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At least 289 records · Page 16Linked to original sources
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↗
USGS2022

Resisting-accepting-directing: Ecosystem management guided by an ecological resilience assessment

As anthropogenic influences push ecosystems past tipping points and into new regimes, complex management decisions are complicated by rapid ecosystem changes that may be difficult to reverse. For managers who grapple with how to manage ecosystems under novel conditions and heightened uncertainty, advancing our understanding of regime shifts is paramount. As part of an ecological resilience assessment, researchers and managers have collaborated to identify alternate regimes and build an understanding of the thresholds and factors that govern regime shifts in the Upper Mississippi River System. To describe the management implications of our assessment, we integrate our findings with a recently developed framework that explicitly acknowledges ecosystem regime change and outlines management approaches of resisting change, accepting change, or directing change. More specifically, we developed guidance for using knowledge of desirability of current conditions, distance to thresholds, and general resilience (that is, an ecosystem’s capacity to cope with uncertain disturbances) to navigate the resist-accept-direct (RAD) framework. We applied this guidance to outline strategies that resist, accept, or direct change in the context of management of aquatic vegetation, floodplain vegetation, and fish communities across nearly 2000 river kilometers. We provide a case study for how knowledge of ecological dynamics can aid in assessing which management approach(es) are likely to be most ecologically feasible in a changing world. Continued learning from management decisions will be critical to advance our understanding of how ecosystems respond and inform the management of ecosystems for desirable and resilient outcomes.

Illinois, Iowa, Kentucky, Minnesota, Missouri, Wis↗
USGS2013

Fort Collins Science Center Ecosystem Dynamics branch--interdisciplinary research for addressing complex natural resource issues across landscapes and time

The Ecosystem Dynamics Branch of the Fort Collins Science Center offers an interdisciplinary team of talented and creative scientists with expertise in biology, botany, ecology, geology, biogeochemistry, physical sciences, geographic information systems, and remote-sensing, for tackling complex questions about natural resources. As demand for natural resources increases, the issues facing natural resource managers, planners, policy makers, industry, and private landowners are increasing in spatial and temporal scope, often involving entire regions, multiple jurisdictions, and long timeframes. Needs for addressing these issues include (1) a better understanding of biotic and abiotic ecosystem components and their complex interactions; (2) the ability to easily monitor, assess, and visualize the spatially complex movements of animals, plants, water, and elements across highly variable landscapes; and (3) the techniques for accurately predicting both immediate and long-term responses of system components to natural and human-caused change. The overall objectives of our research are to provide the knowledge, tools, and techniques needed by the U.S. Department of the Interior, state agencies, and other stakeholders in their endeavors to meet the demand for natural resources while conserving biodiversity and ecosystem services. Ecosystem Dynamics scientists use field and laboratory research, data assimilation, and ecological modeling to understand ecosystem patterns, trends, and mechanistic processes. This information is used to predict the outcomes of changes imposed on species, habitats, landscapes, and climate across spatiotemporal scales. The products we develop include conceptual models to illustrate system structure and processes; regional baseline and integrated assessments; predictive spatial and mathematical models; literature syntheses; and frameworks or protocols for improved ecosystem monitoring, adaptive management, and program evaluation. The descriptions in this fact sheet provide snapshots of our three research emphases, followed by descriptions of select current projects.

Fact Sheet↗
USGS2015

Floodplain complexity and surface metrics: influences of scale and geomorphology

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Geomorphology↗
USGS2021

The demographic and ecological factors shaping diversification among rare Astragalus species

Aim Evolutionary radiations are central to the origin and maintenance of biodiversity, yet we rarely understand how they are jointly shaped by demography and ecological opportunity. Astragalus is the largest plant genus in the world and is disproportionately comprised of rare species restricted to narrow geographic and ecological regions. Here, we explored the demographic and ecological mechanisms underlying patterns of diversification in a threatened Astragalus species complex endemic to a small desert region in the western United States. Location Southeast Utah, USA. Methods We used high‐throughput DNA sequencing to infer genetic structure, genetic diversity, and demographic history (i.e., the timing of population divergence, effective population sizes and gene flow) among Astragalus taxa. We performed landscape genetic analyses to quantify the relationships between genetic differentiation, geographic distance, and ecological distance based on bioclimatic and soil variables. Finally, we identified putative adaptive loci that show higher genetic differentiation between taxa than expected based on our inferred neutral demographic model. Results We found evidence of low gene flow between three highly differentiated taxa (currently delineated as A . iselyi , A . sabulosus var. sabulosus and A. sabulosus var. vehiculus ) that rapidly diverged from a small ancestral population near the beginning of the last glacial period. Genomic signatures revealed long‐term effective population sizes are 2–10× larger than recent census sizes, perhaps due to the maintenance of standing genetic variation through seed banks. Consistent with limited dispersal and local adaptation, genome‐wide patterns of differentiation are shaped by geographic distance (isolation‐by‐distance) and climate and soil variation (isolation‐by‐environment). Taxon‐specific adaptation is further supported by uncovering putative adaptive loci. Main Conclusions Our findings suggest that interactions between demography (i.e., dispersal limitations and seeds banks) and ecological opportunity (i.e., spatial and temporal environmental heterogeneity) may promote diversification, endemism, and rarity among closely related Astragalus species and similar plant clades distributed across complex landscapes.

Utah↗
USGS2018

Synchrony — An emergent property of recreational fisheries

Recreational fisheries are traditionally managed at local scales, but more effective management could be achieved using a cross‐scale approach. To do this, we must first understand how local processes scale up to influence landscape patterns between anglers and resources. We highlight how population‐based synchrony methods, used in conjunction with a complex‐adaptive‐systems framework, can reveal emergent spatial properties within social‐ecological systems such as recreational fisheries. Herein, we quantified the level of spatial synchrony in angler behaviour, defined the relationship between angler synchrony and distance among waterbodies, and highlighted social‐ecological attributes contributing to these patterns. We leveraged a 111 waterbody‐year (34 waterbodies, 5‐year collection period) recreational fisheries dataset from Nebraska, USA to address these objectives. Intra‐annual patterns in angler behaviour were moderately synchronous across large spatial scales and predominately unrelated to distance among waterbodies. Large‐scale synchronous patterns in angler behaviour emerged from local‐scale interactions between angler heterogeneity and waterbody diversity. Spatial synchrony in angler behaviour is an emergent property that resulted from local‐level processes that scaled up to form large‐scale patterns. We posit that angler utility in combination with waterbodies sharing these desired utility components caused spatial synchrony among anglers with similar preferences or specializations. The level of spatial synchrony in angler behaviour will therefore depend on the degree of angler heterogeneity and waterbody diversity on the landscape, with high or low levels of both leading to low and high levels of spatial synchrony respectively. Synthesis and applications. Synchrony‐based methods proved useful for unveiling an emergent property in recreational fisheries that is beneficial for effective cross‐scale management. It may not be appropriate to extrapolate information and apply uniform management actions among local waterbodies because angler behaviour was not synchronous at small scales. Rather, anglers respond uniquely to waterbody diversity and therefore substitute waterbodies may be dispersed throughout the landscape. Creating boat access, for example could yield unintended consequences for a particular angler group and cause local and regional shifts in angler behaviour. Evaluating appropriate management options will require a cross‐scale monitoring approach that captures angler heterogeneity and waterbody diversity at multiple scales. Recreational fisheries are traditionally managed at local scales, but more effective management could be achieved using a cross‐scale approach. To do this, we must first understand how local processes scale up to influence landscape patterns between anglers and resources. We highlight how population‐based synchrony methods, used in conjunction with a complex‐adaptive‐systems framework, can reveal emergent spatial properties within social‐ecological systems such as recreational fisheries. Herein, we quantified the level of spatial synchrony in angler behaviour, defined the relationship between angler synchrony and distance among waterbodies, and highlighted social‐ecological attributes contributing to these patterns. We leveraged a 111 waterbody‐year (34 waterbodies, 5‐year collection period) recreational fisheries dataset from Nebraska, USA to address these objectives. Intra‐annual patterns in angler behaviour were moderately synchronous across large spatial scales and predominately unrelated to distance among waterbodies. Large‐scale synchronous patterns in angler behaviour emerged from local‐scale interactions between angler heterogeneity and waterbody diversity. Spatial synchrony in angler behaviour is an emergent property that resulted from local‐level processes that scaled up to form large‐scale patterns. We posit that angler

Journal of Applied Ecology↗
USGS2021

Exploiting common senses: Sensory ecology meets wildlife conservation and management

Multidisciplinary approaches to conservation and wildlife management are often effective in addressing complex, multi-factor problems. Emerging fields such as conservation physiology and conservation behaviour can provide innovative solutions and management strategies for target species and systems. Sensory ecology combines the study of ‘how animals acquire’ and process sensory stimuli from their environments, and the ecological and evolutionary significance of ‘how animals respond’ to this information. We review the benefits that sensory ecology can bring to wildlife conservation and management by discussing case studies across major taxa and sensory modalities. Conservation practices informed by a sensory ecology approach include the amelioration of sensory traps, control of invasive species, reduction of human–wildlife conflicts and relocation and establishment of new populations of endangered species. We illustrate that sensory ecology can facilitate the understanding of mechanistic ecological and physiological explanations underlying particular conservation issues and also can help develop innovative solutions to ameliorate conservation problems.

Conservation Physiology↗
USGS2015

Chemical mixtures and environmental effects: a pilot study to assess ecological exposure and effects in streams

Assessment and management of the risks of exposure to complex chemical mixtures in streams are priorities for human and environmental health organizations around the world. The current lack of information on the composition and variability of environmental mixtures and a limited understanding of their combined effects are fundamental obstacles to timely identification and prevention of adverse human and ecological effects of exposure. This report describes the design of a field-based study of the composition and biological activity of chemical mixtures in U.S. stream waters affected by a wide range of human activities and contaminant sources. The study is a collaborative effort by the U.S. Geological Survey and the U.S. Environmental Protection Agency. Scientists sampled 38 streams spanning 24 States and Puerto Rico. Thirty-four of the sites were located in watersheds impacted by multiple contaminant sources, including industrial and municipal wastewater discharges, crop and animal agricultural runoff, urban runoff, and other point and nonpoint contaminant sources. The remaining four sites were minimally development reference watersheds. All samples underwent comprehensive chemical and biological characterization, including sensitive and specific direct analysis for over 700 dissolved organic and inorganic chemicals and field parameters, identification of unknown contaminants (environmental diagnostics), and a variety of bioassays to evaluate biological activity and toxicity.

Open-File Report↗
USGS2000

[Book review] Ecological Scale - Theory and Applications by D.L. Peterson and V. Thomas Parker, editors

Covering the complexity of the scale topic, this volume represents an important compilation of information on a topic that is often misunderstood, and one for which little attention is paid (although, thankfully, this seems to be on the decline). Although technical, this book provides full exposure to the scale issue in ecology and is an important reference for researchers and resource managers who are working to understand and preserve ecological function in parks. The authors and editors have combined to provide a needed examination of a very important topic. In summary, why purchase all those books on scale when just one will do? The mountain of information alone stuffed into this one book should prompt all parks to get a copy and have it on hand as a quick and ready reference.

Park Science↗
USGS2004

Abundance estimation and conservation biology

Abundance is the state variable of interest in most population–level ecological research and in most programs involving management and conservation of animal populations. Abundance is the single parameter of interest in capture–recapture models for closed populations (e.g., Darroch, 1958; Otis et al., 1978; Chao, 2001). The initial capture–recapture models developed for partially (Darroch, 1959) and completely (Jolly, 1965; Seber, 1965) open populations represented efforts to relax the restrictive assumption of population closure for the purpose of estimating abundance. Subsequent emphases in capture–recapture work were on survival rate estimation in the 1970’s and 1980’s (e.g., Burnham et al., 1987; Lebreton et al.,1992), and on movement estimation in the 1990’s (Brownie et al., 1993; Schwarz et al., 1993). However, from the mid–1990’s until the present time, capture–recapture investigators have expressed a renewed interest in abundance and related parameters (Pradel, 1996; Schwarz & Arnason, 1996; Schwarz, 2001). The focus of this session was abundance, and presentations covered topics ranging from estimation of abundance and rate of change in abundance, to inferences about the demographic processes underlying changes in abundance, to occupancy as a surrogate of abundance. The plenary paper by Link & Barker (2004) is provocative and very interesting, and it contains a number of important messages and suggestions. Link & Barker (2004) emphasize that the increasing complexity of capture–recapture models has resulted in large numbers of parameters and that a challenge to ecologists is to extract ecological signals from this complexity. They offer hierarchical models as a natural approach to inference in which traditional parameters are viewed as realizations of stochastic processes. These processes are governed by hyperparameters, and the inferential approach focuses on these hyperparameters. Link & Barker (2004) also suggest that our attention should be focused on relationships between demographic processes such as survival and recruitment, the two quantities responsible for changes in abundance, rather than simply on the magnitudes of these quantities. They describe a type of Jolly–Seber capture–recapture model that permits inference about the underlying relationship between per capita recruitment rates and survival rates (Link & Barker, this volume). Implementation used Bayesian Markov Chain Monte Carlo methods and appeared to work well, yielding inferences about the relationship between recruitment and survival that were robust to selection of prior distribution. We believe that readers will find their arguments compelling, and we expect to see increased use of hierarchical modeling approaches in capture–recapture and related fields. Otto (presentation without paper) also recommended use of hierarchical models in analysis of multiple data sources dealing with population dynamics of North American mallards. He integrated survival inferences from ringing data, abundance information from aerial survey data, and recruitment information based on age ratios from a harvest survey. He used a Leslie matrix population projection model as an integrating framework and obtained estimates of breeding population size using all data.Otto’s approach also permitted inference about biases in estimated quantities. As with the work of Link & Barker (2004), we find Otto’s recommendation to use hierarchical models to integrate data from multiple sources to be very compelling. Alisauskas et al. (2004) report results of an analysis of capture–recapture data for a askatchewan population of white–winged scoters. They used the approach of Pradel (1996) to estimate population growth rate (See the PDF) directly. Estimates for 1975–1985 were quite low, but estimates for the recent period, 2000–2003,increased to values > 1. Parameter estimates for seniority, survival and per capita recruitment (Pradel, 1996) led to the inference that increased recruitment was largely responsible for the improvements in population status and growth. However, various data sources also indicated that this increase in recruitment was likely a result of increased immigration rather than improved reproduction on the area. This latter inference is important from a conservation perspective in indicating the importance of birds in other locations to growth and health of the study population. Lukacs and Burnham presented material to be published elsewhere that dealt with the use of genetic markers in capture–recapture studies. The data sources for such studies are samples of hair or feces, which are then analyzed using molecular genetic techniques in order to determine individual genotypes with respect to a usually small number of loci. Two types of classification error can arise in such analyses. First, if only a small number of loci is examined, then there may be nonnegligible probabilities that multiple individual animals will have the same genotypes. The second type of error arises during the polymerase chain reaction (PCR) process and can result from failure of alleles to amplify (allelic dropout) or from PCR inhibitors in hair and feces that produce the appearance of false alleles or misprinting (Creel et al., 2003). Lukacs and Burnham developed models that formally incorporate possible misclassification of samples resulting from these errors. These models permit estimation of parameters such as abundance and survival in a manner that properly incorporates this uncertainty of individual identity. We anticipate that noninvasive sampling based on molecular genetic analyses of hair or feces will become extremely important for some species, and that the models of Lukacs and Burnham will become very popular for such analyses. MacKenzie & Nichols (2004) discuss the use of occupancy (proportion of patches or habitat area that is occupied) as a surrogate for abundance. In cases of territorial species and where birds occur at low densities, the number of occupied patches may provide a reasonable estimate of abundance. In other cases, occupancy can be viewed as providing information about one tail of the abundance distribution, P (N = 0). The motivation for considering occupancy as a surrogate for abundance is that occupancy is based on so–called presence–absence surveys that are frequently less expensive of time and effort than methods that estimate abundance directly. We describe one set of models that can be used to estimate occupancy for a single season and another that can be used to estimate parameters such as local probabilities of extinction and colonization that are associated with occupancy dynamics. We outline a possible hybrid approach that combines occupancy data with data on marked individuals in order to betterexplore the mechanisms underlying occupancy dynamics. These five presentations made for an interesting session containing useful information and recommendations for future work. A number of themes connecting these presentations could be emphasized. For example, two of the presentations considered alternatives to standard capture–recapture sampling that can be used to draw inferences about abundance, or a portion of the abundance distribution, with field methods that should be less expensive than usual capture–recapture approaches of handling animals. We believe that the most important theme of the session was the emphasis on the processes responsible for changes in abundance. In particular, we are excited by the potential for using hierarchical models as a means of investigating relationships among vital rates and as a means of combining multiple sources of data relevant to system dynamics. Indeed, we expect the importance of this session theme to be reflected in the content and presentations of the next EURING meeting.

Animal Biodiversity and Conservation↗
USGS2005

Assessing spatial coupling in complex population dynamics using mutual prediction and continuity statistics

A number of important questions in ecology involve the possibility of interactions or ?coupling? among potential components of ecological systems. The basic question of whether two components are coupled (exhibit dynamical interdependence) is relevant to investigations of movement of animals over space, population regulation, food webs and trophic interactions, and is also useful in the design of monitoring programs. For example, in spatially extended systems, coupling among populations in different locations implies the existence of redundant information in the system and the possibility of exploiting this redundancy in the development of spatial sampling designs. One approach to the identification of coupling involves study of the purported mechanisms linking system components. Another approach is based on time series of two potential components of the same system and, in previous ecological work, has relied on linear cross-correlation analysis. Here we present two different attractor-based approaches, continuity and mutual prediction, for determining the degree to which two population time series (e.g., at different spatial locations) are coupled. Both approaches are demonstrated on a one-dimensional predator?prey model system exhibiting complex dynamics. Of particular interest is the spatial asymmetry introduced into the model as linearly declining resource for the prey over the domain of the spatial coordinate. Results from these approaches are then compared to the more standard cross-correlation analysis. In contrast to cross-correlation, both continuity and mutual prediction are clearly able to discern the asymmetry in the flow of information through this system.

Theoretical Population Biology↗
USGS2021

Cape Romain partnership for coastal protection

This final report summarizes activities, outcomes, and lessons learned from a 3-year project titled “Climate Change Adaptation for Coastal National Wildlife Refuges” with the Cape Romain National Wildlife Refuge (NWR) and local partners in the surrounding South Carolina Lowcountry. The Lowcountry is classified as the 10-county area encompassing the coastal plain of South Carolina (this report specifically focuses on Berkeley, Charleston, and Georgetown Counties). The goals of this work, sponsored by the U.S. Geological Survey’s Southeast Climate Adaptation Science Center (SECASC), were to foster active engagement with stakeholders; to develop a comprehensive definition of adaptation problems faced by agencies, organizations, and individuals near the Cape Romain NWR that accounts for global change, local values, knowledge and perceptions; and to encourage social learning and building of effective networks and trust across South Carolina Lowcountry organizations and individuals. Although project scoping began at the scale of the Atlantic seaboard, by engaging with NWRs from Massachusetts to Florida, participating refuge personnel eventually selected the Cape Romain NWR to serve as a case study for testing our goals. The Cape Romain Partnership for Coastal Conservation was established to address global change impacts at a regional level and includes representation from Federal and State resource agencies, local conservation nongovernmental organizations, and organizations representing underserved community interests. Research topics, originating from discussions with Cape Romain Partnership for Coastal Conservation members, focused on quantifying key drivers of change including localized sea-level rise (SLR) predictions, estimates of coastal hurricane inundation as amplified by SLR, and urban growth trends and forecasts. These key drivers provided a foundation to engage stakeholders in planning exercises to begin a process of collective understanding and collaborative decision making. The goal of this process was to develop collective strategies of adaptation to enhance community and ecosystem resilience in the South Carolina Lowcountry. South Carolina’s Lowcountry is experiencing rapid environmental and social transformation because of SLR rates approaching twice the global average, chronic tidal flooding and catastrophic storm surges, erosion and loss of habitats that provide essential services to wildlife and humans, and increasing social polarization fueled by aggressive low-density urban growth and other forms of land conversion. To support characterizations of plausible future scenarios, we used available or, in some cases, developed new models to project future conditions of key environmental and social-economic drivers. Because of the imprecision of mean global SLR projections, the SECASC commissioned a climatological study to account for local conditions and multiple representative concentration pathways to project a tailored distribution of future sea levels. These projections were matched to SLR scenarios provided by existing models to anticipate the range of future coastal habitat changes in the South Carolina Lowcountry. SLR scenarios were also incorporated into existing storm-surge models, which do not account for alternate baseline sea levels, to project the local effects of future hurricanes. To evaluate the extent and effects of population growth and urban expansion, we relied on an existing urban-growth model to map the spatial distribution of land-conversion probabilities, the total area of which is predicted to increase twofold to threefold over the next 60 years. In addition to this simplified model, an econometric model is in development to account for nonlinear feedback dynamics in land value, land use, and ecosystem service production. Although not yet completed, the goals of this model are to produce more-detailed projections of growth dynamics and to allow predictions of development patterns resulting from alternate land-use planning policies and incentives. Collaborative planning for an uncertain future requires more than providing decision makers with information on future physical and ecological conditions; developing effective and consensual strategies must also integrate sociological values, multiple cultural perspectives, and an understanding of human behavior. To support broad stakeholder engagement in integrative approaches to adaptation planning, emphasis was placed on the importance of considering differences in how individuals perceive their environment and create meaning. Because cultural frameworks form the basis for perceptions and, ultimately, the behaviors of individuals and institutions, we describe a model of human behavior and how it can be used to understand the effect of cultural complexity and variation in perception on choices, behavioral change, and long-term maintenance of behaviors. We consider a model commonly used in the field of behavioral health that accommodates variation in human perception when describing stages of behavior and the dynamics of behavioral change. Tailoring communication and engagement activities to targeted stakeholders is likely to benefit from increased understanding of behavioral change processes. The complex nature of this problem limited the usefulness of a traditional decision-analytic approach, we explored alternative methods for engagement, collaborative learning and decision making. Recognizing that project partners and Lowcountry stakeholders may be at different stages of preparedness and interest level for modifying behavior as a function of global change, we facilitated a scenario-planning exercise to familiarize partners with this well-established approach for communicating the opportunities and threats arising under alternative, plausible futures. We developed narratives for four alternative South Carolina Lowcountry scenarios to be used in later strategic planning that focus on quantitative trends for three primary drivers with high impact and high uncertainty: manifestations of climate change, social-political shifts at a global level, and forces of local value and power structures. This scenario-planning exercise underscored the complex relation between the temporospatial scale of the production of ecological goods and services and the institutional scale at which they are managed. We then guided the partners through an assessment of the relevant strengths and weaknesses of the Cape Romain Partnership for Coastal Protection, using the threats and opportunities characterized by each scenario to understand how the partnership might respond when attempting to meet conservation and societal objectives. The partnership identified key strengths including partnership experience, outreach and technical capacities, a substantial conservation land base, and high social cohesion in the South Carolina Lowcountry. Limited communication expertise, institutional inertia, and insufficient staffing and funding were recognized as important weaknesses across the partnership. By examining and scoring combinations of internal strengths and weaknesses and external threats and opportunities, the partnership developed sets of prioritized strategies to consider in the context of a given scenario. Although we had insufficient time to examine all scenarios in detail, the intent was to identify a portfolio of strategic actions to address threats and opportunities represented in multiple plausible futures. Top-ranking strategies encompassed a range of actions that focused on strengthening the conservation community and communicating the benefits of nature (that is, ecosystem services) to leveraging partnerships to expand land protection. This report also details the methods and preliminary results of several models developed or applied in support of this project. Two parcel-selection algorithms were used to evaluate anticipated habitat changes and patterns of urban growth to guide decisions on optimal conservation reserve design to protect habitat communities. One approach used a widely available planning software (MARXAN) to maximize conservation benefits near the Cape Romain NWR, whereas the other approach was a novel application of economic theory to account for uncertainty in future conditions and for the risks of unanticipated habitat loss. This latter model applies modern portfolio theory to estimate the risk of investing in any portfolio of land parcels (that is, candidate “reserves”) under climate-change uncertainty by quantifying the variation and spatial correlation of conservation benefits derived from each portfolio. We expanded the range of actions beyond simply whether or not to invest in a set of land parcels, an approach commonly used in spatial conservation planning, to also include consideration of divestment from currently protected lands. Such refinements allow for better accounting of system dynamics and can evaluate the benefits of flexible conservation tools such as rolling easements. Model results were conditional on a decision maker’s risk tolerance but highlighted general strategies of land conservation to increase future habitat representation beyond what is expected under the current protected land base. We built models that may help inform coastal planning by estimating salinity dynamics and the performance of oyster reef restoration efforts to predict the combined effects of global change and management of freshwater flows on coastal habitats and the processes that contribute to their resilience. These models can support restoration decisions by evaluating the expected benefits of site locations for shoreline protection and fisheries production. Lastly, we developed a spatially explicit economic model that predicts feedback dynamics among land value, land-use change, and effects on ecosystem service provision to explore zoning policies and incentives on urban growth and ecosystem services. We summarize these efforts with insights and considerations for the Cape Romain Partnership for Coastal Protection to continue to engage stakeholders in effective adaptation planning. First, notions of place attachment (referred to as sense of place), and the role of culture in social discourse are increasingly being used to understand the complex interactions between society and the environment and how societies respond and adapt to climate change. Sense of place was a unifying theme whenever the future of the South Carolina Lowcountry was discussed. The contribution of the South Carolina Lowcountry’s environmental wealth, rich cultural heritage, and quality of life to sense of place has important implications for how adaptation planning might best be pursued. More community-based governance of the commons (in other words, natural and cultural resources held in common), in which broad stakeholder participation and power sharing are key elements, is considered important. This devolution of governance is characterized by polycentric institutions and self-organizing social networks that promote a local culture of knowledge sharing, problem solving, and learning. These so-called bridging organizations (or individuals) often provide the leadership necessary to bring together potentially disparate Government agencies and institutions, private organizations, and individuals in a collective process of problem solving. Our observations also suggest that the conservation community in the South Carolina Lowcountry views its activities as integral to the broader governance of social-ecological systems, in which responses to the forces of global change are mediated through culture, economics, and politics. Rather than directly competing with other interests, the South Carolina Lowcountry conservation community seems to embrace an interpretation of conservation in which the fundamental objective is the quality of human life rather than environmental protection. Fundamental to the types of governance reforms described above is the notion of coproduction, in which experts and users collaborate to develop a shared body of knowledge. In this approach, scientists work with stakeholders to help frame questions, design research, and collect and analyze data. Such sustained collaborations are increasingly believed to be an effective way to produce useable (or actionable) science. The emphasis on social learning, leveraging strong social networks, coordinating and deliberating among diverse stakeholders, and applying principles of adaptive management is an essential contribution to adaptive capacity. The diverse and robust set of scientific approaches, methods to help stakeholders collaborate in effective and goal-driven planning processes, and decision tools resulting from this project hopefully will assist Cape Romain NWR and its partners prepare for climatic, ecological, and social changes over the coming decades.

South Carolina↗
USGS2021

Progress towards integrating an understanding of chemical ecology into sea lamprey control

The sea lamprey, Petromyzon marinus , is a destructive invader in the Laurentian Great Lakes that relies on several complex chemical cues to complete their life cycle. The central roles of chemical cues in sea lamprey reproduction provide opportunities to leverage knowledge of sea lamprey chemical ecology when developing alternative or supplemental strategies for sea lamprey control. A solid foundation has been laid regarding sea lamprey chemical ecology, with recent advances in our understanding of the migratory pheromone, male sex pheromone, and alarm cues broadening our fundamental understanding of the diversity, complexity, and evolution of chemical cues used by sea lamprey. Additionally, research applying semiochemicals in differing management scenarios has provided useful insights into the challenges of incorporating chemical cues into the sea lamprey control program. Here, we synthesize new findings related to fundamental research of chemosensory cues along with knowledge learned from management-based tests and explore options for integrating an understanding of chemical ecology into sea lamprey control in light of new knowledge. We also highlight current unknowns and future research needs that should be addressed prior to implementation of sea lamprey chemical ecology into the sea lamprey control program.

Great Lakes↗
USGS2021

Improving the ability of a BACI design to detect impacts within a kelp‐forest community

Distinguishing between human impacts and natural variation in abundance remains difficult because most species exhibit complex patterns of variation in space and time. When ecological monitoring data are available, a before‐after‐control‐impact (BACI) analysis can control natural spatial and temporal variation to better identify an impact and estimate its magnitude. However, populations with limited distributions and confounding spatial‐temporal dynamics can violate core assumptions of BACI‐type designs. In this study, we assessed how such properties affect the potential to identify impacts. Specifically, we quantified the conditions under which BACI analyses correctly (or incorrectly) identified simulated anthropogenic impacts in a spatially and temporally replicated data set of fish, macroalgal, and invertebrate species found on nearshore subtidal reefs in southern California, USA. We found BACI failed to assess very localized impacts, and had low power but high precision when assessing region‐wide impacts. Power was highest for severe impacts of moderate spatial scale, and impacts were most easily detected in species with stable, widely distributed populations. Serial autocorrelation in the data greatly inflated false impact detection rates, and could be partly controlled for statistically, while spatial synchrony in dynamics had no consistent effect on power or false detection rates. Unfortunately, species that offer high power to detect real impacts were also more likely to detect impacts where none had occurred. However, considering power and false detection rates together can identify promising indicator species, and collectively analyzing data for similar species improved the net ability to assess impacts. These insights set expectations for the sizes and severities of impacts that BACI analyses can detect in real systems, point to the importance of serial autocorrelation (but not of spatial synchrony), and indicate how to choose the species, and groups of species, that can best identify impacts.

Ecological Applications↗
USGS2023

Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin

Quantifying the effects of streamflow alteration on assemblage response is central to understanding the role humans play in shaping aquatic environments. These changes represent a level of complexity that impedes developing quantitative links between flow and ecological response because stream hydrology is strongly intertwined with natural and anthropogenic factors. Better management outcomes require disentangling these linkages. Benthic macroinvertebrate data were combined with GIS-derived natural and anthropogenic basin characteristics to identify factors associated with changes in flow processes and assemblage characteristics. Models linking streamflow metrics and macroinvertebrate response at basin and subregion scales were developed using boosted regression tree (BRT) analysis. Basin-scale BRT analyses revealed that links between macroinvertebrate response and flow metrics were often obscured, whereas more homogeneous subregions were better able to discern relations with flow. Urban land cover was the primary factor accounting for changes in flow characteristics. Elevation, land cover, and high flow frequency were the principal variables driving changes in assemblage structure within subregions. Assemblage metrics and traits were equally useful for building response models and were affected similarly by streamflow alteration. Results indicate that response models should be developed based on upland and coastal subregions. However, when defining subregions, care should be taken to maintain data sufficiency. Developing practical flow-protection standards that support a balance between human water requirements and ecological integrity requires models that reduce uncertainty and identify management-relevant drivers. However, effective management often differs by location and models developed at the subregion level may be more applicable to management and stakeholder interests.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2010

Use of Continuous Monitors and Autosamplers to Predict Unmeasured Water-Quality Constituents in Tributaries of the Tualatin River, Oregon

Management of water quality in streams of the United States is becoming increasingly complex as regulators seek to control aquatic pollution and ecological problems through Total Maximum Daily Load programs that target reductions in the concentrations of certain constituents. Sediment, nutrients, and bacteria, for example, are constituents that regulators target for reduction nationally and in the Tualatin River basin, Oregon. These constituents require laboratory analysis of discrete samples for definitive determinations of concentrations in streams. Recent technological advances in the nearly continuous, in situ monitoring of related water-quality parameters has fostered the use of these parameters as surrogates for the labor intensive, laboratory-analyzed constituents. Although these correlative techniques have been successful in large rivers, it was unclear whether they could be applied successfully in tributaries of the Tualatin River, primarily because these streams tend to be small, have rapid hydrologic response to rainfall and high streamflow variability, and may contain unique sources of sediment, nutrients, and bacteria. This report evaluates the feasibility of developing correlative regression models for predicting dependent variables (concentrations of total suspended solids, total phosphorus, and Escherichia coli bacteria) in two Tualatin River basin streams: one draining highly urbanized land (Fanno Creek near Durham, Oregon) and one draining rural agricultural land (Dairy Creek at Highway 8 near Hillsboro, Oregon), during 2002-04. An important difference between these two streams is their response to storm runoff; Fanno Creek has a relatively rapid response due to extensive upstream impervious areas and Dairy Creek has a relatively slow response because of the large amount of undeveloped upstream land. Four other stream sites also were evaluated, but in less detail. Potential explanatory variables included continuously monitored streamflow (discharge), stream stage, specific conductance, turbidity, and time (to account for seasonal processes). Preliminary multiple-regression models were identified using stepwise regression and Mallow's Cp, which maximizes regression correlation coefficients and accounts for the loss of additional degrees of freedom when extra explanatory variables are used. Several data scenarios were created and evaluated for each site to assess the representativeness of existing monitoring data and autosampler-derived data, and to assess the utility of the available data to develop robust predictive models. The goodness-of-fit of candidate predictive models was assessed with diagnostic statistics from validation exercises that compared predictions against a subset of the available data. The regression modeling met with mixed success. Functional model forms that have a high likelihood of success were identified for most (but not all) dependent variables at each site, but there were limitations in the available datasets, notably the lack of samples from high-flows. These limitations increase the uncertainty in the predictions of the models and suggest that the models are not yet ready for use in assessing these streams, particularly under high-flow conditions, without additional data collection and recalibration of model coefficients. Nonetheless, the results reveal opportunities to use existing resources more efficiently. Baseline conditions are well represented in the available data, and, for the most part, the models reproduced these conditions well. Future sampling might therefore focus on high flow conditions, without much loss of ability to characterize the baseline. Seasonal cycles, as represented by trigonometric functions of time, were not significant in the evaluated models, perhaps because the baseline conditions are well characterized in the datasets or because the other explanatory variables indirectly incorporate seasonal aspects. Multicollinearity among independent variabl

Scientific Investigations Report↗
USGS2017

Using high-throughput DNA sequencing, genetic fingerprinting, and quantitative PCR as tools for monitoring bloom-forming and toxigenic cyanobacteria in Upper Klamath Lake, Oregon, 2013 and 2014

Monitoring the community structure and metabolic activities of cyanobacterial blooms in Upper Klamath Lake, Oregon, is critical to lake management because these blooms degrade water quality and produce toxic microcystins that are harmful to humans, domestic animals, and wildlife. Genetic tools, such as DNA fingerprinting by terminal restriction fragment length polymorphism (T-RFLP) analysis, high-throughput DNA sequencing (HTS), and real-time, quantitative polymerase chain reaction (qPCR), provide more sensitive and rapid assessments of bloom ecology than traditional techniques. The objectives of this study were (1) to characterize the microbial community at one site in Upper Klamath Lake and determine changes in the cyanobacterial community through time using T-RFLP and HTS in comparison with traditional light microscopy; (2) to determine relative abundances and changes in abundance over time of toxigenic Microcystis using qPCR; and (3) to determine relative abundances and changes in abundance over time of Aphanizomenon , Microcystis , and total cyanobacteria using qPCR. T-RFLP analysis of total cyanobacteria showed a dominance of only one or two distinct genotypes in samples from 2013, but results of HTS in 2013 and 2014 showed more variations in the bloom cycle that fit with the previous understanding of bloom dynamics in Upper Klamath Lake and indicated that potentially toxigenic Microcystis was more prevalent in 2014 than in years prior. The qPCR-estimated copy numbers of all target genes were higher in 2014 than in 2013, when microcystin concentrations also were higher. Total Microcystis density was shown with qPCR to be a better predictor of late-season increases in microcystin concentrations than the relative proportions of potentially toxigenic cells. In addition, qPCR targeting Aphanizomenon at one site in Upper Klamath Lake indicated a moderate bloom of this species (corresponding to chlorophyll a concentrations between approximately 75 and 200 micrograms per liter) from mid-June to mid-August, 2014. After August 18, the Aphanizomenon bloom was overtaken by Microcystis late in the season as microcystin concentrations peaked. Overall, results of this study showed how DNA-based, genetic methods may provide rapid and sensitive diagnoses for the presence of toxigenic cyanobacteria and that they are useful for general monitoring or ecological studies and identification of cyanobacterial community members in complex aquatic habitats. These same methods can also be used to simultaneously address spatial (horizontal and vertical) and temporal variation and under different conditions. Additionally, with some modifications, the same techniques can be applied to different sample types, including water, sediment, and tissue.

Oregon↗
USGS2016

End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology

The rugosity or complexity of the seafloor has been shown to be an important ecological parameter for fish, algae, and corals. Historically, rugosity has been measured either using simple and subjective manual methods such as ‘chain-and-tape’ or complicated and expensive geophysical methods. Here, we demonstrate the application of structure-from-motion (SfM) photogrammetry to generate high-resolution, three-dimensional bathymetric models of a fringing reef from existing underwater video collected to characterize the seafloor. SfM techniques are capable of achieving spatial resolution that can be orders of magnitude greater than large-scale lidar and sonar mapping of coral reef ecosystems. The resulting data provide finer-scale measurements of bathymetry and rugosity that are more applicable to ecological studies of coral reefs than provided by the more expensive and time-consuming geophysical methods. Utilizing SfM techniques for characterizing the benthic habitat proved to be more effective and quantitatively powerful than conventional methods and thus might portend the end of the ‘chain-and-tape’ method for measuring benthic complexity.

Coral Reefs↗