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Aim This paper presents the statistical bases for temporal beta‐diversity analysis, a method to study changes in community composition through time from repeated surveys at several sites. Surveys of that type are presently done by ecologists around the world. A temporal beta‐diversity Index (TBI) is computed for each site, measuring the change in species composition between the first (T1) and second surveys (T2). TBI indices can be decomposed into losses and gains; they can also be tested for significance, allowing one to identify the sites that have changed in composition in exceptional ways. This method will be of value to identify exceptional sites in space–time surveys carried out to study anthropogenic impacts, including climate change. Innovation The null hypothesis of the TBI test is that a species assemblage is not exceptionally different between T1 and T2, compared to assemblages that could have been observed at this site at T1 and T2 under conditions corresponding to H0. Tests of significance of coefficients in a dissimilarity matrix are usually not possible because the values in the matrix are interrelated. Here, however, the dissimilarity between T1 and T2 for a site is computed with different data from the dissimilarities used for the T1–T2 comparison at other sites. It is thus possible to compute a valid test of significance in that case. In addition, the paper shows how TBI dissimilarities can be decomposed into loss and gain components (of species, or abundances‐per‐species) and how a B–C plot can be produced from these components, which informs users about the processes of biodiversity losses and gains through time in space–time survey data. Main conclusion Three applications of the method to different ecological communities are presented. This method is applicable worldwide to all types of communities, marine, and terrestrial. R software is available implementing the method. This paper describes a new method, temporal beta‐diversity analysis, to study the changes in community composition through time from repeated surveys at several sites. (a) A temporal beta‐diversity Index (TBI) is computed for each site, measuring the change in species composition between the first and second surveys. TBI indices can be tested for significance, allowing one to identify the sites that have changed in composition in exceptional ways. (b) It is often of interest to examine the species loss and gain components of the TBI indices because change through time is directional. Graphical procedures are demonstrated. Several examples from the ecological literature are provided.

Islands harbour evolutionary and ecologically unique biota, which are currently disproportionately threatened by a multitude of anthropogenic factors, including habitat loss, invasive species and climate change. Native forests on oceanic islands are important refugia for endemic species, many of which are rare and highly threatened. Long-term monitoring schemes for those biota and ecosystems are urgently needed: (i) to provide quantitative baselines for detecting changes within island ecosystems, (ii) to evaluate the effectiveness of conservation and management actions, and (iii) to identify general ecological patterns and processes using multiple island systems as repeated ‘natural experiments’. In this contribution, we call for a Global Island Monitoring Scheme (GIMS) for monitoring the remaining native island forests, using bryophytes, vascular plants, selected groups of arthropods and vertebrates as model taxa. As a basis for the GIMS, we also present new, optimized monitoring protocols for bryophytes and arthropods that were developed based on former standardized inventory protocols. Effective inventorying and monitoring of native island forests will require: (i) permanent plots covering diverse ecological gradients (e.g. elevation, age of terrain, anthropogenic disturbance); (ii) a multiple-taxa approach that is based on standardized and replicable protocols; (iii) a common set of indicator taxa and community properties that are indicative of native island forests’ welfare, building on, and harmonized with existing sampling and monitoring efforts; (iv) capacity building and training of local researchers, collaboration and continuous dialogue with local stakeholders; and (v) long-term commitment by funding agencies to maintain a global network of native island forest monitoring plots.

Aim: The knowledge of biodiversity facets such as species composition, distribution and ecological niche is fundamental for the construction of biogeographic hypotheses and conservation strategies. However, the knowledge on these facets is affected by major shortfalls, which are even more pronounced in the tropics. This study aims to evaluate the effect of sampling bias and variation in collection effort on Linnean, Wallacean and Hutchinsonian shortfalls and diversity measures as species richness, endemism and beta-diversity. Location: Brazil. Methods: We have built a database with over 1.5 million records of arthropods, vertebrates and angiosperms of Brazil, based on specimens deposited in scientific collections and on the taxonomic literature. We used null models to test the collection bias regarding the proximity to access routes. We also tested the influence of sampling effort on diversity measures by regression models. To investigate the Wallacean shortfall, we modelled the geographic distribution of over 4000 species and compared their observed distribution with models. To quantify the Hutchinsonian shortfall, we used environmental Euclidean distance of the records to identify regions with poorly sampled environmental conditions. To estimate the Linnean shortfall, we measured the similarity of species composition between regions close to and far from access routes. Results: We demonstrated that despite the differences in sampling effort, the strong collection bias affects all taxonomic groups equally, generating a pattern of spatially biased sampling effort. This collection pattern contributes greatly to the biodiversity knowledge shortfalls, which directly affects the knowledge on the distribution patterns of diversity. Main conclusions: The knowledge on species richness, species composition and endemism in the Brazilian biodiversity is strongly biased spatially. Despite differences in sampling effort for each taxonomic group, roadside bias affected them equally. Species composition similarity decreased with the distance from access routes, suggesting collection surveys at sites far from roads could increase the probability of sampling new geographic records or new species.

A major goal in ecology is to understand mechanisms that influence patterns of biodiversity and community assembly at various spatial and temporal scales. Understanding how community composition is created and maintained also is critical for natural resource management and biological conservation. In this study, we investigated environmental and spatial factors influencing beta diversity of local fish assemblages along the longitudinal gradient of a nearly pristine Neotropical river in the Colombian Llanos. Standardized surveys were conducted during the low-water season at 34 sites within the Bita River Basin. Physical, chemical, and landscape parameters were recorded at each site, and asymmetric eigenvector maps were used as spatial variables. To examine the relative influence of dispersal and environmental variables on beta diversity and its components, distance-based redundancy analysis (db-RDA) and variation partitioning analysis were conducted. We proposed that spatial scale of analysis and position within the river network would constrain patterns of beta diversity in different ways. However, results indicated that in this system, high beta diversity was consistent among species assemblages no matter the scale of analysis or position within the river network. Species replacement (turnover) dominated beta diversity, an indication of the importance of species sorting. These findings suggested that conservation of fish diversity in tropical rivers requires maintenance of both habitat heterogeneity (spatial variation in habitat conditions) and connectivity at the scale of entire river basins.

AIM: To propose a unified framework for quantifying taxon (Tβ), phylogenetic (Pβ) and functional (Fβ) beta diversity via pairwise comparisons of communities, which allows these types of beta diversity to be partitioned into ecologically meaningful additive components. LOCATION: Global, with case studies in Europe and the Azores archipelago. METHODS: Using trees as a common representation for taxon, phylogenetic and functional diversity, we partition total beta diversity (βₜₒₜₐₗ) into its replacement (turnover, βᵣₑₚₗ) and richness difference (βᵣᵢcₕ) components according to which part of a global tree was shared by or unique to communities that were being compared. We demonstrate the application of this framework using artificial and empirical examples (mammals in Europe and epigean arthropods in the Azores). RESULTS: Our empirical examples show that comparing Pβ and Fβ with the most commonly used Tβ revealed previously hidden patterns of beta diversity. More importantly, we demonstrate that partitioning Pβₜₒₜₐₗ and Fβₜₒₜₐₗ into their respective βᵣₑₚₗ and βᵣᵢcₕ components facilitates the detection of more complex patterns than using the overall coefficients alone, further elucidating the different forces operating in community assembly. MAIN CONCLUSIONS: The methods presented here allow the integration and full comparison of Tβ, Pβ and Fβ. They provide a tool for effectively disentangling the replacement (turnover) and richness difference components of the different biodiversity facets within the same methodological framework.

AIM: The variation in species composition among sites, or beta diversity, can be decomposed into replacement and richness difference. A debate is ongoing in the literature concerning the best ways of computing and interpreting these indices. This paper first reviews the historical development of the formulae for decomposing dissimilarities into replacement, richness difference and nestedness indices. These formulae are presented for species presence–absence and abundance using a unified algebraic framework. The indices decomposing beta play different roles in ecological analysis than do beta‐diversity indices. INNOVATION: Replacement and richness difference indices can be interpreted and related to ecosystem processes. The pairwise index values can be summed across all pairs of sites; these sums form a valid decomposition of total beta diversity into total replacement and total richness difference components. Different communities and study areas can be compared: some may be dominated by replacement, others by richness/abundance difference processes. Within a region, differences among sites measured by these indices can then be analysed and interpreted using explanatory variables or experimental factors. The paper also shows that local contributions of replacement and richness difference to total beta diversity can be computed and mapped. A case study is presented involving fish communities along a river. MAIN CONCLUSIONS: The different forms of indices are based upon the same functional numerators. These indices are complementary; they can help researchers understand different aspects of ecosystem functioning. The methods of analysis used in this paper apply to any of the indices recently proposed. Further work, based on ecological theory and numerical simulations, is required to clarify the precise meaning and domain of application of the different forms. The forms available for presence–absence and quantitative data are both useful because these different data types allow researchers to answer different types of ecological or biogeographic questions.

1. A fundamental aim in community ecology is to elucidate the processes structuring communities. The key to understanding community patterns is to account for species differences and similarities in how they respond to large-scale environmental gradients and partition local resources. Using phylogenetic relationships as a representation of species' ecological differences, we use phylogenetic beta-diversity (PBD) to examine how patterns of community relatedness change across space. 2. Specifically, we examine how PBD informs our understanding of the processes (spatial or environmental) directing species assembly along montane environmental gradients – in particular, whether patterns are consistent with niche conservatism. Also, we examine the depth of phylogenetic turnover to see where in evolutionary history shared environmental tolerances appear conserved. 3. For angiosperm communities situated to the east and west of the Continental Divide (CD) in the Rocky Mountain National Park in CO, USA, we compare nine beta-diversity indices (taxonomic, TBD: Jaccard, Bray–Curtis and Gower; PBD: PhyloSor, UniFrac, Dnn, Dpw, Rao's D and Rao's H) to changes in space, environment and environment controlling for space with the partial PROTEST method. 4. We find that PBD differs from taxonomic beta-diversity and some PBD metrics were redundant with one another (i.e. Rao's D & Dpw and UniFrac & PhyloSor). The indices' different sensitivities to evolutionary depth affected their responses to environmental and spatial gradients: TBD consistently associated greater with all factors (space, environment and environment controlled for space) than PBD metrics; PBD metrics more sensitive to recent changes were more highly correlated with all factors than those metrics sensitive to turnover deeper in the phylogeny. Generally, beta-diversity associated strongest with environment and least with space. 5. Synthesis. Taxonomic and phylogenetic beta-diversity complements each other to provide an enhanced perspective of the process governing community structure. Together, they depict patterns expected under niche conservatism for the Rocky Mountain angiosperm communities, that is, species' names change faster than their evolutionary relationships across space.

AIM: One of the main gaps in the assessment of biodiversity is the lack of a unified framework for measuring its taxonomic and functional facets and for unveiling the underlying patterns. LOCATION: Europe, 25 large river basins. METHODS: Here, we develop a decomposition of functional β‐diversity, i.e. the dissimilarity in functional composition between communities, into a functional turnover and a functional nestedness‐resultant component. RESULTS: We found that functional β‐diversity was lower than taxonomic β‐diversity. This difference was driven by a lower functional turnover compared with taxonomic turnover while the nestedness‐resultant component was similar for taxonomic and functional β‐diversity. MAIN CONCLUSIONS: Fish faunas with different species tend to share the same functional attributes. The framework presented in this paper will help to analyse biogeographical patterns as well as to measure the impact of human activities on the functional facets of biodiversity.

Aim: We investigated patterns of species richness and community dissimilarity along elevation gradients using globally replicated, standardized surveys of vascular plants. We asked how these patterns of diversity are influenced by anthropogenic pressures (road construction and non-native species). Location: Global. Time period: 2008–2015. Major taxa studied: Vascular plants. Methods: Native and non-native vascular plant species were recorded in 943 plots along 25 elevation gradients, in nine mountain regions, on four continents. Sampling took place in plots along and away from roads. We analysed the effects of elevation and distance from road on species richness patterns and community dissimilarity (beta-diversity), and assessed how non-native species modified such elevational diversity patterns. Results: Globally, native and total species richness showed a unimodal relationship with elevation that peaked at lower-mid elevations, but these patterns were altered along roads and due to non-native species. Differences in elevational species richness patterns between regions disappeared along roadsides, and non-native species changed the patterns' character in all study regions. Community dissimilarity was reduced along roadsides and through non-native species. We also found a significant elevational decay of beta-diversity, which however was not affected by roads or non-native species. Main conclusions: Idiosyncratic native species richness patterns in plots away from roads implicate region-specific mechanisms underlying these patterns. However, along roadsides a clearer elevational signal emerged and species richness mostly peaked at mid-elevations. We conclude that both roads and non-native species lead to a homogenization of species richness patterns and plant communities in mountains.

The concept of metacommunity (i.e., a set of local communities linked by dispersal) has gained great popularity among community ecologists. However, metacommunity research mostly addresses questions on spatial patterns of biodiversity at the regional scale, whereas conservation planning requires quantifying temporal variation in those metacommunities and the contributions that individual (local) sites make to regional dynamics. We propose that recent advances in diversity-partitioning methods may allow for a better understanding of metacommunity dynamics and the identification of keystone sites. We used time series of the 2 components of beta diversity (richness and replacement) and the contributions of local sites to these components to examine which sites controlled source-sink dynamics in a highly dynamic model system (an intermittent river). The relative importance of the richness and replacement components of beta diversity fluctuated over time, and sample aggregation led to underestimation of beta diversity by up to 35%. Our literature review revealed that research on intermittent rivers would benefit greatly from examination of beta-diversity components over time. Adequately appraising spatiotemporal variability in community composition and identifying sites that are pivotal for maintaining biodiversity at the landscape scale are key needs for conservation prioritization and planning. Thus, our framework may be used to guide conservation actions in highly dynamic ecosystems when time-series data describing biodiversity across sites connected by dispersal are available.