Multivariate dispersion as a measure of beta diversity

Beta diversity can be defined as the variability in species composition among sampling units for a given area. We propose that it can be measured as the average dissimilarity from individual observation units to their group centroid in multivariate space, using an appropriate dissimilarity measure. Differences in beta diversity among different areas or groups of samples can be tested using this approach. The choice of transformation and dissimilarity measure has important consequences for interpreting results. For kelp holdfast assemblages from New Zealand, variation in species composition was greater in smaller holdfasts, while variation in relative abundances was greater in larger holdasts. Variation in community structure of Norwegian continental shelf macrobenthic fauna increased with increases in environmental heterogeneity, regardless of the measure used. We propose a new dissimilarity measure which allows the relative weight placed on changes in composition vs. abundance to be specified explicitly.     

Hierarchical partitioning of ant diversity: implications for conservation of biogeographical diversity in arid and semi‐arid areas

Aim The scale of observation is important in detecting the spatial variation of biological assemblages, which should be taken into consideration for an appropriate plan of biogeographical conservation. We investigated whether (1) World Wildlife Fund’s ecoregion units are the appropriate scale for conserving ant diversity in Iran, (2) each ecoregion represents a distinct ant community composition and (3) patterns of diversity partitioning differ among four ecoregions. Location Iran, a sampling transect along four arid and semi‐arid ecoregions. Methods We applied hierarchical partitioning to data collected from a nested sampling design including four hierarchical levels: ‘local’, ‘landscape’, ‘ecoregional’ and ‘whole‐region’. Observed alpha and beta diversity components were compared with values of null distributions. Hierarchical cluster analysis was applied to evaluate similarity of ant species composition among ecoregions. Results Partitioning of whole‐region species richness showed that 85% of the species richness was generated by beta diversity among ecoregions and landscapes. The highest value of diversity was generated by beta diversity among ecoregions. Unlike whole‐region partitioning, separate partitioning within each ecoregion revealed that beta component among localities contributed to species richness of each ecoregion. Ecoregions showed different patterns of diversity partitioning. The alpha component contributed largely to the total diversity of two ecoregions, but for two other ecoregions, beta component contributed more than alpha component. Cluster analysis identified four discrete ant species compositions; however, it split landscapes of one ecoregion into two distinct groups. Main conclusions Whole‐region diversity partitioning indicates that ecoregions represent the appropriate scale for conserving ant diversity and that each ecoregion has a distinct ant fauna. However, different conservation strategies should be considered for different ecoregions owing to the differing scales of variation within them. Boundaries of ecoregions remain a subject for further studies. The influence of climate change on ecoregional boundaries should be considered and should be predicted with respect to future conservation maps.     

Stable baselines of temporal turnover underlie high beta diversity in tropical arthropod communities

While the high species diversity of tropical arthropod communities has often been linked to marked spatial heterogeneity, their temporal dynamics have received little attention. This study addresses this gap by examining spatio‐temporal variation in the arthropod communities of a tropical montane forest in Honduras. By employing DNA barcode analysis and Malaise trap sampling across 4 years and five sites, 51,596 specimens were assigned to 8,193 presumptive species. High beta diversity was linked more strongly to elevation than geographic distance, decreasing by 12% when only the dominant species were considered. When sampling effort was increased by deploying more traps at a site, beta diversity only decreased by 2%, but extending sampling across years decreased beta diversity by 27%. Species inconsistently detected among years, likely transients from other settings, drove the low similarity in species composition among traps only a few metres apart. The dominant, temporally persistent species substantially influenced the cyclic pattern of change in community composition among years. This pattern likely results from divergence–convergence dynamics, suggesting a stable baseline of temporal turnover in each community. The overall results establish that large sample sizes are necessary to reveal species richness, but are not essential for quantifying beta diversity. This study further highlights the need for standardized methods of sampling and species identification to generate the comparative data required to evaluate biodiversity change in space and time.     

A diversity of beta diversities: straightening up a concept gone awry. Part 1. Defining beta diversity as a function of alpha and gamma diversity

The term beta diversity has been used to refer to a wide variety of phenomena. Although all of these encompass some kind of compositional heterogeneity between places, many are not related to each other in any predictable way. The present two‐part review aims to put the different phenomena that have been called a beta component of diversity into a common conceptual framework, and to explain what each of them measures. In this first part, the focus is on defining beta diversity. This involves deciding what diversity is and how the observed total or gamma diversity (γ) is partitioned into alpha (α) and beta (β) components. Several different definitions of “beta diversity” that result from these decisions have been used in the ecological literature. True beta diversity is obtained when the total effective number of species in a dataset (true gamma diversityγ) is multiplicatively partitioned into the effective number of species per compositionally distinct virtual sampling unit (true alpha diversityα_d) and the effective number of such compositional units (β_Md=γ/α_d). All true diversities quantify the effective number of types of entities. Because the other variants of “beta diversity” that have been used by ecologists quantify other phenomena, an alternative nomenclature is proposed here for the seven most popular beta components: regional‐to‐local diversity ratio, two‐way diversity ratio, absolute effective species turnover (=regional diversity excess), Whittaker's effective species turnover, proportional effective species turnover, regional entropy excess and regional variance excess. In the second part of the review, the focus will be on how to quantify these phenomena in practice. This involves deciding how the sampling units that contribute to total diversity are selected, and whether the entity that is quantified is all of “beta diversity”, a specific part of “beta diversity”, the rate of change in “beta diversity” in relation to a given external factor, or something else.     

Beta diversity as the variance of community data: dissimilarity coefficients and partitioning

Beta diversity can be measured in different ways. Among these, the total variance of the community data table Y can be used as an estimate of beta diversity. We show how the total variance of Y can be calculated either directly or through a dissimilarity matrix obtained using any dissimilarity index deemed appropriate for pairwise comparisons of community composition data. We addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination. Our comparison analysis classified the coefficients under study into five types, three of which are appropriate for beta diversity assessment. Our approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova . Total beta can be partitioned into Species Contributions (SCBD: degree of variation of individual species across the study area) and Local Contributions (LCBD: comparative indicators of the ecological uniqueness of the sites) to Beta Diversity. Moreover, total beta can be broken up into within‐ and among‐group components by manova , into orthogonal axes by ordination, into spatial scales by eigenfunction analysis or among explanatory data sets by variation partitioning.     

Latitudinal gradients in the phenetic diversity of New World bat communities

Although the examination of latitudinal gradients of species richness is common, little attention has been devoted to other components of biodiversity such as phenetic diversity. Because the phenotype reflects aspects of an organism's environment, ecological relationships and evolutionary history, measures of phenetic diversity likely provide complimentary information to that of species richness, and may provide unique insights for understanding the mechanistic basis to patterns of biodiversity. Herein, we evaluate latitudinal gradients in the phenetic diversity of 32 New World bat communities. Seven morphological characters were used to estimate phenotypic variation among bat species within local communities. Principal components analysis decomposed this variation into axes of size and shape. Three measures of phenetic diversity were calculated separately for size and for shape axes. The range of species scores on a particular axis described the amount of phenetic variation encompassed by species in a community. The standard deviation of minimum spanning‐tree segment lengths described uniformity of species. Average nearest‐neighbor distances described local packing. We separately regressed these six measures on local species richness and latitude separately. Variation in species richness accounted for a significant amount of variation in each measure of phenetic diversity. Latitude also accounted for significant variation in phenetic diversity except for the standard deviation of minimum‐spanning tree segment lengths and the average nearest‐neighbor distance on the shape axis. More importantly, gradients in phenetic diversity were significantly different than would be expected as a consequence of latitudinal gradients in species richness. Nonetheless, when variation among communities regarding the richness and composition of their regional faunas was taken into consideration, differences between empirical and simulated gradients were nonsignificant. Thus, factors that determine the composition of regional faunas have a great impact on the phenetic diversity of communities and ultimately the latitudinal gradient in biodiversity.     

Computing additive beta-diversity from presence and absence scores: a critique and alternative parameters

Whittaker first proposed to measure the variation in species composition among plots or beta-diversity as the ratio between regional diversity (gamma-diversity) and average local diversity (alpha-diversity). More recently, an alternative way of partitioning diversity for which beta-diversity is obtained as the difference between gamma-diversity and average alpha-diversity has become very popular for linking the structure of species assemblages to ecosystem functioning in a spatially explicit manner. Unfortunately, additive beta-diversity computed from species presences and absences suffers from the major drawback of being dependent on regional species richness. For instance, if the separation between beta-diversity and gamma-diversity is incomplete, so that variation in species composition is affected by species richness, then differences in beta-diversity values among different sets of plots could reflect differences in the species count rather than any fundamental difference in species composition among the plots. Based on the above observation, in this paper I will first propose a basic requirement for beta-diversity measures that adequately captures our intuitive notion of independence of species richness. Next, I will show that additive beta-diversity computed from species presence and absence scores can be interpreted within the framework of fuzzy set theory. Finally, based on this unusual "fuzzy" interpretation of additive beta-diversity, I will introduce two families of parametric beta-diversity measures whose members have varying sensitivities to the presence of rare and frequent species.     

Partitioning the turnover and nestedness components of beta diversity

Aim  Beta diversity (variation of the species composition of assemblages) may reflect two different phenomena, spatial species turnover and nestedness of assemblages, which result from two antithetic processes, namely species replacement and species loss, respectively. The aim of this paper is to provide a unified framework for the assessment of beta diversity, disentangling the contribution of spatial turnover and nestedness to beta-diversity patterns.
Innovation  I derive an additive partitioning of beta diversity that provides the two separate components of spatial turnover and nestedness underlying the total amount of beta diversity. I propose two families of measures of beta diversity for pairwise and multiple-site situations. Each family comprises one measure accounting for all aspects of beta diversity, which is additively decomposed into two measures accounting for the pure spatial turnover and nestedness components, respectively. Finally, I provide a case study using European longhorn beetles to exemplify the relevance of disentangling spatial turnover and nestedness patterns.
Main conclusion  Assigning the different beta-diversity patterns to their respective biological phenomena is essential for analysing the causality of the processes underlying biodiversity. Thus, the differentiation of the spatial turnover and nestedness components of beta diversity is crucial for our understanding of central biogeographic, ecological and conservation issues.     

Species turnover in lake littorals: spatial and temporal variation of benthic macroinvertebrate diversity and community composition

Aims Despite wide consensus that ecological patterns and processes should be studied at multiple spatial scales, the temporal component of diversity variation has remained poorly examined. Specifically, rare species may exhibit patterns of diversity variation profoundly different from those of dominant taxa. Location Southern Finland. Methods We used multiplicative partitioning of true diversities (species richness, Shannon diversity) to identify the most important scale(s) of variation of benthic macroinvertebrate communities across several hierarchical scales, from individual samples to multiple littorals, lakes and years. We also assessed the among‐scale variability of benthic macroinvertebrate community composition by using measures of between‐ and within‐group distances at hierarchical scales. Results On average, a single benthic sample contained 23% of the total regional macroinvertebrate species pool. For both species richness and Shannon diversity, beta‐diversity was clearly the major component of regional diversity, with within‐littoral beta‐diversity (β₁) being the largest component of gamma‐diversity. The interannual component of total diversity was small, being almost negligible for Shannon index. Among‐sample (within‐littoral) diversity was related to variation of substratum heterogeneity at the same scale. By contrast, only a small proportion of rare taxa was found in an average benthic sample. Thus, dominant species among lakes and years were about the same, whereas rare species were mostly detected in a few benthic samples in one lake (or year). For rare species, the temporal component of diversity was more important than spatial turnover at most scales. Main conclusions While individual species occurrences and abundances, particularly those of rare taxa, may vary strongly through space and time, patterns of dominance in lake littoral benthic communities are highly predictable. Consequently, many rare species will be missed in temporally restricted samples of lake littorals. In comprehensive biodiversity surveys, interannual sampling of littoral macroinvertebrate communities is therefore needed.     

Hydrological and environmental variables outperform spatial factors in structuring species,trait composition,and beta diversity of pelagic algae

There has been increasing interest in algae‐based bioassessment, particularly, trait‐based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well‐proven ecohydrological modeling enabled to predict long‐term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait‐based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long‐term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.     

The variation of tree beta diversity across a global network of forest plots

Aims With the aim of understanding why some of the world's forests exhibit higher tree beta diversity values than others, we asked: (1) what is the contribution of environmentally related variation versus pure spatial and local stochastic variation to tree beta diversity assessed at the forest plot scale; (2) at what resolution are these beta‐diversity components more apparent; and (3) what determines the variation in tree beta diversity observed across regions/continents? Location World‐wide. Methods We compiled an unprecedented data set of 10 large‐scale stem‐mapping forest plots differing in latitude, tree species richness and topographic variability. We assessed the tree beta diversity found within each forest plot separately. The non‐directional variation in tree species composition among cells of the plot was our measure of beta diversity. We compared the beta diversity of each plot with the value expected under a null model. We also apportioned the beta diversity into four components: pure topographic, spatially structured topographic, pure spatial and unexplained. We used linear mixed models to interpret the variation of beta diversity values across the plots. Results Total tree beta diversity within a forest plot decreased with increasing cell size, and increased with tree species richness and the amount of topographic variability of the plot. The topography‐related component of beta diversity was correlated with the amount of topographic variability but was unrelated to its species richness. The unexplained variation was correlated with the beta diversity expected under the null model and with species richness. Main conclusions Because different components of beta diversity have different determinants, comparisons of tree beta diversity across regions should quantify not only overall variation in species composition but also its components. Global‐scale patterns in tree beta diversity are largely coupled with changes in gamma richness due to the relationship between the latter and the variation generated by local stochastic assembly processes.     

Measuring beta‐diversity from taxonomic similarity

Question: The utility of beta (β‐) diversity measures that incorporate information about the degree of taxonomic (dis)similarity between species plots is becoming increasingly recognized. In this framework, the question for this study is: can we define an ecologically meaningful index of β‐diversity that, besides indicating simple species turnover, is able to account for taxonomic similarity amongst species in plots? Methods: First, the properties of existing measures of taxonomic similarity measures are briefly reviewed. Next, a new measure of plot‐to‐plot taxonomic similarity is presented that is based on the maximal common subgraph of two taxonomic trees. The proposed measure is computed from species presences and absences and include information about the degree of higher‐level taxonomic similarity between species plots. The performance of the proposed measure with respect to existing coefficients of taxonomic similarity and the coefficient of Jaccard is discussed using a small data set of heath plant communities. Finally, a method to quantify β‐diversity from taxonomic dissimilarities is discussed. Results: The proposed measure of taxonomic β‐diversity incorporates not only species richness, but also information about the degree of higher‐order taxonomic structure between species plots. In this view, it comes closer to a modern notion of biological diversity than more traditional measures of β‐di‐versity. From regression analysis between the new coefficient and existing measures of taxonomic similarity it is shown that there is an evident nonlinearity between the coefficients. This nonlinearity demonstrates that the new coefficient measures similarity in a conceptually different way from previous indices. Also, in good agreement with the findings of previous authors, the regression between the new index and the Jaccard coefficient of similarity shows that more than 80% of the variance of the former is explained by the community structure at the species level, while only the residual variance is explained by differences in the higher‐order taxonomic structure of the species plots. This means that a genuine taxonomic approach to the quantification of plot‐to‐plot similarity is only needed if we are interested in the residual system's variation that is related to the higher‐order taxonomic structure of a pair of species plots.     

From plots to islands: species diversity at different scales

Aim To investigate how plant diversity of whole islands (‘gamma’) is related to alpha and beta diversity patterns among sampling plots within each island, thus exploring aspects of diversity patterns across scales. Location Nineteen islands of the Aegean Sea, Greece. Methods Plant species were recorded at both the whole‐island scale and in small 100 m² plots on each island. Mean plot species richness was considered as a measure of alpha diversity, and six indices of the ‘variation’‐type beta diversity were also applied. In addition, we partitioned beta diversity into a ‘nestedness’ and a ‘replacement’ component, using the total species richness recorded in all plots of each island as a measure of ‘gamma’ diversity. We also applied 10 species–area models to predict the total observed richness of each island from accumulated plot species richness. Results Mean alpha diversity was not significantly correlated with the overall island species richness or island area. The range of plot species richness for each island was significantly correlated with both overall species richness and area. Alpha diversity was not correlated with most indices of beta diversity. The majority of beta diversity indices were correlated with whole‐island species richness, and this was also true for the ‘replacement’ component of beta diversity. The rational function model provided the best prediction of observed island species richness, with Monod’s and the exponential models following closely. Inaccuracy of predictions was positively correlated with the number of plots and with most indices of beta diversity. Main conclusions Diversity at the broader scale (whole islands) is shaped mainly by variation among small local samples (beta diversity), while local alpha diversity is not a good predictor of species diversity at broader scales. In this system, all results support the crucial role of habitat diversity in determining the species–area relationship.     

Diversity and community composition of butterflies and odonates in an ENSO-induced fire affected habitat mosaic: a case study from East Kalimantan, Indonesia

Little is known about the diversity of tropical animal communities in recently fire‐affected environments. Here we assessed species richness, evenness, and community similarity of butterflies and odonates in landscapes located in unburned isolates and burned areas in a habitat mosaic that was severely affected by the 1997/98 ENSO (El Niño Southern Oscillation) event in east Kalimantan, Indonesian Borneo. In addition related community similarity to variation in geographic distance between sampling sites and the habitat/vegetation structure Species richness and evenness differed significantly among landscapes but there was no congruence between both taxa. The species richness of butterflies was, for example, highest in sites located in a very large unburned isolate whereas odonate species richness was highest in sites located in a small unburned isolate and once‐burned forest. We also found substantial variation in the habitat/vegetation structure among landscapes but this was mainly due to variation between unburned and burned landscapes and variation among burned landscapes. Both distance and environment (habitat/vegetation) contributed substantially to explaining variation in the community similarity (beta diversity) of both taxa. The contribution of the environment was, however, mainly due to variation between unburned and burned landscapes, which contained very different assemblages of both taxa. Sites located in the burned forest contained assemblages that were intermediate between assemblages from sites in unburned forest and sites from a highly degraded slash‐and‐burn area indicating that the burned forest was probably recolonised by species from these disparate environments. We, furthermore, note that in contrast to species richness (alpha diversity) the patterns of community similarity (beta diversity) were highly congruent between both taxa. These results indicate that community‐wide multivariate measures of beta diversity are more consistent among taxa and more reliable indicators of disturbance, such as ENSO‐induced burning, than univariate measures.     

Taxonomic diversity as complementary information to assess plant species diversity in secondary vegetation and primary tropical deciduous forest

Question: Species diversity is commonly expressed as the number of species present in an area, but this unique value assumes that all species contribute equally to the area's biodiversity. Can taxonomic diversity be used as a complementary measure for species richness in order to assess plant biodiversity in remnants of primary forest and patches of secondary vegetation? Location: Veracruz, Mexico. Methods: Using data from six sampling transects of each vegetation type in an elevation gradient (400‐900 m a.s.l.), we compare the point, mean and cumulative floristic diversity of primary forest and secondary vegetation in a tropical deciduous landscape, using species richness and two measures of taxonomic diversity: average taxonomic distinctness (Δ+) and variation in taxonomic distinctness (Λ+). We performed a randomization test to detect differences in the observed taxonomic diversity, from the expected values derived from the species pool of each vegetation type. Results: We found that the species of secondary vegetation are more closely related at low taxonomic levels (lower Δ+ value) than the species of primary forest remnants. Also, in secondary vegetation the distribution of species is uneven among the taxonomic levels and units (high Λ+ value). These patterns are consistent for point, mean and cumulative taxonomic diversity. Families Asteraceae, Euphorbiaceae, Fabaceae and Poaceae are over‐represented, while families Bromeliaceae, Cactaceae, Orchidaceae and Pteridaceae are under‐represented in secondary vegetation. Conclusions: Although in a previous paper we concluded that secondary vegetation is more alpha‐diverse than primary forest (in terms of both cumulative and mean species richness), and beta‐diversity between vegetation types is notoriously high, we now provide a wider view by highlighting the importance of taxonomic diversity in primary forest remnants. Our data indicate that to measure biodiversity accurately, we should seek to capture its different facets. This will allow us to make conservation recommendations based on a broader view, and not on a single dimension.     

How beta diversity and the underlying causes vary with sampling scales in the Changbai mountain forests

This study aims to establish a relationship between the sampling scale and tree species beta diversity temperate forests and to identify the underlying causes of beta diversity at different sampling scales. The data were obtained from three large observational study areas in the Changbai mountain region in northeastern China. All trees with a dbh ≥1 cm were stem‐mapped and measured. The beta diversity was calculated for four different grain sizes, and the associated variances were partitioned into components explained by environmental and spatial variables to determine the contributions of environmental filtering and dispersal limitation to beta diversity. The results showed that both beta diversity and the causes of beta diversity were dependent on the sampling scale. Beta diversity decreased with increasing scales. The best‐explained beta diversity variation was up to about 60% which was discovered in the secondary conifer and broad‐leaved mixed forest (CBF) study area at the 40 × 40 m scale. The variation partitioning result indicated that environmental filtering showed greater effects at bigger grain sizes, while dispersal limitation was found to be more important at smaller grain sizes. What is more, the result showed an increasing explanatory ability of environmental effects with increasing sampling grains but no clearly trend of spatial effects. The study emphasized that the underlying causes of beta diversity variation may be quite different within the same region depending on varying sampling scales. Therefore, scale effects should be taken into account in future studies on beta diversity, which is critical in identifying different relative importance of spatial and environmental drivers on species composition variation.     

The spatial scaling of beta diversity

Beta diversity is an important concept used to describe turnover in species composition across a wide range of spatial and temporal scales, and it underpins much of conservation theory and practice. Although substantial progress has been made in the mathematical and terminological treatment of different measures of beta diversity, there has been little conceptual synthesis of potential scale dependence of beta diversity with increasing spatial grain and geographic extent of sampling. Here, we evaluate different conceptual approaches to the spatial scaling of beta diversity, interpreted from ‘fixed’ and ‘varying’ perspectives of spatial grain and extent. We argue that a ‘sliding window’ perspective, in which spatial grain and extent covary, is an informative way to conceptualize community differentiation across scales. This concept more realistically reflects the varying empirical approaches that researchers adopt in field sampling and the varying scales of landscape perception by different organisms. Scale dependence in beta diversity has broad implications for emerging fields in ecology and biogeography, such as the integration of fine‐resolution ecogenomic data with large‐scale macroecological studies, as well as for guiding appropriate management responses to threats to biodiversity operating at different spatial scales.     

Dispersal enhances beta diversity in nectar microbes

Dispersal is considered a key driver of beta diversity, the variation in species composition among local communities, but empirical tests remain limited. We manipulated dispersal of nectar‐inhabiting bacteria and yeasts via flower‐visiting animals to examine how dispersal influenced microbial beta diversity among flowers. Contrary to the prevailing view that dispersal lowers beta diversity, we found beta diversity was highest when dispersal was least limited. Our analysis suggested that this unexpected pattern might have resulted from stronger priority effects under increased dispersal. Dispersal is highly stochastic, generating variability in species arrival history and consequently the potential for community divergence via priority effects, in these and likely many other microbial, plant, and animal communities. Yet most previous experiments eliminated this possibility. We suggest that the positive effects of dispersal on beta diversity, like the one we report here, may have been greatly underappreciated.     

Contrasting effects of mosaic structure on alpha and beta diversity of bird assemblages in a human‐modified landscape

Habitat loss and fragmentation are key processes causing biodiversity loss in human‐modified landscapes. Knowledge of these processes has largely been derived from measuring biodiversity at the scale of ‘within‐habitat’ fragments with the surrounding landscape considered as matrix. Yet, the loss of variation in species assemblages ‘among’ habitat fragments (landscape‐scale) may be as important a driver of biodiversity loss as the loss of diversity ‘within’ habitat fragments (local‐scale). We tested the hypothesis that heterogeneity in vegetation cover is important for maintaining alpha and beta diversity in human‐modified landscapes. We surveyed bird assemblages in eighty 300‐m‐long transects nested within twenty 1‐km² vegetation ‘mosaics’, with mosaics assigned to four categories defined by the cover extent and configuration of native eucalypt forest and exotic pine plantation. We examined bird assemblages at two spatial scales: 1) within and among transects, and 2) within and among mosaics. Alpha diversity was the mean species diversity within‐transects or within‐mosaics and beta diversity quantified the effective number of compositionally distinct transects or mosaics. We found that within‐transect alpha diversity was highest in vegetation mosaics defined by continuous eucalypt forest, lowest in mosaics of continuous pine plantation, and at intermediate levels in mosaics containing eucalypt patches in a pine matrix. We found that eucalypt mosaics had lower beta diversity than other mosaic types when ignoring relative abundances, but had similar or higher beta diversity when weighting with species abundances. Mosaics containing both pine and eucalypt forest differed in their bird compositional variation among transects, despite sharing a similar suite of species. This configuration effect at the mosaic scale reflected differences in vegetation composition among transects. Maintaining heterogeneity in vegetation cover could help to maintain variation among bird assemblages across landscapes, thus partially offsetting local‐scale diversity losses due to fragmentation. Critical to this is the retention of remnant native vegetation.     

The effects of forest conversion to oil palm on ground‐foraging ant communities depend on beta diversity and sampling grain

Beta diversity – the variation in species composition among spatially discrete communities – and sampling grain – the size of samples being compared – may alter our perspectives of diversity within and between landscapes before and after agricultural conversion. Such assumptions are usually based on point comparisons, which do not accurately capture actual differences in total diversity. Beta diversity is often not rigorously examined. We investigated the beta diversity of ground‐foraging ant communities in fragmented oil palm and forest landscapes in Sabah, Malaysia, using diversity metrics transformed from Hill number equivalents to remove dependences on alpha diversity. We compared the beta diversities of oil palm and forest, across three hierarchically nested sampling grains. We found that oil palm and forest communities had a greater percentage of total shared species when larger samples were compared. Across all grains and disregarding relative abundances, there was higher beta diversity of all species among forest communities. However, there were higher beta diversities of common and very abundant (dominant) species in oil palm as compared to forests. Differences in beta diversities between oil palm and forest were greatest at the largest sampling grain. Larger sampling grains in oil palm may generate bigger species pools, increasing the probability of shared species with forest samples. Greater beta diversity of all species in forest may be attributed to rare species. Oil palm communities may be more heterogeneous in common and dominant species because of variable community assembly events. Rare and also common species are better captured at larger grains, boosting differences in beta diversity between larger samples of forest and oil palm communities. Although agricultural landscapes support a lower total diversity than natural forests, diversity especially of abundant species is still important for maintaining ecosystem stability. Diversity in agricultural landscapes may be greater than expected when beta diversity is accounted for at large spatial scales.