A new conceptual and methodological framework for exploring and explaining pattern in presence – absence data

A conceptual framework is proposed to evaluate the relative importance of beta diversity, nestedness and agreement in species richness in presence – absence data matrices via partitioning pairwise gamma diversity into additive components. This is achieved by calculating three complementary indices that measure similarity, relative species replacement, and relative richness difference for all pairs of sites, and by displaying the results in a two‐dimensional simplex diagram, or ternary plot. By summing two terms at a time, three one‐dimensional simplices are derived correspondig to different contrasts: beta diversity versus similarity, species replacement versus nestedness and, finally, richness difference versus richness agreement. The simplex diagrams can be used to interpret underlying data structures by showing departure from randomness towards well‐interpretable directions, as demonstrated by artificial and actual examples. In particular, one may appreciate how far data structure deviates from three extreme model situations: perfect nestedness, anti‐nestedness and perfect gradient. Throughout the paper, we pay special attention to the measurement and interpetation of beta diversity and nestedness for pairs of sites, because these concepts have been in focus of ecological reseach for decades. The novel method can be used in community ecology, conservation biology, and biogeography, whenever the objective is to recover explanatory ecological processes behind patterns conveyed by presence–absence data.     

Ecological traits reveal functional nestedness of bird communities in habitat islands: a global survey

The widespread destruction and fragmentation of natural habitats around the world creates a strong incentive to understand how species and communities respond to such pressures. The vast majority of research into habitat fragmentation has focused solely on species presence or absence. However, analyses using innovative functional methodologies offer the prospect of providing new insights into the key questions surrounding community structure in fragmented systems. A key topic in fragmentation research is nestedness (i.e. the ordered composition of species assemblages involving a significant tendency for packing of the presence–absence matrix into a series of proper subsets). To date, nestedness analyses have been concerned solely with nestedness of species membership. Here, we capitalize on the publication of a recent nestedness index (traitNODF) in which the branch lengths of functional dendrograms are incorporated into the standard NODF nestedness index. Using bird community data from 18 forest‐habitat‐island studies, and measurements of eight continuous functional traits from over 1000 bird species, we conduct the first synthetic analysis of nestedness from a functional perspective (i.e. a nestedness analysis which incorporates how similar species are in terms of their ecological traits). We use two null models to test the significance of any observed functional nestedness, and investigate the role of habitat island area in driving functional nestedness. We also determine whether functional nestedness is driven primarily by species composition or by differences in species’ traits. We found that the majority (94%) of datasets were functionally nested by island area when a permutation null model was used, although only 11–22% of datasets were significantly functionally nested when a more conservative fixed‐fixed null model was used. Species composition was always the most important driver of functional nestedness, but the effect of differences in species traits was occasionally quite large. Our results isolate the importance of island area in driving functional nestedness where it does occur and show that habitat loss results in the ordered loss of functional traits. This analysis demonstrates the potential insights that may derive from testing for ordered patterns of functional diversity. Synthesis The widespread fragmentation of natural habitats around the world creates a strong incentive to understand how ecological communities respond to such pressures. A key topic in this research agenda is nestedness; however, to date, nestedness analyses have been concerned solely with species presence or absence. Using data from 18 bird‐habitat‐island studies we conduct the first synthetic analysis of nestedness from a functional perspective (i.e. a nestedness analysis which incorporates how similar species are in terms of their ecological traits). Our findings suggest that many bird‐habitat island communities are significantly functionally nested, although our results were sensitive to the null model used. Our study demonstrates the benefits of testing for ordered patterns of functional diversity.     

Abundance and nestedness in interaction networks

Nestedness is a useful metric that characterizes the generalist–specialist balance in ecological communities. Although several nestedness indices have been proposed, few have explored how species abundance per se affects their performance and the ability to detect true interaction networks. We here develop a mathematical framework that takes into account abundance in estimates of nestedness. We use an analytical approach to relate abundance and nestedness. In our null model the probability of interaction among species is determined solely as function of their abundances. Assuming a power-law abundance model we analytically find the nestedness index and its coefficient of variability. We find that the sloping abundance distribution of our null model generates more nested structures. On the other hand steeper abundances lead to higher coefficients of variability. Both results suggest that nestedness analysis should be evaluated and explanations sought carefully.     

Inferences about nested subsets structure when not all species are detected

Comparisons of species composition among isolated ecological communities of different size have often provided evidence that the species in communities with lower species richness form nested subsets of the species in larger communities. In the vast majority of studies, the question of nested subsets has been addressed using information on presence‐absence, where a “0” is interpreted as the absence of a given species from a given location. Most of the methodological discussion in earlier studies investigating nestedness concerns the approach to generation of model‐based matrices corresponding to the null hypothesis of a nonnested pattern. However, it is most likely that in many situations investigators cannot detect all the species present in the location sampled. The possibility that zeros in incidence matrices reflect nondetection rather than absence of species has not been considered in studies addressing nested subsets, even though the position of zeros in these matrices forms the basis of earlier inference methods. These sampling artifacts are likely to lead to erroneous conclusions about both variation over space in species richness, and the degree of similarity of the various locations. Here we propose an approach to investigation of nestedness, based on statistical inference methods explicitly incorporating species detection probability, that take into account the probabilistic nature of the sampling process. We use presence‐absence data collected under Pollock's robust capture‐recapture design, and resort to an estimator of species richness originally developed for closed populations to assess the proportion of species shared by different locations. We develop testable predictions corresponding to the null hypothesis of a nonnested pattern, and an alternative hypothesis of perfect nestedness. We also present an index for assessing the degree of nestedness of a system of ecological communities. We illustrate our approach using avian data from the North American Breeding Bird Survey collected in Florida Keys.     

Can species distribution models be used to describe plant abundance patterns?

In recent years, there has been increasing interest in modelling of species abundance data in addition to presence data. In this study, we assessed the similarities and differences between presence‐absence distributions and abundance distributions along similar environmental gradients, derived, respectively, from presence‐absence and abundance data. Moreover, we examined the possibility of using presence‐absence distribution models to derive abundance distributions. For this purpose, we used Braun‐Blanquet abundance scores for 243 vascular species at 10 996 French forest sites. Species distribution models were used to analyse the link between the patterns of occurrence, low abundance and high abundance for each species with regard to mean annual temperature, June water balance, and soil pH. For each species, differences in the modelled distributions were characterised by the ecological optimum and ecological amplitude. A comparison of the presence‐absence and abundance distributions for all species revealed similar optima and different amplitudes along the three ecological factors. An abundant‐centre distribution was observed in environmental space, with species abundance being greatest at the optimal conditions and lower at less favourable conditions of the species occurrence response. Geographical habitat mapping also shows centred, high‐abundance suitability within the presence habitat of each species. We conclude that species distribution models derived from presence‐absence data provide useful information about the ecological optima of abundance distributions but overestimate the range of habitats suitable for high species abundance. This study demonstrates the utility of presence‐absence data for ecologist and conservation biologist when they are interested in the optimal conditions of high species abundance.     

Null model tests of clustering of species, negative co-occurrence patterns and nestedness in meta-communities

We propose tests for patterns in meta-community structure. The tests for clustering and nestedness of the occurrences of species and negative co-occurrence patterns provide four important innovations. Firstly, they are not restricted to the analysis of communities along one-dimensional gradients or to the main axis of variation. Secondly, abundance data can also be considered in the null model whereas most previous approaches could consider only presence/absence data. And thirdly, habitat suitability and spatial autocorrelation can be incorporated in the null model so that patterns that might be caused by biotic interactions can be distinguished from patterns which are the result of differences in the suitability or accessibility of sites for the examined organisms. Finally, the test for nestedness is also appropriate if there is more than one set of nested subsets. A re-analysis of 35 data sets with these tests showed the importance of considering the autocorrelation of the occurrences of species in analyses of meta-community structure and demonstrated the advantage of abundance data for tests of clustering of species. With abundance data it could be shown that there is a significant clustering of species, i.e. there are positive associations of species in most meta-communities, even if an environmentally or spatially constrained null model is used for the test. Co-occurrence patterns that might indicate interspecific competition were found in many of the analysed presence/absence data sets. Surprisingly the analysis of abundance data sets provides less evidence for interspecific competition. A hierarchical organization of communities, i.e. nestedness, turned out to be a rare pattern, if the autocorrelation of the occurrences of species is considered.     

Species and individual replacements contribute more than nestedness to shape vertebrate scavenger metacommunities

Understanding the mechanisms that organize biodiversity is central in ecology and conservation. Beta diversity links local (alfa) and regional (gamma) diversity, giving insight into how communities organize spatially. Metacommunity ecology provides the framework to interpret regional and local processes interacting to shape communities. However, the lack of metacommunity studies for large vertebrates may limit the understanding and compromise the preservation of ecosystem functions and services. We aim to understand the mechanisms underlying differences in species composition among vertebrate scavenger communities ? which provide key ecosystem functions, e.g. carrion consumption ? within a metacommunity context. We obtained species richness and abundances at scavenger communities consuming ungulate carcasses monitored through motion‐triggered remote cameras in seven terrestrial ecosystems in Spain. We partitioned beta diversity to decompose incidence‐based (species presence/absence) and abundance‐based dissimilarities into their components (turnover/balanced variation and nestedness/abundance gradient, respectively). We identified the environmental factors explaining the observed patterns. The vertebrate scavenger metacommunity consisted of 3101 individuals from 30 species. Changes in composition among ecosystems were mostly (> 84%) due to species or individual replacement (i.e. turnover or balanced variation). Species or individual loss/gain (i.e. nestedness or abundance gradient) accounted for 13–16% of these changes. Mean carcass weight, elevation and habitat diversity were the main factors explaining species/individual replacement. Our findings suggest that local processes such as species‐sorting through habitat heterogeneity would dominate scavenger metacommunity dynamics together with stochastic forces (i.e. related to carrion unpredictability and scavenging being a widespread strategy among vertebrates). The presence of structured patterns (i.e. nestedness) in beta diversity could reflect a role of deterministic processes: mass‐effects through dispersal and defaunation. Vultures are long‐distance foragers and functionally dominant species, which would connect local assemblages within the metacommunity, supporting scavenger diversity and functions across space. These results highlight the importance of managing vertebrate scavenger assemblages within a metacommunity context.     

Nestedness in riverine mussel communities: patterns across sites and fish hosts

The pattern of nestedness, where species present in depauperate locations are subsets of species present in locations with higher species diversity, is often found in ecological communities. Mussel communities examined in four rivers in the upper Tennessee River basin appeared significantly nested. Mussel species distributions were mostly unrelated to differences in immigration and only weakly related to downstream direction, giving some indication of structuring by differences in extinction. Mussel species distributions were not related to the number of fish species used as hosts for mussel larvae. Mussel species were more likely to overlap on common fish hosts; however, the host‐use matrix was not nested – groups of mussel species used different sets of host fish species in a pattern that appeared phylogenetically related. Sites with high fish host abundance may support high mussel diversity by promoting the survival of mussel species that are less able to attract and infect hosts. Thus, nestedness in freshwater mussel communities may be driven by the array of host fish resources, combined with differences in species’ abilities to use fish hosts. An understanding of the nested pattern in this region can aid conservation of this imperiled fauna.     

Climate drives temporal replacement and nested‐resultant richness patterns of Scottish coastal vegetation

Beta diversity quantifies spatial and/or temporal variation in species composition. It is comprised of two distinct components, species replacement and nestedness, which derive from opposing ecological processes. Using Scotland as a case study and a β‐diversity partitioning framework, we investigate temporal replacement and nestedness patterns of coastal grassland species over a 34‐yr time period. We aim to 1) understand the influence of two potentially pivotal processes (climate and land‐use changes) on landscape‐scale (5 × 5 km) temporal replacement and nestedness patterns, and 2) investigate whether patterns from one β‐diversity component can mask observable patterns in the other. We summarised key aspects of climate driven macro‐ecological variation as measures of variance, long‐term trends, between‐year similarity and extremes, for three important climatic predictors (minimum temperature, water‐balance and growing degree‐days). Shifts in landscape‐scale heterogeneity, a proxy of land‐use change, was summarised as a spatial multiple‐site dissimilarity measure. Together, these climatic and spatial predictors were used in a multi‐model inference framework to gauge the relative contribution of each on temporal replacement and nestedness patterns. Temporal β‐diversity patterns were reasonably well explained by climate change but weakly explained by changes in landscape‐scale heterogeneity. Climate was shown to have a greater influence on temporal nestedness than replacement patterns over our study period, linking nestedness patterns, as a result of imbalanced gains and losses, to climatic warming and extremes respectively. Important climatic predictors (i.e. growing degree‐days) of temporal β‐diversity were also identified, and contrasting patterns between the two β‐diversity components revealed. Results suggest climate influences plant species recruitment and establishment processes of Scotland's coastal grasslands, and while species extinctions take time, they are likely to be facilitated by climatic perturbations. Our findings also highlight the importance of distinguishing between different components of β‐diversity, disentangling contrasting patterns than can mask one another.     

Ordinal response regression models in ecology

Abstract. Although ordinal data are not rare in ecology, ecological studies have, until now, seriously neglected the use of specific ordinal regression models. Here, we present three models – the Proportional Odds, the Continuation Ratio and the Stereotype models – that can be successfully applied to ordinal data. Their differences and respective fields of application are discussed. Finally, as an example of application, PO models are used to predict spatial abundance of plant species in a Geographical Information System. It shows that ordinal models give as good a result as binary logistic models for predicting presence‐absence, but are additionally able to predict abundance satisfactorily.     

Measuring fractions of beta diversity and their relationships to nestedness: a theoretical and empirical comparison of novel approaches

Beta diversity and nestedness are central concepts of ecology and biogeography and evaluation of their relationships is in the focus of contemporary ecological and conservation research. Beta diversity patterns are originated from two distinct processes: the replacement (or turnover) of species and the loss (or gain) of species leading to richness differences. Nested distributional patterns are generally thought to have a component deriving from beta diversity which is independent of replacement processes. Quantification of these phenomena is often made by calculating a measure of beta diversity, and the resulting value being subsequently partitioned into a contribution by species replacement plus a fraction shared by beta diversity and nestedness. Three methods have been recently proposed for such partitioning, all of them based on pairwise comparisons of sites. In this paper, the performance of these methods was evaluated on theoretical grounds and tested by a simulation study in which different gradients of dissimilarity, with known degrees of species replacement and species loss, were created. Performance was also tested using empirical data addressing land‐use induced changes in endemic arthropod communities of the Terceira Island in the Azores. We found that the partitioning of β_cc (dissimilarity in terms of the Jaccard index) into two additive fractions, β_‐3 (dissimilarity due to species replacement) plus β_rich (dissimilarity due to richness differences) reflects the species replacement and species loss processes across the simulated gradients in an ecologically and mathematically meaningful way, whilst the other two methods lack mathematical consistency and prove conceptually self‐contradictory. Moreover, the first method identified a selective local extinction process for endemic arthropods, triggered by land‐use changes, while the latter two methods overweighted the replacement component and led to false conclusions. Their basic flaw derives from the fact that the proposed replacement and nestedness components (deemed to account for species loss) are not scaled in the same way as the measure that accounts for the total dissimilarity (Sørensen and Jaccard indices). We therefore recommend the use of β_cc=β_‐3+β_rich, since its components are scaled in the same units and their responses are proportional to the replacement and the gain/loss of species.     

The dilemma of binary or weighted data in interaction networks

Despite the increasing number of studies dealing with interaction networks in the last few years, there is still a lack of knowledge about how their structural organization are affected by changes in binary or weighted data. To fill this gap, we collected ants foraging on plants with extrafloral nectaries in 10 sites within the Brazilian Amazon to evaluate if the generality, vulnerability, nestedness, and modularity observed in these ant-plant networks could be affected by changes in data categories. Specifically, we used three matrices built by different data categories: (i) binary data (i.e., presence or absence of an interaction between a plant and an ant species); (ii) frequency data (i.e., number of times in which a plant species interacted with an ant species); and (iii) abundance data (i.e., number of workers of an ant species recorded foraging on a plant species). In general, when analyzing different matrix categories, we observed changes in the structural organization of the studied ant-plant interaction networks. Surprisingly, however, at the species level, both categories of weighted data (i.e., frequency and abundance data) seem to be equally appropriate for describing the role of ant species. Our results highlight the need to expand the discussion about data categories in ecological interaction studies to understand how different data categories may lead to different ecological interpretations.     

Climate change likely to reduce orchid bee abundance even in climatic suitable sites

Studies have tested whether model predictions based on species’ occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence–absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence–absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability–abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest.     

Testing the predictive performance of distribution models

Distribution models are used to predict the likelihood of occurrence or abundance of a species at locations where census data are not available. An integral part of modelling is the testing of model performance. We compared different schemes and measures for testing model performance using 79 species from the North American Breeding Bird Survey. The four testing schemes we compared featured increasing independence between test and training data: resubstitution, random data hold‐out and two spatially segregated data hold‐out designs. The different testing measures also addressed different levels of information content in the dependent variable: regression R² for absolute abundance, squared correlation coefficient r² for relative abundance and AUC/Somer’s D for presence/absence. We found that higher levels of independence between test and training data lead to lower assessments of prediction accuracy. Even for data collected independently, spatial autocorrelation leads to dependence between random hold‐out test data and training data, and thus to inflated measures of model performance. While there is a general awareness of the importance of autocorrelation to model building and hypothesis testing, its consequences via violation of independence between training and testing data have not been addressed systematically and comprehensively before. Furthermore, increasing information content (from correctly classifying presence/absence, to predicting relative abundance, to predicting absolute abundance) leads to decreasing predictive performance. The current tests for presence/absence distribution models are typically overly optimistic because a) the test and training data are not independent and b) the correct classification of presence/absence has a relatively low information content and thus capability to address ecological and conservation questions compared to a prediction of abundance. Meaningful evaluation of model performance requires testing on spatially independent data, if the intended application of the model is to predict into new geographic or climatic space, which arguably is the case for most applications of distribution models.     

Terrestrial bird community patterns on the coralline islands of the Dahlak Archipelago, Red Sea, Eritrea

Aim This study aims to explain the patterns of species richness and nestedness of a terrestrial bird community in a poorly studied region. Location Twenty‐six islands in the Dahlak Archipelago, Southern Red Sea, Eritrea. Methods The islands and five mainland areas were censused in summer 1999 and winter 2001. To study the importance of island size, isolation from the mainland and inter‐island distance, I used constrained null models for the nestedness temperature calculator and a cluster analysis. Results Species richness depended on island area and isolation from the mainland. Nestedness was detected, even when passive sampling was accounted for. The nested rank of islands was correlated with area and species richness, but not with isolation. Idiosyncrasies appeared among species‐poor and species‐rich islands, and among common and rare species. Cluster analysis showed differences among species‐rich islands, close similarity among species‐poor and idiosyncratic islands, and that the compositional similarity among islands decreased with increasing inter‐island distance. Thus, faunas of species‐poor, smaller islands were more likely to be subsets of faunas of species‐rich, larger islands if the distance between the islands was short. Main conclusions Species richness and nestedness were related to island area, and nestedness also to inter‐island distances but not to isolation from the mainland. Thus, nestedness and species richness are not affected in the same way by area and distance. Moreover, idiosyncrasies may have been the outcome of species distributions among islands being influenced also by non‐nested distributions of habitats, inter–specific interactions, and differences in species distributions across the mainland. Idiosyncrasies in nested patterns may be as important as the nested pattern itself for conservation – and conservation strategies based on nestedness and strong area effects (e.g. protection of only larger islands) may fail to preserve idiosyncratic species/habitats.     

Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation

Species distribution models are the tool of choice for large-scale population monitoring, environmental association studies and predictions of range shifts under future environmental conditions. Available data and familiarity of the tools rather than the underlying population dynamics often dictate the choice of specific method – especially for the case of presence–absence data. Yet, for predictive purposes, the relationship between occupancy and abundance embodied in the models should reflect the actual population dynamics of the modelled species. To understand the relationship of occupancy and abundance in a heterogeneous landscape at the scale of local populations, we built a spatio-temporal regression model of populations of the Glanville fritillary butterfly Melitaea cinxia in a Baltic Sea archipelago. Our data comprised nineteen years of habitat surveys and snapshot data of land use in the region. We used variance partitioning to quantify relative contributions of land use, habitat quality and metapopulation covariates. The model revealed a consistent and positive, but noisy relationship between average occupancy and mean abundance in local populations. Patterns of abundance were highly variable across years, with large uncorrelated random variation and strong local population stochasticity. In contrast, the spatio-temporal random effect, habitat quality, population connectivity and patch size explained variation in occupancy, vindicating metapopulation theory as the basis for modelling occupancy patterns in fragmented landscapes. Previous abundance was an important predictor in the occupancy model, which points to a spillover of abundance into occupancy dynamics. While occupancy models can successfully model large-scale population structure and average occupancy, extinction probability estimates for local populations derived from occupancy-only models are overconfident, as extinction risk is dependent on actual, not average, abundance.     

Once again on the components of pairwise beta diversity

Presence–absence based beta diversity defined for pairs of sites may be partitioned into components following two different ways of thinking. Within the framework of Baselga (abbreviated hereafter as BAS), nestedness is crucial and dissimilarity is partitioned into replacement (turnover) and nestedness-resultant fractions. The method proposed by Podani and Schmera (POD), however, places emphasis on the mathematical additivity of components and divides dissimilarity into replacement and richness difference components. A recent comparison by Baselga and Leprieur (2015), on the example of the Jaccard family of indices, emphasizes the independence of replacement component from absolute richness difference and concludes that the replacement function of the BAS framework is the only true measure of species replacement. As a response to this study, we show here that 1) the sacrifice one must make for independence is that the components themselves are scaled differently and are not always comparable ecologically, 2) absolute (raw) replacement and richness difference are not independent, so that independence from the latter cannot be a fundamental criterion that a replacement measure should satisfy, 3) relativization applied in the POD framework is ecologically interpretable, leading to a meaningful conceptualization of species replacement, 4) the BAS and POD methods are linked through a generalized replacement function, 5) both the BAS and POD approaches may produce high correlations with environmental variables, whereas 6) the POD approach offers in many respects more illuminating demonstrations of the underlying changes of pattern than the graphs of Baselga and Leprieur for both artificial and actual fish distribution data.     

Using intraspecific variation of functional traits and environmental factors to understand the formation of nestedness patterns of a local forest community

从功能性状的种内变异和环境因子的角度理解局域森林群落嵌套格局的成因