistemic barriers would benefit from attention in both disciplines. The implications of a successful convergence go beyond advancing ecological disciplines or achieving an artificial general intelligence—they are critical for both persisting and thriving in an uncertain future.

Proceedings of the National Academy of Sciences

Analysis of ecological context for identifying vegetation and animal conservation planning foci: An example from the arid South-western USA

In developing conservation strategies, it is important to maximize effects of conservation within a specified land tract and to maximize conservation effects on surrounding area (ecological context). The authors proposed two criteria to select biotic entities for conservation foci: (1) the relative occurrence of fauna or flora in a tract is greater than that of an ecological context region; and (2) occurrence of the fauna or flora is relatively limited in the ecological context region. Using extensive spatial data on vegetation and wildlife habitat distribution, the authors identified strategic vegetation and fauna conservation foci for the 400 000 ha Fort Bliss military reservation in New Mexico and Texas relative to a 164 km radius ecological context region intersecting seven ecological zones and the predicted habitat distribution of 616 animal species. The authors set two specific criteria: (1) predicted area of a species' occurrence is <50% of the ecological context region; and (2) percentage of Fort Bliss intersecting the species' or vegetation community predicted areas in the ecological context region is >5% (Fort Bliss is 4.2% of the region). These criteria selected one vegetation class and 40 animal species. Further, these vegetation and animal foci were primarily located in two areas of Fort Bliss. Sensitivity analyses with other analytical radii corroborated the context radius used. Conservation of the two areas and associated taxa will maximize the contribution of Fort Bliss's conservation efforts in its ecological proximity. This relatively simple but information-rich process represents economical and defensible preliminary contextual analysis for detailed conservation planning.

Journal of Environmental Planning and Management

Calculating background levels for ecological risk parameters in toxic harbor sediment

Establishing background levels for biological parameters is necessary in assessing the ecological risks from harbor sediment contaminated with toxic chemicals. For chemicals in sediment, the term contaminated is defined as having concentrations above background and significant human health or ecological risk levels. For biological parameters, a site could be considered contaminated if levels of the parameter are either more or less than the background level, depending on the specific parameter. Biological parameters can include tissue chemical concentrations in ecological receptors, bioassay responses, bioaccumulation levels, and benthic community metrics. Chemical parameters can include sediment concentrations of a variety of potentially toxic chemicals. Indirectly, contaminated harbor sediment can impact shellfish, fish, birds, and marine mammals, and human populations. This paper summarizes the methods used to define background levels for chemical and biological parameters from a survey of ecological risk investigations of marine harbor sediment at California Navy bases. Background levels for regional biological indices used to quantify ecological risks for benthic communities are also described. Generally, background stations are positioned in relatively clean areas exhibiting the same physical and general chemical characteristics as nearby areas with contaminated harbor sediment. The number of background stations and the number of sample replicates per background station depend on the statistical design of the sediment ecological risk investigation, developed through the data quality objective (DQO) process. Biological data from the background stations can be compared to data from a contaminated site by using minimum or maximum background levels or comparative statistics. In Navy ecological risk assessments (ERA's), calculated background levels and appropriate ecological risk screening criteria are used to identify sampling stations and sites with contaminated sediments.

California

Ecological status of aquatic communities in selected streams in the Milwaukee Metropolitan Sewerage District planning area of Wisconsin, 2004–13

A total of 14 wadable streams in urban or urbanizing watersheds near Milwaukee, Wisconsin, were sampled in 2004, 2007, 2010, and 2013 to assess the ecological status of aquatic communities (biota), including benthic algae and invertebrates, and fish. To assess temporal variation, additional community sampling was also done at a subset of three sites in 2011 and 2012. Relative abundances of each type of organism were used to calculate biological metrics, such as richness and diversity, percentages of intolerant and tolerant organisms, and indexes of biotic integrity for invertebrates and fish. Selected environmental (physical and chemical) data in the streams were collected to evaluate potential relations to the biota and the ecological health of the stream. Physical and chemical data included land use/land cover, stream discharge from U.S. Geological Survey (USGS) streamgages (except at 2 creeks that were not gaged), stream habitat, microhabitat at invertebrate collection locations, water quality (except at 2 creeks that were not gaged), field measurements of several water-quality constituents, measures of benthic algal biomass, and toxicity and chemical tests on extracts from passive samplers deployed at a subset of 6 sites. Relative abundances of organisms and biological metrics were compared among sampling years and with environmental metrics to evaluate the ecological status of these streams and determine primary stressors on the aquatic communities, with the aim of helping resource managers understand and work toward improving the ecological health of these and other urban and urbanizing rivers in the study area. Biological metrics for most sites indicated some level of diminished ecological status when compared across all sampled sites and when compared with rating scales for selected metrics. The least degraded sites among all those sampled—indicated by aggregate bioassessments for algae, invertebrates, and fish metrics and in order starting with the best overall condition—were the Milwaukee River near Cedarburg, Menomonee River at Menomonee Falls, Jewel Creek, and Milwaukee River at Milwaukee. The most degraded sites were Menomonee River at Wauwatosa, Root River at Greenfield, Lincoln Creek, and the Kinnickinnic River. Differences in aggregate bioassessments indicate that aquatic communities at the Menomonee River at Wauwatosa site and the Root River at Greenfield site were worse in 2013 than in 2004; however, Oak Creek and Honey Creek sites were better. In 2013, several sites had less than 30-percent pollution-sensitive diatoms indicating degraded algal assemblages. Invertebrate metrics for most of the 14 sites in 2013 were lower than in 2004 and indicate that invertebrate assemblages at most sampled sites were more degraded in 2013. Tolerant fish taxa made up more than 40 percent of assemblages at most sites and nearly 100 percent of assemblages at four sites. At times, in some smaller streams, too few fish were captured to compute an Index of Biotic Integrity with confidence, and invertebrates provided a better means for assessing the ecological status and water quality. With these few exceptions, the use of all three groups of biota provided the most robust assessments at the 14 sites in 2004–13. Physical and chemical stressors were correlated to adverse effects on aquatic biota at the sampled streams. Passive samplers were deployed at a subset of six sites in 2013. Microtox results indicated there was little or no toxicity at the Milwaukee River near Cedarburg site and at the Oak Creek site, slight toxicity at the Lincoln Creek and Honey Creek sites, and moderate toxicity at the Milwaukee River at Milwaukee site and the Little Menomonee River site; however, based on cytochrome-P450 reporter gene system toxicity tests, potential toxicity from hydrophobic organic contaminants was measured at all six sites. For all 14 sites, physical and chemical stressors related to urbanization correlated with biological metrics for algae, invertebrates, and fish. Most stressors for aquatic biota reflected an urban signature. Stressors related to ecological condition in our study were chemical and physical, such as developed land, impervious surface in the watershed, urban land in a buffer area around the stream (a 100-foot [30-meter]-wide area on each side of the stream, and maximum instantaneous discharge normalized by drainage area (a measure of flood and scour effects). Chemical stressors included low waterborne concentrations of dissolved oxygen and high concentrations of chloride, zinc and other metals, nutrients (nitrite and phosphorus), and fecal coliform bacteria. Although algae, invertebrates, and fish did not always demonstrate a significant response to the same stressors, higher abundances of high total phosphorus-indicator diatoms, lower ratings for invertebrate biotic integrity indexes and percentages of mayflies-stoneflies-caddisflies, and lower values for fish biotic integrity indexes underscored possible adverse effects of even low levels of developed land. Developed land is typically associated with more rapid runoff, which washes chemicals from impervious surfaces into area waterways and degrades stream habitat for aquatic communities. However, with respect to at least chloride from road salt, diatoms tolerant to dissolved salts were significantly lower with as little as 1-percent mixed forest in the watershed. Lower percentages of urban land in the stream buffer correlated with healthier aquatic assemblages of algae, invertebrates, and fish. The assessment of algal, invertebrate, and fish assemblages coupled with physical and chemical data were highly useful in evaluating the ecological status of aquatic communities at the 14 sites and for determining environmental stressors that may be contributing to reduced stream condition. Some of the stressors could potentially be removed or lessened with stream rehabilitation or changes in watershed management.

Wisconsin

Toward a social-ecological theory of forest macrosystems for improved ecosystem management

The implications of cumulative land-use decisions and shifting climate on forests, require us to integrate our understanding of ecosystems, markets, policy, and resource management into a social-ecological system. Humans play a central role in macrosystem dynamics, which complicates ecological theories that do not explicitly include human interactions. These dynamics also impact ecological services and related markets, which challenges economic theory. Here, we use two forest macroscale management initiatives to develop a theoretical understanding of how management interacts with ecological functions and services at these scales and how the multiple large-scale management goals work either in consort or conflict with other forest functions and services. We suggest that calling upon theories developed for organismal ecology, ecosystem ecology, and ecological economics adds to our understanding of social-ecological macrosystems. To initiate progress, we propose future research questions to add rigor to macrosystem-scale studies: (1) What are the ecosystem functions that operate at macroscales, their necessary structural components, and how do we observe them? (2) How do systems at one scale respond if altered at another scale? (3) How do we both effectively measure these components and interactions, and communicate that information in a meaningful manner for policy and management across different scales?

Forests

Preliminary testing of flow-ecology hypotheses developed for the GCP LCC region

The Ecological Limits of Hydrological Alteration (ELOHA) framework calls for the development of flow-ecology hypotheses to support protection of the flow regime from ecologically harmful alteration due to human activities. As part of a larger instream flow project for the Gulf Coast Prairie Landscape Conservation Cooperative (GCP LCC), regional flow-ecology hypotheses were developed for fish, mussels, birds, and riparian vegetation (Davis and Brewer 20141 ). The objective of this study was to assess the usefulness of existing ecological and hydrological data to test these hypotheses or others that may be developed in the future. Several databases related to biological collections and hydrologic data from Oklahoma, Texas, and Louisiana were compiled. State fish-community data from Oklahoma and Louisiana were summarized and paired with existing USGS gage data having at least a 40-year period of record that could be separated into reference and current conditions for comparison. The objective of this study was not to conduct exhaustive analyses of these data, the hypotheses, or analyses interpretation, but rather to use these data to determine if existing data were adequate to statistically test the regional flow-ecology hypotheses. The regional flow-ecology hypotheses were developed for the GCP LCC by a committee chaired by Shannon Brewer and Mary Davis (Davis and Brewer 2014). Existing data were useful for informing the hypotheses and suggest support for some hypotheses, but also highlight the need for additional testing and development as some results contradicted hypotheses. Results presented here suggest existing data are adequate to support some flow-ecology hypotheses; however, lack of sampling effort reported with the fish collections and the need for ecoregion-specific analyses suggest more data would be beneficial to analyses in some ecoregions. Additional fish sampling data from Texas and Louisiana will be available for future analyses and may ameliorate some of the data concerns and improve hypothesis interpretation. If the regional hydrologic model currently under development by the U.S. Geological Survey for the South-Central Climate Science Center is improved to produce daily hydrographs, it will enable use of fish data at ungaged locations. In future efforts, exhaustive analyses using these data, in addition to the development of more complex multivariate hypotheses, would be beneficial to understanding data gaps, particularly as relevant to species of conservation concern.

Cooperator Science Series

Flow-ecology relationships are spatially structured and differ among flow regimes

In streams, hydrology is a predominant driver of ecological structure and function. Providing adequate flows to support aquatic life, or environmental flows, is therefore a top management priority in stream systems. Flow regime classification is a widely accepted approach for establishing environmental flow guidelines. However, it is surprisingly difficult to quantify relationships between hydrology and ecology (flow–ecology relationships) while describing how these relationships vary across classified flow regimes. Developing such relationships is complicated by several sources of spatial bias, such as autocorrelation due to spatial design, flow regime classification and other environmental or ecological sources of spatial bias. We used mixed moving‐average spatial stream network models to develop flow–ecology relationships across classified flow regimes and to assess spatial patterns of these relationships. We compared relationships between fish traits and life‐history strategies with hydrologic metrics across flow regimes and assessed whether spatial autocorrelation influenced these relationships. Trait–hydrology relationships varied between flow regimes and across all streams combined. Some relationships between traits and hydrologic metrics fit predictions based on life‐history theory, while others exhibited unexpected relationships with hydrology. Spatial factors described a large proportion of variability in fish traits and different patterns of spatial autocorrelation were observed in different flow regimes. Synthesis and applications. Further work is needed to understand why flow–ecology relationships vary across classified flow regimes and why these relationships may not fit predictions based on life‐history theories. Managers determining environmental flow standards need to be aware that different hydrologic metrics are often important drivers of fish trait diversity in different flow regimes. Flow–ecology relationships may therefore be confounded by spatial structure inherent in flow regime classification and much existing biological data. Complex patterns of spatial bias should be considered when managing stream systems within an environmental flows framework.

Journal of Applied Ecology

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

Movement is influenced by landscape structure, configuration and geometry, but measuring distance as perceived by animals poses technical and logistical challenges. Instead, movement is typically measured using Euclidean distance, irrespective of location or landscape structure, or is based on arbitrary cost surfaces. A recently proposed extension of spatial capture-recapture (SCR) models resolves this issue using spatial encounter histories of individuals to calculate least-cost paths (ecological distance: Ecology , 94 , 2013, 287) thereby relaxing the Euclidean assumption. We evaluate the consequences of not accounting for movement heterogeneity when estimating abundance in highly structured landscapes, and demonstrate the value of this approach for estimating biologically realistic space-use patterns and landscape connectivity. We simulated SCR data in a riparian habitat network, using the ecological distance model under a range of scenarios where space-use in and around the landscape was increasingly associated with water (i.e. increasingly less Euclidean). To assess the influence of miscalculating distance on estimates of population size, we compared the results from the ecological and Euclidean distance based models. We then demonstrate that the ecological distance model can be used to estimate home range geometry when space use is not symmetrical. Finally, we provide a method for calculating landscape connectivity based on modelled species-landscape interactions generated from capture-recapture data. Using ecological distance always produced unbiased estimates of abundance. Explicitly modelling the strength of the species-landscape interaction provided a direct measure of landscape connectivity and better characterised true home range geometry. Abundance under the Euclidean distance model was increasingly (negatively) biased as space use was more strongly associated with water and, because home ranges are assumed to be symmetrical, produced poor characterisations of home range geometry and no information about landscape connectivity. The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

Methods in Ecology and Evolution