Demographic and life history traits explain patterns in species vulnerability to extinction

Hernández‐Yáñez, Haydée; Kim, Su Yeon; Che‐Castaldo, Judy

doi:10.1371/journal.pone.0263504

Cited by 21 publications

(16 citation statements)

References 49 publications

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“…Certain traits predispose species to declines and extinction, and traits that drive a population response to an extrinsic source of potential mortality vary between threats (Fisher & Owens, 2004; Hernández‐Yáñez et al., 2022). For example, specialized species are particularly vulnerable to habitat loss, and large‐bodied species are more prone to overharvesting and overpredation by invasive predators due to their slow reproductive rates (Fisher & Owens, 2004).…”

Section: Introductionmentioning

confidence: 99%

Modeling mammal response to fire based on species’ traits

Pocknee

Legge

McDonald

et al. 2023

Conservation Biology

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Fire has shaped ecological communities worldwide for millennia, but impacts of fire on individual species are often poorly understood. We performed a meta‐analysis to predict which traits, habitat, or study variables and fire characteristics affect how mammal species respond to fire. We modeled effect sizes of measures of population abundance or occupancy as a function of various combinations of these traits and variables with phylogenetic least squares regression. Nine of 115 modeled species (7.83%) returned statistically significant effect sizes, suggesting most mammals are resilient to fire. The top‐ranked model predicted a negative impact of fire on species with lower reproductive rates, regardless of fire type (estimate = –0.68), a positive impact of burrowing in prescribed fires (estimate = 1.46) but not wildfires, and a positive impact of average fire return interval for wildfires (estimate = 0.93) but not prescribed fires. If a species’ International Union for Conservation of Nature Red List assessment includes fire as a known or possible threat, the species was predicted to respond negatively to wildfire relative to prescribed fire (estimate = –2.84). These findings provide evidence of experts’ abilities to predict whether fire is a threat to a mammal species and the ability of managers to meet the needs of fire‐threatened species through prescribed fire. Where empirical data are lacking, our methods provide a basis for predicting mammal responses to fire and thus can guide conservation actions or interventions in species or communities.

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Section: Introductionmentioning

confidence: 99%

Modeling mammal response to fire based on species’ traits

Pocknee

Legge

McDonald

et al. 2023

Conservation Biology

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“…The potential of this impressive and rapidly increasing amount of information is starting to be realised. Indeed, through combining these demographic models, researchers have identified functional traits that explain variation in plant life history strategies (Adler et al, 2014; also see Bernard et al, 2022), short-term (transient) characteristics that drive the demographic dynamics of plant populations in variable environments (McDonald, Stott, Townley, & Hodgson, 2016), and ways in which life history strategies allow species to persist alongside a changing climate (Paniw, Ozgul, & Salguero-Gómez, 2018;Paniw, Maag, Cozzi, Clutton-Brock, & Ozgul, 2019;Jelbert et al, 2019;Hernández-Yáñez, Kim, & Che-Castaldo, 2022;Jackson, Le Coeur, & Jones, 2022;Le Coeur, Yoccoz, Salguero-Gómez, & Vindenes, 2022).…”

Section: Introductionmentioning

confidence: 99%

A standard protocol to report discrete stage-structured demographic information

Gascoigne

Rolph

Sankey

et al. 2023

Preprint

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Stage-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. Here, 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. Over 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. Combining 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.

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“…Comparative analyses often rely on the collation of published data to obtain sufficient sample sizes. There are numerous recent examples of this (Dalgleish et al 2010, Bullock et al 2012, Burns et al 2013), and large‐scale collaborative efforts to collate global demographic and life history and related data are increasingly common (Wright et al 2004, Loh et al 2005, Kattge et al 2011, Salguero‐Gómez et al 2015, Capdevila et al 2022, Hernández‐Yáñez et al 2022, Cant et al 2023). Such databases provide a rich resource for workers focussing on life‐history strategies and demographic performance.…”

Section: Introductionmentioning

confidence: 99%

Plant demographic knowledge is biased towards short‐term studies of temperate‐region herbaceous perennials

Römer,

Dahlgren,

Salguero‐Gómez

et al. 2023

Oikos

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Plant demography has a long history resulting in a large knowledge base. Comparative analysis of this information allows exploration of the drivers of demographic patterns globally and the study of life‐history evolution. Studies aiming to generalise demographic patterns rely on data being derived from a representative sample. However, the data are likely to be taxonomically, geographically and methodologically biased. Matrix population models (MPMs) are widely‐used in plant demography, so an assessment of publications using MPMs is a convenient way to assess the distribution of plant demographic knowledge using this modelling approach. We assessed bias in this knowledge using data from the COMPADRE Plant Matrix Database, containing MPMs for > 700 species. We show that tree species and tropical areas are under‐represented, while herbaceous perennials and temperate areas are over‐represented. There is a positive association between the number of studies per country and per capita GDP. Most studies have low spatiotemporal replication with 43% of studies conducted over < four years, and only 17% replicated across > three sites. This limited spatiotemporal coverage means existing data may not represent the environmental conditions the species experience. These biases and knowledge gaps inhibit theory development and limit current utility for identifying useful generalities for management decisions, such as typical responses to climate change. It is likely that similar biases extend to other demographic modelling tools such as integral projection models. We urge researchers to address these biases and close these knowledge gaps.

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Demographic and life history traits explain patterns in species vulnerability to extinction

Cited by 21 publications

References 49 publications

Modeling mammal response to fire based on species’ traits

Modeling mammal response to fire based on species’ traits

A standard protocol to report discrete stage-structured demographic information

Plant demographic knowledge is biased towards short‐term studies of temperate‐region herbaceous perennials

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