The Probabilistic Niche Model Reveals the Niche Structure and Role of Body Size in a Complex Food Web

The niche model has been widely used to model the structure of complex food webs, and yet the ecological meaning of the single niche dimension has not been explored. In the niche model, each species has three traits, niche position, diet position and feeding range. Here, a new probabilistic niche model, which allows the maximum likelihood set of trait values to be estimated for each species, is applied to the food web of the Benguela fishery. We also developed the allometric niche model, in which body size is used as the niche dimension. About 80% of the links in the empirical data are predicted by the probabilistic niche model, a significant improvement over recent models. As in the niche model, species are uniformly distributed on the niche axis. Feeding ranges are exponentially distributed, but diet positions are not uniformly distributed below the predator. Species traits are strongly correlated with body size, but the allometric niche model performs significantly worse than the probabilistic niche model. The best-fit parameter set provides a significantly better model of the structure of the Benguela food web than was previously available. The methodology allows the identification of a number of taxa that stand out as outliers either in the model's poor performance at predicting their predators or prey or in their parameter values. While important, body size alone does not explain the structure of the one-dimensional niche

Mapping functional traits: comparing abundance and presence-absence estimates at large spatial scales

Efforts to quantify the composition of biological communities increasingly focus on functional traits. The composition of communities in terms of traits can be summarized in several ways. Ecologists are beginning to map the geographic distribution of trait-based metrics from various sources of data, but the maps have not been tested against independent data. Using data for birds of the Western Hemisphere, we test for the first time the most commonly used method for mapping community trait composition – overlaying range maps, which assumes that the local abundance of a given species is unrelated to the traits in question – and three new methods that as well as the range maps include varying degrees of information about interspecific and geographic variation in abundance. For each method, and for four traits (body mass, generation length, migratory behaviour, diet) we calculated community-weighted mean of trait values, functional richness and functional divergence. The maps based on species ranges and limited abundance data were compared with independent data on community species composition from the American Christmas Bird Count (CBC) scheme coupled with data on traits. The correspondence with observed community composition at the CBC sites was mostly positive (62/73 correlations) but varied widely depending on the metric of community composition and method used (R2: 5.6×10−7 to 0.82, with a median of 0.12). Importantly, the commonly-used range-overlap method resulted in the best fit (21/22 correlations positive; R2: 0.004 to 0.8, with a median of 0.33). Given the paucity of data on the local abundance of species, overlaying range maps appears to be the best available method for estimating patterns of community composition, but the poor fit for some metrics suggests that local abundance data are urgently needed to allow more accurate estimates of the composition of communities

Effects of climate, species interactions, and dispersal on decadal colonization and extinction rates of Iberian tree species

We studied the relative importance of climate, abundance of potentially competing species, and dispersal in explaining local colonization and extinction rates of tree species throughout mainland Spain. We used a Bayesian framework to parameterize a patch occupancy model to 23 species censused in 46,596 permanent plots in a 1 × 1 km grid across most Spanish forests. For most species, dispersal was the single best predictor of colonization, whereas climate and dispersal were equally important as predictors of extinction. Precipitation was positively correlated with the colonization rate of 12 out of 13 deciduous broad-leaved species, and negatively correlated with the extinction rate of nine of them. In contrast, precipitation equally decreased colonization and extinction of five out of eight of needle-leaved species (Juniperus and Pinus spp.). There was, however, marked variation among species in the magnitude of these effects, with some species exhibiting contrasting patterns for the colonization and the extinction process. Abundance of competing tree species (= summed plot basal area) was consistently correlated with decreased colonization of all needle-leaved species, and it increased the extinction rate of 6 out of 8 of these species. It had, nonetheless, weak facilitative effect on some broad-leaved species by promoting colonization (3 of 13 species) and decreasing extinction (7 of 13 species). With local colonization and extinction data, non-equilibrial and dynamic species distribution modelling can be improved by incorporating measures of biotic interactions and dispersal effects, along with traditional climate variables.Ministerio de Economía y CompetitividadComunidad de Madri

Effects of climate, species interactions, and dispersal on decadal colonization and extinction rates of Iberian tree species

We studied the relative importance of climate, abundance of potentially competing species, and dispersal in explaining local colonization and extinction rates of tree species throughout mainland Spain. We used a Bayesian framework to parameterize a patch occupancy model to 23 species censused in 46,596 permanent plots in a 1 × 1 km grid across most Spanish forests. For most species, dispersal was the single best predictor of colonization, whereas climate and dispersal were equally important as predictors of extinction. Precipitation was positively correlated with the colonization rate of 12 out of 13 deciduous broad-leaved species, and negatively correlated with the extinction rate of nine of them. In contrast, precipitation equally decreased colonization and extinction of five out of eight of needle-leaved species (Juniperus and Pinus spp.). There was, however, marked variation among species in the magnitude of these effects, with some species exhibiting contrasting patterns for the colonization and the extinction process. Abundance of competing tree species (= summed plot basal area) was consistently correlated with decreased colonization of all needle-leaved species, and it increased the extinction rate of 6 out of 8 of these species. It had, nonetheless, weak facilitative effect on some broad-leaved species by promoting colonization (3 of 13 species) and decreasing extinction (7 of 13 species). With local colonization and extinction data, non-equilibrial and dynamic species distribution modelling can be improved by incorporating measures of biotic interactions and dispersal effects, along with traditional climate variables.Ministerio de Economía y CompetitividadComunidad de Madri

Environmental heterogeneity, bird-mediated directed dispersal, and oak woodland dynamics in Mediterranean Spain

Vegetation dynamics in complex landscapes depend on interactions among\ud environmental heterogeneity, disturbance, habitat fragmentation, and seed dispersal\ud processes. We explore how these features combine to affect the regional abundances and\ud distributions of three Quercus (oak) species in central Spain: Q. faginea (deciduous tree), Q.\ud ilex (evergreen tree), and Q. coccifera (evergreen shrub). We develop and parameterize a\ud stochastic patch occupancy model (SPOM) that, unlike previous SPOMs, includes\ud environmentally driven variation in disturbance and establishment. Dispersal in the model\ud is directed toward local (nearby) suitable habitat patches, following the observed seed-caching\ud behavior of the European Jay. Model parameters were estimated using Bayesian methods and\ud survey data from 12 047 plots. Model simulations were conducted to explore the importance of\ud different dispersal modes (local directed, global directed, local random, global random). The\ud SPOM with local directed dispersal gave a much better fit to the data and reproduced observed\ud regional abundance, abundance–environment correlations, and spatial autocorrelation in\ud abundance for all three species. Model simulations suggest that jay-mediated directed dispersal\ud increases regional abundance and alters species–environment correlations. Local dispersal is\ud estimated to reduce regional abundances, amplify species–environment correlations, and\ud amplify spatial autocorrelation.\ud Parameter estimates and model simulations reveal important species-specific differences in\ud sensitivity to environmental perturbations and dispersal mode. The dominant species Q. ilex is\ud estimated to be highly fecund, but on the edge of its climatic tolerance. Therefore Q. ilex gains\ud little from directed dispersal, suffers little from local dispersal, and is relatively insensitive to\ud changes in habitat cover or disturbance rate; but Q. ilex is highly sensitive to altered drought\ud length. In contrast, the rarest species, Q. coccifera, is well adapted to the climate and soils but\ud has low fecundity; thus, it is highly sensitive to changes in dispersal, habitat cover, and\ud disturbance but insensitive to altered drought length. Finally, Q. faginea is estimated to be\ud both at the edge of its climatic tolerance and to have low fecundity, making it sensitive to all\ud perturbations. Apparently, co-occurring species can exhibit very different interactions among\ud dispersal, environmental characteristics, and physiological tolerances, calling for increased\ud attention to species-specific dynamics in determining regional vegetation responses to\ud anthropogenic perturbations

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

Evaluating the combined effects of climate and land-use change on tree species distributions

A large proportion of the world's biodiversity is reportedly threatened by habitat loss and climate change. However, there are few studies that investigate the interaction between these two threats using empirical data.Here, we investigate interactions between climate change and land use change in the future distribution of 23 dominant tree species in mainland Spain. We simulated changes up to year 2100 using a climate-dependent Stochastic Patch Occupancy Model, parameterized with colonization and extinction events recorded in 46 569 survey plots.We estimated that the distribution of 17 out of 23 tree species are expanding, and hence not at equilibrium with the climate. However, climate change will make the future occupancy of 15 species lower than expected if climate, and habitat, remained stable (baseline scenario).Climate change, when combined with 20% habitat loss, was estimated to reduce species occupancy by an average of 23% if habitat loss is spatially clumped, relative to baseline projections, and by 35% if scattered. If habitat loss occurred in areas already impacted by human activities, species occupancy would be reduced by 26%. Land-use changes leading to habitat gain (i.e. creation through e.g. reforestation), could slightly mitigate the effects of climate change; but a 20% increment in habitat would reduce climate-change-driven losses in species occupancy by only ~3%.Synthesis and applications. The distributions of the most common tree species in mainlandSpain are expanding, but climate change threatens to reduce this expansion by 18% for 15of the 23 studied species. Moreover, if the habitat of these species is simultaneously lost, theoccupancies of all of them will be reduced further, with variation depending on the spatialpattern of the lost habitats. However, we did not detect synergies between climate change andhabitat loss. The combined effect (with 20% habitat loss) was 5–13% less than what it wouldbe if the effects were additive. Importantly, reforestation could partially offset the negativeeffects of climate change, but complete mitigation would require an increase in forested landof 80%, and the prioritization of territories that are less impacted by human activities.Ministerio de Economía y CompetitividadComunidad de Madri

A bestiary of non-linear functions for growth analysis

Plant growth is an essential ecological process, integrating across scales from physiology to community dynamics. Predicting the growth of plants is essential to understand a wide range of ecological issues, including competition, plant-herbivore interactions and ecosystem functioning.
A challenge in modeling plant growth is that growth rates almost universally decrease with increasing size, for a variety of reasons. Traditional analyses of growth are hampered by the need to remain within the structures of linear models, which handle this slowing poorly. We demonstrate the implementation of a variety of non-linear models that are more appropriate for modeling plant growth than are the traditional, linear, models.
Ecological inference is frequently based on growth rates, rather than model parameters. Traditional calculations of absolute and relative growth rates assume that they are invariant with respect to time or biomass, which is almost never valid. We advocate and demonstrate the calculation of function-derived growth rates, which highlight the time- and biomass-varying nature of growth. We further show how uncertainty in estimated parameter values can be propagated to express uncertainty in absolute and relative growth rates. 
The use of non-linear models and function-derived growth rates can facilitate testing novel hypotheses in population and community ecology. Even so, we acknowledge that fitting non-linear models can be tricky. To foster the spread of these methods, we make many recommendations for ecologists to follow when their hypotheses lead them into the subject of plant growth. 
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Influences of Forest Structure, Climate and Species Composition on Tree Mortality across the Eastern US

Few studies have quantified regional variation in tree mortality, or explored whether species compositional changes or within-species variation are responsible for regional patterns, despite the fact that mortality has direct effects on the dynamics of woody biomass, species composition, stand structure, wood production and forest response to climate change. Using Bayesian analysis of over 430,000 tree records from a large eastern US forest database we characterised tree mortality as a function of climate, soils, species and size (stem diameter). We found (1) mortality is U-shaped vs. stem diameter for all 21 species examined; (2) mortality is hump-shaped vs. plot basal area for most species; (3) geographical variation in mortality is substantial, and correlated with several environmental factors; and (4) individual species vary substantially from the combined average in the nature and magnitude of their mortality responses to environmental variation. Regional variation in mortality is therefore the product of variation in species composition combined with highly varied mortality-environment correlations within species. The results imply that variation in mortality is a crucial part of variation in the forest carbon cycle, such that including this variation in models of the global carbon cycle could significantly narrow uncertainty in climate change predictions

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