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At least 613 records · Page 34Linked to original sources
USGS2019

Life history, genetics, range expansion and new frontiers of the lionfish (Pterois volitans, Perciformes: Pteroidae) in Latin America

Pterois volitans (lionfish) is a midsize predatory fish commonly found in waters of the western Pacific and Indian Ocean. The species was first documented in Dania Beach, Florida (northwestern Caribbean) in 1985. Since that time the species has expanded its range rapidly to the Northwestern Atlantic Ocean, Gulf of Mexico, and Caribbean Sea. Since its introduction P. volitans has changed community structure and biodiversity of Caribbean reef communities and other coastal tropical ecosystems. Continuous introductions (accidental or intentional), limited natural predators, naïve-range prey behavior, high predation rates on competitors, continuous reproduction, and an extended period of larval dispersal have been the keys for successful invasion and rapid range extension of P. volitans . This invasion has become so severe that it has been recognized as one of the world’s top conservation issues. Here, we review the life history, behavior, and historical and contemporary genetic patterns that facilitate expansion and the colonization process. A greater understanding of lionfish biology, ecology, and the changes related to its present condition as a super-invader could improve current and future management strategies and new detection and response methodologies. We also examine new invasion frontiers that this species has the potential to colonize such as the eastern Pacific. This information will provide managers, the scientific community, and the civil society better tools for eradication, control and management of future invasions of this and other invasive species.

Caribbean Sea, Latin America↗
USGS2013

Contraception can lead to trophic asynchrony between birth pulse and resources

Abiotic inputs such as photoperiod and temperature can regulate reproductive cyclicity in many species. When humans perturb this process by intervening in reproductive cycles, the ecological consequences may be profound. Trophic mismatches between birth pulse and resources in wildlife species may cascade toward decreased survival and threaten the viability of small populations. We followed feral horses (Equus caballus) in three populations for a longitudinal study of the transient immunocontraceptive porcine zona pellucida (PZP), and found that repeated vaccinations extended the duration of infertility far beyond the targeted period. After the targeted years of infertility, the probability of parturition from post-treated females was 25.6% compared to 64.1% for untreated females, when the data were constrained only to females that had demonstrated fertility prior to the study. Estimated time to parturition increased 411.3 days per year of consecutive historical treatment. Births from untreated females in these temperate latitude populations were observed to peak in the middle of May, indicating peak conception occurred around the previous summer solstice. When the post-treated females did conceive and give birth, parturition was an estimated 31.5 days later than births from untreated females, resulting in asynchrony with peak forage availability. The latest neonate born to a post-treated female arrived 7.5 months after the peak in births from untreated females, indicating conception occurred within 24–31 days of the winter solstice. These results demonstrate surprising physiological plasticity for temperate latitude horses, and indicate that while photoperiod and temperature are powerful inputs driving the biological rhythms of conception and birth in horses, these inputs may not limit their ability to conceive under perturbed conditions. The protracted infertility observed in PZP-treated horses may be of benefit for managing overabundant wildlife, but also suggests caution for use in small refugia or rare species.

PLoS ONE↗
USGS2015

Tropical insular fish assemblages are resilient to flood disturbance

Periods of stable environmental conditions, favoring development of ecological communities regulated by density-dependent processes, are interrupted by random periods of disturbance that may restructure communities. Disturbance may affect populations via habitat alteration, mortality, or displacement. We quantified fish habitat conditions, density, and movement before and after a major flood disturbance in a Caribbean island tropical river using habitat surveys, fish sampling and population estimates, radio telemetry, and passively monitored PIT tags. Native stream fish populations showed evidence of acute mortality and downstream displacement of surviving fish. All fish species were reduced in number at most life stages after the disturbance, but populations responded with recruitment and migration into vacated upstream habitats. Changes in density were uneven among size classes for most species, indicating altered size structures. Rapid recovery processes at the population level appeared to dampen effects at the assemblage level, as fish assemblage parameters (species richness and diversity) were unchanged by the flooding. The native fish assemblage appeared resilient to flood disturbance, rapidly compensating for mortality and displacement with increased recruitment and recolonization of upstream habitats.

Ecosphere↗
USGS2002

U.S. coral reefs; imperiled national treasures

Coral reefs are home to 25% of all marine species. However, the tiny colonial animals that build these intricate limestone masses are dying at alarming rates. If this trend continues, in 20 years the living corals on many of the world's reefs will be dead and the ecosystems that depend on them severely damaged. As part of the effort to protect our Nation's extensive reefs, U.S. Geological Survey (USGS) scientists are working to better understand the processes that affect the health of these ecologically and economically important ecosystems.

Fact Sheet↗
USGS2012

USGS Zebra Mussel Monitoring Program for north Texas

The U.S. Geological Survey (USGS) Zebra Mussel Monitoring Program for north Texas provides early detection and monitoring of zebra mussels ( Dreissena polymorpha ) by using a holistic suite of detection methods. The program is designed to assess zebra mussel occurrence, distribution, and densities in north Texas waters by using four approaches: (1) SCUBA diving, (2) water-sample collection with plankton tow nets (followed by laboratory analyses), (3) artificial substrates, and (4) water-quality sampling. Data collected during this type of monitoring can assist rapid response efforts and can be used to quantify the economic and ecological effects of zebra mussels in the north Texas area. Monitoring under this program began in April 2010. The presence of large zebra mussel populations often causes undesirable economic and ecological effects, including damage to water-processing infrastructure and hydroelectric powerplants (with an estimated 10-year cost of $3.1 billion), displacement of native mussels, increases in concentrations of certain species of cyanobacteria, and increases in concentrations of geosmin (an organic compound that results in taste and odor issues in water). Since no large-scale, environmentally safe eradication method has been developed for zebra mussels, it is difficult to remove established populations. Broad physicochemical adaptability, prolific reproductive capacity, and rapid dispersal methods have enabled zebra mussels, within a period of about 20 years, to establish populations under differing environmental conditions across much of the eastern part of the United States. In Texas, the presence of zebra mussels was first confirmed in April 2009 in Lake Texoma in the Red River Basin along the Texas-Oklahoma border. They were most likely introduced into Lake Texoma through overland transport from an infested water body. Since then, the presence of zebra mussels has been reported in both the Red River and Washita River arms of Lake Texoma, in Sister Grove Creek, and in Ray Roberts Lake. Water managers tasked with supplying the 6.6 million residents of the Dallas-Fort Worth metropolitan area must ensure that the area receives a continuous supply of water that meets both the needs of the current (2012) and the projected (doubling in number by 2050) populations. This metropolitan area depends on surface water captured in area reservoirs, including those in the Trinity River Basin, for the primary source of drinking water. The presence of an established zebra mussel population in a reservoir in the Trinity River Basin could result in increased operations and maintenance costs for water resource managers and could potentially serve as a source population leading to further expansion of this aquatic nuisance species.

Oklahoma County, Texas County↗
USGS2018

Hydrologic conditions in Kansas, water year 2017

The U.S. Geological Survey, in cooperation with Federal, State, and local agencies, maintains a long-term network of hydrologic monitoring stations in Kansas. These data and associated analyses provide a unique overview of the hydrologic conditions and help improve the understanding of Kansas’ water resources. Yearly assessments of hydrologic conditions are made by comparing statistical analysis of current and past water year data for the period of record. These data provide critical information for protecting life and property, managing water supplies, forecasting floods, operating reservoirs, designing bridges and culverts, processing interstate and intrastate water rights claims, ecological monitoring, and many other uses.

Kansas↗
USGS2004

Mute swans: Natural (?) environmental indicators

The rapid expansion of the Chesapeake Bay's population of feral mute swans (Cygnus olar), coupled with a dramatic Bay-wide decline in submerged aquatic vegetation (SAV), has fueled much of the current debate surrounding the need for a management plan to protect the aquatic food resources that are critical to many species native to the Bay. Crucial to this decision process is a sound understanding of the ecological ramifications of having the year-round presence of a large, nonnative, aquatic herbivore on the Bay. Ultimately, this will require a quantitative assessment of the ecological harm currently posed by mute swans before a biologically defensible management strategy can be developed. Unfortunately, very little new information specific to the Bay's mute swan population has been gathered since Reese first studied them in the late 1960s and 1970s. While the debate over what to do about the rapidly expanding mute swan population continues, there is much that can be gained from study of this beautiful intruder. Several recent studies of the feeding habits of mute swans have shown that mutes can provide a unique barometer, or indicator, of environmental conditions. Because of their reliance on SAV as a primary food source, monitoring the density of swans utilizing a particular area can give some indication of the status of the area's grass beds. This phenomenon was clearly demonstrated during the summer of 1999 when there was a dramatic decline in the number of swans observed around the Eastern Neck NWR, a traditional population stronghold. The shift in bird use was precipitated by a rapid, large-scale collapse of the area's aquatic grass beds, possibly the result of a prolonged drought. During the winter of 2000/2001, a similar ecological assessment was conducted by comparing body weights of swans collected from Tangier Sound, an area with relatively abundant grass beds, and swans from the waters adjacent to Eastern Neck Island. Swans weights tended to reflect the conditions of their surroundings, with the Tangier Sound birds being slightly heavier at the onset of the breeding season. Interestingly, the birds at Eastern Neck showed a 1 kg decline in weight after dispersal from their wintering locations and entered the breeding season with noticeably less subcutaneous fat than the birds sampled in Tangier Sound. The fact that mute swans are nonmigratory and feed exclusively on benthic food items makes them an ideal organ-ism to monitor the degree of contamination of sediments within the Bay. In 1995, we compared the accumulation of metals by mute swans and other waterfowl and related it to metal concentrations in the sediments from the areas where the birds were collected. This study led to the development of an exposure model that more accurately assesses the risk of exposure to environmental contaminants through incidental ingestion of sediments, as opposed to the traditional assessment of contaminant accumulation through the food chain. This sediment exposure pathway was subsequently shown to be the primary route of exposure of swans to metals in risk assessments conducted at two Superfund sites.

Book chapter↗
USGS2018

Assessing and communicating the impacts of climate change on the Southern California coast

Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal communities, development, and ecosystems as we currently know them. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies for projected increased levels of coastal flooding and erosion, coastal managers need user-friendly planning tools based on the best available climate and coastal science. In anticipation of these climate change impacts, many communities are in the early stages of climate change adaptation planning but lack the scientific information and tools to adequately address the potential impacts. In collaboration with leading scientists worldwide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections and translate that information using sophisticated physical process models into planning-scale physical, ecological, and economic exposure, shoreline change, and impact assessments, all delivered in two simple, user-friendly, online tools. Our results show that by the end of the 21st century, over 250,000 residents and nearly $40 billion in building value across Southern California could be exposed to coastal flooding from storms, sea level rise, and coastal change. Results for the other major population center in California (the greater San Francisco Bay Area) are also available but not explicitly discussed in this report. Together, CoSMoS has now assessed the exposure of 95% of the 26 million coastal residents of the State (17 million in Southern California).

California↗
USGS2022

Democratizing macroecology: Integrating unoccupied aerial systems with the National Ecological Observatory Network

Macroecology research seeks to understand ecological phenomena with causes and consequences that accumulate, interact, and emerge across scales spanning several orders of magnitude. Broad-extent, fine-grain information (i.e., high spatial resolution data over large areas) is needed to adequately capture these cross-scale phenomena, but these data have historically been costly to acquire and process. Unoccupied aerial systems (UAS or drones carrying a sensor payload) and the National Ecological Observatory Network (NEON) make the broad-extent, fine-grain observational domain more accessible to researchers by lowering costs and reducing the need for highly specialized equipment. Integration of these tools can further democratize macroecological research, as their strengths and weaknesses are complementary. However, using these tools for macroecology can be challenging because mental models are lacking, thus requiring large up-front investments in time, energy, and creativity to become proficient. This challenge inspired a working group of UAS-using academic ecologists, NEON professionals, imaging scientists, remote sensing specialists, and aeronautical engineers at the 2019 NEON Science Summit in Boulder, Colorado, to synthesize current knowledge on how to use UAS with NEON in a mental model for an intended audience of ecologists new to these tools. Specifically, we provide (1) a collection of core principles for collecting high-quality UAS data for NEON integration and (2) a case study illustrating a sample workflow for processing UAS data into meaningful ecological information and integrating it with NEON data collected on the ground—with the Terrestrial Observation System—and remotely—from the Airborne Observation Platform. With this mental model, we advance the democratization of macroecology by making a key observational domain—the broad-extent, fine-grain domain—more accessible via NEON/UAS integration.

Ecosphere↗
USGS2005

Multiple hypotheses testing of fish incidence patterns in an urbanized ecosystem

Ecological and evolutionary theories have focused traditionally on natural processes with little attempt to incorporate anthropogenic influences despite the fact that humans are such an integral part of virtually all ecosystems. A series of alternate models that incorporated anthropogenic factors and traditional ecological mechanisms of invasion to account for fish incidence patterns in urban lakes was tested. The models were based on fish biology, human intervention, and habitat characteristics. However, the only models to account for empirical patterns were those that included fish invasiveness, which incorporated species-specific information about overall tolerance and fecundity. This suggests that species-specific characteristics are more important in general distributional patterns than human-mediated dispersal. Better information of illegal stocking activities is needed to improve human-mediated models, and more insight into basic life history of ubiquitous species is needed to truly understand underlying mechanisms of biotic homogenization. ?? Springer 2005.

Aquatic Ecology↗
USGS2026

Estimation of parental abundance using hierarchical Bayesian modeling with data augmentation

Pedigree-based estimation methods leverage the fact that each offspring in a cohort is genotypically “marked” by its parents and represent a recent and promising toolset for estimating population dynamics. This includes pedigree accumulation estimators that model the “accumulation” of inferred unique parents within a given cohort to estimate parental abundance. Unlike close-kin mark-recapture approaches, which rely on intercohort comparisons, pedigree accumulation modeling can be completed solely using intracohort samples. This is particularly advantageous for semelparous species, where intercohort pairs are impossible and adult life stages can be difficult to sample without affecting their likelihood of successfully reproducing. Previous work has evaluated a range of estimators for such datasets, concluding that the non-parametric Chao estimator provides the most accurate and precise estimates for feasible levels of sampling effort. We used simulated data to evaluate an alternative estimator based on hierarchical modeling and data augmentation in a Bayesian framework. Results indicate that estimates from the hierarchical Bayesian estimator had comparable accuracy and better precision than both the previously tested Chao1 estimator and the improved iChao formulation across a range of sample sizes and sex ratios. Furthermore, the Bayesian estimator was far more robust to simulated errors in pedigree reconstruction, especially the presence of false negatives. Hierarchical Bayesian pedigree accumulation models can also provide additional insight into underlying reproductive ecology through their use of an explicit observation process, allowing for the incorporation or estimation of species- and population-specific reproductive dynamics. More broadly, the parametric nature of these models offers opportunities to efficiently pool information among datasets as well as to propagate uncertainty within more complex models.

Ecology and Evolution↗
USGS2019

Predicting paleoclimate from compositional data using multivariate Gaussian process inverse prediction

Multivariate compositional count data arise in many applications including ecology, microbiology, genetics and paleoclimate. A frequent question in the analysis of multivariate compositional count data is what underlying values of a covariate(s) give rise to the observed composition. Learning the relationship between covariates and the compositional count allows for inverse prediction of unobserved covariates given compositional count observations. Gaussian processes provide a flexible framework for modeling functional responses with respect to a covariate without assuming a functional form. Many scientific disciplines use Gaussian process approximations to improve prediction and make inference on latent processes and parameters. When prediction is desired on unobserved covariates given realizations of the response variable, this is called inverse prediction. Because inverse prediction is often mathematically and computationally challenging, predicting unobserved covariates often requires fitting models that are different from the hypothesized generative model. We present a novel computational framework that allows for efficient inverse prediction using a Gaussian process approximation to generative models. Our framework enables scientific learning about how the latent processes co-vary with respect to covariates while simultaneously providing predictions of missing covariates. The proposed framework is capable of efficiently exploring the high dimensional, multi-modal latent spaces that arise in the inverse problem. To demonstrate flexibility, we apply our method in a generalized linear model framework to predict latent climate states given multivariate count data. Based on cross-validation, our model has predictive skill competitive with current methods while simultaneously providing formal, statistical inference on the underlying community dynamics of the biological system previously not available.

Annals of Applied Statistics↗
USGS2005

Quantile regression reveals hidden bias and uncertainty in habitat models

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias were induced by confounding with missing variables associated with other improtant processes, a problem common in statistical modeling of ecological phenomena. Simulations for a large ( N = 10 000) finite population representing grid locations on a landscape demonstrated various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable. Quantile (0 ≤ τ ≤ 1) regression parameters for linear models that excluded the important, unmeasured variable revealed bias relative to parameters from the generating model. Depending on whether interactions of the measured and unmeasured variables were negative (interference interactions) or positive (facilitation interactions) in simulations without spatial structuring, either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Heterogeneous, nonlinear response patterns occurred with correlations between the measured and unmeasured variables. When the unmeasured variable was spatially structured, variation in parameters across quantiles associated with heterogeneous effects of the habitat variable was reduced by modeling the spatial trend surface as a cubic polynomial of location coordinates, but substantial hidden bias remained. Sampling ( n = 20–300) simulations demonstrated that regression quantile estimates and confidence intervals constructed by inverting weighted rank score tests provided valid coverage of these parameters. Local forms of quantile weighting were required for obtaining correct Type I error rates and confidence interval coverage. Quantile regression was used to estimate effects of physical habitat resources on a bivalve ( Macomona liliana ) in the spatially structured landscape on a sandflat in a New Zealand harbor. Confidence intervals around predicted 0.10 and 0.90 quantiles were used to estimate sampling intervals containing 80% of the variation in densities in relation to bed elevation. Spatially structured variation in bivalve counts estimated by a cubic polynomial trend surface remained after accounting for the nonlinear effects of bed elevation, indicating the existence of important spatially structured processes that were not adequately represented by the measured habitat variables.

Ecology↗
USGS2013

Maintaining and restoring sustainable ecosystems in southern Nevada

Managers in southern Nevada are challenge with determining appropriate goals and objectives and developing viable approaches for maintaining and restoring sustainable ecosystems in a time of rapid socio-ecological and environmental change. Sustainable or "healthy" ecosystems supply clean air, water and habitat for a diverse array of plants and animals. As described in Chapter 1, sustainable ecosystems retain characteristic processes like hydrological flux and storage, geomorphic processes, biogeochemical cycling and storage, biological activity and productivity, and population regeneration and reproduction over the normal cycle of disturbance events (modified from Chapin and others 1996 and Christensen and others 1996). Ecological restoration of stressed or disturbed ecosystems in an integral part of managing for sustainable ecosystems. The Society of Ecological Restoration International (SERI) defines ecological restoration as the process of assisting the recovery of an ecosystem that has been degraded, damaged, or destroyed (SERI 2004). Many of the southern Nevada's ecosystems are being subjected to anthropogenic stressors that span global, regional, and local scales (Chapter 2)., and are crossing ecological thresholds to new alternative states (Chapter 4 and Chapter 5). These alternative states often represent novel communities with disturbance regimes that differ significantly from historic conditions. Past management and restoration goals often focused on returning ecosystems to pre-disturbance conditions (Harris and others 2006). This approach assumes stable or equilibrium conditions and ignores changes in ecosystems processes due to land uses, increases in CO 2 concentrations, and climate change. A more realistic approach is to base management and restoration goals on the current potential of an ecosystem to support a given set of ecological conditions, and on the likelihood of future change due to warming climate (Harris and others 2006). This approach requires understanding ecosystem resilience to anthropogenic disturbance and climate change, the alternative states that exist for ecosystems, and the factors that result in threshold crossing (Bestelmeyer and others 2009; Hobbs and Harris 2001; Stingham and others 2003; Whisemnant 1999). It also requires the ability to predict how climate is likely to influence ecosystems in the future (Harris and others 2006). This chapter addresses the restoration aspects of Sub-goal 1.3 in the SNAP Science Research Strategy which is to restore and sustain proper function of southern Nevada's watersheds and landscapes (able 1.3; Turner and others 2009). The effects of global, regional and local stresses on southern Nevada ecosystems are presented in Chapter 2. Here, we discuss appropriate objectives and develop guidelines for maintaining and restoring southern Nevada ecosystems. We then discuss the differences in ecological resilience to stress and disturbance and resistance to invasive species in southern Nevada ecosystems and describe restoration and management approaches for the different ecosystem types. We conclude with knowledge gaps and management implications.

Nevada↗
USGS2023

The unmarked R package: Twelve years of advances in occurrence and abundance modelling in ecology

Species distribution models (SDMs) are widely applied to understand the processes governing spatial and temporal variation in species abundance and distribution but often do not account for measurement errors such as false negatives and false positives. We describe unmarked , a package for the freely available and open-source R software that provides a complete workflow for modelling species distribution and abundance while explicitly accounting for measurement errors. Here we focus on recent advances in unmarked functionality to support multi-species, multi-state, and multi-season data, as well as support for fitting models with random effects. For illustration, we present an analysis of Acadian Flycatcher Empidonax virescens abundance on Roanoke River National Wildlife Refuge, North Carolina, USA, over 18 years. We found that Acadian Flycatcher abundance was initially greater in hardwood plantation habitat relative to bottomland hardwood forest along river levees but that abundance declined over time in both habitats. We plan for unmarked development to keep pace with advances in hierarchical modelling in ecology, including better handling of continuous-time data from camera trap and automated recording units and integrated models for multiple data streams.

Methods in Ecology & Evolution↗
USGS2017

Making ecological models adequate

Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems’ responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.

Ecology Letters↗
USGS2007

Calculating background levels for ecological risk parameters in toxic harbor sediment

Establishing background levels for biological parameters is necessary in assessing the ecological risks from harbor sediment contaminated with toxic chemicals. For chemicals in sediment, the term contaminated is defined as having concentrations above background and significant human health or ecological risk levels. For biological parameters, a site could be considered contaminated if levels of the parameter are either more or less than the background level, depending on the specific parameter. Biological parameters can include tissue chemical concentrations in ecological receptors, bioassay responses, bioaccumulation levels, and benthic community metrics. Chemical parameters can include sediment concentrations of a variety of potentially toxic chemicals. Indirectly, contaminated harbor sediment can impact shellfish, fish, birds, and marine mammals, and human populations. This paper summarizes the methods used to define background levels for chemical and biological parameters from a survey of ecological risk investigations of marine harbor sediment at California Navy bases. Background levels for regional biological indices used to quantify ecological risks for benthic communities are also described. Generally, background stations are positioned in relatively clean areas exhibiting the same physical and general chemical characteristics as nearby areas with contaminated harbor sediment. The number of background stations and the number of sample replicates per background station depend on the statistical design of the sediment ecological risk investigation, developed through the data quality objective (DQO) process. Biological data from the background stations can be compared to data from a contaminated site by using minimum or maximum background levels or comparative statistics. In Navy ecological risk assessments (ERA's), calculated background levels and appropriate ecological risk screening criteria are used to identify sampling stations and sites with contaminated sediments.

California↗
USGS2024

Feedbacks: A new synthesis of causal loops across ecology

Feedbacks are the basic linkages of living systems. In organisms, they regulate the processes of growth and homeostasis, as well as their interactions with their world. Feedback, which Judson (1980) called ‘one of the chief themes of scientific understanding,' is equally important in ecological systems. The ecological literature is rich in papers dealing with the role of feedback in various phenomena. However, we know of no comprehensive synthesis of feedbacks in ecology. Pichon et al. (2024) accomplish this, and for the first time show that ecological feedbacks can be categorized in terms of a small number of fundamental attributes. The paper brings the array of different types of feedbacks into a manageable order, providing not only the relevant theoretical framework but also guidance on methods for applying understanding to practical issues.

Ecography↗