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USGS2016

Application of decision science to resilience management in Jamaica Bay

This book highlights the growing interest in management interventions designed to enhance the resilience of the Jamaica Bay socio-ecological system. Effective management, whether the focus is on managing biological processes or human behavior or (most likely) both, requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections). In systems characterized by many interacting components and high uncertainty, making probabilistic predictions is often difficult and requires careful thinking not only about system dynamics, but also about how management objectives are specified and the analytic method used to select the preferred action(s). Developing a clear statement of the problem(s) and articulation of management objectives is often best achieved by including input from managers, scientists and other stakeholders affected by the decision through a process of joint problem framing (Marcot and others 2012; Keeney and others 1990). Using a deliberate, coherent and transparent framework for deciding among management alternatives to best meet these objectives then ensures a greater likelihood for successful intervention. Decision science provides the theoretical and practical basis for developing this framework and applying decision analysis methods for making complex decisions under uncertainty and risk.

Book chapter↗

USGS2020

Drivers and consequences of apex predator diet composition in the Canadian Beaufort Sea

Polar bears ( Ursus maritimus ) rely on annual sea ice as their primary habitat for hunting marine mammal prey. Given their long lifespan, wide geographic distribution, and position at the top of the Arctic marine food web, the diet composition of polar bears can provide insights into temporal and spatial ecosystem dynamics related to climate-mediated sea ice loss. Polar bears with the greatest ecological constraints on diet composition may be most vulnerable to climate-related changes in ice conditions and prey availability. We used quantitative fatty acid signature analysis (QFASA) to estimate the diets of polar bears ( n = 419) in two western Canadian Arctic subpopulations (Northern Beaufort Sea and Southern Beaufort Sea) from 1999 to 2015. Polar bear diets were dominated by ringed seal ( Pusa hispida ), with interannual, seasonal, age- and sex-specific variation. Foraging area and sea ice conditions also affected polar bear diet composition. Most variation in bear diet was explained by longitude, reflecting spatial variation in prey availability. Sea ice conditions (extent, thickness, and seasonal duration) declined throughout the study period, and date of sea ice break-up in the preceding spring was positively correlated with female body condition and consumption of beluga whale ( Delphinapterus leucas ), suggesting that bears foraged on beluga whales during entrapment events. Female body condition was positively correlated with ringed seal consumption, and negatively correlated with bearded seal consumption. This study provides insights into the complex relationships between declining sea ice habitat and the diet composition and foraging success of a wide-ranging apex predator.

Northwest Territories, Yukon↗

USGS2004

Mineral stimulation of subsurface microorganisms: release of limiting nutrients from silicates

Microorganisms play an important role in the weathering of silicate minerals in many subsurface environments, but an unanswered question is whether the mineral plays an important role in the microbial ecology. Silicate minerals often contain nutrients necessary for microbial growth, but whether the microbial community benefits from their release during weathering is unclear. In this study, we used field and laboratory approaches to investigate microbial interactions with minerals and glasses containing beneficial nutrients and metals. Field experiments from a petroleum-contaminated aquifer, where silicate weathering is substantially accelerated in the contaminated zone, revealed that phosphorus (P) and iron (Fe)-bearing silicate glasses were preferentially colonized and weathered, while glasses without these elements were typically barren of colonizing microorganisms, corroborating previous studies using feldspars. In laboratory studies, we investigated microbial weathering of silicates and the release of nutrients using a model ligand-promoted pathway. A metal-chelating organic ligand 3,4 dihydroxybenzoic acid (3,4 DHBA) was used as a source of chelated ferric iron, and a carbon source, to investigate mineral weathering rate and microbial metabolism. In the investigated aquifer, we hypothesize that microbes produce organic ligands to chelate metals, particularly Fe, for metabolic processes and also form stable complexes with Al and occasionally with Si. Further, the concentration of these ligands is apparently sufficient near an attached microorganism to destroy the silicate framework while releasing the nutrient of interest. In microcosms containing silicates and glasses with trace phosphate mineral inclusions, microbial biomass increased, indicating that the microbial community can use silicate-bound phosphate inclusions. The addition of a native microbial consortium to microcosms containing silicates or glasses with iron oxide inclusions correlated to accelerated weathering and release of Si into solution as well as the accelerated degradation of the model substrate 3,4 DHBA. We propose that silicate-bound P and Fe inclusions are bioavailable, and microorganisms may use organic ligands to dissolve the silicate matrix and access these otherwise limiting nutrients.

Chemical Geology↗

USGS2025

Suturing fragmented landscapes: Mosaic hybrid zones in plants may facilitate ecosystem resiliency

Many widespread plant taxa of western North America have diversified into phenotypically and genetically divergent lineages due to complex biogeographic histories across heterogeneous landscapes. Mosaic hybrid zones can form when geographically co-occurring, yet environmentally distinct, lineages cross-pollinate and form hybrids that occupy unique environmental niches absent of a geographic cline. This expands the total environmental space across which parental and hybrid individuals grow, resulting in larger, less fragmented geographic distributions. Here, we highlight hybridization mosaics across three study systems containing taxa critical to widespread plant communities in western North America: Ericameria nauseosa , Artemisia tridentata , and Sphaeralcea fendleri . The systems contain diverged taxa that co-occur across the landscape and hybridize readily. Hybridization among taxa has facilitated niche expansion into intermediate environments consistent with unique combinations of adaptive genetic variation, creating more continuity within each study system—study systems occupy ~820 to 270,000 km 2 more geographic area by virtue of hybridization. Furthermore, hybrids are predicted to play important roles in future climates, as they may occupy 8 to 475% larger distributions compared to present. Convergent patterns signal mosaic hybridization as an underappreciated mechanism with broad ecological and evolutionary ramifications. Leveraging mosaic hybridization may assist the creation of restoration management plans that aim to mitigate the deleterious effects of habitat fragmentation on ecosystems in the context of climate change.

western United States↗

USGS2015

Status and trends of land change in the Midwest–South Central United States—1973 to 2000

U.S. Geological Survey (USGS) Professional Paper 1794–C is the third in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Midwest–South Central United States between 1973 and 2000. Volumes A, B, and D provide similar analyses for the Western United States, the Great Plains of the United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Midwest–South Central United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Midwest–South Central United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research.

Professional Paper↗

USGS2009

Learning to be different: Acquired skills, social learning, frequency dependence, and environmental variation can cause behaviourally mediated foraging specializations

Question: How does the ability to improve foraging skills by learning, and to transfer that learned knowledge, affect the development of intra-population foraging specializations? Features of the model: We use both a state-dependent life-history model implemented by stochastic dynamic programming (SDPM) and an individual-based model (IBM) to capture the dynamic nature of behavioural preferences in feeding. Variables in the SDPM include energy reserves, skill levels, energy and handling time per single prey item, metabolic rate, the rates at which skills are learned and forgotten, the effect of skills on handling time, and the relationship between energy reserves and fitness. Additional variables in the IBM include the probability of successful weaning, the logistic dynamics of the prey species with stochastic recruitment, the intensity of top-down control of prey by predators, the mean and variance in skill levels of new recruits, and the extent to which learned Information can be transmitted via matrilineal social learning. Key range of variables: We explore the effects of approaching the time horizon in the SDPM, changing the extent to which skills can improve with experience, increasing the rates of learning or forgetting of skills, changing whether the learning curve is constant, accelerating (T-shaped) or decelerating ('r'-shaped), changing both mean and maximum possible energy reserves, changing metabolic costs of foraging, and changing the rate of encounter with prey. Conclusions: The model results show that the following factors increase the degree of prey specialization observed in a predator population: (1) Experience handling a prey type can substantially improve foraging skills for that prey. (2) There is limited ability to retain complex learned skills for multiple prey types. (3) The learning curve for acquiring new foraging skills is accelerating, or J-shaped. (4) The metabolic costs of foraging are high relative to available energy reserves. (5) Offspring can learn foraging skills from their mothers (matrilineal social learning). (6) Food abundance is limited, such that average individual energy reserves are low Additionally, the following factors increase the likelihood of alternative specializations co-occurring in a predator population: (1) The predator exerts effective top-down control of prey abundance, resulting in frequency-dependent dynamics. (2) There is stochastic Variation in prey population dynamics, but this Variation is neither too extreme in magnitude nor too 'slow' with respect to the time required for an individual forager to learn new foraging skills. For a given predator population, we deduce that the degree of specialization will be highest for those prey types requiring complex capture or handling skills, while prey species that are both profitable and easy to capture and handle will be included in the diet of all individuals. Frequency-dependent benefits of selecting alternative prey types, combined with the ability of foragers to improve their foraging skills by learning, and transmit learned skills to offspring, can result in behaviourally mediated foraging specialization, and also lead to the co-existence of alternative specializations. The extent of such specialization is predicted to be a variable trait, increasing in locations or years when intra-specific competition is high relative to inter-specific competition. ?? 2009 M. Tim Tinker.

Evolutionary Ecology Research↗

USGS2016

Effect of cysteine and humic acids on bioavailability of Ag from Ag nanoparticles to a freshwater snail

Metal-based engineered nanoparticles (NPs) will undergo transformations that will affect their bioavailability, toxicity and ecological risk when released to the environment, including interactions with dissolved organic material. The purpose of this paper is to determine how interactions with two different types of organic material affect the bioavailability of silver nanoparticles (AgNPs). Silver uptake rates by the pond snail Lymnaea stagnalis were determined after exposure to 25 nmol l-1 of Ag as PVP AgNPs, PEG AgNPs or AgNO3, in the presence of either Suwannee River humic acid or cysteine, a high-affinity thiol-rich organic ligand. Total uptake rate of Ag from the two NPs was either increased or not strongly affected in the presence of 1 – 10 mg 1-1 humic acid. Humic substances contain relatively few strong ligands for Ag explaining their limited effects on Ag uptake rate. In contrast, Ag uptake rate was substantially reduced by cysteine. Three components of uptake from the AgNPs were quantified in the presence of cysteine using a biodynamic modeling approach: uptake of dissolved Ag released by the AgNPs, uptake of a polymer or large (>3kD) Ag-cysteine complex and uptake of the nanoparticle itself. Addition of 1:1 Ag:cysteine reduced concentrations of dissolved Ag, which contributed to, but did not fully explain the reductions in uptake. A bioavailable Ag-cysteine complex (> 3kD) appeared to be the dominant avenue of uptake from both PVP AgNPs and PEG AgNPs in the presence of cysteine. Quantifying the different avenues of uptake sets the stage for studies to assess toxicity unique to NPs.

NanoImpact↗

USGS2015

Status and trends of land change in the Great Plains of the United States--1973 to 2000

Preface U.S. Geological Survey (USGS) Professional Paper 1794–B is the second in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Great Plains of the United States between 1973 and 2000. Volumes A, C, and D provide similar analyses for the Western United States, the Midwest–South Central United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Great Plains of the United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Great Plains of the United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research. This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov .

Great Plains↗

USGS2014

Using cumulative diet data and stable isotope analysis to determine trophic position of walleye Sander vitreus in a large, complex system

Diet studies have traditionally been used to determine prey use and food web dynamics, while stable isotope analysis provides for a time-integrated approach to evaluate food web dynamics and characterize energy flow in aquatic systems. Direct comparison of the two techniques is rare and difficult to conduct in large, species rich systems. We compared changes in walleye Sander vitreus trophic position (TP) derived from paired diet content and stable isotope analysis. Individual diet-derived TP estimates were dissimilar to stable isotope-derived TP estimates. However, cumulative diet-derived TP estimates integrated from May 2001 to May 2002 corresponded to May 2002 isotope-derived estimates of TP. Average walleye TP estimates from the spring season appear representative of feeding throughout the entire previous year.

Journal of Freshwater Ecology↗

USGS1997

Fungal life-styles and ecosystem dynamics: Biological aspects of plant pathogens, plant endophytes and saprophytes

This chapter discusses various biochemical, genetic, ecological, and evolutionary aspects of fungi that express either symbiotic or saprophytic life-styles. An enormous pool of potential pathogens exists in both agricultural and natural ecosystems, and virtually all plant species are susceptible to one or more fungal pathogens. Fungal pathogens have the potential to impact on the genetic structure of populations of individual plant species, the composition of plant communities and the process of plant succession. Endophytic fungi exist for at least part of their life cycles within the tissues of a plant host. This group of fungi is distinguished from plant pathogens because they do not elicit significant disease symptoms. However, endophytes do maintain the genetic and biochemical mechanisms required for infection and colonization of plant hosts. Fungi that obtain chemical nutrients from dead organic matter are known as saprophytes and are critical to the dynamics and resilience of ecosystems. There are two modes of saprophytic growth: one in which biomolecules that are amenable to transport across cell walls and membranes are directly absorbed, and another in which fungi must actively convert complex biopolymers into subunit forms amenable to transportation into cells. Regardless of life-style, fungi employ similar biochemical mechanisms for the acquisition and conversion of nutrients into complex biomolecules that are necessary for vegetative growth, production and dissemination of progeny, organismal competition, and survival during periods of nutrient deprivation or environmental inclemency.

Advances in Botanical Research↗

USGS2001

Macroinvertebrate instream flow studies after 20 years: A role in stream management and restoration

Over the past two decades of refinement and application of instream flow evaluations, we have examined the hydraulic habitat of aquatic macroinvertebrates in a variety of conditions, along with the role of these macroinvertebrates in sustaining ecosystem integrity. Instream flow analyses assume that predictable changes in channel flow characteristics can, in turn, be used to predict the change in the density or distribution of lotic species or, more appropriately, the availability of useable habitat for those species. Five major hydraulic conditions most affect the distribution and ecological success of lotic biota: suspended load, bedload movement, and water column effects, such as turbulence, velocity profile, and substratum interactions (near-bed hydraulics). The interactions of these hydraulic conditions upon the morphology and behavior of the individual organisms govern the distribution of aquatic biota. Historically, management decisions employing the Physical Habitat Simulation (PHABSIM) have focused upon prediction of available habitat for life stages of target fish species. Regulatory agencies have rarely included evaluation of benthos for flow reservations. Although ‘taxonomic discomfort’ may be cited for the reluctant use or creation of benthic criteria, we suggest that a basic misunderstanding of the links between benthic macroinvertebrate and the fish communities is still a problem. This is derived from the lack of a perceived ‘value’ that can be assigned to macroinvertebrate species. With the exception of endangered mussel species (for which PHABSIM analysis is probably inappropriate), this is understandable. However, it appears that there is a greater ability to predict macroinvertebrate distribution (that is, a response to the change in habitat quality or location) and diversity without complex population models. Also, habitat suitability criteria for water quality indicator taxa (Ephemeroptera, Plecoptera, and Trichoptera; the so-called ‘EPTs’) may also provide additional management options to stream regulators. The greatest application for macroinvertebrate criteria will be in low-order streams where a more immediate link to fish communities can be established. We present an example from Queens Creek, in North Carolina, USA, in which monthly allocations required to preserve the integrity of the benthic macroinvertebrate community were significantly higher than for the target benthic fish species, Cottus bairdi . In the months when both Cottus and community diversity of macroinvertebrates were the ‘bottleneck’ life stages, preservation of only fish species could result in an additional 5–25% loss in macroinvertebrate habitat. We suggest that, as there becomes an increased emphasis on maintaining macroinvertebrates as monitors of stream health, there will be a concurrent emphasis on incorporating hydraulic habitat conditions as a part of bioassessment.

Regulated Rivers: Research & Management↗

USGS2017

A Bayesian method for assessing multiscalespecies-habitat relationships

Context Scientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large. Objectives Our objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance. Methods We introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA. Results Our method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%. Conclusions Given the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Nebraska↗

USGS2016

Where the wild things are: A research agenda for studying wildlife-wilderness relationship

We explore the connection between US designated wilderness areas and wildlife with the goal of establishing a research agenda for better understanding this complex relationship. Our research agenda has two components. The first, “wildlife for wilderness,” considers the impact of wildlife on wilderness character. Whereas studies show that wildlife is important in both the perception and actual enhancement of wilderness character, the context and particulars of this relationship have not been evaluated. For instance, is knowing that a rare, native species is present in a wilderness area enough to increase perceptions of naturalness (an important wilderness quality)? Or does the public need to observe the species or its sign (e.g., tracks) for this benefit? The second part of our research agenda, “wilderness for wildlife,” considers the types of research needed to understand the impact of wilderness areas on wildlife and biodiversity conservation. Several studies show the effect of one area being designated wilderness on one wildlife species. Yet, there has been no research that examines how the networks of wilderness areas in the National Wilderness Preservation System (NWPS) are used by a species or a community of species. Furthermore, we found no studies that focused on how the NWPS affects ecological or trophic interactions among species. We hope that by providing a research agenda, we can spur multiple lines of research on the topic of wildlife and wilderness.

Journal of Forestry↗

USGS2016

Structured decision making as a framework for large-scale wildlife harvest management decisions

Fish and wildlife harvest management at large spatial scales often involves making complex decisions with multiple objectives and difficult tradeoffs, population demographics that vary spatially, competing stakeholder values, and uncertainties that might affect management decisions. Structured decision making (SDM) provides a formal decision analytic framework for evaluating difficult decisions by breaking decisions into component parts and separating the values of stakeholders from the scientific evaluation of management actions and uncertainty. The result is a rigorous, transparent, and values-driven process. This decision-aiding process provides the decision maker with a more complete understanding of the problem and the effects of potential management actions on stakeholder values, as well as how key uncertainties can affect the decision. We use a case study to illustrate how SDM can be used as a decision-aiding tool for management decision making at large scales. We evaluated alternative white-tailed deer ( Odocoileus virginianus ) buck-harvest regulations in New York designed to reduce harvest of yearling bucks, taking into consideration the values of the state wildlife agency responsible for managing deer, as well as deer hunters. We incorporated tradeoffs about social, ecological, and economic management concerns throughout the state. Based on the outcomes of predictive models, expert elicitation, and hunter surveys, the SDM process identified management alternatives that optimized competing objectives. The SDM process provided biologists and managers insight about aspects of the buck-harvest decision that helped them adopt a management strategy most compatible with diverse hunter values and management concerns.

Ecosphere↗

USGS2009

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.

Landscape Ecology↗

USGS2020

Factors influencing Cinnamon Teal nest attendance patterns

Patterns of nest attendance in birds result from complex behaviours and influence the success of reproductive events. Incubation behaviours vary based on individual body condition, energy requirements and environmental factors. We assessed nest attendance patterns in Cinnamon Teal Spatula cyanoptera breeding in the San Luis Valley of Colorado in 2016–2017 using trail and video cameras to observe behaviours throughout incubation. We evaluated the effect of temporal, life-history and environmental covariates on the frequency and duration of incubation recesses as well as the incubation constancy. There was considerable model uncertainty among the models used to evaluate recess frequency. Recess duration varied according to the interaction between nest age and a quadratic effect of time of day, with hens on older nests taking longer recesses in the afternoon and hens on nests earlier in incubation taking longer recesses in the morning and evening. Incubation constancy decreased with higher ambient temperatures in the study area. This study provides evidence that Cinnamon Teal modify their behaviour during incubation according to the age of the nest and the time of day. These results improve our knowledge of Cinnamon Teal breeding ecology and shed light on the behaviours that fast-lived species may use to cope with environmental factors during nesting.

Colorado↗

USGS2020

Robust geographical determinants of infection prevalence and a contrasting latitudinal diversity gradient for haemosporidian parasites in Western Palearctic birds

Identifying robust environmental predictors of infection probability is central to forecasting and mitigating the ongoing impacts of climate change on vector‐borne disease threats. We applied phylogenetic hierarchical models to a data set of 2,171 Western Palearctic individual birds from 47 species to determine how climate and landscape variation influence infection probability for three genera of haemosporidian blood parasites ( Haemoproteus , Leucocytozoon , and Plasmodium ). Our comparative models found compelling evidence that birds in areas with higher vegetation density (captured by the normalized difference vegetation index [NDVI]) had higher likelihoods of carrying parasite infection. Magnitudes of this relationship were remarkably similar across parasite genera considering that these parasites use different arthropod vectors and are widely presumed to be epidemiologically distinct. However, we also uncovered key differences among genera that highlighted complexities in their climate responses. In particular, prevalences of Haemoproteus and Plasmodium showed strong but contrasting relationships with winter temperatures, supporting mounting evidence that winter warming is a key environmental filter impacting the dynamics of host‐parasite interactions. Parasite phylogenetic community diversities demonstrated a clear but contrasting latitudinal gradient, with Haemoproteus diversity increasing towards the equator and Leucocytozoon diversity increasing towards the poles. Haemoproteus diversity also increased in regions with higher vegetation density, supporting our evidence that summer vegetation density is important for structuring the distributions of these parasites. Ongoing variation in winter temperatures and vegetation characteristics will probably have far‐reaching consequences for the transmission and spread of vector‐borne diseases.

Molecular Ecology↗

USGS2023

Patterns, drivers, and a predictive model of dam removal cost in the United States

Given the burgeoning dam removal movement and the large number of dams approaching obsolescence in the United States, cost estimating data and tools are needed for dam removal prioritization, planning, and execution. We used the list of removed dams compiled by American Rivers to search for publicly available reported costs for dam removal projects. Total cost information could include component costs related to project planning, dam deconstruction, monitoring, and several categories of mitigation activities. We compiled reported costs from 455 unique sources for 668 dams removed in the United States from 1965 to 2020. The dam removals occurred within 571 unique projects involving 1–18 dams. When adjusted for inflation into 2020 USD, cost of these projects totaled \$1.522 billion, with per-dam costs ranging from $1 thousand (k) to \$268.8 million (M). The median cost for dam removals was \$157k, \$823k, and \$6.2M for dams that were< 5 m, between 5–10 m, and > 10 m in height, respectively. Geographic differences in total costs showed that northern states in general, and the Pacific Northwest in particular, spent the most on dam removal. The Midwest and the Northeast spent proportionally more on removal of dams less than 5 m in height, whereas the Northwest and Southwest spent the most on larger dam removals > 10 m tall. We used stochastic gradient boosting with quantile regression to model dam removal cost against potential predictor variables including dam characteristics (dam height and material), hydrography (average annual discharge and drainage area), project complexity (inferred from construction and sediment management, mitigation, and post-removal cost drivers), and geographic region. Dam height, annual average discharge at the dam site, and project complexity were the predominant drivers of removal cost. The final model had an R 2 of 57% and when applied to a test dataset model predictions had a root mean squared error of $5.09M and a mean absolute error of \$1.45M, indicating its potential utility to predict estimated costs of dam removal. We developed a R shiny application for estimating dam removal costs using customized model inputs for exploratory analyses and potential dam removal planning.

Frontiers in Ecology and Evolution↗