Biology subjects

Vinton, A. C.

Publications and source records attributed to Vinton, A. C..

5 recordsLinked to original sources

bioRxiv2026

Reproductive Trade-offs in Caribbean Corals: Plasticity Accelerates While Fragmentation Delays Reproductive Capacity

In modular organisms, where growth and fragmentation blur the boundaries between individuals, the interplay between asexual and sexual reproduction creates complex fitness trade-offs. Life-history theory predicts that resources allocated to one fitness component necessarily reduce investment in others, yet detecting these trade-offs in wild populations of clonal organisms remains challenging. Phenotypic plasticity can enhance survival, yet its influence on reproductive capacity and life history trade-offs remains poorly understood. Using a fully crossed reciprocal transplant design, we tracked 263 colonies of the branching coral Acropora cervicornis across nine reef sites over 42 months, investigating relationships between fragmentation, morphological plasticity, and the capacity for sexual reproduction. Breakage patterns reflected both environmental and genetic factors. Primary branch breaks created a "double negative" effect--simultaneously more than doubling mortality risk and delaying attainment of a validated reproductive size class by [~]40%. Conversely, higher morphological plasticity in surface area-to-volume ratio accelerated sexual maturation up to 6-fold, counteracting the negative effects of fragmentation. In parallel, a simple demographic model parameterized with published fecundity data estimated that primary breakage reduces expected cumulative reproductive output by [~]58%, a result robust across a wide range of parameter assumptions. These results demonstrate a fundamental reproductive trade-off in which asexual reproduction through fragmentation undermines sexual reproductive potential by reducing colony size. Moreover, our findings reveal that fragmentation susceptibility is broadly heritable and subject to selection, and identify a compensatory mechanism through which plasticity enhances fitness beyond immediate survival.

evolutionary biology↗

bioRxiv2023

A Novel Simulation Framework for Validation of Ecological Network Inference

O_LIUnderstanding how the differential magnitude and sign of ecological interactions vary across space is vital to assessing ecosystem resilience to biodiversity loss and predict community assemblies. This necessity for ecological network knowledge and their labour-intensive sampling requirements has spurred the creation of ecological network inference methodology. Recent research has identified inconsistencies in networks inferred using different approaches thus necessitating quantification of inference performance to facilitate choice of network inference approach. C_LIO_LIHere we develop a data simulation method to generate data products fit for network inference and subsequently quantify the validity of two well-established ecological interaction network inference methods - HMSC and COOCCUR. The simulation framework we present here can be parameterised using real-world information (e.g., biological interactions observed in-situ and bioclimatic niche preferences) thus representing network inference capabilities in real-world applications. Using this framework, it is thus possible to evaluate the performance of any ecological network inference approach. C_LIO_LIWe identify a concerningly large range in accuracy of inferred networks as compared to true, realisable association networks. These differences in inference accuracy are governed by a paradigm of input data types and environmental parameter estimation as previously suggested. To establish a workflow for quantification of network inference reliability, we suggest analysis procedures with which to explore inference and detection probabilities of association types of different identity and sign with respect to bioclimatic niche preferences and association strength of association partner-species. C_LIO_LIWith this study, we provide the groundwork with which to validate and compare ecological network inference methods, and ultimately vastly increase our ability to understand and predict species biodiversity across space and time. C_LI

bioinformatics↗

bioRxiv2023

Structured demographic buffering: A framework to explore the environment drivers and demographic mechanisms underlying demographic buffering

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of these strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environment factors and demographic characteristics are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to quantify the relative effects of three key drivers of demographic buffering: environment components (e.g., temporal autocorrelation and variance), population structure, and demographic rates (e.g., progression and fertility). Using Integral Projection Models, we explore how these drivers impact the demographic buffering abilities of three plant species with different life histories and demonstrate how our approach successfully characterises a populations capacity to demographically buffer against environmental stochasticity in a changing world.

ecology↗

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↗

bioRxiv2019

Evolutionary rescue is determined by differential selection on demographic rates and density dependence.

Accelerated rates of climate change are expected to either lead to populations adapting and persisting, or suffering extinction. Traditionally ecological models make extinction predictions based on how environmental change alters the intrinsic growth rate (r). However, these often ignore potential for evolutionary rescue, or to avoid extinction via adaptive evolution. Moreover, the environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). Therefore, when we consider the potential for evolutionary rescue, populations with the same r can have different abilities to persist amidst environmental change. We cant adequately understand evolutionary rescue without accounting for demography, and interactions between density dependence and environmental change. Using stochastic birth-death population models, we found evolutionary rescue more likely when environmental change alters birth rather than the death rate. Furthermore, species that evolve via density dependent selection are less vulnerable to extinction than species that undergo selection independent of population density. Resolving the key demographic factors affected by environmental change can lead to an understanding of how populations evolve to avoid extinction. By incorporating these considerations into our models we can better predict how species will respond to climate change.

ecology↗