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At least 37 records · Page 2Linked to original sources
USGS2019

Negative frequency-dependent foraging behaviour in a generalist herbivore (Alces alces) and its stabilizing influence on food-web dynamics

1. Resource selection is widely appreciated to be context‐dependent and shaped by both biological and abiotic factors. However, few studies have empirically assessed the extent to which selective foraging behaviour is dynamic and varies in response to environmental conditions for free‐ranging animal populations. 2. Here, we assessed the extent that forage selection fluctuated in response to different environmental conditions for a free‐ranging herbivore, moose (Alces alces), in Isle Royale National Park, over a 10‐year period. More precisely, we assessed how moose selection for coniferous versus deciduous forage in winter varied between geographic regions and in relation to (a) the relative frequency of forage types in the environment (e.g. frequency‐dependent foraging behaviour), (b) moose abundance, (c) predation rate (by grey wolves) and (d) snow depth. These factors are potentially important for their influence on the energetics of foraging. We also built a series of food‐chain models to assess the influence of dynamic foraging strategies on the stability of food webs. 3. Our analysis indicates that moose exhibited negative frequency dependence, by selectively exploiting rare resources. Frequency‐dependent foraging was further mediated by density‐dependent processes, which are likely to be predation, moose abundance or some combination of both. In particular, frequency dependence was weaker in years when predation risk was high (i.e. when the ratio of moose to wolves was relatively low). Selection for conifers was also slightly weaker during deep snow years. 4. The food‐chain analysis indicates that the type of frequency‐dependent foraging strategy exhibited by herbivores had important consequences for the stability of ecological communities. In particular, the dynamic foraging strategy that we observed in the empirical analysis (i.e. negative frequency dependence being mediated by density‐dependent processes) was associated with more stable food web dynamics compared to fixed foraging strategies. 5. The results of this study indicated that forage selection is a complex ecological process, varying in response to both biological (predation and moose density) and abiotic factors (snow depth) and over relatively small spatial scales (between regions). This study also provides a useful framework for assessing the influence of other aspects of foraging behaviour on the stability of food web dynamics.

Michigan↗
USGS2023

Evidence for density-dependent effects on body composition of a large omnivore in a changing Greater Yellowstone Ecosystem

Understanding the density-dependent processes that drive population demography in a changing world is critical in ecology, yet measuring performance–density relationships in long-lived mammalian species demands long-term data, limiting scientists' ability to observe such mechanisms. We tested performance–density relationships for an opportunistic omnivore, grizzly bears ( Ursus arctos , Linnaeus, 1758) in the Greater Yellowstone Ecosystem, with estimates of body composition (lean body mass and percent body fat) serving as indicators of individual performance over two decades (2000–2020) during which time pronounced environmental changes have occurred. Several high-calorie foods for grizzly bears have mostly declined in recent decades (e.g., whitebark pine [ Pinus albicaulis , Engelm, 1863]), while increasing human impacts from recreation, development, and long-term shifts in temperatures and precipitation are altering the ecosystem. We hypothesized that individual lean body mass declines as population density increases (H1), and that this effect would be more pronounced among growing individuals (H2). We also hypothesized that omnivory helps grizzly bears buffer energy intake from changing foods, with body fat levels being independent from population density and environmental changes (H3). Our analyses showed that individual lean body mass was negatively related to population density, particularly among growing-age females, supporting H1 and partially H2. In contrast, population density or sex had little effect on body fat levels and rate of accumulation, indicating that sufficient food resources were available on the landscape to accommodate successful use of shifting food sources, supporting H3. Our results offer important insights into ecological feedback mechanisms driving individual performances within a population undergoing demographic and ecosystem-level changes. However, synergistic effects of continued climate change and increased human impacts could lead to more extreme changes in food availability and affect observed population resilience mechanisms. Our findings underscore the importance of long-term studies in protected areas when investigating complex ecological relationships in an increasingly anthropogenic world.

Idaho, Montana, Wyoming↗
USGS2021

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

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

Florida↗
USGS2015

Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24

The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.

Book chapter↗
USGS2011

Pathology and failure in the design and implementation of adaptive management

The conceptual underpinnings for adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex ecological systems as a result non-linear interactions among components and emergence, yet management decisions must still be made. The strength of adaptive management is in the recognition and confrontation of such uncertainty. Rather than ignore uncertainty, or use it to preclude management actions, adaptive management can foster resilience and flexibility to cope with an uncertain future, and develop safe to fail management approaches that acknowledge inevitable changes and surprises. Since its initial introduction, adaptive management has been hailed as a solution to endless trial and error approaches to complex natural resource management challenges. However, its implementation has failed more often than not. It does not produce easy answers, and it is appropriate in only a subset of natural resource management problems. Clearly adaptive management has great potential when applied appropriately. Just as clearly adaptive management has seemingly failed to live up to its high expectations. Why? We outline nine pathologies and challenges that can lead to failure in adaptive management programs. We focus on general sources of failures in adaptive management, so that others can avoid these pitfalls in the future. Adaptive management can be a powerful and beneficial tool when applied correctly to appropriate management problems; the challenge is to keep the concept of adaptive management from being hijacked for inappropriate use.

Journal of Environmental Management↗
USGS2012

More than a meal: integrating non-feeding interactions into food webs

Organisms eating each other are only one of many types of well documented and important interactions among species. Other such types include habitat modification, predator interference and facilitation. However, ecological network research has been typically limited to either pure food webs or to networks of only a few (<3) interaction types. The great diversity of non-trophic interactions observed in nature has been poorly addressed by ecologists and largely excluded from network theory. Herein, we propose a conceptual framework that organises this diversity into three main functional classes defined by how they modify specific parameters in a dynamic food web model. This approach provides a path forward for incorporating non-trophic interactions in traditional food web models and offers a new perspective on tackling ecological complexity that should stimulate both theoretical and empirical approaches to understanding the patterns and dynamics of diverse species interactions in nature.

Ecology Letters↗
USGS2026

Connecting and coordinating conservation action across landscapes through regional planning processes and syntheses

Modern threats to conservation are often global; however, relevant conservation decisions and actions typically occur within local jurisdictions. The socio-ecological complexity of these problems requires collaboration across large landscapes, diverse community interests, and geopolitical boundaries, yet a lack of interoperability of planning products among decision makers, jurisdictions, and objectives impedes collaboration. Here, we provide a working model for the collaborative, iterative development of a landscape conservation design (LCD) in the Midwest region of the United States, the Midwest Conservation Blueprint, and demonstrate its applicability to the coordination of voluntary conservation actions and investments across jurisdictional boundaries. We used spatial prioritization software to synthesize over 20 datasets to develop a basemap of priority lands and waters for conservation across a diverse set of societal and ecological values (e.g., water quality, biodiversity, recreation). The Midwest Conservation Blueprint is a living plan, updated annually based on improvements in underlying data, understanding of local conditions, and public input. Landscape-scale planning is not designed to replace local knowledge or supersede decision-making authorities. However, by synthesizing existing data that represent diverse socio-ecological values and planning at a broader scale, the Midwest Conservation Blueprint documents where there are shared priorities and opportunities for collaborative landscape conservation.

Midwest↗
USGS2012

Ecological impacts of non-native species

Non-native species are considered one of the greatest threats to freshwater biodiversity worldwide (Drake et al. 1989; Allen and Flecker 1993; Dudgeon et al. 2005). Some of the first hypotheses proposed to explain global patterns of amphibian declines included the effects of non-native species (Barinaga 1990; Blaustein and Wake 1990; Wake and Morowitz 1991). Evidence for the impact of non-native species on amphibians stems (1) from correlative research that relates the distribution or abundance of a species to that of a putative non-native species, and (2) from experimental tests of the effects of a non-native species on survival, growth, development or behaviour of a target species (Kats and Ferrer 2003). Over the past two decades, research on the effects of non-native species on amphibians has mostly focused on introduced aquatic predators, particularly fish. Recent research has shifted to more complex ecological relationships such as influences of sub-lethal stressors (e.g. contaminants) on the effects of non-native species (Linder et al. 2003; Sih et al. 2004), non-native species as vectors of disease (Daszak et al. 2004; Garner et al. 2006), hybridization between non-natives and native congeners (Riley et al. 2003; Storfer et al. 2004), and the alteration of food-webs by non-native species (Nystrom et al. 2001). Other research has examined the interaction of non-native species in terms of facilitation (i.e. one non-native enabling another to become established or spread) or the synergistic effects of multiple non-native species on native amphibians, the so-called invasional meltdown hypothesis (Simerloff and Von Holle 1999). Although there is evidence that some non-native species may interact (Ricciardi 2001), there has yet to be convincing evidence that such interactions have led to an accelerated increase in the number of non-native species and cumulative impacts are still uncertain (Simberloff 2006). Applied research on the control, eradication, and management of non-native species has only just begun but some promising results have already emerged (see below), giving hope to a very difficult conservation issue. This chapter provides an overview of the role of non-native species in amphibian declines and summarizes the current state of knowledge of non-native species that are known, or considered to be, a threat to amphibian species and populations. The biological and socio-economic issues of non-native species control are examined and brief case studies of successful eradication programmes are provided.

Book chapter↗
USGS2011

High throughput computing: a solution for scientific analysis

Public land management agencies continually face resource management problems that are exacerbated by climate warming, land-use change, and other human activities. As the U.S. Geological Survey (USGS) Fort Collins Science Center (FORT) works with managers in U.S. Department of the Interior (DOI) agencies and other federal, state, and private entities, researchers are finding that the science needed to address these complex ecological questions across time and space produces substantial amounts of data. The additional data and the volume of computations needed to analyze it require expanded computing resources well beyond single- or even multiple-computer workstations. To meet this need for greater computational capacity, FORT investigated how to resolve the many computational shortfalls previously encountered when analyzing data for such projects. Our objectives included finding a solution that would: harness existing Computer Processing Units (CPUs) when they're idle to run multiple jobs concurrently, which reduces the overall processing time without requiring additional hardware; offer an effective, centralized job-management system; handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses High Throughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

Report↗
USGS2018

Phylogeny and species traits predict bird detectability

Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.

Ecography↗
USGS2017

A new parameterization for integrated population models to document amphibian reintroductions

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog ( Rana pretiosa ) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010–2011 to 0.86 in 2012–2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data.

Ecological Applications↗
USGS2017

Decadal declines in avian herbivore reproduction: density-dependent nutrition and phenological mismatch in the Arctic

A full understanding of population dynamics depends not only on estimation of mechanistic contributions of recruitment and survival, but also knowledge about the ecological processes that drive each of these vital rates. The process of recruitment in particular may be protracted over several years, and can depend on numerous ecological complexities until sexually mature adulthood is attained. We addressed long-term declines (23 breeding seasons, 1992–2014) in the per capita production of young by both Ross's Geese ( Chen rossii ) and Lesser Snow Geese ( Chen caerulescens caerulescens ) nesting at Karrak Lake in Canada's central Arctic. During this period, there was a contemporaneous increase from 0.4 to 1.1 million adults nesting at this colony. We evaluated whether (1) density-dependent nutritional deficiencies of pre-breeding females or (2) phenological mismatch between peak gosling hatch and peak forage quality, inferred from NDVI on the brood-rearing areas, may have been behind decadal declines in the per capita production of goslings. We found that, in years when pre-breeding females arrived to the nesting grounds with diminished nutrient reserves, the proportional composition of young during brood-rearing was reduced for both species. Furthermore, increased mismatch between peak gosling hatch and peak forage quality contributed additively to further declines in gosling production, in addition to declines caused by delayed nesting with associated subsequent negative effects on clutch size and nest success. The degree of mismatch increased over the course of our study because of advanced vegetation phenology without a corresponding advance in Goose nesting phenology. Vegetation phenology was significantly earlier in years with warm surface air temperatures measured in spring (i.e., 25 May–30 June). We suggest that both increased phenological mismatch and reduced nutritional condition of arriving females were behind declines in population-level recruitment, leading to the recent attenuation in population growth of Snow Geese.

Ecology↗
USGS2026

Exploring management options for moose at their southern range limits considering growing disease risk

1. Populations of cold-adapted species are increasingly vulnerable along their low-latitude range limits due to shifting environmental conditions, biotic interactions, and anthropogenic pressures. Managing these populations is particularly challenging because of complex ecological dynamics, conflicting stakeholder interests, and decision-making under uncertainty. 2. We explored population growth (λ) of moose ( Alces alces ) under different hypothetical management scenarios, simulating combinations of five hypothetical harvest levels with three levels of disease impact. 3. Facing current disease, the population could support multiple levels of conservative harvest. Under elevated levels of disease-caused mortality, projections indicated declines for all harvest scenarios. We projected increases across all harvest scenarios when overlap with white-tailed deer ( Odocoileus virginianus ) was hypothetically reduced and disease mortality in moose minimized. We investigated whether uncertainty in moose demographic parameters altered population trajectory, and found changes in adult fecundity and calf survival could alter harvest decisions when λ<1. 4. Practical implication . While moose population trajectories may remain stable under current conditions, management of white-tailed deer that reduces moose exposure to lethal parasites may provide the greatest utility in sustaining moose in New York given the potential for increased disease. Continued monitoring of population size, growth, and disease prevalence would inform sustainable moose harvest levels that balance social and ecological management considerations.

New York↗
USGS2018

A guide to Bayesian model checking for ecologists

Checking that models adequately represent data is an essential component of applied statistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in their research. The appeal of this modeling paradigm is undeniable, as researchers can build and fit models that embody complex ecological processes while simultaneously accounting for observation error. However, ecologists tend to be less focused on checking model assumptions and assessing potential lack of fit when applying Bayesian methods than when applying more traditional modes of inference such as maximum likelihood. There are also multiple ways of assessing the fit of Bayesian models, each of which has strengths and weaknesses. For instance, Bayesian P values are relatively easy to compute, but are well known to be conservative, producing P values biased toward 0.5. Alternatively, lesser known approaches to model checking, such as prior predictive checks, cross‐validation probability integral transforms, and pivot discrepancy measures may produce more accurate characterizations of goodness‐of‐fit but are not as well known to ecologists. In addition, a suite of visual and targeted diagnostics can be used to examine violations of different model assumptions and lack of fit at different levels of the modeling hierarchy, and to check for residual temporal or spatial autocorrelation. In this review, we synthesize existing literature to guide ecologists through the many available options for Bayesian model checking. We illustrate methods and procedures with several ecological case studies including (1) analysis of simulated spatiotemporal count data, (2) N‐mixture models for estimating abundance of sea otters from an aircraft, and (3) hidden Markov modeling to describe attendance patterns of California sea lion mothers on a rookery. We find that commonly used procedures based on posterior predictive P values detect extreme model inadequacy, but often do not detect more subtle cases of lack of fit. Tests based on cross‐validation and pivot discrepancy measures (including the “sampled predictive P value”) appear to be better suited to model checking and to have better overall statistical performance. We conclude that model checking is necessary to ensure that scientific inference is well founded. As an essential component of scientific discovery, it should accompany most Bayesian analyses presented in the literature.

Ecological Monographs↗
USGS2019

Developing an expert elicited simulation model to evaluate invasive species and fire management alternatives

Invasive species can alter ecosystem properties and cause state shifts in landscapes. Resource managers charged with maintaining landscapes require tools to understand implications of alternative actions (or inactions) on landscape structure and function. Simulation models can serve as a virtual laboratory to explore these alternatives and their potential impacts on a landscape. To be useful, however, managers need to participate in model development to ensure that model structure can evaluate the response of key resources to plausible actions. Here, we detail development of a state‐and‐transition simulation model (STSM) to evaluate buffelgrass ( Cenchrus ciliaris L. syn Pennisetum ciliare (L.) Link) in Saguaro National Park (SNP), Arizona, USA, through collaboration between managers and researchers. We integrate expert knowledge and research to create and parameterize a stochastic, spatially explicit STSM to evaluate specific management objectives. We also develop a dynamic link between the STSM and a fire behavior model to allow exploration of potential novel processes introduced to the ecosystem by buffelgrass invasion. Our projections show that buffelgrass can be expected to increase on the landscape and that the integration of fire into the model accelerates the projected rate of invasion and increases degradation of resources of management concern. We highlight the benefit of engaging end users in the modeling process so that the model is targeted to evaluate management objectives, in this case retention of saguaro cacti ( Carnegiea gigantea (Engelm.) Britton & Rose) on the landscape. Being able to integrate an external model that can help address the unique characteristics of a problem such as the introduction of fire into the SNP desert ecosystem increases the ability of simulations to address complex ecological and management questions.

Ecosphere↗
USGS2014

Reflections on a vision for integrated research and monitoring after 15 years

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.

Aquatic Geochemistry↗
USGS2014

Differential invasion success of salmonids in southern Chile: patterns and hypotheses

Biological invasions create complex ecological and societal issues worldwide. Most of the knowledge about invasions comes only from successful invaders, but less is known about which processes determine the differential success of invasions. In this review, we develop a framework to identify the main dimensions driving the success and failure of invaders, including human influences, characteristics of the invader, and biotic interactions. We apply this framework by contrasting hypotheses and available evidence to explain variability in invasion success for 12 salmonids introduced to Chile. The success of Oncorhynchus mykiss and Salmo trutta seems to be influenced by a context-specific combination of their phenotypic plasticity, low ecosystem resistance, and propagule pressure. These well-established invaders may limit the success of subsequently introduced salmonids, with the possible exception of O. tshawytscha, which has a short freshwater residency and limited spatial overlap with trout. Although propagule pressure is high for O. kisutch and S. salar due to their intensive use in aquaculture, their lack of success in Chile may be explained by environmental resistance, including earlier spawning times than in their native ranges, and interactions with previously established and resident Rainbow Trout. Other salmonids have also failed to establish, and they exhibit a suite of ecological traits, environmental resistance, and limited propagule pressure that are variably associated with their lack of success. Collectively, understanding how the various drivers of invasion success interact may explain the differential success of invaders and provide key guidance for managing both positive and negative outcomes associated with their presence.

Reviews in Fish Biology and Fisheries↗
USGS2023

Nonlinear patterns of surface elevation change in coastal wetlands: The value of generalized additive models for quantifying rates of change

In the face of accelerating climate change and rising sea levels, quantifying surface elevation change dynamics in coastal wetlands can help to develop a more complete understanding of the implications of sea-level rise on coastal wetland stability. The surface elevation table-marker horizon (SET-MH) approach has been widely used to quantify and characterize surface elevation change dynamics in coastal marshes and mangrove forests. Whereas past studies that utilized the SET-MH approach have most often quantified rates of surface elevation change using simple linear regression analyses, several recent studies have shown that elevation patterns can include a diverse combination of linear and non-linear patterns. Generalized additive models (GAMs) are an extension of generalized linear models (GLMs) that have previously been used to analyze a variety of complex ecological processes such as cyclical changes in water quality, species distributions, long-term patterns in wetland area change, and palaeoecological time series. Here, we use long-term SET data to demonstrate the value of generalized additive models for analyzing non-linear patterns of surface elevation change in coastal wetlands. Additionally, we illustrate how the GAM approach can be used to effectively quantify rates of elevation change at both landscape- and local site-level scales.

Estuaries and Coasts↗