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At least 145 records · Page 8Linked to original sources

Using time-dependent models to investigate body condition and growth rate of the giant gartersnake

Identifying links between phenotypic attributes and fitness is a primary goal of reproductive ecology. Differences in within-year patterns of body condition between sexes of gartersnakes in relation to reproduction and growth are not fully understood. We conducted an 11-year field study of body condition and growth rate of the giant gartersnake Thamnophis gigas across 13 study areas in the Central Valley of California, USA. We developed a priori mixed effects models of body condition index (BCI), which included covariates of time, sex and snout-vent length and reported the best-approximating models using an information theoretic approach. Also, we developed models of growth rate index (GRI) using covariates of sex and periods based on reproductive behavior. The largest difference in BCI between sexes, as predicted by a non-linear (cubic) time model, occurred during the mating period when female body condition (0.014??0.001 se) was substantially greater than males (-0.027??0.002 se). Males likely allocated energy to search for mates, while females likely stored energy for embryonic development. We also provided evidence that males use more body energy reserves than females during hibernation, perhaps because of different body temperatures between sexes. We found GRI of male snakes was substantially lower during the mating period than during a non-mating period, which indicated that a trade-off existed between searching for mates and growth. These findings contribute to our understanding of snake ecology in a Mediterranean climate. ?? 2009 The Zoological Society of London.

Journal of Zoology↗

Survival of radio-implanted drymarchon couperi (Eastern Indigo Snake) in relation to body size and sex

Drymarchon couperi (eastern indigo snake) has experienced population declines across its range primarily as a result of extensive habitat loss, fragmentation, and degradation. Conservation efforts for D. couperi have been hindered, in part, because of informational gaps regarding the species, including a lack of data on population ecology and estimates of demographic parameters such as survival. We conducted a 2- year radiotelemetry study of D. couperi on Fort Stewart Military Reservation and adjacent private lands located in southeastern Georgia to assess individual characteristics associated with probability of survival. We used known-fate modeling to estimate survival, and an information-theoretic approach, based on a priori hypotheses, to examine intraspecific differences in survival probabilities relative to individual covariates (sex, size, size standardized by sex, and overwintering location). Annual survival in 2003 and 2004 was 0.89 (95% CI = 0.73-0.97, n = 25) and 0.72 (95% CI = 0.52-0.86; n = 27), respectively. Results indicated that body size, standardized by sex, was the most important covariate determining survival of adult D. couperi, suggesting lower survival for larger individuals within each sex. We are uncertain of the mechanisms underlying this result, but possibilities may include greater resource needs for larger individuals within each sex, necessitating larger or more frequent movements, or a population with older individuals. Our results may also have been influenced by analysis limitations because of sample size, other sources of individual variation, or environmental conditions. ?? 2009 by The Herpetologists' League, Inc.

Herpetologica↗

Signals of impending change

Society has an increasing awareness that there are finite limits to what we can expect the planet to absorb and still provide goods and services at current rates 1 . Both historical reconstructions and contemporary events continue to remind us that ecological regime changes are often abrupt rather than gradual. This reality motivates researchers who seek to discover leading indicators for impending ecosystem change. Berdugo et al . 2 report an important advance in our ability to anticipate the conversion of arid lands from self-organized, self-maintaining and productive ecosystems, to a state characterized by disorganization and low functionality. Such conversions have important implications for our understanding of ‘desertification’ — which is a shift from arid to desert-like conditions. Theoretical studies have suggested that patterns in the patchiness of vegetation might indicate how close a system is to making an abrupt change to desert-like conditions 3 , 4 , 5 . Empirical studies, however, have tended to show instead that simply the total cover of vegetation, rather than its arrangement, often foretells the state of the system 4 , 5 , 6 , 7 , 8 , 9 . Berdugo et al . 2 combine these competing ideas into one integrated perspective. They show how major environmental drivers, such as aridity, influence both vegetation cover and patchiness, as well as where self-organizing, stabilizing forces in the vegetation are likely to be found.

Nature Ecology & Evolution↗

A global analysis of traits predicting species sensitivity to habitat fragmentation

Aim Elucidating patterns in species responses to habitat fragmentation is an important focus of ecology and conservation, but studies are often geographically restricted, taxonomically narrow or use indirect measures of species vulnerability. We investigated predictors of species presence after fragmentation using data from studies around the world that included all four terrestrial vertebrate classes, thus allowing direct inter-taxonomic comparison. Location World-wide. Methods We used generalized linear mixed-effect models in an information theoretic framework to assess the factors that explained species presence in remnant habitat patches (3342 patches; 1559 species, mostly birds; and 65,695 records of patch-specific presence–absence). We developed a novel metric of fragmentation sensitivity, defined as the maximum rate of change in probability of presence with changing patch size (‘Peak Change’), to distinguish between general rarity on the landscape and sensitivity to fragmentation per se. Results Size of remnant habitat patches was the most important driver of species presence. Across all classes, habitat specialists, carnivores and larger species had a lower probability of presence, and those effects were substantially modified by interactions. Sensitivity to fragmentation (measured by Peak Change) was influenced primarily by habitat type and specialization, but also by fecundity, life span and body mass. Reptiles were more sensitive than other classes. Grassland species had a lower probability of presence, though sample size was relatively small, but forest and shrubland species were more sensitive. Main conclusions Habitat relationships were more important than life-history characteristics in predicting the effects of fragmentation. Habitat specialization increased sensitivity to fragmentation and interacted with class and habitat type; forest specialists and habitat-specific reptiles were particularly sensitive to fragmentation. Our results suggest that when conservationists are faced with disturbances that could fragment habitat they should pay particular attention to specialists, particularly reptiles. Further, our results highlight that the probability of presence in fragmented landscapes and true sensitivity to fragmentation are predicted by different factors.

Global Ecology and Biogeography↗

Parasites in food webs: the ultimate missing links

Parasitism is the most common consumer strategy among organisms, yet only recently has there been a call for the inclusion of infectious disease agents in food webs. The value of this effort hinges on whether parasites affect food-web properties. Increasing evidence suggests that parasites have the potential to uniquely alter food-web topology in terms of chain length, connectance and robustness. In addition, parasites might affect food-web stability, interaction strength and energy flow. Food-web structure also affects infectious disease dynamics because parasites depend on the ecological networks in which they live. Empirically, incorporating parasites into food webs is straightforward. We may start with existing food webs and add parasites as nodes, or we may try to build food webs around systems for which we already have a good understanding of infectious processes. In the future, perhaps researchers will add parasites while they construct food webs. Less clear is how food-web theory can accommodate parasites. This is a deep and central problem in theoretical biology and applied mathematics. For instance, is representing parasites with complex life cycles as a single node equivalent to representing other species with ontogenetic niche shifts as a single node? Can parasitism fit into fundamental frameworks such as the niche model? Can we integrate infectious disease models into the emerging field of dynamic food-web modelling? Future progress will benefit from interdisciplinary collaborations between ecologists and infectious disease biologists.

Ecology Letters↗

Testing prediction accuracy in short-term ecological studies

Applied ecology is based on an assumption that a management action will result in a predicted outcome. Testing the prediction accuracy of ecological models is the most powerful way of evaluating the knowledge implicit in this cause-effect relationship, however, the prevalence of predictive modeling and prediction testing are spreading slowly in ecology. The challenge of prediction testing is particularly acute for small-scale studies, because withholding data for prediction testing (e.g., via k -fold cross validation) can reduce model precision. However, by necessity small-scale studies are common. We use one such study that explored small mammal abundance along an elevational gradient to test prediction accuracy of models with varying degrees of information content. For each of three small mammal species, we conducted 5000 iterations of the following process: (1) randomly selected 75 % of the data to develop generalized linear models of species abundance that used detailed site measurements as covariates, (2) used an information theoretic approach to compare the top model with detailed covariates to habitat type-only and null models constructed with the same data, (3) tested those models’ ability to predict the 25 % of the randomly withheld data, and (4) evaluated prediction accuracy with a quadratic loss function. Detailed models fit the model-evaluation data best but had greater expected prediction error when predicting out-of-sample data relative to the habitat type models. Relationships between species and detailed site variables may be evident only within the framework of explicitly hierarchical analyses. We show that even with a small but relatively typical dataset ( n = 28 sampling locations across 125 km over two years), researchers can effectively compare models with different information content and measure models’ predictive power, thus evaluating their own ecological understanding and defining the limits of their inferences. Identifying the appropriate scope of inference through prediction testing is ecologically valuable and is attainable even with small datasets.

Maine, New Hampshire↗

Foraging of wading birds on a patchy landscape: Simulating effects of social information, interference competition, and patch selection on prey intake and individual distribution

Foragers on patchy landscapes must acquire sufficient resources despite uncertainty in the location and amount of the resources. Optimal Foraging Theory posits that foragers deal with this uncertainty by using strategies that optimize resource intake within foraging periods. For species such as wading birds, this optimization is closely linked to their survival and reproductive success. Understanding the influence of patch selection on individual resource intake and foraging distribution is therefore crucial. In this study, we simulated how resource distribution, interference competition, and social cues—such as aggregation behaviors—influence resource intake and foraging spatial distribution. We employed an individual-based model simulating wading bird foraging behaviors, with 900 individuals simultaneously foraging across a landscape with unknown resource distribution. Birds employed one of three patch-finding strategies: random, cue-searching, or hybrid, which uses both searching strategies. Each bird decided whether to remain in a patch based on a prey density threshold. We compared the daily resource intake and foraging distribution of birds across different modeled patch-finding strategies, resource distribution patterns, and the presence or absence of interference competition. Wading birds exhibiting aggregation behavior displayed increased intake rates when resources were concentrated and interference minimal. Aggregation behavior led to a closer match with the ideal free distribution when the prey density threshold was optimal. These findings provide theoretical support that aggregation behavior is effective in scenarios where resources are concentrated in a few patches, social cues are used by relatively few individuals, and interference competition is limited.

Ecological Modelling↗

Increasing accuracy of dispersal kernels in grid-based population models

Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels ( σ > 10 cells), the total kernel error was <10 −11 compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10 −11 and invasion time error to <5%.

Ecological Modelling↗

Evaluating early-warning indicators of critical transitions in natural aquatic ecosystems

Ecosystems can show sudden and persistent changes in state despite only incremental changes in drivers. Such critical transitions are difficult to predict, because the state of the system often shows little change before the transition. Early-warning indicators (EWIs) are hypothesized to signal the loss of system resilience and have been shown to precede critical transitions in theoretical models, paleo-climate time series, and in laboratory as well as whole lake experiments. The generalizability of EWIs for detecting critical transitions in empirical time series of natural aquatic ecosystems remains largely untested, however. Here we assessed four commonly used EWIs on long-term datasets of five freshwater ecosystems that have experienced sudden, persistent transitions and for which the relevant ecological mechanisms and drivers are well understood. These case studies were categorized by three mechanisms that can generate critical transitions between alternative states: competition, trophic cascade, and intraguild predation. Although EWIs could be detected in most of the case studies, agreement among the four indicators was low. In some cases, EWIs were detected considerably ahead of the transition. Nonetheless, our results show that at present, EWIs do not provide reliable and consistent signals of impending critical transitions despite using some of the best routinely monitored freshwater ecosystems. Our analysis strongly suggests that a priori knowledge of the underlying mechanisms driving ecosystem transitions is necessary to identify relevant state variables for successfully monitoring EWIs.

Proceedings of the National Academy of Sciences of↗

Integrating growth and survival models for flexible estimation of size-dependent survival in a cryptic, endangered snake

Estimates of demographic rates for animal populations and individuals have many applications for ecological and conservation research. In many animals, survival is size-dependent, but estimating the form of the size–survival relationship presents challenges. For elusive species with low recapture rates, individuals’ size will be unknown at many points in time. Integrating growth and capture–mark–recapture models in a Bayesian framework empowers researchers to impute missing size data, with uncertainty, and include size as a covariate of survival, capture probability, and presence on-site. If there is no theoretical expectation for the shape of the size–survival relationship, spline functions can allow for fitting flexible, data-driven estimates. We use long-term capture–mark–recapture data from the endangered San Francisco gartersnake ( Thamnophis sirtalis tetrataenia ) to fit an integrated growth–survival model. Growth models showed that females reach longer asymptotic lengths than males and that the magnitude of sexual size dimorphism differed among populations. The capture probability and availability of San Francisco gartersnakes for capture increased with snout–vent length. The survival rate of female snakes exhibits a nonlinear relationship with snout–vent length (SVL), with survival flat between 300 mm and 550 mm SVL before decreasing for females between 550 mm and 700 mm SVL. For male snakes, survival decreased for adult males >550 mm SVL. The survival rates of the smallest and largest San Francisco gartersnakes were highly uncertain because recapture rates were very low for these sizes. By integrating growth and survival models and using penalized splines, we found support for size-dependent survival in San Francisco gartersnakes. Our results have applications for devising management activities for this endangered subspecies, and our methods could be applied broadly to the study of size-dependent demography among animals.

California↗

Preface

Despite more than 50 years of research into the human dimensions of recreational f isheries, there is no textbook to present the theoretical grounding, operationalisation, and interpretation of the most elemental social components involved in fisheries management – namely, outcomes and trade-offs, behaviours (and antecedents or predictors of it), and the relationships among actors (fishers, f isher groups, managers, and management organisations). The objective of this edited volume is to reduce this knowledge gap. The book comprises four parts: (I) recreational fisheries as social-ecological systems, (II) disciplinary views of f ishers’ behaviours and outcomes, (III) engagement of fishers to support effective social science, and (IV) interdisciplinary integration for recreational fisheries management. Part I provides the general motivation for an interdisciplinary approach to understand recreational fisheries as coupled systems. Part II provides the foundations of various social science disciplines and highlights linkages and differences in the underlying theories and concepts used. Part III describes various qualitative and quantitative methods to study the social aspects of recreational fisheries in more detail, and Part IV suggests approaches to achieve standardisation and integration of different data streams, including how to link social and ecological data. The book chapters have been written by leading scholars of recreational fisheries science, involving social and economic scientists, political ecologists, and fisheries ecologists with a tradition in either applying human dimensions or working towards integration.

Book chapter↗

Learning complex spatial dynamics of wildlife diseases with machine learning-guided partial differential equations

Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.

Environmental Data Science↗

Egg size scales negatively with system size in a periodic fish species

Optimal egg size theory implies that female organisms balance between fecundity and individual offspring investment according to their environment. Past interspecific studies suggest that fishes in large marine systems generally produce smaller eggs than those in small freshwater systems. We tested whether intraspecific egg size variation reflected a similar pattern by comparing egg size among yellow perch ( Perca flavescens ) populations inhabiting a range of system sizes. In 2018, 2019, and 2023, we collected yellow perch egg samples from 12 locations in systems ranging in surface area from 37 to 5,390,492 ha. First, we found that egg diameter significantly increased with maternal total length in five of eight individually tested populations. After accounting for these maternal effects, we found a significant interaction, where females inhabiting larger lakes, such as the main basins of Lakes Erie and Michigan, produced smaller eggs than those in smaller inland lakes, and the greatest differences were demonstrated among females of greater total length. This egg size variation in the largest females is consistent with interspecific egg size comparisons between marine and freshwater fishes. However, by examining a single species across vastly different environments, we were able to support theoretical expectations that maternal investment in offspring should vary with environmental conditions controlling early-life resource acquisition and competition.

Ecology and Evolution↗

Spatial early warning signals in a lake manipulation

Rapid changes in state have been documented for many of Earth's ecosystems. Despite a growing toolbox of methods for detecting declining resilience or early warning indicators (EWIs) of ecosystem transitions, these methods have rarely been evaluated in whole-ecosystem trials using reference ecosystems. In this study, we experimentally tested EWIs of cyanobacteria blooms based on changes in the spatial structure of a lake. We induced a cyanobacteria bloom by adding nutrients to an experimental lake and mapped fine-resolution spatial patterning of cyanobacteria using a mobile sensor platform. Prior to the bloom, we detected theoretically predicted spatial EWIs based on variance and spatial autocorrelation, as well as a new index based on the extreme values. Changes in EWIs were not discernible in an unenriched reference lake. Despite the fluid environment of a lake where spatial heterogeneity driven by biological processes may be overwhelmed by physical mixing, spatial EWIs detected an approaching bloom suggesting the utility of spatial metrics for signaling ecological thresholds.

Ecosphere↗

Inducible defenses in food webs: Chapter 3.4

This chapter reviews the predicted effects of induced defenses on trophic structure and two aspects of stability, &ldquo;local&rdquo; stability and persistence, as well as presenting novel results on a third, resilience. Food webs are structures of populations in a given location organized according to their predator&ndash;prey interactions. Interaction strengths and, therefore, prey defenses are generally recognized as important ecological factors affecting food webs. Despite this, surprisingly, little light has been shed on the food web-level consequences of inducible defenses. Inducible defenses occur in many taxa in both terrestrial and aquatic food webs. They include refuge use, reduced activity, adaptive life history changes, the production of toxins, synomones and extrafloral nectar, and the formation of colonies, helmets, thorns, or spines. In the chapter, theoretical results for the effects of inducible defenses on trophic structure and the three aspects of stability are reviewed. This is done, in part, using bifurcation analysis&mdash;a type of analysis that is applied to nonlinear dynamic systems described by a set of ordinary differential or difference equations. The work presented in the chapter suggests that heterogeneity, as caused by induced defenses in prey species, has major effects on the functioning of food webs. Inducible defenses occur in many species in both aquatic and terrestrial systems, and theoretical work indicates they have major effects on important food web properties such as trophic structure, local stability, persistence, and resilience.

Book chapter↗

Understanding the genetic effects of recent habitat fragmentation in the context of evolutionary history: Phylogeography and landscape genetics of a southern California endemic Jerusalem cricket (Orthoptera: Stenopelmatidae: Stenopelmatus)

Habitat loss and fragmentation due to urbanization are the most pervasive threats to biodiversity in southern California. Loss of habitat and fragmentation can lower migration rates and genetic connectivity among remaining populations of native species, reducing genetic variability and increasing extinction risk. However, it may be difficult to separate the effects of recent anthropogenic fragmentation from the genetic signature of prehistoric fragmentation due to previous natural geological and climatic changes. To address these challenges, we examined the phylogenetic and population genetic structure of a flightless insect endemic to cismontane southern California, Stenopelmatus 'mahogani' (Orthoptera: Stenopelmatidae). Analyses of mitochondrial DNA sequence data suggest that diversification across southern California began during the Pleistocene, with most haplotypes currently restricted to a single population. Patterns of genetic divergence correlate with contemporary urbanization, even after correcting for (geographical information system) GIS-based reconstructions of fragmentation during the Pleistocene. Theoretical simulations confirm that contemporary patterns of genetic structure could be produced by recent urban fragmentation using biologically reasonable assumptions about model parameters. Diversity within populations was positively correlated with current fragment size, but not prehistoric fragment size, suggesting that the effects of increased drift following anthropogenic fragmentation are already being seen. Loss of genetic connectivity and diversity can hinder a population's ability to adapt to ecological perturbations commonly associated with urbanization, such as habitat degradation, climatic changes and introduced species. Consequently, our results underscore the importance of preserving and restoring landscape connectivity for long-term persistence of low vagility native species. Journal compilation ?? 2006 Blackwell Publishing Ltd.

Molecular Ecology↗

The ODD protocol: A review and first update

The ‘ODD’ (Overview, Design concepts, and Details) protocol was published in 2006 to standardize the published descriptions of individual-based and agent-based models (ABMs). The primary objectives of ODD are to make model descriptions more understandable and complete, thereby making ABMs less subject to criticism for being irreproducible. We have systematically evaluated existing uses of the ODD protocol and identified, as expected, parts of ODD needing improvement and clarification. Accordingly, we revise the definition of ODD to clarify aspects of the original version and thereby facilitate future standardization of ABM descriptions. We discuss frequently raised critiques in ODD but also two emerging, and unanticipated, benefits: ODD improves the rigorous formulation of models and helps make the theoretical foundations of large models more visible. Although the protocol was designed for ABMs, it can help with documenting any large, complex model, alleviating some general objections against such models.

Ecological Modelling↗

Cgsim: An R package for simulation of population genetics for conservation and management applications

Wildlife conservation and management increasingly considers genetic information to plan, understand and evaluate implemented population interventions. These actions commonly include conservation translocation and population reductions through removals. Change in genetic variation in response to management actions can be unintuitive due to the influence of multiple interacting drivers (e.g. genetic drift, life history traits, environmental stochasticity). Simulation is an excellent tool to understand the predicted consequences of different proposed or implemented actions. However, the genetic simulators that are robust to a wide variety of life history traits also have a steep learning curve to appropriately parameterize common management actions. To fill this gap, we have developed cgsim, an R package for simulating the genetic consequences of common management interventions for populations of wildlife species. We developed a set of functions to specifically understand the effects of four main aspects of managing small, declining or isolated populations: loss of genetic diversity to drift, augmenting existing populations (e.g. translocation), population reduction through targeted removals and population catastrophes driven by stochastic extrinsic forces. Our single population simulation model is individual-based, and flexible to a range of life history traits. Here we validate cgsim through comparison of simulations to theoretical expectations of genetic diversity loss and illustrate its applied utility by focusing on a recently published empirical example for the Greater Sage-Grouse. Cgsim is available as an R package at: https://doi.org/10.5066/P1BXBEXJ .

Molecular Ecology Resources↗