Biology subjects

Childs, D. Z.

Publications and source records attributed to Childs, D. Z..

18 recordsLinked to original sources

bioRxiv2026

Vertebrates do not display consistent declines in abundance or stability with contemporary range or realized climate niche centrality

The abundant-centre (ACH) and stable-centre hypotheses (SCH) predict population abundance and stability decline with increasing distances from a species' range and multivariate climate niche centres. ACH and SCH are widely held assumptions underpinning many ecological and conservation applications, with range and climate centrality often assumed to reflect suitability. However, empirical support that abundance (distance-abundance) and stability (distance-variability) decline away from range and climate centres is mixed and hampered by radically different climate centrality assumptions. Here, we test distance-abundance relationships in >5000 vertebrate species and distance-variability relationships in >1000 vertebrate species across their realized geographic and climate niche spaces. We found no vertebrate taxa display consistent declines in abundance or stability with increasing distances from range centres or realized climate (niche) centres modelled from species' breeding ranges, native ranges or contemporary occurrences. Distance-abundance and distance-variability relationships were weak and inconsistent across taxa irrespective of centrality metric, modelling approach, climate variables, abundance metric or dataset. Contemporary vertebrate abundance patterns, therefore, are often decoupled from position in contemporary range and realized climate space, challenging a central assumption of core-periphery models. Broadly, our study indicates that frequently used range and climate centrality metrics may be weak predictors of vertebrate abundance patterns in contemporary landscapes and biological forecasting or climate change applications should be cautious of their unvalidated use.

ecology↗

bioRxiv2026

Multiple ecological and evolutionary mechanisms drive treatment-induced antibiotic resistance

The emergence of resistance within patients during antibiotic treatment is an important cause of treatment failure. However, the ecological and evolutionary mechanisms driving within-patient emergence remain poorly understood. Here, we analysed 24,478 Pseudomonas aeruginosa isolates sampled from 180 bronchiectasis patients during a clinical trial to understand how ciprofloxacin-resistant infections emerged over a one-year period of pulse-dosing. Pre-existing resistance predominated, accelerating resistance emergence relative to patients where resistance emerged by spontaneous mutation or strain immigration. Selective sweeps of costly mutations increased resistance over time in some patients, whereas in others oscillating resistance levels were driven by antibiotic treatment and resistance-growth trade-offs between genetically divergent subpopulations. Our findings show that infections under identical treatment follow diverse and sometimes complex ecological and evolutionary paths to antibiotic resistance, with implications for better predicting and managing treatment-induced antibiotic resistance.

evolutionary biology↗

bioRxiv2025

Metabolomic profiling of glyphosate resistance evolution in green alga Chlamydomonas reinhardtii

The widespread use of glyphosate has led to a rapid increase in glyphosate resistant weeds at a considerable cost to agriculture. Furthermore, agricultural run-off means non-target, natural ecosystems are also affected. Resistance may arise both through mutations to target enzyme EPSPS in the shikimate pathway generating insensitivity to glyphosate and through non-target site mutations regulating the dose of glyphosate reaching the shikimate pathway. Either mechanism may trade-off against normal cell functioning. Here, using experimental evolution of replicated Chlamydomonas reinhardtii populations facing glyphosate, we reveal the metabolomic fingerprint of both glyphosate action and emerging resistance by applying untargeted metabolomic screens throughout the course of resistance evolution. Furthermore, this allows us to evaluate potential underlying molecular mechanisms and fitness costs. We find evidence of build-up of shikimate pathway metabolites, a characteristic signal of glyphosate action, that subsides but does not disappear as resistance evolves, suggesting a fitness trade-off. Concurrent with this is evidence of cell wide disruption of the amino acid pool, that stabilises as resistance evolves. We also found evidence of effects of glyphosate on membrane lipids and increased levels of reactive oxygen species persisting after resistance had evolved. This suggests a considerable effect of the recently described secondary effect of glyphosate: oxidative damage. These data highlight several metabolic processes disrupted by and persisting with the evolution of resistance to glyphosate and may provide a template for enhancing predictions of population and ecosystem effects.

evolutionary biology↗

bioRxiv2024

Glyphosate resistance evolution to lethal and sublethal doses in chemostat populations of model organism Chlamydomonas reinhardtii

Herbicide resistant weeds are an increasing economic and ecological problem world-wide. Evolutionary theory and insight from experiments testing this theory are now a central part of solving resistance problems. More specifically, experimental evolution, where populations are allowed to evolve under specific conditions, can offer substantial insights into the trade-offs that govern the pace at which resistance arises. Here we leverage the green alga Chlamydomonas reinhardtii facing glyphosate as a model plant system to evaluate such theory, monitoring the level of evolved resistance and associated fitness costs throughout the course of adaptation. On a gradient of lethal and sub-lethal doses of glyphosate, we found evidence for evolved resistance from standing genetic variation but limited evidence for classic growth rate trade-offs that are expected to affect the pace of resistance evolution.

evolutionary biology↗

bioRxiv2024

Evidence for a trade-off between glyphosate resistance and anti-grazer defence in green alga Chlamydomonas reinhardtii

O_LIThe widespread and persistent use of herbicides has both selected for dramatically increased levels of herbicide resistance in the weed populations they were designed to control, and increased contamination of non-target ecosystems. C_LIO_LIExperimental evolution using microbes offers the opportunity to explore basic evolutionary theory, including testing for the existence of intrinsic and extrinsic fitness trade-offs, connecting them to the patterns observed in both natural and agricultural populations. C_LIO_LIWe used green alga Chlamydomonas reinhardtii adapted to high and moderate levels of glyphosate to test for an extrinsic cost to glyphosate resistance in the form of a trade-off with clumping, the inducible anti-grazer defence deployed against gape-limited micrograzers. Through exposing the algae to freshwater rotifer Brachionus calyciflorus as well as their isolated info-chemicals, we test whether glyphosate resistance affects ability to deploy defences as well as ability to withstand grazing compared to control populations. C_LIO_LIWe find an increase in variation rather than uni-directional effect of glyphosate treatment, with treated populations exhibiting both lower and higher degree of anti-grazer defence compared to controls. Furthermore, our data suggests there are at least three different glyphosate resistant phenotypes present, with two conferring different extrinsic costs in the form of tradeoff with anti-grazer defence. C_LIO_LIOur study indicates that extrinsic costs to glyphosate resistance may be context dependent in this system, possibly only being present at particular stages in the adaptation process or with particular resistance mechanisms. C_LI

ecology↗

bioRxiv2024

Global genomic diversity of Pseudomonas aeruginosa in bronchiectasis

BackgroundPseudomonas aeruginosa is the dominant pathogen causing lung infections in people with both cystic fibrosis (CF) and bronchiectasis, associated with poorer outcomes. Unlike CF, bronchiectasis has been a neglected disease. More extensive genomic studies of larger bronchiectasis patient cohorts and within patient sampling are needed to improve understanding of the evolutionary mechanisms underpinning P. aeruginosa infections to guide novel and improved treatments. MethodsWe have performed genome sequencing of 2,854 P. aeruginosa isolates from 180 patients attending clinics worldwide to analyse the genomic diversity between and within patient infections. ResultsWe observed high genetic diversity between infections with low incidence of highly transmissible strains. Our genomic data provide evidence for the mutational targets driving P. aeruginosa evolution in bronchiectasis. Some functions found to gain mutations were comparable to CF, including biofilm and iron acquisition, whilst others highlighted distinct evolutionary paths in bronchiectasis such as pyocin production and resistance, and a novel efflux pump gene (PA1874). We also show a high incidence of antimicrobial resistance-associated mutations and acquired resistance genes, in particular multidrug efflux and fluoroquinolone resistance mechanisms. ConclusionsOur findings highlight important differences between P. aeruginosa infections in bronchiectasis and CF and provide evidence of the relatively minor role transmissible strains play in bronchiectasis. Our study provides a 10-fold increase in the available genomic data for these infections and is a global resource to improve our knowledge and understanding, to facilitate better patient outcomes. SummaryThe largest genomic study of Pseudomonas aeruginosa bronchiectasis isolates to-date, providing an unprecedented global genomic resource. We highlight important differences between bronchiectasis and cystic fibrosis, including key genes under selection.

genomics↗

bioRxiv2023

A standard protocol to report discrete stage-structured demographic information

O_LIStage-based demographic methods, such as matrix population models (MPMs), are powerful tools used to address a broad range of fundamental questions in ecology, evolutionary biology, and conservation science. Accordingly, MPMs now exist for over 3,000 species worldwide. These data are being digitised as an ongoing process and periodically released into two large open-access online repositories: the COMPADRE Plant Matrix Database and the COMADRE Animal Matrix Database. During the last decade, data archiving and curation of COMPADRE and COMADRE, and subsequent comparative research, have revealed pronounced variation in how MPMs are parameterized and reported. C_LIO_LIHere, we summarise current issues related to the parameterisation and reporting of MPMs that arise most frequently and outline how they affect MPM construction, analysis, and interpretation. To quantify variation in how MPMs are reported, we present results from a survey identifying key aspects of MPMs that are frequently unreported in manuscripts. We then screen COMPADRE and COMADRE to quantify how often key pieces of information are omitted from manuscripts using MPMs. C_LIO_LIOver 80% of surveyed researchers (n=60) state a clear benefit to adopting more standardised methodologies for reporting MPMs. Furthermore, over 85% of the 300 MPMs assessed from COMPADRE and COMADRE omitted one or more elements that are key to their accurate interpretation. Based on these insights, we identify fundamental issues that can arise from MPM construction and communication and provide suggestions to improve clarity, reproducibility, and future research utilising MPMs and their required metadata. To fortify reproducibility and empower researchers to take full advantage of their demographic data, we introduce a standardized protocol to present MPMs in publications. This standard is linked to www.compadre-db.org, so that authors wishing to archive their MPMs can do so prior to submission of publications, following examples from other open-access repositories such as DRYAD, Figshare, and Zenodo. C_LIO_LICombining and standardising MPMs parameterized from populations around the globe and across the tree of life opens up powerful research opportunities in evolutionary biology, ecology, and conservation research. However, this potential can only be fully realised by adopting standardised methods to ensure reproducibility. C_LI

ecology↗

bioRxiv2022

Using passive acoustic monitoring to estimate the abundance of wide-ranging species in tropical rainforest ecosystems

Most conservation relies on being able to estimate population size accurately. The development, implementation and adaptation of effective conservation strategies rely on quantifying the impacts of different threats on population dynamics, identifying species that need conservation management, and providing feedback on the effectiveness of any management actions. However, current approaches are not suitable for wide-ranging species that reside in tropical ecosystems. Here we use the great green macaw Ara ambiguus as a case study to show that passive acoustic monitoring is an effective tool for collecting data that can then estimate abundance. We estimate a population of 485.65 {+/-} 61 SE great green macaws in Costa Rica during the breeding, suggesting the population here is larger than previously estimated. We have also highlighted potentially important areas for the species in regions that had not previously been studied. We have demonstrated at a population scale that passive acoustic monitoring (PAM) offers conservationists an efficient and effective way to understand population dynamics. With a high proportion of parrot species threatened globally, passive acoustic monitoring will enable effective monitoring and become an essential tool in conservation planning and evaluation. PAM technology has enormous potential to facilitate such assessments because it is easily scalable, recordings can be stored and re-analysed as machine learning, and abundance estimation techniques become more advanced.

ecology↗

bioRxiv2022

Overconfidence undermines global wildlife abundance trends

In the face of rapid global change and an uncertain fate for biodiversity, it is vital to quantify trends in wild populations. These trends are typically estimated from abundance time series for suites of species across large geographic and temporal scales. Such data implicitly contain phylogenetic, spatial, and temporal structure which, if not properly accounted for, may obscure the true magnitude and direction of biodiversity change. Here, using a novel statistical framework to simultaneously account for all three of these structures, we show that the majority of current abundance trends estimates among 10 high-profile datasets, representing millions of abundance observations, are likely unreliable or incorrect. Our new approach suggests that previous models are too simplistic, incorrectly estimating global abundance trends and often dramatically underestimating uncertainty, an aspect that is critical when translating global assessments into policy outcomes. Further, our approach also results in substantial improvements in abundance forecasting accuracy. Whilst our results do not improve the outlook for biodiversity, our framework does allow us to make more robust estimates of global wildlife abundance trends, which is critical for developing policy to protect our biosphere.

ecology↗

bioRxiv2022

Long-term temporal trends in gastrointestinal parasite infection in wild Soay sheep

Monitoring the prevalence and abundance of parasites over time is important for addressing their potential impact on host life-histories, immunological profiles, and their influence as a selective force. Only long-term ecological studies have the potential to shed light on both the temporal trends in infection prevalence and abundance and the drivers of such trends, because of their ability to dissect drivers that may be confounded over shorter time scales. Despite this, only a relatively small number of such studies exist. Here, we analysed changes in the prevalence and abundance of gastrointestinal parasites in the wild Soay sheep population of St Kilda across 31 years. The host population density has increased across the study, and population density is known to increase parasite transmission, but we found that density and year explained temporal variation in parasite prevalence and abundance independently. Prevalence of both strongyle nematodes and coccidian microparasites increased during the study, and this effect varied between lambs, yearlings and adults. Meanwhile, abundance of strongyles was more strongly linked to host density than to temporal (yearly) dynamics, while abundance of coccidia showed a strong temporal trend without any influence of density. Strikingly, coccidian abundance increased threefold across the course of the study in lambs, while increases in yearlings and adults were negligible. Our decades-long, intensive, individual-based study will enable the role of environmental change and selection pressures in driving these dynamics to be determined, potentially providing unparalleled insight into the drivers of temporal variation in parasite dynamics in the wild. Key findingsO_LIWe studied temporal trends in gastrointestinal parasites of wild sheep over 31 years C_LIO_LIYear and host population density explained temporal variation in parasites independently C_LIO_LIPrevalence of both strongyle nematodes and coccidia varied across the study period C_LIO_LIAbundance of strongyles was more closely linked to host density than year C_LIO_LIAbundance of coccidia increased threefold over time in lambs, but did not vary in adults C_LI

ecology↗

bioRxiv2022

Mesostats - A multiplexed, low-cost, do-it-yourself continuous culturing system for experimental evolution of mesocosms

Microbial experimental evolution allows studying evolutionary dynamics in action and testing theory predictions in the lab. Experimental evolution in chemostats (i.e. continuous flow through cultures) has recently gained increased interest as it allows tighter control of selective pressures compared to static batch cultures, with a growing number of efforts to develop systems that are easier and cheaper to construct. This protocol describes the design and construction of a multiplexed chemostat array (dubbed "mesostats") designed for cultivation of algae in 16 concurrent populations, specifically intended for studying adaptation to herbicides. We also present control data from several experiments run on the system to show replicability, data illustrating the effects of common issues like leaks, contamination and clumps, and outline possible modifications and adaptations of the system for future research.

evolutionary biology↗

bioRxiv2022

Rpadrino: an R package to access and use PADRINO, an open access database of Integral Projection Models

O_LIDiscrete time structured population projection models are an important tool for studying population dynamics. Within this field, Integral Projection Models (IPMs) have become a popular method for studying populations structured by continuously distributed traits (e.g. height, weight). Databases of discrete time, discrete state structured population models, for example DATLife (life tables) and COMPADRE & COMADRE (matrix population models), have made quantitative syntheses straightforward to implement. These efforts allow researchers to address questions in both basic and applied ecology and evolutionary biology. There are now over 300 peer-reviewed publications containing IPMs. We describe a novel framework to quickly reconstruct these models for subsequent analyses using Rpadrino R package, which serves as an interface to PADRINO, a new database of structured population models. C_LIO_LIWe introduce an R package, Rpadrino, which enables users to download, subset, reconstruct, and extend published IPMs. Rpadrino makes use of recently created software, ipmr, to provide an engine to reconstruct a wide array of IPMs from their symbolic representations and conduct subsequent analyses. Rpadrino and ipmr are extensively documented to help users learn their usage. C_LIO_LIRpadrino currently enables users to reconstruct 280 IPMs from 40 publications that describe the demography of 14 animal and 26 plant species. All of these IPMs are tested to ensure they reproduce published estimates. Rpadrino provides an interface to augment PADRINO with external data and modify parameter values, creating a platform to extend models beyond their original purpose while retaining full reproducibility. C_LIO_LIPADRINO and Rpadrino provide a toolbox for asking new questions and conducting syntheses with peer-reviewed published IPMs. Rpadrino provides a user-friendly interface so researchers do not need to worry about the database structure or syntax, and can focus on their research questions and analyses. Additionally, Rpadrino is thoroughly documented, and provides numerous examples of how to perform analyses which are not included in the packages functionality. C_LI

ecology↗

bioRxiv2021

ipmr: Flexibly implement Integral Projection Models in R

O_LIIntegral projection models (IPMs) are an important tool for studying the dynamics of populations structured by one or more continuous traits (e.g. size, height, color). Researchers use IPMs to investigate questions ranging from linking drivers to plant population dynamics, planning conservation and management strategies, and quantifying selective pressures in natural populations. The popularity of stage-structured population models has been supported by R scripts and packages (e.g. IPMpack, popbio, popdemo, lefko3) aimed at ecologists, which have introduced a broad repertoire of functionality and outputs. However, pressing ecological, evolutionary, and conservation biology topics require developing more complex IPMs, and considerably more expertise to implement them. Here, we introduce ipmr, a flexible R package for building, analyzing, and interpreting IPMs. C_LIO_LIThe ipmr framework relies on the mathematical notation of the models to express them in code format. Additionally, this package decouples the model parameterization step from the model implementation step. The latter point substantially increases ipmrs flexibility to model complex life cycles and demographic processes. C_LIO_LIipmr can handle a wide variety of models, including density dependence, discretely and continuously varying stochastic environments, and multiple continuous and/or discrete traits. ipmr can accommodate models with individuals cross-classified by age and size. Furthermore, the package provides methods for demographic analyses (e.g. asymptotic and stochastic growth rates) and visualization (e.g. kernel plotting). C_LIO_LIipmr is a flexible R package for integral projection models. The package substantially reduces the amount of time required to implement general IPMs. We also provide extensive documentation with six vignettes and help files, accessible from an R session and online. C_LI

ecology↗

bioRxiv2020

Short-lived plants have stronger demographic responses to climate

To mitigate and adapt to climate change, there is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data, combined with our understanding of plant physiology and life history theory provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesized time series of structured population models from 165 populations from 62 plants around the globe to link plant population growth rates to precipitation and temperature drivers. We expected: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; (2) a higher climate sensitivity in short-lived rather than long-lived species; and (3) a stronger response to climate by species that reproduce more frequently. We found that precipitation anomalies have a nearly three-fold larger effect on{lambda} than temperature. Precipitation has substantially more pronounced effects in more arid sites, but large noise makes this relationship non-significant. Species with shorter generation time have much stronger absolute responses to climate anomalies, while the degree of iteroparity does not correlate with population responses to climate. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning and evolutionary theory.

ecology↗

bioRxiv2019

Global analysis reveals complex demographic responses of mammals to climate change

Approximately 25 % of mammals are threatened globally with extinction, a risk that is amplified under climate change1. Persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development, reproduction), and hence, on population dynamics2. Thus, to quantify which species and places on Earth are most vulnerable to climate-driven extinction, a global understanding of how demographic rates respond to climate is needed3. We synthesise information on such responses in terrestrial mammals, where extensive demographic data are available4. Given the importance of assessing the full spectrum of responses, we focus on studies that quantitatively link climate to multiple demographic rates. We identify 106 such studies, corresponding to 86 mammal species. We reveal a strong mismatch between the locations of demographic studies and the regions and taxa currently recognised as most vulnerable to climate change5,6. Moreover, we show that the effects of climate change on mammals will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others. Assessments of population viability under climate change therefore need to account for multiple demographic responses. We advocate to prioritise coordinated actions to assess mammal demography holistically for effective conservation worldwide.

ecology↗

bioRxiv2019

Tree demographic performance of European tree species at their hot and cold edges.

O_LISpecies range limits are thought to result from a decline in demographic performance at range edges. However, recent studies reporting contradictory patterns in species demographic performance at their edges cast doubt on our ability to predict climate change demographic impacts. To understand these inconsistent demographic responses at the edges, we need to shift the focus from geographic to climatic edges and analyse how species responses vary with climatic constraints at the edge and species ecological strategy. C_LIO_LIHere we parameterised integral projection models with climate and competition effects for 27 tree species using forest inventory data from over 90,000 plots across Europe. Our models estimate size-dependent climatic responses and evaluate their effects on two life trajectory metrics: lifespan and passage time - the time to grow to a large size. Then we predicted growth, survival, lifespan, and passage time at the hot and dry or cold and wet edges and compared them to their values at the species climatic centre to derive indices of demographic response at the edge. Using these indices, we investigated whether differences in species demographic response between hot and cold edges could be explained by their position along the climate gradient and functional traits related to their climate stress tolerance. C_LIO_LIWe found that at cold and wet edges of European tree species, growth and passage time were constrained, whereas at their hot and dry edges, survival and lifespan were constrained. Demographic constraints at the edge were stronger for species occurring in extreme conditions, i.e. in hot edges of hot-distributed species and cold edges of cold-distributed species. Species leaf nitrogen content was strongly linked to their demographic responses at the edge. In contrast, we found only weak links with wood density, leaf size, and xylem vulnerability to embolism. C_LIO_LISynthesis. Our study presents a more complicated picture than previously thought with demographic responses that differ between hot and cold edges. Predictions of climate change impacts should be refined to include edge and species characteristics. C_LI

ecology↗

bioRxiv2017

Interactions between immunotoxicants and parasite stress: implications for host health

Many organisms face a wide variety of biotic and abiotic stressors which reduce individual survival, interacting synergistically to further reduce fitness. Here we studied the effects of two such synergistically interacting stressors; immunotoxicant exposure and parasite infection. We model the dynamics of a within-host infection and the associated immune response of an individual. We consider both the indirect sub-lethal effects on immunosuppression and the direct effects on health and mortality of individuals exposed to toxicants. We demonstrate that sub-lethal exposure to toxicants can promote infection through the suppression of the immune system. This happens through the depletion of the immune response which causes rapid proliferation in parasite load. In addition, high toxicant exposure can alter cellular regulation and cause the breakdown of normal healthy tissue, from which we infer higher mortality risk of the host. We classify this breakdown into three phases of increasing toxicant stress, and demonstrate the range of conditions under which toxicant exposure causes failure at the within-host level. These phases are determined by the relationship between the immunity status, overall cellular health and the level of toxicant exposure. We discuss the implications of our model in the context of individual honey bee health. Our model provides an assessment of how pesticide stress and infection interact to cause the synergistic breakdown of the within-host dynamics of individual honey bees.

epidemiology↗

bioRxiv2017

Exploring population responses to environmental change when there’s never enough data; a factor analytic approach

O_LITemporal variability in the environment drives variation in individuals vital rates, with consequences for population dynamics and life history evolution. Integral projection models (IPMs) are data-driven models widely used to study population dynamics and life history evolution of structured populations in temporally variable environments. However, many data sets have insufficient temporal replication for the environmental drivers of vital rates to be identified with confidence, limiting their use for evaluating population level responses to environmental change.\nC_LIO_LIParameter selection, where the kernel is constructed at each time step by randomly selecting the time-varying parameters from their joint probability distribution, is one approach to including stochasticity in IPMs. We consider a factor analytic (FA) approach for modelling the covariance matrix of time-varying parameters, whereby latent variable(s) describe the covariance among vital rate parameters. This decreases the number of parameters to estimate and, where the covariance is positive, the latent variable can be interpreted as a measure of environmental quality. We demonstrate this using simulation studies and two case studies.\nC_LIO_LIThe simulation studies suggest the FA approach provides similarly accurate estimates of stochastic population growth rate to estimating an unstructured covariance matrix. We demonstrate how the latent parameter can be perturbed to show how selection on reproductive delays in the monocarp Carduus nutans changes under different environmental conditions. We develop a demographic model of the fire dependent herb Eryngium cuneifolium to show how a causal indicator (i.e. a driver of the changes in the environmental quality) can be incorporated with the addition of a single parameter. Using perturbation analyses we determine optimal management strategies for this species.\nC_LIO_LIThis approach estimates fewer parameters than previous approaches and allows novel eco-evolutionary insights. Predictions on population dynamics and life history evolution under different environmental conditions can be made without necessarily identifying causal factors. Environmental drivers can be incorporated with relatively few parameters, allowing for predictions on how populations will be affected by changes to these drivers.\nC_LI

ecology↗