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At least 1,513 records · Page 84Linked to original sources
USGS2022

Complex demographic responses to contrasting climate drivers lead to divergent population trends across the range of a threatened alpine plant

Alpine plants are likely to be particularly vulnerable to climate change because of their restricted distributions and sensitivity to rapid environmental shifts occurring in high-elevation ecosystems. The well-studied Haleakalā silversword (‘āhinahina, Argyroxiphium sandwicense subsp. macrocephalum ) already exhibits substantial climate-associated population decline, and offers the opportunity to understand the ecological and demographic mechanisms that underlie ongoing and predicted range shifts. We use nearly four decades of demographic monitoring for this threatened Hawaiian species, in combination with other biological, ecological and climate data to explore demographic responses across its entire range. We construct and independently validate population models for two elevation zones representing the species’ lower trailing and higher stable regions. Differences in population growth rate (lambda) between trailing and stable regions were influenced most strongly by lower survival of juvenile and small adult size classes, as well as by lower recruitment and lower survival of seedlings and large adults in the trailing region. Furthermore, seed production appears to have decreased from the 1980’s to present in the trailing region, and is now significantly less than in the stable region. Lambda and several underlying vital rates were significantly associated with wetter dry season conditions in the lower trailing region, indicating water limitation. In the higher elevation stable region, in contrast, lambda and vital rates were associated with warmer air temperatures, indicating cold limitation. These contrasting demographic patterns and climate dependencies lead to a high probability of extinction over the next century in the lower region, where most plants occur, but zero probability of the same in the higher region, according to stochastic population projections. Drier future scenarios further increase the probability of extinction at low elevations. The combined results illustrate the complexity in the demographic response and future viability that can occur across the range of a single species.

Global Ecology and Conservation↗
USGS2002

Disentangling sampling and ecological explanations underlying species-area relationships

We used a probabilistic approach to address the influence of sampling artifacts on the form of species-area relationships (SARs). We developed a model in which the increase in observed species richness is a function of sampling effort exclusively. We assumed that effort depends on area sampled, and we generated species-area curves under that model. These curves can be realistic looking. We then generated SARs from avian data, comparing SARs based on counts with those based on richness estimates. We used an approach to estimation of species richness that accounts for species detection probability and, hence, for variation in sampling effort. The slopes of SARs based on counts are steeper than those of curves based on estimates of richness, indicating that the former partly reflect failure to account for species detection probability. SARs based on estimates reflect ecological processes exclusively, not sampling processes. This approach permits investigation of ecologically relevant hypotheses. The slope of SARs is not influenced by the slope of the relationship between habitat diversity and area. In situations in which not all of the species are detected during sampling sessions, approaches to estimation of species richness integrating species detection probability should be used to investigate the rate of increase in species richness with area.

Maryland↗
USGS2019

Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.

Ecology↗
USGS2024

Propagating observation errors to enable scalable and rigorous enumeration of plant population abundance with aerial imagery

Estimating and monitoring plant population size is fundamental for ecological research, as well as conservation and restoration programs. High-resolution imagery has potential to facilitate such estimation and monitoring. However, remotely sensed estimates typically have higher uncertainty than field measurements, risking biased inference on population status. We present a model that accounts for false negative (missed plants) and false positive (misclassified or double-counted plants) error in counts from high-resolution imagery via integration with ground data. We apply it to estimate the abundance of a foundational shrub species in post-wildfire landscapes in the western United States. In these landscapes, plant recruitment is crucial for ecological recovery but locally patchy, motivating the use of spatially extensive measurements from unoccupied aerial systems (UAS). Integrating >16 ha of UAS imagery with >700 georeferenced field plots, we fit our model to generate insights into the prevalence and drivers of observation errors associated with classification algorithms used to distinguish individual plants, relationships between abundance and landscape context, and to generate spatially explicit maps of shrub abundance. Raw counts of plant abundance in high-resolution imagery resulted in substantial false negative and false positive observation errors. The probability of detecting ( p ) adult plants (≥0.25 m tall) varied between sites within 0.52 < p̂adult < 0.82, whereas the detection of smaller plants (<0.25 m) was lower, 0.03 < p̂small < 0.3. On average, we estimate that 19% of all detected plants were false positive errors, which varied spatially in relation to topographic predictors. Abundance declined toward the interior of previous wildfires and was positively associated with terrain roughness. Our study demonstrates that integrated models accounting for imperfect detection improve estimates of plant population abundance derived from inherently imperfect UAS imagery. We believe such models will further improve inference on plant population dynamics—relevant to restoration, wildlife habitat and related objectives—and echo previous calls for remote sensing applications to better differentiate between ecological and observational processes.

Methods in Ecology and Evolution↗
USGS2021

A structured approach to remediation site assessment: Lessons from 15 years of fish spawning habitat creation in the St. Clair‐Detroit River system

Ideally, restoration re‐establishes natural processes in degraded habitats (e.g., flow and sediment regimes). However, in altered systems where process‐based restoration is not feasible, habitat construction is another approach to mitigate degradation. Because habitat construction does not directly focus on restoring processes that build and maintain desired habitats, projects must be developed and placed within the contemporary regulatory, ecological, and hydrogeomorphic context of a system, to maximize effectiveness. Here, we develop a framework for evaluating the regulatory, ecological, and hydrogeomorphic components using 15 years of fish spawning habitat construction in the St. Clair‐Detroit River System. The process began by identifying regulatory requirements at a coarse resolution to quickly focus on locations where ecological potential and hydrogeomorphic constraints could be assessed at finer resolutions. Next, ecological potential was assessed using a lithophilic fish spawning habitat suitability index. The suitability index identified five sites for habitat construction and Lake sturgeon spawning was documented at each site following construction. However, qualitative monitoring showed fine sediments accumulated at older sites. Thus, geomorphic assessments were incorporated to identify sediment sources and model flow within targeted areas. Since geomorphic assessments required the finest resolution and had the most uncertainty, they were conducted after broad‐scale regulatory considerations and ecological assessments narrowed focus to a few candidate sites. The order of operations identified in this case study evolved from the iterative approach of the restoration team, but in retrospect, it helped develop a framework that directed project development resources to aspects with more uncertainty, where learning is most critical.

Michigan, Ontario↗
USGS2021

Foraging in marine habitats increases mercury concentrations in a generalist seabird

Methylmercury concentrations vary widely across geographic space and among habitat types, with marine and aquatic-feeding organisms typically exhibiting higher mercury concentrations than terrestrial-feeding organisms. However, there are few model organisms to directly compare mercury concentrations as a result of foraging in marine, estuarine, or terrestrial food webs. The ecological impacts of differential foraging may be especially important for generalist species that exhibit high plasticity in foraging habitats, locations, or diet. Here, we investigate whether foraging habitat, sex, or fidelity to a foraging area impact blood mercury concentrations in western gulls ( Larus occidentalis ) from three colonies on the US west coast. Cluster analyses showed that nearly 70% of western gulls foraged primarily in ocean or coastal habitats, whereas the remaining gulls foraged in terrestrial and freshwater habitats. Gulls that foraged in ocean or coastal habitats for half or more of their foraging locations had 55% higher mercury concentrations than gulls that forage in freshwater and terrestrial habitats. Ocean-foraging gulls also had lower fidelity to a specific foraging area than freshwater and terrestrial-foraging gulls, but fidelity and sex were unrelated to gull blood mercury concentrations in all models. These findings support existing research that has described elevated mercury levels in species using aquatic habitats. Our analyses also demonstrate that gulls can be used to detect differences in contaminant exposure over broad geographic scales and across coarse habitat types, a factor that may influence gull health and persistence of other populations that forage across the land-sea gradient.

California, Oregon↗
USGS2018

Using spatially‐explicit capture–recapture models to explain variation in seasonal density patterns of sympatric ursids

Understanding how environmental factors interact to determine the abundance and distribution of animals is a primary goal of ecology, and fundamental to the conservation of wildlife populations. Studies of these relationships, however, often assume static environmental conditions, and rarely consider effects of competition with ecologically similar species. In many parts of their shared ranges, grizzly bears Ursus arctos and American black bears U. americanus have nearly complete dietary overlap and share similar life history traits. We therefore tested the hypothesis that density patterns of both bear species would reflect seasonal variation in available resources, with areas of higher primary productivity supporting higher densities of both species. We also hypothesized that interspecific competition would influence seasonal density patterns. Specifically, we predicted that grizzly bear density would be locally reduced due to the ability of black bears to more efficiently exploit patchy food resources such as seasonally abundant fruits. To test our hypotheses, we used detections of 309 grizzly and 597 black bears from two independent genetic sampling methods in spatially‐explicit capture–recapture (SECR) models. Our results suggest grizzly bear density was lower in areas of high black bear density during spring and summer, although intraspecific densities were also important, particularly during the breeding season. Black bears had lower densities in areas of high grizzly bear density in spring; however, density of black bears in early and late summer was best explained by primary productivity. Our results are consistent with the hypothesis that smaller‐bodied, more abundant black bears may influence the density patterns of behaviorally‐dominant grizzly bears through exploitative competition. We also suggest that seasonal variation in resource availability be considered in efforts to relate environmental conditions to animal density.

Montana↗
USGS2018

Spatiotemporal remote sensing of ecosystem change and causation across Alaska

Contemporary climate change in Alaska has resulted in amplified rates of press and pulse disturbances that drive ecosystem change with significant consequences for socio‐environmental systems. Despite the vulnerability of Arctic and boreal landscapes to change, little has been done to characterize landscape change and associated drivers across northern high‐latitude ecosystems. Here we characterize the historical sensitivity of Alaska's ecosystems to environmental change and anthropogenic disturbances using expert knowledge, remote sensing data, and spatiotemporal analyses and modeling. Time‐series analysis of moderate—and high‐resolution imagery was used to characterize land‐ and water‐surface dynamics across Alaska. Some 430,000 interpretations of ecological and geomorphological change were made using historical air photos and satellite imagery, and corroborate land‐surface greening, browning, and wetness/moisture trend parameters derived from peak‐growing season Landsat imagery acquired from 1984 to 2015. The time series of change metrics, together with climatic data and maps of landscape characteristics, were incorporated into a modeling framework for mapping and understanding of drivers of change throughout Alaska. According to our analysis, approximately 13% (~174,000 ± 8700 km 2 ) of Alaska has experienced directional change in the last 32 years (±95% confidence intervals). At the ecoregions level, substantial increases in remotely sensed vegetation productivity were most pronounced in western and northern foothills of Alaska, which is explained by vegetation growth associated with increasing air temperatures. Significant browning trends were largely the result of recent wildfires in interior Alaska, but browning trends are also driven by increases in evaporative demand and surface‐water gains that have predominately occurred over warming permafrost landscapes. Increased rates of photosynthetic activity are associated with stabilization and recovery processes following wildfire, timber harvesting, insect damage, thermokarst, glacial retreat, and lake infilling and drainage events. Our results fill a critical gap in the understanding of historical and potential future trajectories of change in northern high‐latitude regions.

Alaska↗
USGS2020

A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations

Identifying and clearly communicating the drivers of ecosystem function is a crucially important goal for both basic and applied ecology. This has proven difficult because the putative causes (e.g., environment, species identity, biodiversity, and functional traits) are numerous and correlated. The problem is exacerbated by a lack of a formal framework for unambiguously relating theoretical language to precise, quantitative expressions of that language. Using a formal framework for the graphical expression of complex causal hypotheses, we developed a causal diagram of the concepts required to comprehensively test whether hypothesized sets of functional traits mediate the relationship between community structure and ecosystem function. We then used causal analysis, simulations, and field data to develop and test analytical strategies for understanding how community structure influences ecosystem functions via functional traits. Formal causal analysis showed that biodiversity–ecosystem function correlations are non‐causal associations. Using simulations, we showed how biodiversity correlations and species identity effects can arise from misspecification or incomplete mediation by functional trait composites. We also found that different types of model misspecification result in different patterns of residuals, which may be used to diagnose gaps in functional trait hypotheses. Treating the model misspecifications eliminated associations between species identity or biodiversity and ecosystem function. Finally, we provide an example of the analysis of field data to demonstrate how to use these insights to conduct a research program that has the goal of understanding the mechanistic trait relationships that link community structure to ecosystem function.

Ecology↗
USGS2012

Modeling of soil erosion and sediment transport in the East River Basin in southern China

Soil erosion is a major global environmental problem that has caused many issues involving land degradation, sedimentation of waterways, ecological degradation, and nonpoint source pollution. Therefore, it is significant to understand the processes of soil erosion and sediment transport along rivers, and this can help identify the erosion prone areas and find potential measures to alleviate the environmental effects. In this study, we investigated soil erosion and identified the most seriously eroded areas in the East River Basin in southern China using a physically-based model, Soil and Water Assessment Tool (SWAT). We also introduced a classical sediment transport method (Zhang) into SWAT and compared it with the built-in Bagnold method in simulating sediment transport process along the river. The derived spatial soil erosion map and land use based erosion levels can explicitly illustrate the identification and prioritization of the critical soil erosion areas in this basin. Our results also indicate that erosion is quite sensitive to soil properties and slope. Comparison of Bagnold and Zhang methods shows that the latter can give an overall better performance especially in tracking the peak and low sediment concentrations along the river. We also found that the East River is mainly characterized by sediment deposition in most of the segments and at most times of a year. Overall, the results presented in this paper can provide decision support for watershed managers about where the best management practices (conservation measures) can be implemented effectively and at low cost. The methods we used in this study can also be of interest in sediment modeling for other basins worldwide.

Science of the Total Environment↗
USGS1985

Environmental systems and management activities on the Kennedy Space Center, Merritt Island, Florida: results of a modeling workshop

In the early 1960's, the National Aeronautics and Space Administration (NASA) began purchasing 140,000 acres on Merritt Island, Florida, in order to develop a center for space exploration. Most of this land was acquired to provide a safety and security buffer around NASA facilities. NASA, as the managing agency for the Kennedy Space Center (KSC), is responsible for preventing or controlling environmental pollution from the Federal facilities and activities at the Space Center and is committed to use all practicable means to protect and enhance the quality of the surrounding environment. The Merritt Island National Wildlife Refuge was established in 1963 when management authority for undeveloped lands at KSC was transferred to the U.S. Fish and Wildlife Service. In addition to manage for 11 Federally-listed threatened and endangered species and other resident and migratory fish and wildlife populations, the Refuge has comanagement responsibility for 19,000 acres of mosquito control impoundments and 2,500 acres of citrus groves. The Canaveral National Seashore was developed in 1975 when management of a portion of the coastal lands was transferred from NASA to the National Park Service. This multiagency jurisdiction on Merritt Island has resulted in a complex management environment. The modeling workshop described in this report was conducted May 21-25, 1984, at the Kennedy Space Center to: (1) enhance communication among the agencies with management responsibilities on Merritt Island; (2) integrate available information concerning the development, management, and ecology of Merritt Island; and (3) identify key research and monitoring needs associated with the management and use of the island's resources. The workshop was structured around the formulation of a model that would simulate primary management and use activities on Merritt Island and their effects on upland, impoundment, and estuarine vegetation and associated wildlife. The simulation model is composed of four connected submodels. The Uplands submodel calculates changes in acres and structural components of vegetation communities resulting from succession, fire, facilities development, and shuttle launch depositions, as well as the quantity and quality of surface runoff and aquifer input to an impoundment and an estuary. The Impoundment submodel next determines water quality and quantity and changes in vegetation resulting from water level manipulation and prescribed burning. The Estuary submodel than determines water quality parameters and acres of seagrass beds. Finally, the Wildlife submodel calculates habitat suitability indices for key species of interest, based on vegetation conditions in the uplands and impoundments and on several hydrologic parameters. The model represents a hypothetical management unit with 2,500 acres of uplands, a 600-acre impoundment, and a 1,500-acre section of estuary. Two management scenarios were run to analyze model behavior. The scenarios differ in the frequency of shuttle launches and prescribed burning, the extent of facilities development, the amount of land disposed waste material applied, and the nature and timing of impoundment water level control. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. Open communication occurs among the Federal, State, and local agencies involved with activities on Merritt Island and the agencies have a cooperative working relationship. The workshop provided an opportunity for all of these agencies to meet at one time and have focused discussions on the key environmental and multiagency resource management issues. The workshop framework helped to integrate information and assumptions from a number of disciplines and agencies. This integration occurred in the computer simulation model and among workshop participants as submodel linkages were developed and scenario results discussed. A number of research needs were identified at the workshop during the model building and testing exercises and associated discussions. These needs were based on the informed judgement of researchers and managers familiar with Merritt Island or similar areas, rather than on a comprehensive literature review of sensitivity analysis of the preliminary model developed at the workshop. Some of the needs can be addressed by interpreting the results of completed studies from similar geographic areas as they relate to Merritt Island, while other will require additional research studies on Merritt Island. Major research needs associated with the Upland submodel include behavior of the near-surface aquifer, factors limiting slash pine regeneration, frequency and effects of natural fire on various cover types, cumulative effects of shuttle launches, and fate in upland soils of nitrogen and phosphorous from land applied waste material. Key Impoundment submodel needs include documentation of vegetation changes in response to altered water depth, salinity, and nutrient concentrations and better specification of the functional characteristics of impoundments as chemical filters. Important information gaps identified in the Estuary submodel include a more complete analysis of factors contributing to phytoplankton abundance, evaluation of sources of turbidity other than phytoplankton, and identification and quantification of factors limiting seagrass distribution. Primary research needs associated with the Wildlife submodel include a survey of breeding habitat, production data, and harvest data for mottled ducks; data on the emigration and immigration of juvenile mullet (and other transient fish) in the impoundment; the contribution of various seagrasses to habitat requirements of sea trout; and the effects of dissolved oxygen on survival of juvenile sea trout. Ideally, the modeling workshop process is iterative in nature. Periods between workshops are used for research, data collection, and model refinement. Each workshop integrates information collected since the last workshop and produces a more credible model that is more useful in evaluating management alternatives. Participants felt that continued application of this process would help provide ongoing integration and communication among agencies and would allow each agency's planning and management activities to be viewed within the context of an overall assessment.

Report↗
USGS2014

Integrating research tools to support the management of social-ecological systems under climate change

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Ecology and Society↗
USGS2021

An integrated path for spatial capture–recapture and animal movement modeling

Ecologists and conservation biologists increasingly rely on spatial capture–recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

Ecology↗
USGS2019

Successful molecular detection studies require clear communication among diverse research partners

Molecular detection techniques are powerful tools used in ecological applications ranging from diet analyses to pathogen surveillance. Research partnerships that use these tools often involve collaboration among professionals with expertise in field biology, laboratory techniques, quantitative modeling, wildlife disease, and natural resource management. However, in many cases, each of these collaborators lacks specific knowledge about the approaches, decisions, methods, and terminology used by their research partners, which can impede effective communication and act as a barrier to the efficient use of molecular data for ecological inferences and subsequent conservation decision making. We outline a collaborative framework to assist colleagues with diverse types of expertise to effectively translate their scientific and management needs to research partners from other specialties. The molecular techniques used to detect organisms will continue to advance both in sophistication and in the breadth of ecological applications. Our objective is to enable ecologists to harness the full utility of these methods by developing effective collaborative partnerships.

Frontiers in Ecology and the Environment↗
USGS2025

Lake sturgeon behavioral diversity in the Laurentian Great Lakes: Migratory patterns across populations and habitats

Background Characterizing the diversity of migration behaviors from the individual to the population level is essential for understanding how organisms respond to environmental variation and how these responses affect survival and habitat use. Lake sturgeon ( Acipenser fulvescens ) is a species of special concern in the Laurentian Great Lakes that are long-lived and generally classified as intermittent, adfluvial spawners. Observations of lake sturgeon movements at ecologically relevant spatiotemporal scales have shown that migration behavior often varies among individuals within the same population. However, studies on individual populations, particularly when focused only on a part of the life cycle (e.g., often spawning), provide just a partial understanding of the species’ full migratory scope and processes underlying expression of different migratory behaviors. To better understand lake sturgeon migratory diversity, we characterized and compared migratory behaviors of six lake sturgeon populations occupying environments that varied in habitat availability and connectivity in different Laurentian Great Lakes. Methods Sequence analysis combined with agglomerative hierarchical clustering and visual inspection of daily location data were used to identify distinct lake sturgeon migratory behaviors present in each population. Results Seven distinct migratory behaviors were identified based on differential patterns of lake and river use that encompass spawning and other seasonal periods. Behaviors were categorized as annual spring river, intermittent spring river, intermittent two-step, annual summer river, annual winter river, and annual interlake migrants along with river residents. The presence and frequency of migratory behaviors varied substantially among populations. Conclusions Our study demonstrated that migratory diversity is a general feature of lake sturgeon life history that may be partially shaped by habitat availability and connectivity. Given these results, we propose a conceptual model that links habitat availability and connectivity to migratory diversity and predict a positive association between them. This updated framework provides a cohesive basis for understanding lake sturgeon migratory behavior across variable ecological contexts in the Laurentian Great Lakes and will help promote future research to refute or refine the model.

Laurentian Great Lakes↗
USGS2019

Effects of urban multi-stressors on three stream biotic assemblages

During 2014, the U.S. Geological Survey (USGS) National Water-Quality Assessment(NAWQA) project assessed stream quality in 75 streams across an urban disturbance gradient within the Piedmont ecoregion of southeastern United States. Our objectives were to identify primary instream stressors affecting algal, macroinvertebrate and fish assemblages in wadeable streams. Biotic communities were surveyed once at each site, and various instream stressors were measured during a 4-week index period preceding the ecological sampling. The measured stressors included nutrients; contaminants in water, passive samplers, and sediment; instream habitat; and flow variability. All nine boosted regression tree models – three for each of algae, invertebrates, and fish – had cross-validation R 2 (CV R 2 ) values of 0.41 or above, and an invertebrate model had the highest CV R 2 of 0.65. At least one contaminant metric was important in every model, and minimum daytime dissolved oxygen (DO), nutrients, and flow alteration were important explanatory variables in many of the models. Physical habitat metrics such as sediment substrate were only moderately important. Flow alteration metrics were useful factors in eight of the nine models. Total phosphorus, acetanilide herbicides and flow (time since last peak) were important in all three algal models, whereas insecticide metrics (especially those representing fipronil and imidacloprid) were dominant in the invertebrate models. DO values below approximately 7 mg/L corresponded to a strong decrease in sensitive taxa or an increase in tolerant taxa. DO also showed strong interactions with other variables, particularly contaminants and sediment, where the combined effect of low DO and elevated contaminants increased the impact on the biota more than each variable individually. Contaminants and flow alteration were strongly correlated to urbanization, indicating the importance of urbanization to ecological stream condition in the region.

Science of the Total Environment↗
USGS2021

Integrated hierarchical models to inform management of transitional habitat and the recovery of a habitat specialist

Quantifying the contribution of habitat dynamics relative to intrinsic population processes in regulating species persistence remains an ongoing challenge in ecological and applied conservation. Understanding these drivers and their relationship is essential for managing habitat‐dependent species, especially those that specialize in transitional habitats. Limitations in the ability of natural disturbance to mediate transitional habitat dynamics have resulted in a decline in early‐ and mid‐successional vegetation structure and prompted the need for aggressive habitat management to replace natural perturbations and increase habitat structural complexity. We describe a collaborative effort with a group of independent land managers to design an adaptive management program for restoring an imperiled ecosystem and recovering declining populations of an endemic habitat specialist. We developed a set of integrated, hierarchical models to estimate management‐mediated transition rates among vegetation classes in two dominant scrub communities and the species response (local colonization and extinction probabilities) as a function of habitat state. Models were fit using a long‐term data set of habitat and occupancy observations from 361 Florida scrub‐jay territories across two Florida counties. Occupancy model results correspond closely to previous approaches of estimating differential survival and reproductive success associated with habitat conditions, with highest colonization and lowest extinction rates estimated for those habitat states found to have the highest rates of survival and reproduction. In addition to offering an innovative approach for jointly modeling habitat and species population dynamics, the program we describe will also be of interest from a management perspective by providing guidance for developing collaborative, adaptive management frameworks from the ground up. We engaged land managers via workshops to specify objectives and desired state‐variable conditions, identify management alternatives, and elicit consensus opinions on model parameters. Treating expert opinions as pseudo‐observations to define Dirichlet priors allowed us to make use of existing management knowledge. Formal learning was then accumulated by updating transition probability estimates as management activities were implemented over the study period. We believe this adaptive management framework provides a useful approach for increasing our understanding of complex ecological relationships and hope that it will be adopted by others who have interest in informing management and conservation efforts.

Florida↗
USGS1999

Data set incongruence and correlated character evolution: An example of functional convergence in the hind-limbs of stifftail diving ducks

The unwitting inclusion of convergent characters in phylogenetic estimates poses a serious problem for efforts to recover phylogeny. Convergence is not inscrutable, however, particularly when one group of characters tracks phylogeny and another set tracks adaptive history. In such cases, convergent characters may be correlated with one or a few functional anatomical units and readily identifiable by using comparative methods. Stifftail ducks (Oxyurinae) offer one such opportunity to study correlated character evolution and function in the context of phylogenetic reconstruction. Morphological analyses place stifftail ducks as part of a large clade of diving ducks that includes the sea ducks (Mergini), Hymenolaimus, Merganetta , and Tachyeres , and possibly the pochards (Aythyini). Molecular analyses, on the other hand, place stifftails far from other diving ducks and suggest, moreover, that stifftails are polyphyletic. Mitochondrial cytochrome b gene sequences of eight stifftail species traditionally supposed to form a clade were compared with each other and with sequences from 50 other anseriform and galliform species. Stifftail ducks are not the sister group of sea ducks but lie outside the typical ducks (Anatinae). Of the four traditional stifftail genera, monophyly of Oxyura and its sister group relationship with Nomonyx are strongly supported. Heteronetta probably is the sister group of that clade, but support is weak. Biziura is not a true stifftail. Within Oxyura , Old World species ( O. australis, O. leucocephala, O. maccoa ) appear to form a clade, with New World species ( O. jamaicensis, O. vittata ) branching basally. Incongruence between molecules and morphology is interpreted to be the result of adaptive specialization and functional convergence in the hind limbs of Biziura and true stifftails. When morphological characters are divided into classes, only hind-limb characters are significantly in conflict with the molecular tree. Likewise, null models of synonymous and nonsynonymous substitution based on patterns of codon-degeneracy and chemical dissimilarity indicate that the nucleotide and amino acid changes postulated by the molecular tree are more plausible than those postulated by the morphological tree. These findings teach general lessons about the utility of highly adaptive characters (in particular those related to foraging ecology) and underscore the problems that convergence can pose for attempts to recover phylogeny. They also demonstrate how the concept of natural data partitions and simple models of evolution (e.g., parsimony, likelihood, neutrality) can be used to test the accuracy of independent phylogenetic estimates and provide arguments in favor of one tree topology over another.

Systematic Biology↗