Human-nature connectedness as a pathway to sustainability: A global meta-analysis.

Internationally agreed sustainability goals are being missed. Here, we conduct global meta-analyses to assess how the extent to which humans see themselves as part of nature-known as human-nature connectedness (HNC)-can be used as a leverage point to reach sustainability. A meta-analysis of 147 correlational studies shows that individuals with high HNC had more pronature behaviours and were significantly healthier than those with low HNC. A meta-analysis of 59 experimental studies shows significant increases in HNC after manipulations involving contact with nature and mindfulness practices. Surprisingly, this same meta-analysis finds no significant effect of environmental education on HNC. Thus, HNC is positively linked to mind-sets that value sustainability and behaviours that enhance it. Further, we argue that HNC can be enhanced by targeted practices, and we identify those most likely to succeed. Our results suggest that enhancing HNC, via promotion of targeted practices, can improve sustainability and should be integrated into conservation policy.

General statistical scaling laws for stability in ecological systems.

Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance. These relationships can be calibrated using random or representative samples measured at individual scales, and projected to predict average stability at other scales across a wide range of contexts. Moreover deviations between observed vs. extrapolated scaling relationships can reveal information about unobserved heterogeneity across time, space, or species. We anticipate that these methods will be useful for cross-study synthesis of stability data, extrapolating measurements to unobserved scales, and identifying underlying causes and consequences of heterogeneity.

Scaling up biodiversity-ecosystem functioning relationships: the role of environmental heterogeneity in space and time.

The biodiversity and ecosystem functioning (BEF) relationship is expected to be scale-dependent. The autocorrelation of environmental heterogeneity is hypothesized to explain this scale dependence because it influences how quickly biodiversity accumulates over space or time. However, this link has yet to be demonstrated in a formal model. Here, we use a Lotka-Volterra competition model to simulate community dynamics when environmental conditions vary across either space or time. Species differ in their optimal environmental conditions, which results in turnover in community composition. We vary biodiversity by modelling communities with different sized regional species pools and ask how the amount of biomass per unit area depends on the number of species present, and the spatial or temporal scale at which it is measured. We find that more biodiversity is required to maintain functioning at larger temporal and spatial scales. The number of species required increases quickly when environmental autocorrelation is low, and slowly when autocorrelation is high. Both spatial and temporal environmental heterogeneity lead to scale dependence in BEF, but autocorrelation has larger impacts when environmental change is temporal. These findings show how the biodiversity required to maintain functioning is expected to increase over space and time.

Biotic homogenization destabilizes ecosystem functioning by decreasing spatial asynchrony.

Our planet is facing significant changes of biodiversity across spatial scales. Although the negative effects of local biodiversity (α diversity) loss on ecosystem stability are well documented, the consequences of biodiversity changes at larger spatial scales, in particular biotic homogenization, that is, reduced species turnover across space (ß diversity), remain poorly known. Using data from 39 grassland biodiversity experiments, we examine the effects of ß diversity on the stability of simulated landscapes while controlling for potentially confounding biotic and abiotic factors. Our results show that higher ß diversity generates more asynchronous dynamics among local communities and thereby contributes to the stability of ecosystem productivity at larger spatial scales. We further quantify the relative contributions of α and ß diversity to ecosystem stability and find a relatively stronger effect of α diversity, possibly due to the limited spatial scale of our experiments. The stabilizing effects of both α and ß diversity lead to a positive diversity-stability relationship at the landscape scale. Our findings demonstrate the destabilizing effect of biotic homogenization and suggest that biodiversity should be conserved at multiple spatial scales to maintain the stability of ecosystem functions and services.

Can biomass distribution across trophic levels predict trophic cascades?

The biomass distribution across trophic levels (biomass pyramid) and cascading responses to perturbations (trophic cascades) are archetypal representatives of the interconnected set of static and dynamical properties of food chains. A vast literature has explored their respective ecological drivers, sometimes generating correlations between them. Here we instead reveal a fundamental connection: both pyramids and cascades reflect the dynamical sensitivity of the food chain to changes in species intrinsic rates. We deduce a direct relationship between cascades and pyramids, modulated by what we call trophic dissipation - a synthetic concept that encodes the contribution of top-down propagation of consumer losses in the biomass pyramid. Predictable across-ecosystem patterns emerge when systems are in similar regimes of trophic dissipation. Data from 31 aquatic mesocosm experiments demonstrate how our approach can reveal the causal mechanisms linking trophic cascades and biomass distributions, thus providing a road map to deduce reliable predictions from empirical patterns.

Disentangling local, metapopulation, and cross-community sources of stabilization and asynchrony in metacommunities.

Asynchronous fluctuations of populations are essential for maintaining stable levels of bio-mass and ecosystem function in landscapes. Yet, understanding the stabilization of metacommunities by asynchrony is complicated by the existence of multiple forms of asynchrony that are typically studied independently: Community ecologists, for instance, focus on asynchrony within and among local communities, while population ecologists emphasize asynchrony of populations in metapopulations. Still, other forms of asynchrony, such as that which underlies the spatial insurance effect, are not captured by any existing analytical frameworks. We therefore developed a framework that would in one analysis unmask the stabilizing roles of local communities and metapopulations and so unify these perspectives. Our framework shows that metacommunity stabilization arises from one local and two regional forms of asynchrony: (1) asynchrony among species of a local community, (2) asynchrony among populations of a metapopulation, and (3) cross-community asynchrony, which is between different species in different local communities and underlies spatial insurance. For each type of stabilization, we derived links to diversity indices and associated diversity-stability relationships. We deployed this framework in a set of rock pool invertebrate metacommunities in Discovery Bay, Jamaica, to partition sources of stabilization and test their dependence on diversity. Cross-community asynchrony was the dominant form of stabilization, accounting for >60% of total metacommunity stabilization despite being undetectable with existing frameworks. Environmental variation influenced types of stabilization through different mechanisms. pH and dissolved oxygen, for example, increased asynchrony by decorrelating local species, while salinity did so by changing the abundance structure of metapopulations. Lastly, all types of asynchrony depended strongly on different types of diversity (alpha, metapopulation, and beta diversity drove local, metapopulation, and cross-community asynchrony, respectively) to produce multiple diversity-stability relationships within metacommunities. Our new partition of metacommunity dynamics highlights how different elements-from local communities to metapopulations-combine to stabilize metacommunities and depend critically on contrasting environmental regimes and diversities. Understanding and balancing these sources of stability in dynamic landscapes is a looming challenge for the future. We suggest that synthetic frameworks which merge ecological perspectives will be essential for grasping and safeguarding the stability of natural systems.

Reconciling biodiversity conservation, food production and farmers' demand in agricultural landscapes.

Efficient management of agricultural management should consider multiple services and stakeholders. Yet, it remains unclear how to guarantee ecosystem services for multiple stakeholders' demands, especially considering the observed biodiversity decline following reductions in semi-natural habitat (SNH), and global change. Here, we use an ecosystem service model of intensively-managed agricultural landscapes to derive the best landscape compositions for different stakeholders' demands, and how they vary with stochasticity and the degree of pollination dependence of crops. We analyse three groups of stakeholders assumed to value different ecosystem services most - individual farmers (crop yield per area), agricultural unions (landscape production) and conservationists (biodiversity). Additionally, we consider a social average scenario that aims at maximizing multifunctionality. Trade-offs among stakeholders' demands strongly depend on the degree of pollination dependence of crops, the strength of environmental and demographic stochasticity, and the relative amount of an ecosystem service demanded by each stakeholder. Intermediate amounts of SNH deliver relatively high levels of the three services (social average). Our analysis further suggests that the current levels of SNH protection lie below these intermediate amounts of SNH in intensively-managed agricultural landscapes. Given the worldwide trends in agriculture and global change, current policies should start to consider factors such as crop type and stochasticity, as they can strongly influence best landscape compositions for different stakeholders. Our results suggest ways of managing landscapes to reconcile several actors' demands and ensure for biodiversity conservation and food production.

Trade-offs in the provisioning and stability of ecosystem services in agroecosystems.

Changes in land use generate trade-offs in the delivery of ecosystem services in agricultural landscapes. However, we know little about how the stability of ecosystem services responds to landscape composition, and what ecological mechanisms underlie these trade-offs. Here, we develop a model to investigate the dynamics of three ecosystem services in intensively managed agroecosystems, i.e., pollination-independent crop yield, crop pollination, and biodiversity. Our model reveals trade-offs and synergies imposed by landscape composition that affect not only the magnitude but also the stability of ecosystem service delivery. Trade-offs involving crop pollination are strongly affected by the degree to which crops depend on pollination and by their relative requirement for pollinator densities. We show conditions for crop production to increase with biodiversity and decreasing crop area, reconciling farmers' profitability and biodiversity conservation. Our results further suggest that, for pollination-dependent crops, management strategies that focus on maximizing yield will often overlook its stability. Given that agriculture has become more pollination-dependent over time, it is essential to understand the mechanisms driving these trade-offs to ensure food security.

An invariability-area relationship sheds new light on the spatial scaling of ecological stability.

The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability-area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log-log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy.

Environmental responses, not species interactions, determine synchrony of dominant species in semiarid grasslands.

Temporal asynchrony among species helps diversity to stabilize ecosystem functioning, but identifying the mechanisms that determine synchrony remains a challenge. Here, we refine and test theory showing that synchrony depends on three factors: species responses to environmental variation, interspecific interactions, and demographic stochasticity. We then conduct simulation experiments with empirical population models to quantify the relative influence of these factors on the synchrony of dominant species in five semiarid grasslands. We found that the average synchrony of per capita growth rates, which can range from 0 (perfect asynchrony) to 1 (perfect synchrony), was higher when environmental variation was present (0.62) rather than absent (0.43). Removing interspecific interactions and demographic stochasticity had small effects on synchrony. For the dominant species in these plant communities, where species interactions and demographic stochasticity have little influence, synchrony reflects the covariance in species' responses to the environment.

Evolutionary responses to environmental change: trophic interactions affect adaptation and persistence.

According to recent reviews, the question of how trophic interactions may affect evolutionary responses to climate change remains unanswered. In this modelling study, we explore the evolutionary dynamics of thermal and plant-herbivore interaction traits in a warming environment. We find the herbivore usually reduces adaptation speed and persistence time of the plant by reducing biomass. However, if the plant interaction trait and thermal trait are correlated, herbivores can create different coevolutionary attractors. One attractor has a warmer plant thermal optimum, and the other a colder one compared with the environment. A warmer plant thermal strategy is given a head start under warming, the only case where herbivores can increase plant persistence under warming. Persistence time of the plant under warming is maximal at small or large thermal niche width. This study shows that considering trophic interactions is necessary and feasible for understanding how ecosystems respond to climate change.

Temporal stability in forest productivity increases with tree diversity due to asynchrony in species dynamics.

Theory predicts a positive relationship between biodiversity and stability in ecosystem properties, while diversity is expected to have a negative impact on stability at the species level. We used virtual experiments based on a dynamic simulation model to test for the diversity-stability relationship and its underlying mechanisms in Central European forests. First our results show that variability in productivity between stands differing in species composition decreases as species richness and functional diversity increase. Second we show temporal stability increases with increasing diversity due to compensatory dynamics across species, supporting the biodiversity insurance hypothesis. We demonstrate that this pattern is mainly driven by the asynchrony of species responses to small disturbances rather than to environmental fluctuations, and is only weakly affected by the net biodiversity effect on productivity. Furthermore, our results suggest that compensatory dynamics between species may enhance ecosystem stability through an optimisation of canopy occupancy by coexisting species.

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities.

Predicting ecosystem stability from community composition and biodiversity.

As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species' responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22-75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability.

Biodiversity and ecosystem stability: a synthesis of underlying mechanisms.

There is mounting evidence that biodiversity increases the stability of ecosystem processes in changing environments, but the mechanisms that underlie this effect are still controversial and poorly understood. Here, we extend mechanistic theory of ecosystem stability in competitive communities to clarify the mechanisms underlying diversity-stability relationships. We first explain why, contrary to a widely held belief, interspecific competition should generally play a destabilising role. We then explore the stabilising effect of differences in species' intrinsic rates of natural increase and provide a synthesis of various potentially stabilising mechanisms. Three main mechanisms are likely to operate in the stabilising effects of biodiversity on ecosystem properties: (1) asynchrony of species' intrinsic responses to environmental fluctuations, (2) differences in the speed at which species respond to perturbations, (3) reduction in the strength of competition. The first two mechanisms involve temporal complementarity between species, while the third results from functional complementarity. Additional potential mechanisms include selection effects, behavioural changes resulting from species interactions and mechanisms arising from trophic or non-trophic interactions and spatial heterogeneity. We conclude that mechanistic trait-based approaches are key to predicting the effects of diversity on ecosystem stability and to bringing the old diversity-stability debate to a final resolution.

How competition affects evolutionary rescue.

Populations facing novel environments can persist by adapting. In nature, the ability to adapt and persist will depend on interactions between coexisting individuals. Here we use an adaptive dynamic model to assess how the potential for evolutionary rescue is affected by intra- and interspecific competition. Intraspecific competition (negative density-dependence) lowers abundance, which decreases the supply rate of beneficial mutations, hindering evolutionary rescue. On the other hand, interspecific competition can aid evolutionary rescue when it speeds adaptation by increasing the strength of selection. Our results clarify this point and give an additional requirement: competition must increase selection pressure enough to overcome the negative effect of reduced abundance. We therefore expect evolutionary rescue to be most likely in communities which facilitate rapid niche displacement. Our model, which aligns to previous quantitative and population genetic models in the absence of competition, provides a first analysis of when competitors should help or hinder evolutionary rescue.

Rapid exploiter-victim coevolution: the race is not always to the swift.

The modeling of coevolutionary races has traditionally been dominated by methods invoking a timescale separation between ecological and evolutionary dynamics, the latter assumed to be much slower than the former. Yet it is becoming increasingly clear that in many cases the two processes occur on similar timescales and that such "rapid" evolution can have profound implications for the dynamics of communities and ecosystems. After briefly reviewing the timescale separations most common in coevolution theory, we use a general model of exploiter-victim coevolution to confront predictions from slow-evolution analysis with Monte Carlo simulations. We show how rapid evolution radically alters the dynamics and outcome of coevolutionary arms races. In particular, a fast-evolving exploiter can enable victim diversification and thereby lose a race it is expected to win. We explain simulation results, using mathematical analysis with relaxed timescale separations. Unusual mutation parameters are not required, since rapid evolution naturally emerges from slow competitive exclusion. Our results point to interesting consequences of exploiter rapid evolution and experimentally testable patterns, while indicating that more attention should be paid to rapid evolution in evolutionary theory.

A resource ratio theory of cooperation.

Resource ratio theory predicts that two species may coexist in the presence of two limiting nutrients provided that each species is limited by the resource it is least able to deplete. We modify this classical competition model to allow interspecific cooperation through trading. We show that resource trade expands the realm of stable coexistence, and that optimal trading partners competitively invade and exclude any other trading or non-trading strategy. We show that natural selection favours evolution towards establishment of a trading relationship so long as partners can establish long-term associations even though cooperation may result in a decrease in abundance of one species. This theory substantively expands traditional applications of resource competition models and suggests additional empirical experimentation.

Plant water use affects competition for nitrogen: why drought favors invasive species in California.

Abstract: Classic resource competition theory typically treats resource supply rates as independent; however, nutrient supplies can be affected by plants indirectly, with important consequences for model predictions. We demonstrate this general phenomenon by using a model in which competition for nitrogen is mediated by soil moisture, with competitive outcomes including coexistence and multiple stable states as well as competitive exclusion. In the model, soil moisture regulates nitrogen availability through soil moisture dependence of microbial processes, leaching, and plant uptake. By affecting water availability, plants also indirectly affect nitrogen availability and may therefore alter the competitive outcome. Exotic annual species from the Mediterranean have displaced much of the native perennial grasses in California. Nitrogen and water have been shown to be potentially limiting in this system. We parameterize the model for a Californian grassland and show that soil moisture-mediated competition for nitrogen can explain the annual species' dominance in drier areas, with coexistence expected in wetter regions. These results are concordant with larger biogeographic patterns of grassland invasion in the Pacific states of the United States, in which annual grasses have invaded most of the hot, dry grasslands in California but perennial grasses dominate the moister prairies of northern California, Oregon, and Washington.