Classifying ecosystem stressor interactions: Theory highlights the data limitations of the additive null model and the difficulty in revealing ecological surprises.

Understanding how multiple co-occurring environmental stressors combine to affect biodiversity and ecosystem services is an on-going grand challenge for ecology. Currently, progress has been made through accumulating large numbers of smaller-scale empirical studies that are then investigated by meta-analyses to detect general patterns. There is particular interest in detecting, understanding and predicting 'ecological surprises' where stressors interact in a non-additive (e.g. antagonistic or synergistic) manner, but so far few general results have emerged. However, the ability of the statistical tools to recover non-additive interactions in the face of data uncertainty is unstudied, so crucially, we do not know how well the empirical results reflect the true stressor interactions. Here, we investigate the performance of the commonly implemented additive null model. A meta-analysis of a large (545 interactions) empirical dataset for the effects of pairs of stressors on freshwater communities reveals additive interactions dominate individual studies, whereas pooling the data leads to an antagonistic summary interaction class. However, analyses of simulated data from food chain models, where the underlying interactions are known, suggest both sets of results may be due to observation error within the data. Specifically, we show that the additive null model is highly sensitive to observation error, with non-additive interactions being reliably detected at only unrealistically low levels of data uncertainty. Similarly, plausible levels of observation error lead to meta-analyses reporting antagonistic summary interaction classifications even when synergies co-dominate. Therefore, while our empirical results broadly agree with those of previous freshwater meta-analyses, we conclude these patterns may be driven by statistical sampling rather than any ecological mechanisms. Further investigation of candidate null models used to define stressor-pair interactions is essential, and once any artefacts are accounted for, the so-called 'ecological surprises' may be more frequent than was previously assumed.

Global effects of land use on local terrestrial biodiversity.

Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

Beyond the fast-slow continuum: demographic dimensions structuring a tropical tree community.

Life-history theory posits that trade-offs between demographic rates constrain the range of viable life-history strategies. For coexisting tropical tree species, the best established demographic trade-off is the growth-survival trade-off. However, we know surprisingly little about co-variation of growth and survival with measures of reproduction. We analysed demographic rates from seed to adult of 282 co-occurring tropical tree and shrub species, including measures of reproduction and accounting for ontogeny. Besides the well-established fast-slow continuum, we identified a second major dimension of demographic variation: a trade-off between recruitment and seedling performance vs. growth and survival of larger individuals (≥ 1 cm dbh) corresponding to a 'stature-recruitment' axis. The two demographic dimensions were almost perfectly aligned with two independent trait dimensions (shade tolerance and size). Our results complement recent analyses of plant life-history variation at the global scale and reveal that demographic trade-offs along multiple axes act to structure local communities.

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Understanding the value of plant diversity for ecosystem functioning through niche theory.

Biodiversity experiments have generated robust empirical results supporting the hypothesis that ecosystems function better when they contain more species. Given that ecosystems provide services that are valued by humans, this inevitably suggests that the loss of species from natural ecosystems could diminish their value. This raises two important questions. First, will experimental results translate into the real world, where species are being lost at an alarming rate? And second, what are the benefits and pitfalls of such valuation exercises? We argue that the empirical results obtained in experiments are entirely consistent with well-established theories of species coexistence. We then examine the current body of work through the lens of niche theory and highlight where closer links with theory could open up opportunities for future research. We argue that niche theory predicts that diversity-functioning relationships are likely to be stronger (and require more species) in the field than in simplified experimental settings. However, we caution that while many of the biological processes that promote coexistence can also generate diversity-function relationships, there is no simple mapping between the two. This implies that valuation exercises need to proceed with care.

Synergistic impacts of habitat loss and fragmentation on model ecosystems.

Habitat loss and fragmentation are major threats to biodiversity, yet separating their effects is challenging. We use a multi-trophic, trait-based, and spatially explicit general ecosystem model to examine the independent and synergistic effects of these processes on ecosystem structure. We manipulated habitat by removing plant biomass in varying spatial extents, intensities, and configurations. We found that emergent synergistic interactions of loss and fragmentation are major determinants of ecosystem response, including population declines and trophic pyramid shifts. Furthermore, trait-mediated interactions, such as a disproportionate sensitivity of large-sized organisms to fragmentation, produce significant effects in shaping responses. We also show that top-down regulation mitigates the effects of land use on plant biomass loss, suggesting that models lacking these interactions-including most carbon stock models-may not adequately capture land-use change impacts. Our results have important implications for understanding ecosystem responses to environmental change, and assessing the impacts of habitat fragmentation.

Is 'peak N' key to understanding the timing of flowering in annual plants?

Flowering time in annual plants has large fitness consequences and has been the focus of theoretical and empirical study. Previous theory has concluded that flowering time has evolved over evolutionary time to maximize fitness over a particular season length. We introduce a new model where flowering is cued by a growth-rate rule (peak nitrogen (N)). Flowering is therefore sensitive to physiological parameters and to current environmental conditions, including N availability and the presence of competitors. The model predicts that, when overall conditions are suitable for flowering, plants should never flower after 'peak N', the point during development when the whole-plant N uptake rate reaches its maximum. Our model further predicts correlations between flowering time and vegetative growth rates, and that the response to increased N depends heavily on how this extra N is made available. We compare our predictions to observations in the literature. We suggest that annual plants may have evolved to use growth-rate rules as part of the cue for flowering, allowing them to smoothly and optimally adjust their flowering time to a wide range of local conditions. If so, there are widespread implications for the study of the molecular biology behind flowering pathways.

Modelling land cover change in the Brazilian Amazon: temporal changes in drivers and calibration issues.

Land cover change (LCC) models are used in many studies of human impacts on the environment, but knowing how well these models predict observed changes in the landscape is a challenge. We used nearly three decades of LCC maps to run several LCC simulations to: (1) determine which parameters associated with drivers of LCC (e.g. roads) get selected for which transition (forest to deforested, regeneration to deforested or deforested to regeneration); (2) investigate how the parameter values vary through time with respect to the different activities (e.g. farming); and (3) quantify the influence of choosing a particular time period for model calibration and validation on the performance of LCC models. We found that deforestation of primary forests tends to occur along roads (included in 95 % of models) and outside protected areas (included in all models), reflecting farming establishment. Regeneration tends to occur far from roads (included in 78 % of the models) and inside protected areas (included in 38 % of the models), reflecting the processes of land abandonment. Our temporal analysis of model parameters revealed a degree of variation through time (e.g. effectiveness of protected areas rose by 73 %, p < 0.001), but for the majority of parameters there was no significant trend. The degree to which model predictions agreed with observed change was heavily dependent on the year used for calibration (p < 0.001). The next generation of LCC models may need to embed trends in parameter values to allow the processes determining LCC to change through time and exert their influence on model predictions.

Ecological traits affect the response of tropical forest bird species to land-use intensity.

Land-use change is one of the main drivers of current and likely future biodiversity loss. Therefore, understanding how species are affected by it is crucial to guide conservation decisions. Species respond differently to land-use change, possibly related to their traits. Using pan-tropical data on bird occurrence and abundance across a human land-use intensity gradient, we tested the effects of seven traits on observed responses. A likelihood-based approach allowed us to quantify uncertainty in modelled responses, essential for applying the model to project future change. Compared with undisturbed habitats, the average probability of occurrence of bird species was 7.8 per cent and 31.4 per cent lower, and abundance declined by 3.7 per cent and 19.2 per cent in habitats with low and high human land-use intensity, respectively. Five of the seven traits tested affected the observed responses significantly: long-lived, large, non-migratory, primarily frugivorous or insectivorous forest specialists were both less likely to occur and less abundant in more intensively used habitats than short-lived, small, migratory, non-frugivorous/insectivorous habitat generalists. The finding that species responses to land use depend on their traits is important for understanding ecosystem functioning, because species' traits determine their contribution to ecosystem processes. Furthermore, the loss of species with particular traits might have implications for the delivery of ecosystem services.

Plant growth rates and seed size: a re-evaluation.

Small-seeded plant species are often reported to have high relative growth rate or RGR. However, because RGR declines as plants grow larger, small-seeded species could achieve higher RGR simply by virtue of their small size. In contrast, size-standardized growth rate or SGR factors out these size effects. Differences in SGR can thus only be due to differences in morphology, allocation, or physiology. We used nonlinear regression to calculate SGR for comparison with RGR for 10 groups of species spanning a wide range of life forms. We found that RGR was negatively correlated with seed mass in nearly all groups, but the relationship between SGR and seed mass was highly variable. We conclude that small-seeded species only sometimes possess additional adaptations for rapid growth over and above their general size advantage.

The probabilistic niche model reveals substantial variation in the niche structure of empirical food webs.

The structure of food webs, complex networks of interspecies feeding interactions, plays a crucial role in ecosystem resilience and function, and understanding food web structure remains a central problem in ecology. Previous studies have shown that key features of empirical food webs can be reproduced by low-dimensional "niche" models. Here we examine the form and variability of food web niche structure by fitting a probabilistic niche model to 37 empirical food webs, a much larger number of food webs than used in previous studies. The model relaxes previous assumptions about parameter distributions and hierarchy and returns parameter estimates for each species in each web. The model significantly outperforms previous niche model variants and also performs well for several webs where a body-size-based niche model performs poorly, implying that traits other than body size are important in structuring these webs' niche space. Parameter estimates frequently violate previous models' assumptions: in 19 of 37 webs, parameter values are not significantly hierarchical, 32 of 37 webs have nonuniform niche value distributions, and 15 of 37 webs lack a correlation between niche width and niche position. Extending the model to a two-dimensional niche space yields networks with a mixture of one- and two-dimensional niches and provides a significantly better fit for webs with a large number of species and links. These results confirm that food webs are strongly niche-structured but reveal substantial variation in the form of the niche structuring, a result with fundamental implications for ecosystem resilience and function.

Facultative nitrogen fixation by canopy legumes in a lowland tropical forest.

Symbiotic dinitrogen (N(2)) fixation is often invoked to explain the N richness of tropical forests as ostensibly N(2)-fixing trees can be a major component of the community. Such arguments assume N(2) fixers are fixing N when present. However, in laboratory experiments, legumes consistently reduce N(2) fixation in response to increased soil N availability. These contrasting views of N(2) fixation as either obligate or facultative have drastically different implications for the N cycle of tropical forests. We tested these models by directly measuring N(2)-fixing root nodules and nitrogenase activity of individual canopy-dominant legume trees (Inga sp.) across several lowland forest types. Fixation was substantial in disturbed forests and some gaps but near zero in the high N soils of mature forest. Our findings suggest that canopy legumes closely regulate N(2) fixation, leading to large variations in N inputs across the landscape, and low symbiotic fixation in mature forests despite abundant legumes.

Predicting and understanding forest dynamics using a simple tractable model.

The perfect-plasticity approximation (PPA) is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the eight most common species on each of four soil types in the US Lake states (Michigan, Wisconsin, and Minnesota) by using short-term (

Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations.

*Second-generation Dynamic Global Vegetation Models (DGVMs) have recently been developed that explicitly represent the ecological dynamics of disturbance, vertical competition for light, and succession. Here, we introduce a modified second-generation DGVM and examine how the representation of demographic processes operating at two-dimensional spatial scales not represented by these models can influence predicted community structure, and responses of ecosystems to climate change. *The key demographic processes we investigated were seed advection, seed mixing, sapling survival, competitive exclusion and plant mortality. We varied these parameters in the context of a simulated Amazon rainforest ecosystem containing seven plant functional types (PFTs) that varied along a trade-off surface between growth and the risk of starvation induced mortality. *Varying the five unconstrained parameters generated community structures ranging from monocultures to equal co-dominance of the seven PFTs. When exposed to a climate change scenario, the competing impacts of CO(2) fertilization and increasing plant mortality caused ecosystem biomass to diverge substantially between simulations, with mid-21st century biomass predictions ranging from 1.5 to 27.0 kg C m(-2). *Filtering the results using contemporary observation ranges of biomass, leaf area index (LAI), gross primary productivity (GPP) and net primary productivity (NPP) did not substantially constrain the potential outcomes. We conclude that demographic processes represent a large source of uncertainty in DGVM predictions.

Unlocking the forest inventory data: relating individual tree performance to unmeasured environmental factors.

Geographically extensive forest inventories, such as the USDA Forest Service's Forest Inventory and Analysis (FIA) program, contain millions of individual tree growth and mortality records that could be used to develop broad-scale models of forest dynamics. A limitation of inventory data, however, is that individual-level measurements of light (L) and other environmental factors are typically absent. Thus, inventory data alone cannot be used to parameterize mechanistic models of forest dynamics in which individual performance depends on light, water, nutrients, etc. To overcome this limitation, we developed methods to estimate species-specific parameters (thetaG) relating sapling growth (G) to L using data sets in which G, but not L, is observed for each sapling. Our approach involves: (1) using calibration data that we collected in both eastern and western North America to quantify the probability that saplings receive different amounts of light, conditional on covariates x that can be obtained from inventory data (e.g., sapling crown class and neighborhood crowding); and (2) combining these probability distributions with observed G and x to estimate thetaG using Bayesian computational methods. Here, we present a test case using a data set in which G, L, and x were observed for saplings of nine species. This test data set allowed us to compare estimates of thetaG obtained from the standard approach (where G and L are observed for each sapling) to our method (where G and x, but not L, are observed). For all species, estimates of thetaG obtained from analyses with and without observed L were similar. This suggests that our approach should be useful for estimating light-dependent growth functions from inventory data that lack direct measurements of L. Our approach could be extended to estimate parameters relating sapling mortality to L from inventory data, as well as to deal with uncertainty in other resources (e.g., water or nutrients) or environmental factors (e.g., temperature).

Different but equal: the implausible assumption at the heart of neutral theory.

1. The core assumption of neutral theory is that all individuals in a community have equal fitness regardless of species, and regardless of the species composition of the community. But, real communities consist of species exhibiting large trait differences; hence these differences must be subject to perfect fitness-equalizing trade-offs for neutrality to hold. 2. Here we explain that perfect equalizing trade-offs are extremely unlikely to occur in reality, because equality of fitness among species is destroyed by: (i) any deviation in the functional form of the trade-off away from the one special form that gives equal fitness; (ii) spatial or temporal variation in performance; (iii) random species differences in performance. 3. In the absence of the density-dependent processes stressed by traditional niche-based community ecology, communities featuring small amounts of (i) or (ii) rapidly lose trait variation, becoming dominated by species with similar traits, and exhibit substantially lower species richness compared to the neutral case. Communities featuring random interspecific variation in traits (iii) lose all but a few fortuitous species. 4. Thus neutrality should be viewed, a priori, as a highly improbable explanation for the long-term co-occurrence of measurably different species within ecological communities. In contrast, coexistence via niche structure and density dependence, is robust to species differences in baseline fitness, and so remains plausible. 5. We conclude that: (i) co-occurring species will typically exhibit substantial differences in baseline fitness even when (imperfect) equalizing trade-offs have been taken into account; (ii) therefore, communities must be strongly niche structured, otherwise they would lose both trait variation and species richness; (iii) nonetheless, even in strongly niche-structured communities, it is possible that the abundance of species with similar traits are at least partially free to drift.

Modelling parameter uncertainty reveals bushmeat yields versus survival trade-offs in heavily-hunted duiker Cephalophus spp.

Reliably predicting sustainable exploitation levels for many tropical species subject to hunting remains a difficult task, largely because of the inherent uncertainty associated with estimating parameters related to both population dynamics and hunting pressure. Here, we investigate a modelling approach to support decisions in bushmeat management which explicitly considers parameter uncertainty. We apply the approach to duiker Cephalophus spp., assuming either a constant quota-based, or a constant proportional harvesting, strategy. Within each strategy, we evaluate different hunting levels in terms of both average yield and survival probability, over different time horizons. Under quota-based harvesting, considering uncertainty revealed a trade-off between yield and extinction probability that was not evident when ignoring uncertainty. The highest yield was returned by a quota that implied a 40% extinction risk, whereas limiting extinction risk to 10% reduced yield by 50%-70%. By contrast, under proportional harvesting, there was no trade-off between yield and extinction probability. The maximum proportion returned a yield comparable with the maximum possible under quota-based harvesting, but with extinction risk below 10%. However, proportional harvesting can be harder to implement in practice because it depends on an estimate of population size. In both harvesting approaches, predicted yields were highly right-skewed with median yields differing from mean yields, implying that decision outcomes depend on attitude to risk. The analysis shows how an explicit consideration of all available information, including uncertainty, can, as part of a wider process involving multiple stakeholders, help inform harvesting policies.

Non-linear changes in modelled terrestrial ecosystems subjected to perturbations.

Perturbed ecosystems may undergo rapid and non-linear changes, resulting in 'regime shifts' to an entirely different ecological state. The need to understand the extent, nature, magnitude and reversibility of these changes is urgent given the profound effects that humans are having on the natural world. General ecosystem models, which simulate the dynamics of ecosystems based on a mechanistic representation of ecological processes, provide one novel way to project ecosystem changes across all scales and trophic levels, and to forecast impact thresholds beyond which irreversible changes may occur. We model ecosystem changes in four terrestrial biomes subjected to human removal of plant biomass, such as occurs through agricultural land-use change. We find that irreversible, non-linear responses commonly occur where removal of vegetation exceeds 80% (a level that occurs across nearly 10% of the Earth's land surface), especially for organisms at higher trophic levels and in less productive ecosystems. Very large, irreversible changes to ecosystem structure are expected at levels of vegetation removal akin to those in the most intensively used real-world ecosystems. Our results suggest that the projected twenty-first century rapid increases in agricultural land conversion may lead to widespread trophic cascades and in some cases irreversible changes to ecosystem structure.

The demography of range boundaries versus range cores in eastern US tree species.

Regional species-climate correlations are well documented, but little is known about the ecological processes responsible for generating these patterns. Using the data from over 690,000 individual trees I estimated five demographic rates--canopy growth, understorey growth, canopy lifespan, understorey lifespan and per capita reproduction--for 19 common eastern US tree species, within the core and the northern and southern boundaries, of the species range. Most species showed statistically significant boundary versus core differences in most rates at both boundary types. Differences in canopy and understorey growth were relatively small in magnitude but consistent among species, being lower at the northern (average -17%) and higher at the southern (average +12%) boundaries. Differences in lifespan were larger in magnitude but highly variable among species, except for a marked trend for reduced canopy lifespan at the northern boundary (average -49%). Differences in per capita reproduction were large and statistically significant for some species, but highly variable among species. The rate estimates were combined to calculate two performance indices: R(0) (a measure of lifetime fitness in the absence of competition) was consistently lower at the northern boundary (average -86%) whereas Z* (a measure of competitive ability in closed forest) showed no sign of a consistent boundary-core difference at either boundary.