An important hypothesis for how plants respond to introduction to new ranges is the evolution of increased competitive ability (EICA). EICA predicts that biogeographical release from natural enemies initiates a tradeoff in which exotic species in non-native ranges become larger and more competitive, but invest less in consumer defenses, relative to populations in native ranges. This tradeoff is exceptionally complex because detecting concomitant biogeographical shifts in competitive ability and consumer defense depend upon which traits are targeted, how competition is measured, the defense chemicals quantified, whether defense chemicals do more than defend, whether “herbivory” is artificial or natural, and where consumers fall on the generalist-specialist spectrum. Previous meta-analyses have successfully identified patterns but have yet to fully disentangle this complexity. We used meta-analysis to reevaluate traditional metrics used to test EICA theory and then expanded on these metrics by partitioning competitive effect and competitive tolerance measures and testing Leaf Specific Mass in detail as a response trait. Unlike previous syntheses, our meta-analyses detected evidence consistent with the classic tradeoff inherent to EICA. Plants from non-native ranges imposed greater competitive effects than plants from native ranges and were less quantitatively defended than plants from native ranges. Our results for defense were not based on complex leaf chemistry, but instead were estimated from tannins, toughness traits, and primarily Leaf Specific Mass. Species specificity occurred but did not influence the general patterns. As for all evidence for EICA-like tradeoffs, we do not know if the biogeographical differences we found were caused by tradeoffs per se, but they are consistent with predictions derived from the overarching hypothesis. Underestimating physical leaf structure may have contributed to two decades of tepid perspectives on the tradeoffs fundamental to EICA.
Ecosystems remain under enormous pressure from multiple anthropogenic stressors. Manipulative experiments evaluating stressor interactions and impacts mostly apply stressors under static conditions without considering how variable stressor intensity (i.e., fluctuations) and synchronicity (i.e., timing of fluctuations) affect biological responses. We ask how variable stressor intensity and synchronicity, and interaction type, can influence how multiple stressors affect seagrass. At the highest intensities, fluctuating stressors applied asynchronously reduced seagrass biomass 36% more than for static stressors, yet no such difference occurred for photosynthetic capacity. Testing three separate hypotheses to predict underlying drivers of differences in biological responses highlighted alternative modes of action dependent on how stressors fluctuated over time. Given that environmental conditions are constantly changing, assessing static stressors may lead to inaccurate predictions of cumulative effects. Translating multiple stressor experiments to the real-world, therefore, requires considering variability in stressor intensity and the synchronicity of fluctuations.
Positive interactions have been hypothesized to influence plant community dynamics and species invasions. However, their prevalence and importance relative to negative interactions remain unclear, but are fundamentally important for both theoretical and applied ecology. We examined pairwise biotic interactions using over 50 years of successional data to assess the prevalence of positive interactions and their effects on each focal species (either native or exotic). We found that positive interactions were widespread and the relative frequency of positive and negative interactions varied with establishment stage and between native and exotic species. Specifically, positive interactions were more frequent during early establishment and less frequent at later stages. Positive interactions involving native species were more frequent and stronger than those between exotic species, reducing the impact of invasional meltdown on succession. Our study highlights the role of positive native interactions in shielding communities from biological invasion and enhancing the potential for long-term resilience.
Understanding what drives the vast variability in species range size is still an outstanding question. Among the several processes potentially affecting species ranges, dispersal is one of the most prominent hypothesized predictors. However, the theoretical expectation of a positive dispersal-range size relationship has received mixed empirical support. Here, we synthesized results from 84 studies to investigate in which context dispersal is most important in driving species range size. We found that dispersal traits -- proxies for dispersal ability -- explain range sizes more often in temperate and subtropical regions than in tropical regions, when considering multiple components of dispersal, and when investigating a large number of species to capture dispersal and range size variation. In plants, positive effects of dispersal on range size were less often detected when examining broad taxonomic levels. In animals, dispersal is more important for range size increase in ectotherms than in endotherms. Our synthesis emphasizes the importance of considering different aspects of the dispersal process -departure, transfer, settlement-, niche aspects and evolutionary components, like time for range expansion and past geological-environmental dynamics. We therefore call for a more integrative view of the dispersal process and its causal relationship with range size.
Climate warming is a ubiquitous stressor in freshwater ecosystems, yet its interactive effects with other stressors are poorly understood. We address this by testing the ability of three contrasting null models to predict the joint impacts of warming and a second stressor using a new database of 296 experimental combinations. Despite concerns that stressors will interact to cause synergisms, we found that net impacts were best explained by the effect of the stronger stressor (the dominance null model), especially if it was associated with human land use. Prediction accuracy depended on stressor identity and the magnitude of asymmetry between their effects. These findings suggest we can often effectively forecast impacts of multiple stressors by focusing on the stronger stressor, as habitat alteration and contamination often override the biological consequences of higher temperatures in freshwater ecosystems.
High resolution monitoring is fundamental to understand and predict the dynamics of ecological communities in an era of global change and biodiversity declines. While real-time and fully automated monitoring of the abiotic components of ecosystems has been possible for some time, monitoring the biotic components at different organizational scales, e.g. from individual behaviours and traits to the abundance and distribution of species, is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which are able to extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological populations and communities via such technologies is still in its infancy, being primarily achieved at low spatiotemporal resolutions within specific stages of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify, and count multiple species, and even record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology and conservation: the ability to rapidly generate high resolution, multidimensional, and critically, standardized data across complex ecologies.
1. Thermal performance curves (TPCs) are commonly used to forecast species’ responses to temperature change. Recent work has demonstrated that the breadth and shape of a consumer’s TPC change with resource densities, highlighting the potential for inaccurate forecasts if resource densities are not static. In particular, if resource densities decline, the optimal temperature and breadth of thermal performance also declines leading to an enhanced risk of warming, particularly among species that may incur additional costs of behavioral thermoregulation. 2. Here, we investigate the relationship between resource density and temperature (warming) on the persistence of a consumer population which exerts top-down control on its resource via trophic interaction. Trophic coupling generally reduces the potential for resource declines to exacerbate the negative effects of warming on consumers; when warming has negative effects on the consumer, resource densities tend to increase due to a reduction in top-down control. However, if resources are more sensitive to warming (e.g. due to an asymmetry amongst their thermal performance curves), the negative effects of warming on consumers can be exacerbated by declining resources. 3. Our work elucidates the importance of jointly considering temperature and resource limitation when utilizing assessing the thermal performance of species. We demonstrate how knowledge of the thermal performance of a resource population can be used to generate realized consumer thermal performance curves.
In light of ongoing climate change, it is increasingly important to know how nutritional requirements of ectotherms are affected by changing temperatures. Here, we analyse the wide thermal response of phosphorus (P) requirements via elemental gross growth efficiencies of Carbon (C) and P, and the Threshold Elemental Ratios in different aquatic invertebrate ectotherms such as the freshwater model species Daphnia magna, the marine copepod Acartia tonsa, the marine heterotrophic dinoflagellate Oxyrrhis marina, and larvae of two populations of the marine crab Carcinus maenas. We show that they all share a non-linear cubic thermal response of nutrient requirements. Phosphorus requirements decrease from low to intermediate temperatures, increase at higher temperatures, and decrease again when temperature is excessive. This universality in the thermal response of nutrient requirements is of great importance if we aim to understand or even predict how ectotherm communities will react to global warming and nutrient-driven eutrophication.
As invasive species spread, the ability of local communities to resist invasion depends on the strength of biotic interactions. Evolutionarily unused to the invader, native predators or herbivores may be initially wary of consuming newcomers, allowing them to proliferate. However, these relationships may be highly dynamic, and novel consumer-resource interactions could form as familiarity grows. Here, we explore the development of effective biotic resistance towards a highly invasive alga using multiple space-for-time approaches. We show that the principal native Mediterranean herbivore learns to consume the invader within less than a decade. At recently invaded sites, the herbivore actively avoided the alga, shifting to distinct preference and high consumptions at older sites. This rapid strengthening of the interaction contributed to the eventual collapse of the alga after an initial dominance. Therefore, our results stress the importance of conserving key native populations to allow communities to develop effective resistance mechanisms against invaders.
The potential for forecasting the dynamics of ecological systems is currently unclear, with contrasting opinions regarding its feasibility due to ecological complexity. To investigate forecast skill within and across system complexity, we monitored a microbial system exposed to either constant or fluctuating temperatures in a five months long laboratory experiment. We tested how forecasting of species abundances depends on number and strength of interactions and on model size (number of predictors). We also tested how greater system complexity (i.e. the fluctuating temperatures) impacted these relations. We found that the more a species interacted, the weaker these interactions were and the better its abundance was predicted. Forecast skill increased with model size. Greater system complexity decreased forecast skill for three out of eight species. These insights into how abundance prediction depends on the embedding of the species within the system and on overall system complexity could improve species forecasting and monitoring.
Physiological constraints related to atmospheric temperature pose a limit to body and appendage size in endothermic animals. This relationship has been summarized by two classical principles of biogeography: Bergmann’s and Allen’s rules. Body size may also constrain other phenotypic traits important in ecology, evolution and behaviour, and such effects have seldom been investigated at a continental scale. Through a multilevel-modelling approach, we demonstrate that continent-wide morphology of related African barbets follows predictions of both ecogeographic rules, and that body size mirrors variation in song pitch, an acoustic trait important in species recognition and sexual selection. Specifically, effects on song frequency in accordance with Bergmann’s rule dwarf those of acoustic adaptation at a continental scale. Our findings suggest that macroecological patterns of body size can influence phenotypic traits important in ecology and evolution, and provide a baseline for further studies on the effects of environmental change on bird song.
Primary consumers in aquatic ecosystems are frequently limited by the quality of their food, often expressed as phytoplankton elemental and biochemical composition. Effects of these food quality indicators vary across studies, and the relative importance of elemental (nitrogen and phosphorus) versus biochemical (fatty acid and sterol) limitation in aquatic food webs has been debated. Here we present results of a meta-analysis using >100 experimental studies, which confirms that limitation by N, P, essential fatty acids, and sterols all have significant negative effects on zooplankton performance. However, effects varied by grazer response (growth versus reproduction), specific manipulation, and across taxa. P limitation had greater effects on zooplankton growth than fatty acids, but P and fatty acid limitation had equal effects on reproduction. Furthermore, we show that nutrient co-limitation in zooplankton occurs, that indirect effects induced by P limitation exceed direct effects of mineral P limitation, that effects of nutrient amendments using laboratory phytoplankton isolates exceed those using natural field communities, and that algal physiology mediates zooplankton responses to nutrient limitation. Our meta-analysis reconciles contrasting views about the role of various food quality indicators, and their interactions, for zooplankton performance, and provides a mechanistic understanding of how environmental change affects trophic transfer.
Understanding the factors affecting thermal tolerance is crucial for predicting the impact climate change will have on ectotherms. However, the role developmental plasticity plays in allowing populations to cope with thermal extremes is poorly understood. Here, we meta-analyse how thermal tolerance is acutely and persistently impacted by early thermal environments by using data from 150 experimental studies on 138 ectothermic species. Thermal tolerance only increased by 0.13°C per 1°C change in developmental temperature and substantial variation in plasticity (~36%) was the result of shared evolutionary history and species ecology. Aquatic ectotherms were more than three times as plastic as terrestrial ectotherms. Notably, embryos expressed weaker but more heterogenous plasticity than older life stages, with numerous responses appearing as non-adaptive. While we did not find universal evidence for developmental temperatures to have persistent effects on thermal tolerance, persistent effects were vastly under-studied, and their direction and magnitude varied with ontogeny. Embryonic stages may represent a critical window of vulnerability to changing environments and we urge researchers to consider early life stages when assessing the climate vulnerability of ectotherms. Overall, our synthesis suggests that developmental changes in thermal tolerance will rarely reach levels of perfect compensation and buffer ectotherms from rising temperatures.
The storage effect is a general explanation for coexistence in a variable environment. The generality of the storage effect is both a strength — it can be quantified in many systems — and a challenge — there is not a clear relationship between the abstract conditions for storage effect and species’ life-history traits (e.g., dormancy, stage-structure, non-overlapping generations), thus precluding a simple ecological interpretation of the storage effect. Our goal here is to provide a clearer understanding of the conditions for the storage effect as a step towards a better general explanation for coexistence in a variable environment. Our approach focuses on dividing one of the key conditions for the storage effect, covariance between environment and competition, into two pieces, namely that there must be a causal relationship between environment and competition, and that the effects of the environment do not change too quickly. This finer-grained definition can explain a number of previous results, including 1) that the storage effect promotes annual plant coexistence when the germination rate fluctuates, but not when the seed yield fluctuates, 2) that the storage effect is more likely to be induced by resource competition than apparent competition, and 3) that the spatial storage effect is more probable than the temporal storage effect. Additionally, our expanded definition suggests two novel mechanisms by which the temporal storage effect can arise: transgenerational plasticity, and causal chains of environmental variables. These mechanisms produce coexistence via the storage effect without any need for stage structure or a temporally autocorrelated environment.
Ecologists often rely on observational data to understand causal relationships. Although observational causal inference methodologies exist, model selection based on information criterion (e.g., AIC) remains a common approach used to understand ecological relationships. However, such approaches are meant for predictive inference and is not appropriate for drawing causal conclusions. Here, we highlight the distinction between predictive and causal inference and show how model selection techniques can lead to biased causal estimates. Instead, we encourage ecologists to apply the backdoor criterion, a graphical rule that can be used to determine causal relationships across observational studies.
Forecasting the trajectories of species assemblages in response to ongoing climate change requires quantifying the time lags in the demographic and ecological processes through which climate impacts species' abundances. Since experimental climate manipulations are typically abrupt, the observed species responses may not match their responses to gradual climate change. We addressed this problem by transplanting alpine grassland turfs to lower elevations, recording species' demographic responses to climate and competition, and using these data to parameterize community dynamics models forced by scenarios of gradual climate change. We found that shifts in community structure following an abrupt climate manipulation were not simply accelerated versions of shifts expected under gradual warming, especially when they missed the rise of species benefiting from moderate warming. Time lags in demography and species interactions controlled the pace and trajectory of changing species' abundances under simulated 21st century climate change, and thereby prevented immediate diversity loss.
Many species-rich ecological communities result from adaptive radiation events. The effects of these explosive speciation events on community assembly remain poorly understood. Here, we explore the well-documented radiations of African cichlid fishes and interactions with their flatworm gill parasites (Cichlidogyrus spp.) including 10529 reported infections and 477 different host-parasite combinations collected through a survey of peer-reviewed literature. We assess the evolutionary, ecological, and morphological parameters on meta-communities partially affected by adaptive radiation evens using network metrics, host repertoire measures, and network link prediction (NLP). The hosts’ evolutionary history mostly determined host repertoires. Ecological and evolutionary parameters predicted host-parasite associations, but many interactions remain undetected according to NLP. Parasite meta-communities under host adaptive radiation are more specialised and stable while ecological opportunity and ecological fitting have shaped interactions elsewhere. The cichlid-Cichlidogyrus network is a suitable eco-evolutionary study system but future studies should validate our findings in other radiating host-parasite systems.
The dynamics of cyclic populations distributed in space result from the relative strength of synchronising influences and the limited dispersal of destabilising factors (activators and inhibitors), known to cause multi-annual population cycles. However, while each of these have been well studied in isolation, there is limited empirical evidence about how the processes of synchronisation and activation-inhibition act together, largely owing to the scarcity of datasets with sufficient spatial and temporal scale. We assessed a variety of models that could be underlying the spatio-temporal pattern, designed to capture both theoretical and empirical understandings of travelling waves using large-scale (> 35,000 km2), multi-year (2011-2017) field monitoring data on abundances of common vole (Microtus arvalis), a cyclic agricultural rodent pest. We found most support for a pattern formed from the summation of two radial travelling waves with contrasting speeds that together describe population growth rates across the region.