Biology subjects

Salguero-Gomez, R.

Publications and source records attributed to Salguero-Gomez, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Second-order elasticities for Ecology and Evolution: Unravelling nonlinear fitness responses to perturbations

In ecology and evolutionary biology, understanding the relationship between vital rates (e.g., survival, development, reproduction) and population growth is essential to elucidate how life history strategies are shaped by natural selection. However, the established demographic methods to decipher the relationship between vital rates and population growth often analyse only the linear changes in population fitness as a result of changes in vital rates, thus simplifying the complexities of said relationships. To overcome the widespread linearity simplification, here we introduce the second-order elasticities of mean population fitness, the S-elasticity. The S-elasticity quantifies how changes in one or more vital rates can produce a second-order change in mean fitness. We provide a systematic mathematical framework behind the S-elasticity, revealing its ability to identify the convex and concave responses of mean fitness to perturbations of vital rates. Through structured population models, we demonstrate the distinct roles of linear and nonlinear mean fitness responses, and their combination, enabling to characterise local concavity/convexity of the mean population fitness function. We illustrate the application and the differences of S-elasticities and their biological meanings using matrix population models of the armadillo (Dasupys novemcinctus) and Pynes plum (Astragallus bibullatus). These two case studies showcase how the S-elasticity provides key insights into mean fitness responses to perturbations on demographic process and their correlations. We discuss the improvements that the S-elasticity provides for species management and our understanding of how natural populations cope with environmental change.

ecology↗

bioRxiv2025

Current estimates of population resilience do not predict resilience to directional environmental shifts

Natural systems worldwide are exposed to gradual changes imposed by directional environmental shifts, known as ramp disturbances. However, contemporary assessments of population resilience focus on the resistance and recovery of systems following one-off (i.e., pulse) disturbances. Thus, our current perception of demographic resilience overlooks the potential impacts of the cumulative effects of ramp disturbances on population dynamics. Simulating 50-year ramp disturbance scenarios upon the survival and fecundity dynamics of 511 populations across 344 species, we illustrate non-linear patterns in how directional environmental shifts will reshape the resilience of natural populations. Accordingly, existing estimates of population resilience are not robust against a backdrop of ongoing and continuous environmental change. Instead, we demonstrate the need to quantify how the relative partitioning of energetic resources across survival vs. fecundity informs population resilience. Our findings challenge the use of well-established approaches in forecasting population resilience to ongoing global change.

ecology↗

bioRxiv2025

Poaching exacerbates the effects of climate change on the long-term viability of an endemic South African succulent plant species

O_LINatural populations often face multiple threats that jeopardise their viability, yet most population forecasts consider only single threats, such as shifts in precipitation or temperature. To better understand ecological and conservation challenges, incorporating multiple threats is essential. South African endemic dwarf succulents, for example, are under dual threats from climate change and illegal harvesting for the ornamental plant trade. C_LIO_LIWe developed a stochastic integral projection model (IPM) using demographic data from 1999-2003, for 4776 individuals of the dwarf succulent, Argyroderma pearsonii, to evaluate the impacts of climate change and harvesting on its short-term (<40 years) extinction risk and long-term viability. We built simulations to explore 90 scenarios combining climate conditions (historical, mild climate change [SSP126], and moderate climate change [SSP245]), harvesting methods (fruit harvesting, non-selective plant harvesting, or size-selective plant harvesting), and harvest frequencies (annual to once every decade). We supplemented our approach with perturbation analyses to identify critical demographic components influencing population persistence. C_LIO_LIWe show that historically A. pearsonii populations have been stable or growing. Populations are predicted to remain viable under mild climate change, but moderate climate change results in declines in approximately 50% of simulated populations, though extinctions are not projected within 40 years without harvesting. In contrast, plant harvesting significantly increases extinction risk, especially size-selective harvesting of mature individuals, which disrupts demographic components critical to population growth. Even harvesting as infrequently as once per decade under historical climates leads to declines, with climate change exacerbating these effects. C_LIO_LISynthesis: Illegal harvesting poses a critical threat to biodiversity, as shown in this case study of a South African endemic succulent. Our findings indicate that plant harvesting is unsustainable under any scenario, particularly with projected climatic pressures. However, fruit collection emerges as a potentially sustainable alternative to meet the ornamental plant trades demands. Our study highlights the importance of incorporating multiple threats into population forecasts, providing valuable tools for ecologists and conservation managers. C_LI

ecology↗

bioRxiv2025

Modelling forest dynamics using integral projection models (IPMs) and repeat LiDAR

O_LIEstimating the life histories and population dynamics of trees is important for predicting how forests respond to climate change and disturbances. To do so, ecologist often use stage-structured population models, which explicitly account for individual heterogeneity. However, the data needed to parameterise these models is typically constrained by time- and labour-intensive field methods. C_LIO_LIDespite growing access to remote sensing imagery that could potentially satiate these data-hungry population models, these data remain underutilised in population ecology. Here, we demonstrate a pipeline that integrates repeat-LiDAR data with a type of structured demographic model (Integral Projection Model, IPM) to examine forest-wide dynamics in response to environmental drivers. Using Australias Great Western Woodlands as a case study, we model the survival and growth of [~]40,000 eucalypt trees over a decade to estimate their life expectancy and characterise multiple stages of growth (height growth and crown expansion). C_LIO_LIOur results indicate distinct responses of small trees (where vital rates are predicted by height) and large trees (which invested predominantly in expanding crown area) to proxies for competition and soil moisture (local canopy density and topographic wetness index, respectively). Parameterising structured population models using LiDAR data therefore offers a step-change in perspective towards more ecologically meaningful forest dynamics. C_LIO_LITo broaden the application of this pipeline, we highlight three priorities: (1) Application to more complex systems such as mixed species stands and dense, multilayered canopies); (2) Incorporating complete life histories, including reproduction and early life stages; and (3) Using in long-term or comparative studies through improved availability of high-quality, comparable, repeat-LiDAR surveys. By combining remote sensing data with detailed insights from field- based studies, this pipeline represents a scalable framework for guiding forest management and conservation decisions. C_LI

ecology↗

bioRxiv2024

Genetic diversity and population structure of pedunculate oaks (Quercus robur) in Wytham Woods

O_LIGenetic diversity is fundamental for adaptation to changing environments. It is particularly important in forest trees because of their significant role in natures contribution to people. However, their genetic diversity has been significantly changed by human activities in the past centuries. C_LIO_LIThis paper investigates a focal site, the Wytham Woods, one of the most researched woodlands on Earth, and presents a population genetic study on pedunculate oaks (Quercus robur), a keystone species in the ecosystem. We characterised 210 trees with Genotyping by Sequencing (GbS) and quantified levels of genetic diversity across stands with different histories and management regimes. C_LIO_LIWe detected only a weak population structure within the 218,567 SNPs, such that most genetic variation occurred within but not among stands, which included semi-natural woodland areas and plantations aged between 200 to 50 years ago. We also observed little difference in observed and expected heterozygosity among stand types, but detected some inbreeding in the youngest plantation. We discovered 26,174 SNPs (11.98%) that were highly differentiated and under potential selection. C_LIO_LIWe suggest that the life history traits of oak contribute to its resistance against genetic erosion, which is also observed in beeches, spruces, and pines. Preference for oaks as a timber tree and the tendency to use local seed source might have resulted in the homogeneous population structure. However, tree-to-tree differences may harbour variation in putative adaptive loci. Our study contributes crucial baseline information on for conservation and management of human-modified woodlands, in addition to supporting long-term ecological studies on many other species, which depend on this keystone oak species. C_LI Societal Impact StatementOur study highlights the importance of monitoring and preserving genetic diversity in forest trees, particularly in keystone species like pedunculate oaks. Human activities, including land use changes and forestry practices, could influence their genetic diversity and potentially alter natures contribution to people. We demonstrate how understanding the genetic structure of oaks in stands ranging from semi-natural to plantations could (1) shed light on the natural history and the consequence of human activities in Wytham Woods, (2) support the many continuing, long-term ecological studies including adaptational potential in the oak population, and (3) be translated for other co-occurring species and other woodlands for effective genetic monitoring at large.

genomics↗

bioRxiv2024

Variation in precipitation drives differences in interactions and short-term transient instability between grassland functional groups: a stage-structured community approach

Climate change is expected to increase the frequency and severity of precipitation extremes, causing droughts and flooding. Consequently, grassland communities are forecasted to become increasingly unstable. To predict grassland responses, we need empirical information together with models that reliably extrapolate community dynamics from those observations. However, such prediction is challenging because community models typically simulate long-term (asymptotic) performance, and thus potentially neglect their short-term (transient) performance. Here, we use data from a precipitation experiment performed over eight years to model both short- and long-term responses of three functional groups - grasses, legumes, and non-leguminous forbs - to precipitation extremes. We use multi-functional-group Integral Projection Models and pseudospectral theory, to track grassland community dynamics. We show that the percentage-cover-stage-structure of functional groups shapes their transient instability, and that inter-functional-group interactions are competitive under increased precipitation but facilitative under decreased precipitation. IPMs and pseudospectra enable forecasting of how functional-group-stage-structure drives responses to climatic extremes.

ecology↗

bioRxiv2024

Increases in Arctic extreme climatic events are linked to negative fitness effects on the local biota

1.The Arctic harbours uniquely adapted biodiversity and plays an important role in climate regulation. Strong warming trends in the terrestrial Arctic have been linked to an increase in aboveground biomass (Arctic greening) and community-wide shifts such as the northwards-expansion of boreal species (borealisation). Whilst considerable efforts have been made to understand the effects of warming trends in average temperatures on Arctic biota, far fewer studies have focused on trends in extreme climate events and their biotic effects, which have been suggested to be particularly impactful during the Arctic winter months. Here, we present an analysis of trends in two ecologically-relevant winter extreme events -extreme winter warming and rain-on-snow, followed by a meta-analysis on the evidence base for their effects on Arctic biota. We show a strong increase in extreme winter warming across the entire Arctic and high variability in rain-on-snow trends, with some regions recently experiencing rain-on-snow for the first time whilst others seeing a decrease in these events. Ultimately, both extreme events show significant changes in their characteristics and patterns of emergence. Our meta-analysis -encompassing 178 effect sizes across 17 studies and 49 species- demonstrates that extreme winter warming and rain-on-snow induce negative impacts on Arctic biota, with certain taxonomic groups -notably angiosperms and chordates (mostly vertebrates)- exhibiting higher sensitivity than others. Our study provides evidence for both emerging trends in Arctic winter extreme climate events and significant negative biotic effects of such events -which calls for attention to winter weather variability under climate change in the conservation of Arctic biodiversity, whilst highlighting important knowledge gaps.

ecology↗

bioRxiv2024

Diseases and invasive species have synergistic effects with other anthropogenic threats on the functional and phylogenetic diversity in Testudines and Crocodilia

Understanding how multiple threats interact is crucial for the prioritization of conservation measures. Here, we investigate how interactions between six common threats (climate change, habitat disturbance, global trade, overconsumption, pollution, and emerging diseases/invasive species) affect the functional and phylogenetic diversity of 230 species of Testudines and 21 of Crocodilia. We classify two-way threat interactions into additive, synergistic, and antagonistic according to their effects on functional and phylogenetic diversity. Most threat interactions are antagonistic, the effect of threats jointly is lower than the sum of the effects of threats separately. However, we find that the interaction between emerging diseases or invasive species with other threats has synergistic and additive effects, meaning that the combined effects are greater or equal to the effects of threats separately. Our work can help target conservation strategies and detect key places to address multiple threats when they appear together.

ecology↗

bioRxiv2024

Human populations with low survival at advanced ages and postponed fertility reduce long-term growth in high inflation environments

Temporal variability in inflation can lead to important fluctuations in the long-term growth rate of human populations via their differential impacts on vital rates like survival and fertility. However, historically, demographic studies have overlooked this time-dependent relationship. Here, we test whether human populations have higher stochastic population growth rates when exposed to lower levels of inflation. We also examine if lower survival rates at older ages (>60 years) and fertility rates at the later reproductive years (>30 years) among populations exposed to higher inflation rates determine their expected lower long-term growth rate compared to those exposed to lower inflation rates. To explore the impact of variability in inflation on vital rates response, we develop a quantitative pipeline with four steps, and parameterise it with high-resolution economic and demographic data across 76 countries from 1971-2021. The four steps are (1) defining treatment groups based on levels of trend inflation (creeping inflation (0-3%), walking inflation (3-10%), galloping inflation (10-50%), and hyperinflation (>50%)) among which the stochastic population growth rates will be compared; (2) constructing matrix population models for each environmental state under every treatment. The environmental states for each treatment are defined on the basis of the duration of inflation (e.g., 0, 2, 4, six years or above); (3) estimating the stochastic population growth rate for each treatment by considering a Markovian environment dictated by the long-term frequency (f) and temporal autocorrelation (p) of the treatment; and (4) decomposing the differences in the population growth rate between treatments into contributions from environmental variability and vital rate differences between environments to test how vital rates impact on population growth under varying environmental scenarios. In agreement with our hypothesis, we find that the stochastic population growth rate at lower levels of inflation is systematically higher than that at a higher level of inflation at all stationary frequencies and temporal autocorrelation of the inflation environment. Moreover, the disadvantage in survival at older ages (>60 years) and fertility at ages >30 years led to the lower stochastic growth rate among populations exposed to higher level of inflation such as walking inflation compared to lower level of inflation, such as creeping inflation. Our framework explicitly links human population performance and inflation environment by describing nonlinear feedback between inflation, human survival, fertility, population growth, and its age structure. We discuss the potential of our approach to study the life-history strategies and population dynamics of a wide range of drivers of environmental variability.

animal behavior and cognition↗

bioRxiv2024

Population responses to environmental stochasticity are primarily driven by survival-reproduction trade-offs and mediated by aridity

Forecasting responses of natural populations to increasingly stochastic environments is a major challenge in Ecology and Conservation Biology. We now know that populations can modulate how their vital rates (e.g., survival, reproduction) change through time to minimise the negative impacts of environmental stochasticity. However, despite the important analytical and theoretical advances that have led to this knowledge, we still do not know (1) how much this ability of natural populations to buffer against environmental stochasticity can vary in nature, nor (2) the drivers of these strategies, with likely candidates including the environmental regimes themselves, as well as the life history traits and phylogenetic ancestry of the species of interest. To address these questions, we parameterised a Bayesian generalised linear mixed model with high-resolution vital rate data from 134 natural populations across 89 species of plants and animals. We show that population responses to environmental stochasticity vary three orders of magnitude along a demographic buffering continuum. Furthermore, the position of a given population along said continuum is predicted by a survival-reproduction trade-off and by the degree of aridity the population experiences. Our findings open a promising avenue of research to improve ecological forecasts and management of natural populations in the Anthropocene.

ecology↗

bioRxiv2024

Life Histories and Study Duration matter less than Prior Knowledge of Vital Rates to Inverse Integral Projection Models

O_LIEcology has been surprisingly slow to address the uncertainty and bias that results from using short-term time series to draw long-term inference. To improve our understanding of assumptions around the temporal structure of vital rates (e.g., survival, reproduction), we need tools that are feasible and capture longer-term, state-structured population dynamics. C_LIO_LIHere, we use inverse modelling of a set of integral projection models (IPMs) to show how demographic rates can be accurately reconstructed from state-structure fluctuations in a population time-series. We use a particle-filtering optimisation algorithm to fit vital rates from time-series of varying length, parameter combinations, priors, and life histories. C_LIO_LIWe show how key life history traits such as generation time have little effect on the ability of our approach to accurately identify vital rates using state structure over time. Further, contrary to our expectations, the duration of our time-series data has relatively modest impact on the estimation of vital rates compared to the critical role of prior knowledge on vital rates. C_LIO_LIur framework to estimate IPM vital rates highlights the potential of inverse models to extend time-series for demographic models, but also demonstrates that long-term time-series are not a perfect surrogate for detailed demographic inference. We discuss the need for more work exploring the conditions when inverse modelling is an adequate tool based on species traits. C_LI

ecology↗

bioRxiv2024

A video-rate hyperspectral camera for monitoring plant health and biodiversity

Hyperspectral cameras are a key enabling technology in precision agriculture, biodiversity monitoring, and ecological research. Consequently, these applications are fuelling a growing demand for devices that are suited to widespread deployment in such environments. Current hyperspectral cameras, however, require significant investment in post-processing, and rarely allow for live-capture assessments. Here, we introduce a novel hyperspectral camera that combines live spectral data and high-resolution imagery. This camera is suitable for integration with robotics and automated monitoring systems. We explore the utility of this camera for applications including chlorophyll detection and live display of spectral indices relating to plant health. We discuss the performance of this novel technology and associated hyperspectral analysis methods to support an ecological study of grassland habitats at Wytham Woods, UK.

ecology↗

bioRxiv2024

Sociality shapes the life histories of animals along the fast-slow continuum, but does not affect their senescence

The role of sociality in the demography of animals has become an intense focus of research in recent decades. However, efforts to understand the sociality-demography nexus have focused on single species or isolated taxonomic groups. Consequently, we lack generality regarding how sociality associates with demographic traits within the Animal Kingdom. Here, I propose a continuum of sociality, from solitary to tightly social, and test whether this continuum correlates with the key demographic properties of 152 species, from jellyfish to humans. After correction for body mass and phylogenetic relationships, I show that the sociality continuum is associated with key life history traits: more social species live longer, postpone maturity, have greater generation time, and greater probability of achieving reproduction than solitary, gregarious, communal, or colonial species. Contrary to the social buffering hypothesis, sociality does not result in more buffered populations. While more social species have a lower ability to benefit from disturbances, they display greater resistance than more solitary species. Finally, I also show that sociality does not shape reproductive or actuarial senescence rates. This cross-taxonomic examination of sociality across the demography of 13 taxonomic classes highlights keyways in which individual interactions shape most aspects of animal demography.

animal behavior and cognition↗

bioRxiv2023

Climate change has desynchronized insect and vegetation phenologies across Europe

Climate change is drastically affecting the phenologies of species worldwide, including shifts in development1-3. The potential impact of climate change on the synchronicity of plant-insect phenology is particularly concerning since the stability of pollination networks and food chains depends on their tight temporal dependencies4-6. Furthermore, the recently reported "insect armageddon"7 makes it urgent to establish trends and identify primary drivers of plant-insect phenological synchrony. Here, coupling high-resolution remote sensing and citizen science data across Europe over 34 years, we examine the differences in occurrence dates of 1,584 herbivorous insects across four orders and the corresponding dates of leaf unfolding. We find that 61.2% of the vegetation and insect phenologies have become highly asynchronous, with vegetation phenology advancing four-fold faster than insect phenology. These trends were modulated by insects life-cycles and taxonomic order. A primary driver of this phenological mismatch is the higher sensitivity of vegetation phenology than insect phenology to climate, which has prevented insects from matching the pace of plant phenological advance in the growing season. Our analyses provide a unique continental overview and underlying mechanisms of the asynchronicity between vegetation and insect phenologies, thus enhancing our ability to predict and manage its potential cascading ecological effects.

ecology↗

bioRxiv2023

"Negative density dependence promotes persistence of a globally rare yet locally abundant plant species (Oenoethera coloradensis)"

O_LIIdentifying the mechanisms underlying the persistence of rare species has long been a motivating question for ecologists. Classical theory implies that community dynamics should be driven by common species, and that natural selection should not allow small populations of rare species to persist. Yet, a majority of the species found on Earth are rare. Consequently, several mechanisms have been proposed to explain their persistence, including negative density dependence, demographic compensation, vital rate buffering, asynchronous responses of sub-populations to environmental heterogeneity, and fine-scale source-sink dynamics. Persistence of seeds in a seed bank, which is often ignored in models of population dynamics, can also buffer small populations against collapse. C_LIO_LIWe used integral projection models (IPMs) to examine the population dynamics of Oenothera coloradensis, a rare, monocarpic perennial forb, and determine whether any of five proposed demographic mechanisms for rare species persistence contribute to the long-term viability of two populations. We also evaluated how including a discrete seed bank stage changed population models for this species. C_LIO_LIIncluding a seed bank stage in population models had a significant positive impact on modeled O. coloradensis population growth rate. Using IPMs that included a discrete seedbank state, we found that negative density-dependence was the only supported mechanism for the persistence of this rare species. C_LIO_LISynthesis: IPMs of two populations of the rare species O. coloradensis emphasize the importance of including cryptic life stages such as seed banks in demographic models, but fail to provide strong support for most of the proposed mechanisms of rare species persistence. We propose that high micro-site abundance in a spatially heterogeneous environment enables this species to persist, allowing it to sidestep the demographic and genetic challenges of small population size that rare species typically face. These results emphasize that globally rare species can employ many different strategies for persistence, including the somewhat counter-intuitive phenomenon of local abundance. This reinforces the need for customized management and conservation strategies that mirror the diversity of mechanisms that allow rare species persistence. C_LI

ecology↗

bioRxiv2023

From disturbances to nonlinear fitness and back.

Disturbances can occur as short-lived pulses (e.g., storms) or sustained presses (e.g., chronic drought). Much work in ecology has developed methods to help predict how natural populations respond to disturbances, but analyses of pulse and press disturbances has been largely disconnected. We present a unified matrix framework that links presses and pulses within the same analytical approach, showing how transient nonlinearities and demography shape fitness. We find that transient responses to pulse disturbances accumulate to determine the long-term response to press disturbances. For structured-population models, this cumulative change is given by a new Transient Response Matrix (TRM). Strikingly, the TRM also yields the second derivatives of population growth rate with respect to matrix elements. Thus, there is an intimate but unexpected relationship between nonlinear selection pressures on demographic rates, and the transient dynamics of populations. This relationship yields a strong correlation between TRM and generation time across 439 unique plant and animal species (2690 population models). We also show that the TRM is directly related to Cohens cumulative distance measure for populations converging to stability. Our framework provides ecologists with a general tool to predict population responses to diverse environmental changes.

ecology↗

bioRxiv2023

Differences in adult survival drive divergent demographic responses to a decade of field warming on the Tibetan Plateau

O_LIA central question in biodiversity conservation is whether species will maintain viable population dynamics under future climate change. Assessing species extinction risk under climate warming requires demographic studies integrating vital rate responses to long-term warming throughout species life cycle. However, studies of this nature are rare. C_LIO_LIHere, we examine the demographic responses of two co-occurring herbaceous plants, Elymus nutans Griseb. and Helictotrichon tibeticum (Roshev.) Holub, after a decade (2011-2020) of in situ active warming by 2{degrees}C in the grasslands of the Tibetan Plateau. We parameterise Integral Projection Models (IPMs) to project the population dynamics under ambient and long-term warming conditions, and examine the key vital rates responsible for any potential differences in population growth rates. C_LIO_LIWarming has contrasting effects on the two functionally similar co-occurring species: warming promotes the population growth rate of H. tibeticum, but intensifies the population decline of E. nutans. Our elasticity analyses show that survival is the most important vital rate for population viability in both species under both ambient and warmed conditions. Furthermore, our retrospective Life Table Response Experiment (LTRE) analysis reveals that the contrasting fates of the two species under warming mainly arise from the different responses of adult survival, which is significantly promoted in H. tibeticum but slightly reduced in E. nutans. Individual shrinkage occurred 1.6-fold more frequently under warming than ambient conditions for both species, and made considerable negative contributions to their population growth rates in warmed plots. However, such negative effects are offset in H. tibeticum (but not E. nutans) by the positive contribution to population growth rate of the associated increased survival. C_LIO_LISynthesis. Our study illustrates that the responses to climate warming may vary considerably between similar co-occurring species, and species with a demographically compensatory strategy may avoid population collapse. Additionally, caution is needed when generalizing findings among functionally similar species, and that conservation measures should be tailored at the species level. C_LI

ecology↗

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↗