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At least 667 records · Page 37Linked to original sources

Control of a dominant predator influences the occurrence of a mesocarnivore of conservation concern

Context Interspecific interactions shape ecological communities, influence community dynamics, and drive co-evolution. Despite their ecological significance, predation and competition remain understudied in plains spotted skunks ( Spilogale interrupta ), a species of conservation concern. Clarifying how predator management influences their occurrence is crucial for effective conservation. Aims We investigated how coyote ( Canis latrans ) management affects the occupancy of plains spotted skunks and whether interspecific interactions with domestic cats ( Felis catus ) and striped skunks ( Mephitis mephitis ) influence plains spotted skunk occurrence. Methods We analysed live-trap data from east-central South Dakota collected in spring of 2021 and 2022. The study area encompassed portions of counties that implemented disparate predator management regimes, including one with systematic annual coyote removal and another without. We used single-species occupancy models to estimate detection and occupancy probabilities for plains spotted skunks, domestic cats, and striped skunks, incorporating environmental factors, including the site-specific predator control regime. We then applied conditional two-species occupancy models to test whether cats and striped skunks influenced plains spotted skunk occurrence. Key results Plains spotted skunks had the lowest occupancy, followed by domestic cats, and striped skunks. Our findings showed significant associations between coyote removal and occupancy probabilities for each mesocarnivore species. Plains spotted skunks had higher occupancy in areas where coyotes were annually removed. Spotted skunk occurrence was not conditional on either domestic cat or striped skunk occurrence. Conclusions In our study system, cats appear to pose less predation risk to spotted skunks than do other predators, reducing the likelihood that cats significantly influence spotted skunk occupancy. Defensive behaviours and use of spatial refugia by plains spotted skunks may further mitigate predation risk. In addition, co-evolutionary pressures may have led to trait adaptations that facilitate the independent co-occurrence of plains spotted skunks and striped skunks. Implications Our findings highlighted the ecological consequences of predator management and the importance of considering predator–prey dynamics in conservation and management planning. Strategies aimed at conserving plains spotted skunks should integrate predator control measures while considering broader mesocarnivore community interactions.

South Dakota↗

The value of information is context dependent: A demonstration of decision tools to address multispecies river temperature management under uncertainty

Trade-offs among objectives in natural resource management can be exacerbated in altered ecosystems and when there is uncertainty in predicted management outcomes. Multi-criteria decision analysis and value of information (VOI) are underutilized decision tools that can assist fisheries managers in handling trade-offs and evaluating the importance of uncertainty. We demonstrate the use of these tools using a case study in the Sacramento River, California, USA, where two imperiled species with different temperature requirements, winter-run Chinook Salmon Oncorhynchus tshawytscha and Green Sturgeon Acipenser medirostris , spawn and rear in the artificially cold Shasta Dam tailwater. A temperature-control device installed on Shasta Dam maintains cool water for Chinook Salmon; however, uncertainties exist related to the effects of temperatures on the spawning and rearing of both species. We consider four alternative hypotheses in models of early life-stage dynamics to evaluate the effects of alternative temperature management strategies on Chinook Salmon and Green Sturgeon management objectives. We used VOI to quantify the increase in management performance that can be expected by resolving hypothesis-based uncertainties as a function of the weight assigned to species-specific objectives. We found the decision was hindered by uncertainty; the best performing alternative depends on which hypothesis is true, with warmer or cooler alternative management strategies recommended when weights favor Green Sturgeon or Chinook Salmon objectives, respectively. The value of reducing uncertainty was highest when Green Sturgeon was slightly favored, highlighting the interaction between scientific uncertainty and decision makers' values. Our demonstration features multi-criteria decision analysis and VOI as transparent, deliberative tools that can assist fisheries managers in confronting value conflicts, prioritizing resolution of uncertainty, and optimally managing aquatic ecosystems.

Fisheries↗

Modeling, mapping, and measuring the risk of freshwater invasive species across Alaska

Freshwater ecosystems of the Alaskan Arctic and Subarctic provide resources that are culturally, ecologically, and economically invaluable. Presently, these regions are relatively free of the impacts from invasive species compared to southern latitudes. To date, there have been relatively few verified introductions of aquatic invasive species (AIS) to freshwater ecosystems in Alaska. The expanding list and distribution of AIS has led to significant negative ecological and economic impacts (e.g., waterweed Elodea nuttalli ; E. canadensis and northern pike Esox Lucius introduced outside its native range in Alaska). Escalating human activity across Alaskan lands and waters, coupled with rapidly shifting environmental conditions, increases the potential for new species introductions and subsequent establishment. Creating a proactive framework for well-informed decision-making and action can improve the effectiveness of prevention efforts and bolster decision support tools that help resource managers direct limited resources. Prioritizing AIS that may be introduced and become established, as well as the locations at highest risk of invasion, is foundational to building a proactive invasive species management framework in Alaska. This project sought to identify and prioritize AIS known to be invasive in the contiguous United States, evaluate current and future habitat suitability for AIS in Alaska, and assess potential for AIS to be transported to habitats across Alaska, utilizing similar assessment methods as implemented for Bering Sea marine invasive species and non-native plants in Alaska. To accomplish this goal, the objectives of the project were to: 1) develop a formal ranked list of potential AIS to freshwater systems of Alaska; 2) assess the level of establishment risk for potential AIS by developing habitat suitability models for waterbodies across Alaska; and 3), identify potential pathways and specific vectors for high-risk AIS to invade Alaska and develop a framework for how vector analysis will be completed to understand transport risk. Overall, our goal is horizon scanning which is defined by Roy et al. (2019) as “a systematic examination of potential threats and opportunities, within a given context, and likely future developments, which are at the margin of current thinking and planning.” The scans include pathway analyses and risk screening of species present at pathway origin points, with a focus on identifying species at high risk of being introduced, becoming established, spreading, and causing harm. We refined a list of 28 AIS from a list of hundreds based on characterizations of species’ invasiveness and species’ proximity to Alaska (USGS 2020; GBIF 2022). Next, we evaluated the relative invasiveness of individual species to create an initial AIS ranking. We sought to characterize habitat suitability of AIS by selecting variables that were continental in scale, covering North America to include Alaska as well as the lower 48 states comparing natural discharge, sub-basin average terrain slope (degrees), average silt fraction, average organic carbon, lithological class, and human footprint in sub-basin in 2009. We estimated AIS habitat suitability across the entire state of Alaska using the physiological tolerances of the AIS (Appendix 2). We also evaluated pathways and vectors for the introduction of AIS (Appendix 2). Many pathways and vectors considered did not meet the criteria for Alaska or freshwater systems. Of the 28 ranked species that we categorized as very high, high, and moderate levels of invasiveness; all three risk groups included fish and mollusks (Appendix 2). One commonality of the very high-invasiveness-ranked species was the availability of Ecological Risk Screening Summary documents (USFWS, 2022) produced by U.S. Fish and Wildlife Service (USFWS), except for the goldfish ( Carassius auratus ) and the New Zealand mudsnail ( Potamopyrgus antipodarum ). The Ecological Risk Screening Summary is now available for New Zealand mudsnails. In general, fish species often ranked very high or high in invasiveness and included sportfish and aquarium fish, suggesting the importance of pathways such as aquarium trade, fishing industry, intentional (but illegal) introductions of sportfishes and aquarium fishes for establishment. The technique we used for habitat suitability models necessitated aquatic environmental datasets that were continental in scale, which was often interpolated from very coarse resolution source data layers, particularly in Alaska. Better spatial data representing aquatic environments would likely improve this approach. While the lack of introductions in Alaska and nearby provinces and states is encouraging, the lack of occurrence data for the focal species also created complications for habitat suitability modeling. Despite the challenges, the habitat suitability models indicated limited suitability for warmwater species while some species, such as Brook trout (S alvelinus fontinalis ), have high habitat suitability across Alaska no matter what threshold approach is taken. Some environmental predictors were more important than others. Specifically, the most important predictor variable, ‘frost free days,’ was critical for 15 out of 28 species as expected due to harsh winter conditions in Arctic and Subarctic regions. The second most important predictor was ‘subbasin land surface runoff’, a variable that indicates the amount of discharge and runoff, while the third most important predictor was ‘snow cover’ another indication of winter conditions. Overall, the ability to understand the effect of future climate scenarios on the establishment of AIS was challenging. A detailed dataset of freshwater temperatures and water chemistry (e.g., pH, calcium) would greatly improve the ability to predict invasiveness of freshwater species to Alaska’s ecosystems on a regional basis. Future studies may benefit from a more focused geographic scope examining a group of subbasins or a regional basin rather than the entire state. These drainages could be selected based upon the mostly likely locations of introduction pathways. The two most prevalent pathway risks for AIS are in-state transfer and stowaways/contaminants. Although there are examples of introductions from other pathways, the risk is somewhat mitigated by Alaska’s climate and regulations. However, variable application of protocols for inspection and cleaning of fishing gear, watercraft, and other similar items while traveling into Alaska as well as transferring from waterbody to waterbody within the state creates a substantial risk in introducing invasive species. We plot cumulative invasive vulnerability for all subbasins and for the top 10% of subbasins (Appendix 3).

Alaska↗

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↗

Nutrient limitation of phytoplankton in Chesapeake Bay: Development of an empirical approach for water-quality management

Understanding the temporal and spatial roles of nutrient limitation on phytoplankton growth is necessary for developing successful management strategies. Chesapeake Bay has well-documented seasonal and spatial variations in nutrient limitation, but it remains unknown whether these patterns of nutrient limitation have changed in response to nutrient management efforts. We analyzed historical data from nutrient bioassay experiments (1992–2002) and data from long-term, fixed-site water-quality monitoring program (1990–2017) to develop empirical approaches for predicting nutrient limitation in the surface waters of the mainstem Bay. Results from classification and regression trees (CART) matched the seasonal and spatial patterns of bioassay-based nutrient limitation in the 1992–2002 period much better than two simpler, non-statistical approaches. An ensemble approach of three selected CART models satisfactorily reproduced the bioassay-based results (classification rate = 99%). This empirical approach can be used to characterize nutrient limitation from long-term water-quality monitoring data on much broader geographic and temporal scales than would be feasible using bioassays, providing a new tool for informing water-quality management. Results from our application of the approach to 21 tidal monitoring stations for the period of 2007–2017 showed modest changes in nutrient limitation patterns, with expanded areas of nitrogen-limitation and contracted areas of nutrient saturation (i.e., not limited by nitrogen or phosphorus). These changes imply that long-term reductions in nitrogen load have led to expanded areas with nutrient-limited phytoplankton growth in the Bay, reflecting long-term water-quality improvements in the context of nutrient enrichment. However, nutrient limitation patterns remain unchanged in the majority of the mainstem, suggesting that nutrient loads should be further reduced to achieve a less nutrient-saturated ecosystem.

Maryland, Virginia↗

Estimating spatial and temporal components of variation in count data using negative binomial mixed models

P artitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

Iowa, Maine, Michigan, Ohio, Wisconsin↗

Defining anural malformations in the context of a developmental problem

This paper summarizes terminology and general concepts involved in animal development for the purpose of providing background for the study and understanding of frog malformations. The results of our radiographic investigation of rear limb malformations in Rana pipiens provide evidence that frog malformations are the product of early developmental errors. Although bacteria, parasites and viruses were identified in these metamorphosed frogs, the relevant window to look for the teratogenic effect of these agents is in the early tadpole stage during limb development. As a result, our microbiological findings must be regarded as inconclusive relative to determining their contribution to malformations because we conducted our examinations on metamorphosed frogs not tadpoles. Future studies need to look at teratogenic agents (chemical, microbial, physical or mechanical) that are present in the embryo, tadpole, and their environments at the stages of development that are relevant for the malformation type. The impact of these teratogenic agents then needs to be assessed in appropriate animal models using studies that are designed to mimic field conditions. The results of these laboratory tests should then be analyzed in such a way that will allow comparison with the findings in the wild-caught tadpoles and frogs.

Journal of the Iowa Academy of Science↗

Habitat amount and edge effects, not perch proximity, nest exposure, or vegetation diversity affect cowbird parasitism in agricultural landscapes

Context Prior research documented relationships between brown-headed cowbird ( Molothrus ater ) brood parasitism and edge effects, proximity of perches, and nest exposure. Those relationships have not been evaluated in agroecosystems containing extremes of fragmentation and vegetation diversity. Objectives We compared three existing hypotheses on how cowbirds locate host nests with two new hypotheses regarding habitat amount and vegetation diversity to determine how the configuration and location of agricultural conservation practices affect grassland bird nest parasitism rates and predicted rates for eight common conservation practices. Methods We assessed cowbird parasitism of grassland bird nests on corn and soybean farms in Iowa, USA, and measured perch proximity, nest exposure, edge effects, habitat amount, and vegetation diversity for each nest. We fit a global generalized linear mixed-effects model and compared importance of model parameters using odds ratios. We predicted parasitism likelihood for every subset model and averaged predictions to explore individual effects. Results The variables that most influenced parasitism rates included main effects for nest initiation day-of-season (OR = 0.71, CI 95 = 0.60–0.84) and the landscape variables of distance to nearest crop edge (0.63, 0.51–0.76) and proportion of grass land cover within 660 m (0.75, 0.57–1.00). We found little support that perch proximity, nest exposure, or native vegetation diversity affected parasitism. We also assessed parasitism likelihood by conservation practice and found no significant differences. Conclusions Our results provide evidence to support the edge effect and habitat amount hypotheses, but not the nest exposure, vegetation diversity, or perch proximity hypotheses.

Iowa↗

Current and projected flood exposure for Alaska coastal communities

Globally, coastal communities experience flood hazards that are projected to worsen from climate change and sea level rise. The 100-year floodplain or record flood are commonly used to identify risk areas for planning purposes. Remote communities often lack measured flood elevations and require innovative approaches to estimate flood elevations. This study employs observation-based methods to estimate the record flood elevation in Alaska communities and compares results to elevation models, infrastructure locations, and sea level rise projections. In 46 analyzed communities, 22% of structures are located within the record floodplain. With sea level rise projections, this estimate increases to 30–37% of structures by 2100 if structures remain in the same location. Flood exposure is highest in western Alaska. Sea level rise projections suggest northern Alaska will see similar flood exposure levels by 2100 as currently experienced in western Alaska. This evaluation of record flood height, category, and history can be incorporated into hazard planning documents, providing more context for coastal flood exposure than previously existed for Alaska. This basic flood exposure method is transferable to other areas with similar mapping challenges. Identifying current and projected hazardous zones is essential to avoid unintentional development in floodplains and improve long-term safety.

Alaska↗

Iterative models for early detection of invasive species across spread pathways

Species distribution models can be used to direct early detection of invasive species, if they include proxies for invasion pathways. Due to the dynamic nature of invasion, these models violate assumptions of stationarity across space and time. To compensate for issues of stationarity, we iteratively update regionalized species distribution models annually for European gypsy moth ( Lymantria dispar dispar ) to target early detection surveys for the USDA APHIS gypsy moth program. We defined regions based on the distances from the invasion spread front where shifts in variable importance occurred and included models for the non-quarantine portion of the state of Maine, a short-range region, an intermediate region, and a long-range region. We considered variables that represented potential gypsy moth movement pathways within each region, including transportation networks, recreational activities, urban characteristics, and household movement data originating from gypsy moth infested areas (U.S. Postal Service address forwarding data). We updated the models annually, linked the models to an early detection survey design, and validated the models for the following year using predicted risk at new positive detection locations. Human-assisted pathways data, such as address forwarding, became increasingly important predictors of gypsy moth detection in the intermediate-range geographic model as more predictor data accumulated over time (relative importance = 5.9%, 17.36%, and 35.76% for 2015, 2016, and 2018, respectively). Receiver operating curves showed increasing performance for iterative annual models (area under the curve (AUC) = 0.63, 0.76, and 0.84 for 2014, 2015, and 2016 models, respectively), and boxplots of predicted risk each year showed increasing accuracy and precision of following year positive detection locations. The inclusion of human-assisted pathway predictors combined with the strategy of iterative modeling brings significant advantages to targeting early detection of invasive species. We present the first published example of iterative species distribution modeling for invasive species in an operational context.

Minnesota, Wisconsin, Illinois, Indiana, Ohio, Wes↗

The role of phosphorus and nitrogen on chlorophyll a: Evidence from hundreds of lakes

The effect of nutrients on phytoplankton biomass in lakes continues to be a subject of debate by aquatic scientists. However, determining whether or not chlorophyll a (CHL) is limited by phosphorus (P) and/or nitrogen (N) is rarely considered using a probabilistic method in studies of hundreds of lakes across broad spatial extents. Several studies have applied a unified CHL-nutrient relationship to determine nutrient limitation, but pose a risk of ecological fallacy because they neglect spatial heterogeneity in ecological contexts. To examine whether or not CHL is limited by P, N, or both nutrients in hundreds of lakes and across diverse ecological settings, a probabilistic machine learning method, Bayesian Network, was applied. Spatial heterogeneity in ecological context was accommodated by the probabilistic nature of the results. We analyzed data from 1382 lakes in 17 US states to evaluate the cause-effect relationships between CHL and nutrients. Observations of CHL, total phosphorus (TP), and total nitrogen (TN) were discretized into three trophic states (oligo-mesotrophic, eutrophic, and hypereutrophic) to train the model. We found that although both nutrients were related to CHL trophic state, TP was more related to CHL than TN, especially under oligo-mesotrophic and eutrophic CHL conditions. However, when the CHL trophic state was hypereutrophic, both TP and TN were important. These results provide additional evidence that P-limitation is more likely under oligo-mesotrophic or eutrophic CHL conditions and that co-limitation of P and N occurs under hypereutrophic CHL conditions. We also found a decreasing pattern of the TN/TP ratio with increasing CHL concentrations, which might be a key driver for the role change of nutrients. Previous work performed at smaller scales support our findings, indicating potential for extension of our findings to other regions. Our findings enhance the understanding of nutrient limitation at macroscales and revealed that the current debate on the limiting nutrient might be caused by failure to consider CHL trophic state. Our findings also provide prior information for the site-specific eutrophication management of unsampled or data-limited lakes.

Water Research↗

Community clusters of tsunami vulnerability in the US Pacific Northwest

Many coastal communities throughout the world are threatened by local (or near-field) tsunamis that could inundate low-lying areas in a matter of minutes after generation. Although the hazard and sustainability literature often frames vulnerability conceptually as a multidimensional issue involving exposure, sensitivity, and resilience to a hazard, assessments often focus on one element or do not recognize the hazard context. We introduce an analytical framework for describing variations in population vulnerability to tsunami hazards that integrates ( i ) geospatial approaches to identify the number and characteristics of people in hazard zones, ( ii ) anisotropic path distance models to estimate evacuation travel times to safety, and ( iii ) cluster analysis to classify communities with similar vulnerability. We demonstrate this approach by classifying 49 incorporated cities, 7 tribal reservations, and 17 counties from northern California to northern Washington that are directly threatened by tsunami waves associated with a Cascadia subduction zone earthquake. Results suggest three primary community groups: ( i ) relatively low numbers of exposed populations with varied demographic sensitivities, ( ii ) high numbers of exposed populations but sufficient time to evacuate before wave arrival, and ( iii ) moderate numbers of exposed populations but insufficient time to evacuate. Results can be used to enhance general hazard-awareness efforts with targeted interventions, such as education and outreach tailored to local demographics, evacuation training, and/or vertical evacuation refuges.

California, Oregon, Washington↗

Hydrodynamics structure plankton communities and interactions in a freshwater tidal estuary

Drivers of phytoplankton and zooplankton dynamics vary spatially and temporally in estuaries due to variation in hydrodynamic exchange and residence time, complicating efforts to understand controls on food web productivity. We conducted approximately monthly (2012–2019; n = 74) longitudinal sampling at 10 fixed stations along a freshwater tidal terminal channel in the San Francisco Estuary, California, characterized by seaward to landward gradients in water residence time, turbidity, nutrient concentrations, and plankton community composition. We used multivariate autoregressive state space (MARSS) models to quantify environmental (abiotic) and biotic controls on phytoplankton and mesozooplankton biomass. The importance of specific abiotic drivers (e.g., water temperature, turbidity, nutrients) and trophic interactions differed significantly among hydrodynamic exchange zones with different mean residence times. Abiotic drivers explained more variation in phytoplankton and zooplankton dynamics than a model including only trophic interactions, but individual phytoplankton–zooplankton interactions explained more variation than individual abiotic drivers. Interactions between zooplankton and phytoplankton were strongest in landward reaches with the longest residence times and the highest zooplankton biomass. Interactions between cryptophytes and both copepods and cladocerans were stronger than interactions between bacillariophytes (diatoms) and zooplankton taxa, despite contributing less biovolume in all but the most landward reaches. Our results demonstrate that trophic interactions and their relative strengths vary in a hydrodynamic context, contributing to food web heterogeneity within estuaries at spatial scales smaller than the freshwater to marine transition.

California↗

Structured decision making as a proactive approach to dealing with sea level rise in Florida

Sea level rise (SLR) projections along the coast of Florida present an enormous challenge for management and conservation over the long term. Decision makers need to recognize and adopt strategies to adapt to the potentially detrimental effects of SLR. Structured decision making (SDM) provides a rigorous framework for the management of natural resources. The aim of SDM is to identify decisions that are optimal with respect to management objectives and knowledge of the system. Most applications of SDM have assumed that the managed systems are governed by stationary processes. However, in the context of SLR it may be necessary to acknowledge that the processes underlying managed systems may be non-stationary, such that systems will be continuously changing. Therefore, SLR brings some unique considerations to the application of decision theory for natural resource management. In particular, SLR is expected to affect each of the components of SDM. For instance, management objectives may have to be reconsidered more frequently than under more stable conditions. The set of potential actions may also have to be adapted over time as conditions change. Models have to account for the non-stationarity of the modeled system processes. Each of the important sources of uncertainty in decision processes is expected to be exacerbated by SLR. We illustrate our ideas about adaptation of natural resource management to SLR by modeling a non-stationary system using a numerical example. We provide additional examples of an SDM approach for managing species that may be affected by SLR, with a focus on the endangered Florida manatee.

Florida↗

Landscape connectivity planning for adaptation to future climate and land-use change

Purpose of Review We examined recent literature on promoting habitat connectivity in the context of climate change (CC) and land-use change (LUC). These two global change forcings have wide-reaching ecological effects that are projected to worsen in the future. Improving connectivity is a common adaptation strategy, but CC and LUC can also degrade planned connections, potentially reducing their effectiveness. We synthesize advances in connectivity design approaches, identify challenges confronted by researchers and practitioners, and offer suggestions for future research. Recent Findings Recent studies incorporated future CC into connectivity design more often than LUC and rarely considered the two drivers jointly. When considering CC, most studies have focused on relatively broad spatial and temporal extents and have included either species-based targets or coarse-filter targets like geodiversity and climate gradients. High levels of uncertainty about future LUC and lack of consistent, readily available model simulations are likely hindering its inclusion in connectivity modeling. This high degree of uncertainty extends to efforts to jointly consider future CC and LUC. Summary We argue that successful promotion of connectivity as a means to adapt to CC and LUC will depend on (1) the velocity of CC, (2) the velocity of LUC, and (3) the degree of existing landscape fragmentation. We present a new conceptual framework to assist in identifying connectivity networks given these three factors. Given the high uncertainty associated with future CC and LUC, incorporating insights from decision science into connectivity planning will facilitate the development of more robust adaptation strategies.

Current Landscape Ecology Reports↗

Long-term plant responses to climate are moderated by biophysical attributes in a North American desert

Recent elevated temperatures and prolonged droughts in many already water-limited regions throughout the world, including the southwestern U.S., are likely to intensify according to future climate-model projections. This warming and drying can negatively affect perennial vegetation and lead to the degradation of ecosystem properties. To better understand these detrimental effects, we formulate a conceptual model of dryland ecosystem vulnerability to climate change that integrates hypotheses on how plant species will respond to increases in temperature and drought, including how plant responses to climate are modified by landscape, soil, and plant attributes that are integral to water availability and use. We test the model through a synthesis of fifty years of repeat measurements of perennial plant species cover in large permanent plots across the Mojave Desert, one of the most water-limited ecosystems in North America. Plant species ranged in their sensitivity to precipitation in different seasons, capacity to increase in cover with high precipitation, and resistance to decrease in cover with low precipitation. Our model successfully explains how plant responses to climate are modified by biophysical attributes in the Mojave Desert. For example, deep-rooted plants were not as vulnerable to drought on soils that allowed for deep water percolation, whereas shallow-rooted plants were better buffered from drought on soils that promoted water retention near the surface. Synthesis. Our results emphasize the importance of understanding climate-vegetation relationships in the context of biophysical attributes that influence water availability and provide an important forecast of climate-change effects, including plant mortality and land degradation in dryland regions throughout the world.

California, Nevada↗

Exploring extensions to multi-state models with multiple unobservable states

Many biological systems include a portion of the target population that is unobservable during certain life history stages. Transition to and from an unobservable state may be of primary interest in many ecological studies and such movements are easily incorporated into multi-state models. Several authors have investigated properties of open-population multi-state mark-recapture models with unobservable states, and determined the scope and constraints under which parameters are identifiable (or, conversely, are redundant), but only in the context of a single observable and a single unobservable state (Schmidt et al. 2002; Kendall and Nichols 2002; Schaub et al. 2004; Kendall 2004). Some of these constraints can be relaxed if data are collected under a version of the robust design (Kendall and Bjorkland 2001; Kendall and Nichols 2002; Kendall 2004; Bailey et al. 2004), which entails >1 capture period per primary period of interest (e.g., 2 sampling periods within a breeding season). The critical assumption shared by all versions of the robust design is that the state of the individual (e.g. observable or unobservable) remains static for the duration of the primary period (Kendall 2004). In this paper, we extend previous work by relaxing this assumption to allow movement among observable states within primary periods while maintaining static observable or unobservable states. Stated otherwise, both demographic and geographic closure assumptions are relaxed, but all individuals are either observable or unobservable within primary periods. Within these primary periods transitions are possible among multiple observable states, but transitions are not allowed among the corresponding unobservable states. Our motivation for this work is exploring potential differences in population parameters for pond-breeding amphibians, where the quality of habitat surrounding the pond is not spatially uniform. The scenario is an example of a more general case where individuals move between habitats both during the breeding season (within primary periods; transitions among observable states only) and during the non-breeding season (between primary periods; transitions between observable and unobservable states). Presumably, habitat quality affects demographic parameters (e.g. survival and breeding probabilities). Using this model we are able to test this prediction for amphibians and determine if individuals move to more favorable habitats to increase survival and breeding probabilities.

Book chapter↗

An ecosystem-scale model of PFAS dynamics in stream-to-riparian food webs

Per- and polyfluoroalkyl substances (PFAS) are widespread contaminants in aquatic ecosystems, where they bioaccumulate and trophically transfer through food webs. We derived an ecosystem-scale model assessing Σ 12 PFAS partitioning, bioaccumulation by larval aquatic insects, bioamplification by adult aquatic insects, and trophic transfer from aquatic insects to riparian spiders using data collected across five streams in a mildly impacted watershed. Partitioning involved the greatest PFAS enrichments (range in posterior median log 10 k d values = 1.5–2.1), with lesser concentration increases from particulates to larval aquatic insects and from larval to adult aquatic insects, and Σ 12 PFAS concentration decreases from adult aquatic insects to spiders. Among the 12 compounds, PFOS had the largest proportional contribution to Σ 12 PFAS concentrations for all sample types, with consistently increasing concentrations from surface water to adult aquatic insects. Σ 12 PFAS concentrations (5.4–51 ppb wet weight), body burdens (0.44–5.2 ng per individual), and bioamplification factors (0.15–4.9) differed considerably among five common aquatic insect taxa. This study presents a robust modeling framework for PFAS trophodynamics and offers insights into the biological controls that contribute to the context dependency of PFAS at the interfaces of aquatic and terrestrial food webs.

Connecticut, Massachusetts↗