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The sum of Akaike weights (SW) is often used to quantify relative variable importance (RVI) within the information-theoretic (IT) multimodel inference framework. A recent study (Galipaud et al. 2014, Methods in Ecology and Evolution 5: 983) questioned the validity of the SW approach. Regrettably, this study is flawed because SW was evaluated with an inappropriate benchmark. Irrespective of this study's methodological issues, RVI metrics based on the relative contribution of explanatory variables in explaining the variance in the response variable (partitioned R2-based) are lacking in multimodel inference., We re-evaluated the validity of SW by repeating Galipaud et al.'s experiment but with an appropriate benchmark. When explanatory variables are uncorrelated, the quantity that SW estimates (i.e. the probability that a variable is included in the actual best IT model) is monotonically related to squared zero-order correlation coefficients ( r2) between explanatory variables and the response variable. The degree of correspondence between SW and r2 rankings (not values) of variables in data sets with uncorrelated explanatory variables was therefore used as a benchmark to evaluate the validity of SW as a RVI metric. To address the lack of partitioned R2-based RVI metrics in multimodel inference, we proposed 2 metrics: (a) I weighted, the average model probability-weighted partitioned R2; and (b) I best, the partitioned R2 derived from the best IT model. We performed Monte Carlo simulations to evaluate the utility of I weighted and I best versus partitioned R2 derived from the global model ( I global)., SW rankings matched r2 rankings of variables; therefore, SW is a valid measure of RVI. Among partitioned R2-based metrics, I weighted and I global were generally more accurate in estimating the population partitioned R2. I weighted performed better when explanatory variables were uncorrelated, whereas I global was better in smaller data sets with correlated explanatory variables. To improve the utility of I weighted in such data sets, we proposed approaches to eliminate or reduce the influence of correlated variables., Despite recent criticisms, our results show that SW is a valid RVI metric. To quantify RVI in terms of the R2 explained by each variable, I weighted and I global are the preferred RVI metrics. [ABSTRACT FROM AUTHOR]

Nutrient enrichment of native grasslands can promote invasion by exotic plant species, leading to reduced biodiversity and altered ecosystem function. Empirical evidence suggests that positive feedbacks may make such transitions difficult to reverse. We developed a mathematical model of grassland dynamics in which one group of species (native) is a better competitor for nitrogen (N) and another group (exotic) is a better competitor for light. We parameterized the model for a grassland community and reproduced observed transitions from a native- to an exotic-dominated state under N loading. Within known bounds of parameter values, both smooth and hysteretic transitions are plausible. The model also predicts that N loading alone is insufficient to achieve a transition to an exotic-dominated state on a timescale relevant to grassland management (a few decades), and that therefore some other disturbance (e.g., fire suppression or heaving grazing) must be present to accelerate it. The model predicts that to restore a grassland to a native-dominated state after N inputs have been reduced, fire and carbon supplements would be most effective. Further field research in N-enriched invaded grasslands is required to establish the strengths of positive feedbacks and, in turn, the consequences of anthropogenic modification of grasslands worldwide. [ABSTRACT FROM AUTHOR]

The compositional complexity of an assemblage is not expressible as a single number; standard measures such as diversities (Hill numbers) and entropies (Rényi entropies and Tsallis entropies) vary in their order q which determines the measures' emphasis on rare or common species. Ranking and comparing assemblages depend on the choice of q. Rather than selecting one or a few measures to describe an assemblage, it is preferable to convey the complete story by presenting a continuous profile, a plot of diversity or entropy as a function of q ≥ 0. This makes it easy to visually compare the compositional complexities of multiple assemblages and to judge the evenness of the relative abundance distributions of the assemblages. In practice, the profile is plotted for all values of q from 0 to q = 3 or 4 (beyond which it generally changes little)., These profiles are usually generated by substituting species sample proportions into the complexity measures. However, this empirical approach typically underestimates the true profile for low values of q, because samples usually miss some of the assemblage's species due to under-sampling. Although bias-reduction methods exist for individual measures of order q = 0, 1 and 2, there has been no analytic method that unifies these bias-corrected estimates into a continuous profile., For incomplete sampling data, this work proposes a novel analytic method to obtain accurate, continuous, low-bias diversity and entropy profiles with focus on low orders of q (0 ≤ q ≤ 3). Our approach is based on reformulating the diversity and entropy of any order q in terms of the successive discovery rates of new species with respect to sample size, that is the successive slopes of the species accumulation curve. A bootstrap method is applied to obtain approximate variances of our proposed profiles and to construct the associated confidence intervals., Extensive simulations from theoretical models and real surveys show that the proposed profiles greatly reduce under-sampling bias and have substantially lower bias and mean-squared error than the empirical profile, especially for q ≤ 1. Our method is also extended to deal with incidence data. [ABSTRACT FROM AUTHOR]

The niche is a fundamental ecological concept that underpins many explanations of patterns of biodiversity. The complexity of niche processes in ecological systems, however, means that it is difficult to capture them accurately in theoretical models of community assembly. In this study, we build upon simple neutral biodiversity models by adding the important ingredient of overlapping niche structure. Our model is spatially implicit and contains a fixed number of equal-sized habitats. Each species in the metacommunity arises through a speciation event; at which time, it is randomly assigned a fundamental niche or set of environments/habitats in which it can persist. Within each habitat, species compete with other species that have different but overlapping fundamental niches. Species abundances then change through ecological drift; each, however, is constrained by its maximum niche breadth and by the presence of other species in its habitats. Using our model, we derive analytical expressions for steady-state species abundance distributions, steady-state distributions of niche breadth across individuals and across species, and dynamic distributions of niche breadth across species. With this framework, we identify the conditions that produce the log-series species abundance distribution familiar from neutral models. We then identify how overlapping niche structure can lead to other species abundance distributions and, in particular, ask whether these new distributions differ significantly from species abundance distributions predicted by non-overlapping niche models. Finally, we extend our analysis to consider additional distributions associated with realized niche breadths. Overall, our results show that models with overlapping niches can exhibit behavior similar to neutral models, with the caveat that species with narrow fundamental niche breadths will be very rare. If narrow-niche species are common, it must be because they are in a non-overlapping niche or have countervailing advantages over broad-niche species. This result highlights the role that niches can play in establishing demographic neutrality. [ABSTRACT FROM AUTHOR]

Many questions in ecology and evolutionary biology consider response variables that are functions (e.g. species-abundance distributions) rather than a single scalar value (e.g. species richness). Although methods for analysing function-valued data have been available for several decades, ecological and evolutionary applications are rare., We outline methods for regression when the response variable is a function ('function regression') and introduce the r package FREE, which focuses on straightforward implementation and interpretation of function regression analyses. Several computational methods are implemented, including machine learning and several Bayesian methods. We compare different methods using simulated data and real ecological data on individual-size distributions ( ISDs) of fish and trees., No single method performed best overall, with several performing equally well for a given data set. Which method to use depends on sample sizes and the questions being considered; in many cases, a consensus approach should be used to combine or compare fitted models., Function regression allows the direct modelling of many function-valued data (e.g. species-abundance distributions) rather than having to reduce those functions to a single scalar response variable (e.g. species diversity or functional diversity indices). Our ecological examples using ISD data show that larger rivers support more-even fish-size distributions than smaller rivers and that low initial planting densities lead to more-even tree-size distributions than high initial planting densities. Function regression provided more informative and intuitive interpretations of these data than conventional non-function-valued approaches. [ABSTRACT FROM AUTHOR]

The α-, β-, γ-diversity decomposition methodology is commonly used to investigate changes in diversity over space or time but rarely conjointly. However, with the ever-increasing availability of large-scale biodiversity monitoring data, there is a need for a sound methodology capable of simultaneously accounting for spatial and temporal changes in diversity., Using the properties of Chao's index, we adapted Rao's framework of diversity decomposition between orthogonal dimensions to a multiplicative α-, β-, γ-decomposition of functional or phylogenetic diversity over space and time, thereby combining their respective properties. We also developed guidelines for interpreting both temporal and spatial β-diversities and their interaction., We characterized the range of β-diversity estimates and their relationship to the nested decomposition of diversity. Using simulations, we empirically demonstrated that temporal and spatial β-diversities are independent from each other and from α- and γ-diversities when the study design is balanced, but not otherwise. Furthermore, we showed that the interaction term between the temporal and the spatial β-diversities lacked such properties., We illustrated our methodology with a case study of the spatio-temporal dynamics of functional diversity in bird assemblages in four regions of France. Based on these data, our method makes it possible to discriminate between regions experiencing different diversity changes in time. Our methodology may therefore be valuable for comparing diversity changes over space and time using large-scale data sets of repeated surveys. [ABSTRACT FROM AUTHOR]

Artificial illumination of the night is increasing globally. There is growing evidence of a range of ecological impacts of artificial light and awareness of light pollution as a significant environmental issue. In urban and suburban areas, complex spatial patterns of light sources, structures and vegetation create a highly heterogeneous night-time light environment for plants and animals., We developed a method for modelling the night-time light environment at a high spatial resolution in a small urban area for ecological studies. We used the position and height of street lights, and digital terrain and surface models, to predict the direct light intensity at different wavelengths at different heights above the ground surface., Validation against field measurements of night-time light showed that modelled light intensities in the visible and ultraviolet portions of the spectrum were accurate., We show how this model can be used to map biologically relevant lightscapes across an urban landscape. We also illustrate the utility of the model using night-time light maps as resistance surfaces in the software package circuitscape to predict potential movement of model nocturnal species between habitat patches and to identify key corridors and barriers to movement and dispersal., Understanding the ecological effects of artificial light requires knowledge of the light environment experienced by organisms throughout the diurnal and annual cycles, during periods of activity and rest and during different life stages. Our approach to high-resolution mapping of artificial lightscapes can be adapted to the sensitivity to light of different species and to other urban, suburban, rural and industrial landscapes. [ABSTRACT FROM AUTHOR]

The relationship between species richness and ecosystem function, as measured by productivity or biomass, is of long-standing theoretical and practical interest in ecology. This is especially true for forests, which represent a majority of global biomass, productivity and biodiversity., Here, we conduct an analysis of relationships between tree species richness, biomass and productivity in 25 forest plots of area 8-50 ha from across the world. The data were collected using standardized protocols, obviating the need to correct for methodological differences that plague many studies on this topic., We found that at very small spatial grains (0.04 ha) species richness was generally positively related to productivity and biomass within plots, with a doubling of species richness corresponding to an average 48% increase in productivity and 53% increase in biomass. At larger spatial grains (0.25 ha, 1 ha), results were mixed, with negative relationships becoming more common. The results were qualitatively similar but much weaker when we controlled for stem density: at the 0.04 ha spatial grain, a doubling of species richness corresponded to a 5% increase in productivity and 7% increase in biomass. Productivity and biomass were themselves almost always positively related at all spatial grains., Synthesis. This is the first cross-site study of the effect of tree species richness on forest biomass and productivity that systematically varies spatial grain within a controlled methodology. The scale-dependent results are consistent with theoretical models in which sampling effects and niche complementarity dominate at small scales, while environmental gradients drive patterns at large scales. Our study shows that the relationship of tree species richness with biomass and productivity changes qualitatively when moving from scales typical of forest surveys (0.04 ha) to slightly larger scales (0.25 and 1 ha). This needs to be recognized in forest conservation policy and management. [ABSTRACT FROM AUTHOR]

The large-scale distribution patterns of alien invasive plants (AIP) can provide key information and a theoretical basis for management strategies, including the prevention of invasions, the control and eradication of established AIPs, and the identification of areas at high risk of invasion. This study aims to quantify distribution patterns of AIP in China, to develop approaches that measure the social, economic, and ecological impacts, and to identify areas that are at higher risk of plant invasion. Based on published literature, there were 384 AIPs in China, representing 233 genera from 66 families. Climatic factors were among the primary factors determining AIPs' overall distribution patterns. The majority of AIPs were tropically distributed in China, meaning that they were mainly restricted to southern China. Temperate-distributed AIPs, those distributed only or predominantly in northern China, were fewer but had higher average rates of spread than tropically distributed AIPs. Average ecological and economic impact per AIP was negatively correlated with AIP richness, meaning that areas with relatively few AIPs nevertheless have some of the most detrimental ones. Our comparative evaluation showed that the risk of invasion differed among regions of China, with high-risk areas in southern China (Yunnan, Guangxi, and Guangdong) and central coastal areas of eastern China (Shandong, Hebei, and Jiangsu). In the context of climate change, areas around latitudes of 33° N, including Hebei, Shandong, Henan, and Jiangsu, should be given more attention for the control and prevention of plant invasions. Predictions of high-risk areas for future invasions differed depending on the scale of aggregation and the evaluation index, indicating that invasive risk assessments should be based on multiple factors. [ABSTRACT FROM AUTHOR]

Many problems in ecology require the estimation of rates of dispersal of individuals or propagules across physical boundaries. Such problems arise in invasion ecology, forest dynamics, and the neutral theory of biodiversity. In a forest plot, for example, one might ask what proportion of the seed rain originates from outside the plot. A recent study presented analytical approximations that relate the rate of immigration across a boundary to plot geometry and to the parameters of a dispersal kernel in one- and two-dimensional environments. In this study, we provide a more rigorous derivation of these expressions and we derive a more general expression that applies in environments of arbitrary dimension. We discuss potential applications of the one-, two-, and three-dimensional results to ecological problems. [ABSTRACT FROM AUTHOR]

The article presents a study regarding the use of info-gap theory to choose between two alternative land uses such as the establishment of an exotic timber plantation and native vegetation conservation. The study made use the linear equations by ordinary least-squares regression to define the reward functions for the two alternative land-use decisions. The result of the study shows the sensitivity of the info-gap analyses to the choice of uncertainty model.

central challenge in community ecology is to predict patterns of biodiversity with mechanistic models. The neutral model of biodiversity is a simple model that appears to provide parsimonious and accurate predictions of biodiversity patterns in some ecosystems, even though it ignores processes such as species interactions and niche structure. In a recent paper, we used analytical techniques to reveal why the mean predictions of the neutral model are robust to niche structure in high diversity but not low-diversity ecosystems. In the present paper, we explore this phenomenon further by generating stochastic simulated data from a spatially implicit hybrid niche-neutral model across different speciation rates. We compare the resulting patterns of species richness and abundance with the patterns expected from a pure neutral and a pure niche model. As the speciation rate in the hybrid model increases, we observe a surprisingly rapid transition from an ecosystem in which diversity is almost entirely governed by niche structure to one in which diversity is statistically indistinguishable from that of the neutral model. Because the transition is rapid, one prediction of our abstract model is that high-diversity ecosystems such as tropical forests can be approximated by one simple model-the neutral model-whereas low-diversity ecosystems such as temperate forests can be approximated by another simple model-the niche model. Ecosystems that require the hybrid model are predicted to be rare, occurring only over a narrow range of speciation rates. [ABSTRACT FROM AUTHOR]

Understanding the factors that govern the commonness and rarity of individual species is a central challenge in community ecology. Empirical studies have often found that abundance is related to traits associated with competitive ability and suitability to the local environment and, more recently, also to negative conspecific density dependence. Here, we construct a theoretical framework to show how a species' abundance is, in general, expected to be dependent on its per-capita growth rate when rare and the rate at which its growth rate declines with increasing abundance (strength of stabilization). We argue that per-capita growth rate when rare can be interpreted as competitive ability and that strength of stabilization largely reflects negative conspecific inhibition. We then analyze a simple spatially implicit model in which each species is defined by three parameters that affect its juvenile survival: its generalized competitive effect on others, its generalized response to competition, and an additional negative effect on conspecifics. This model facilitates the stable coexistence of an arbitrarily large number of species and qualitatively reproduces empirical relationships between abundance, competitive ability, and negative conspecific density dependence. Our results provide theoretical support for the combined roles of competitive ability and negative density dependence in the determination of species abundances in real ecosystems, and suggest new avenues of research for understanding abundance in models and in real communities. [ABSTRACT FROM AUTHOR]

A fundamental challenge in ecology is to understand the mechanisms that govern patterns of relative species abundance. Previous numerical simulations have suggested that complex niche-structured models produce species abundance distributions (SADs) that are qualitatively similar to those of very simple neutral models that ignore differences between species. However, in the absence of an analytical treatment of niche models, one cannot tell whether the two classes of model produce the same patterns via similar or different mechanisms. We present an analytical proof that, in the limit as diversity becomes large, a strong niche model give rises to exactly the same asymptotic form of SAD as the neutral model, and we verify the analytical predictions for a Panamanian tropical forest data set. Our results strongly suggest that neutral processes drive patterns of relative species abundance in high-diversity ecological communities, even when strong niche structure exists. However, neutral theory cannot explain what generates high diversity in the first place, and it may not be valid in low-diversity communities. Our results also confirm that neutral theory cannot be used to infer an absence of niche structure or to explain ecosystem function. [ABSTRACT FROM AUTHOR]

Carbon sequestration by afforestation can help mitigate global climate change but may have adverse environmental and economic impacts in some regions. For example, economic incentives for carbon sequestration may encourage the expansion of Pinus radiata timber plantations in the Fynbos biome of South Africa, with negative consequences for water supply and biodiversity. I built a dynamic ecological–economic model to investigate whether afforestation of a Fynbos catchment with Pinus radiata is economically viable when the potential benefits of carbon sequestration and timber production are balanced against the losses to water supply. I found that afforestation appears viable to the forestry industry under current water tariffs and current carbon accounting legislation, but would appear unviable if the forestry industry were to pay the true cost of water used by the plantations. I also found that under various plausible future economic scenarios, afforestation can be associated with either large future economic gains or losses, suggesting a need for future analyses based on branches of decision theory that deal with severe uncertainty. I conclude with a general recommendation that climate legislation should be explicit about the conditions under which afforestation for carbon sequestration of native vegetation is a legitimate climate mitigation strategy. [Copyright &y& Elsevier]

Ellner et al. (2020) state that identifying the mechanisms producing positive invasion growth rates (IGR) is useful in characterising species persistence. We agree about the importance of the sign of IGR as a binary indicator of persistence, but question whether its magnitude provides much information once the sign is given. [ABSTRACT FROM AUTHOR]