Biology subjects

Esler, K. J.

Publications and source records attributed to Esler, K. J..

4 recordsLinked to original sources

bioRxiv2026

Fundamental-realized niche contrasts shape multi-scale species coexistence

Ecological theory states that the geographic ranges and coexistence of species are determined by fundamental and realized niches -- the sets of environments where a species intrinsic population growth rate is positive in the absence and presence of competitors, respectively. Yet large-scale tests of niche theory have been hampered by the challenge to obtain sufficient data on demography and competition. Here, we quantify fundamental and realized niches by combining data on variation in fundamental demographic rates, community composition and the abiotic environment across the global geographic ranges of 29 shrub species from the South African Fynbos biome (a global biodiversity hotspot). Estimated pairwise competition coefficients and fundamental-realized niche contrasts reveal multi-scale mechanisms of species coexistence. At small scales, species generally exert stronger competition on themselves than on other species. At biogeographical scales, more competitive species have narrower fundamental niches but are not significantly better dispersed, which provides evidence for a generalist-specialist trade-off rather than a competition-colonization trade-off. Under both present and future climates, interspecific competition more strongly limits the realized niches and geographic ranges of generalist species. The large-scale application of niche theory thus identifies key forces shaping biodiversity and indicates that generalist species may be more strongly impacted by climate change than previously thought.

ecology↗

bioRxiv2023

An integrative trait-based framework to infer resource budgets and life-histories of long-lived plants

A fundamental assumption of functional ecology is that functional traits determine life-histories. Yet correlations between traits and life-history components are often weak, especially for long lived plants. This is because trade-offs, constraints, dynamic resource budgets and the scaling from single organs to entire plants cause complex relationships between traits and life-history. To elucidate these relationships, we present an integrated Trait-Resource-Life-History (TRL) framework that infers how functional traits affect organ-level costs and benefits of different life history components, how these costs and benefits shape the dynamics of whole-plant resource acquisition and allocation, and how these dynamics translate into life history. We illustrate this framework by developing a TRL model for a functionally diverse group of woody plants (22 species of the genus Protea from the South African Greater Cape Floristic Region). Using hierarchical Bayesian latent state-space modelling, we statistically parameterise this model from data on year-to-year variation in growth, reproduction and maternal care (serotiny) for 600 individuals. The parameterised model reveals that higher resource acquisition translates into both larger absolute resource pools and greater proportional resource allocation to reproduction. Accordingly, specific leaf area, a key trait increasing resource acquisition, is associated with larger resource pools, an earlier age of maturity as well as increased vegetative and reproductive performance at young to intermediate ages. In contrast, seed nitrogen content has opposing effects on the benefits of different organs and thus only shows weak correlations with life-history components. Importantly, the TRL model identifies trait and resource-mediated trade-offs at the level of organs, whole-plant resource budgets and life-histories. It can thus quantify key components of life-history theory that are so far largely inaccessible for long-lived plants. This permits novel insights into ecological and evolutionary mechanisms shaping life-histories. Application of the proposed framework to a broad range of plant systems should be facilitated by the increasing availability of trait and demographic data, whole-plant phenotyping and high resolution remote sensing. The integration of the TRL framework with models of biotic interactions further holds promise for a resource-based understanding of community dynamics across trophic levels and a closer integration of functional ecology, evolutionary ecology, community ecology and ecosystem science.

ecology↗

bioRxiv2023

Functional traits shape plant-plant interactions and recruitment in a hotspot of woody plant diversity.

O_LIUnderstanding and predicting recruitment in species-rich plant communities requires identifying the functional determinants of both density-independent performance and interactions. C_LIO_LIIn a common-garden field experiment with 25 species of the woody plant genus Protea, we varied the initial spatial and taxonomic arrangement of seedlings and followed their survival and growth during recruitment. Neighbourhood models quantified how six key functional traits affect density-independent performance, interaction effects and responses. C_LIO_LITrait-based neighbourhood models accurately predicted individual survival and growth from the initial spatial and functional composition of species-rich experimental communities. Functional variation among species caused substantial variation in density-independent survival and growth that was not correlated with interaction effects and responses. Interactions were spatially-restricted but had important, predominantly competitive, effects on recruitment. Traits increasing the acquisition of limiting resources (water for survival, soil P for growth) mediated a trade-off between competitive effects and responses. Moreover, resprouting species had higher survival but reduced growth, likely reinforcing the survival-growth trade-off in adult plants. C_LIO_LIThe combination of field experiments and trait-based neighbourhood analyses holds substantial potential for community ecology. It permits the identification of traits that mediate performance trade-offs promoting coexistence in species-rich communities and contributes key knowledge to guide conservation and restoration of biodiversity hotspots. C_LI

ecology↗

bioRxiv2019

Mismatches between niches and geographic ranges of plants depend on life history traits

The ecological niche of a species describes the variation in population growth rates along environmental gradients that drives geographic range dynamics. Niches are thus central for understanding and forecasting species geographic distributions. However, theory predicts that migration limitation, source-sink dynamics and time-lagged local extinction can cause mismatches between niches and geographic distributions. It is still unclear how relevant these niche-distribution mismatches are for biodiversity dynamics and how they depend on species life history traits. This is mainly due to a lack of the comprehensive, range-wide demographic data needed to directly infer ecological niches for multiple species. Here we quantify niches from extensive demographic measurements along environmental gradients across the geographic ranges of 26 plant species (Proteaceae; South Africa). We then test whether life history explains variation in species niches and niche-distribution mismatches. Niches are generally wider for species with high seed dispersal or persistence abilities. Life history traits also explain the considerable interspecific variation in niche-distribution mismatches: poorer dispersers are absent from larger parts of their potential geographic ranges, whereas species with higher persistence ability more frequently occupy environments outside their ecological niche. Our study thus identifies major demographic and functional determinants of species niches and geographic distributions. It highlights that the inference of ecological niches from geographical distributions is most problematic for poorly dispersed and highly persistent species. We conclude that the direct quantification of ecological niches from demographic responses to environmental variation is a crucial step towards a better predictive understanding of biodiversity dynamics under environmental change.

ecology↗