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Tropical forest tree communities are structured by a range of large-scale drivers including elevation, certain high-impact anthropogenic activities (e.g., deforestation), and fires. However, low-impact human activities such as foraging may also be subtly but notably altering the composition of tropical forest tree communities. The study assessed the (i) differences in species diversity, patterns of relative abundance, and pairwise beta diversity between trees with edible and inedible fruits and seeds along an elevation gradient, and (ii) impact of human foraging on the forest tree communities in Oban Division of Cross River National Park, Nigeria. Fifteen permanent 40 by 40 m plots were established along an elevational gradient (120–460 m above mean sea level). All trees of 0.1 m diameter at breast height (dbh) and above were measured, identified, and, with the aid of structured questionnaires, classified into those with edible and inedible fruits/seeds. A total of 35 edible species with density of 128 stems/hectare and basal area of 11.99 m2/hectare, and 109 inedible species with density of 364 stems/hectare and basal area of 22.42 m2/hectare were sampled. However, the evenness of edible and inedible species was similar at pooled and plot levels. For inedible species, there was a positive relationship between pairwise beta diversity and elevation, and this was driven mainly by turnover. In contrast, edible species exhibited a non-significant trend between elevation and beta diversity. Thus, the study showed that human foraging of edible fruits may have subtly influenced patterns of species diversity and community structure in this tropical forest. FUNDING: Petroleum Technology Development Fund (PTDF), Nigeria, Grant/Award Number: PTDF/ED/PHD/ASA/1342/18. info:eu-repo/semantics/publishedVersion

AIM: The world's islands support disproportionate levels of endemic avian biodiversity despite suffering numerous extinctions. While intensive recent research has focused on island bird conservation or extinction, few global syntheses have considered these factors together from the perspective of morphological trait diversity. Here, we provide a global summary of the status and ecology of extant and extinct island birds, the threats they face and the implications of species loss for island functional diversity. LOCATION: Global. TAXON: Birds. METHODS: We provide a review of the literature on threatened and extinct island birds, with a particular focus on global studies that have incorporated functional diversity. Alongside this, we analyse IUCN Red List data in relation to distribution, threats and taxonomy. Using null models and functional hypervolumes, in combination with morphological trait data, we assess the functional diversity represented by threatened and extinct island endemic birds. RESULTS AND MAIN CONCLUSIONS: We find that almost half of all island endemic birds extant in 1500 CE are currently either extinct or threatened with extinction, with the majority of threatened extant species having declining population trends. We also found evidence of 66 island endemic subspecies extinctions. The primary threats to extant island endemic birds currently are agriculture, biological resource use, and invasive species. While there is overlap between the hotspots of threatened and extinct island endemics birds, there are some notable differences, including the Philippines and Indonesia, which support a substantial number of threatened species but have no recorded post-1500 CE bird extinctions. Traits associated with threatened island endemic birds are large body mass, flightlessness, aquatic predator, omnivorous and vertivorous trophic niches, marine habitat affinity, and, paradoxically, higher dispersal ability. Critically, we find that threatened endemics (i) occupy distinct areas of beak morphospace, and (ii) represent substantial unique areas of the overall functional space of island endemics. We caution that the loss of threatened species may have severe effects on the ecological functions birds provide on islands. Government of Catalonia, Grant/Award Number: 2020 BP 00067. info:eu-repo/semantics/publishedVersion

Research on island species–area relationships (ISAR) has expanded to incorporate functional (IFDAR) and phylogenetic (IPDAR) diversity. However, relative to the ISAR, we know little about IFDARs and IPDARs, and lack synthetic global analyses of variation in form of these three categories of island diversity–area relationship (IDAR). Here, we undertake the first comparative evaluation of IDARs at the global scale using 51 avian archipelagic data sets representing true and habitat islands. Using null models, we explore how richness-corrected functional and phylogenetic diversity scale with island area. We also provide the largest global assessment of the impacts of species introductions and extinctions on the IDAR. Results show that increasing richness with area is the primary driver of the (non-richness corrected) IPDAR and IFDAR for many data sets. However, for several archipelagos, richness-corrected functional and phylogenetic diversity changes linearly with island area, suggesting that the dominant community assembly processes shift along the island area gradient. We also find that archipelagos with the steepest ISARs exhibit the biggest differences in slope between IDARs, indicating increased functional and phylogenetic redundancy on larger islands in these archipelagos. In several cases introduced species seem to have ‘re-calibrated’ the IDARs such that they resemble the historic period prior to recent extinctions. info:eu-repo/semantics/publishedVersion

The study of functional diversity (FD) provides ways to understand phenomena as complex as community assembly or the dynamics of biodiversity change under multiple pressures. Different frameworks are used to quantify FD, either based on dissimilarity matrices (e.g., Rao entropy, functional dendrograms) or multidimensional spaces (e.g. convex hulls, kernel-density hypervolumes). While the first does not enable the measurement of FD within a richness/divergence/regularity framework, or results in the distortion of the functional space, the latter does not allow for comparisons with phylogenetic diversity (PD) measures and can be extremely sensitive to outliers.We propose the use of neighbor-joining trees (NJ) to represent and quantify functional diversity in a way that combines the strengths of current FD frameworks without many of their weaknesses. Our proposal is also uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles.We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel-density hypervolumes using both simulated and empirical datasets.Using NJ we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree-based representations. Moreover, the method is directly comparable with PD measures, and enables quantification of the richness, divergence and regularity of the functional space.

Habitat islands can be defined as distinct patches of habitat surrounded by less contrasting matrix types. In contrast to true island biogeography (traditionally the study of islands surrou...

Human activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbance affect the shape of macroecological patterns, and therefore analyzing these patterns can provide insights into how ecosystems are affected by land use change. We here use arthropod census data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: native forest, exotic forest, semi-natural pasture and intensive pasture, to examine the effects of land use type on three macroecological patterns: the species abundance distribution, the metabolic rate distribution of individuals and the species–area relationship. The maximum entropy theory of ecology (METE) has successfully predicted these patterns across habitats and taxa in undisturbed ecosystems, and thus provides a null expectation for their shapes. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture is consistently the worst fit, and the intensive pasture is intermediately well fit. We show that the direction of failure of the METE predictions at the pasture sites is likely due to the hyper-dominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium, leading to greater heterogeneity in composition and complex dynamics that violate METE's assumption of static state variables. The comparative better fit for the intensive pasture plausibly results from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux. Analyzing deviations from theoretical predictions across land use type provides useful information about how land use and disturbance affect ecosystems, and such comparisons could be useful across other habitats and taxa. Funding for this project was provided in part by grant DEB 1751380 from the US National Science Foundation, as well as by grants to PAVB FCT-UIDP/00329/2020-2024 (Thematic Line 1 – integrated ecological assessment of environmental change on biodiversity) and MACRISK – PTDC/BIA-CBI/0625/2021, through the FCT – Fundação para a Ciência e a Tecnologia. MB acknowledges the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) (PGSD2-517114-2018). Data acquisition was provided by the projects: ‘Consequences of land use change on Azorean fauna and flora – the 2010 Target' (Ref: Direcção Regional de Ciência e Tecnologia M.2.1.2/I/003/2008) and ‘Direcção Regional dos Recursos Florestais' (‘Secretaria Regional da Agricultura e Pescas') through the Project ‘Reservas Florestais dos Açores: Cartografia e Inventariação dos Artrópodes Endémicos dos Açores' (PROJ. 17.01 – 080203). info:eu-repo/semantics/publishedVersion

Tobias, Joseph A., Sheard, Catherine, Pigot, Alex L., Devenish, Adam J. M., Yang, Jingyi, Sayol, Ferran, Neate‐Clegg, Montague H. C., Alioravainen, Nico, Weeks, Thomas L., Barber, Robert A., Walkden, Patrick A., MacGregor, Hannah E. A., Jones, Samuel E. I., Vincent, Claire, Phillips, Anna G., Marples, Nicola M., Montaño‐Centellas, Flavia A., Leandro‐Silva, Victor, Claramunt, Santiago, Darski, Bianca, Freeman, Benjamin G., Bregman, Tom P., Cooney, Christopher R., Hughes, Emma C., Capp, Elliot J. R., Varley, Zoë K., Friedman, Nicholas R., Korntheuer, Heiko, Corrales‐Vargas, Andrea, Trisos, Christopher H., Weeks, Brian C., Hanz, Dagmar M., Töpfer, Till, Bravo, Gustavo A., Remeš, Vladimír, Nowak, Larissa, Carneiro, Lincoln S., Moncada R., Amilkar J., Matysioková, Beata, Baldassarre, Daniel T., Martínez‐Salinas, Alejandra, Wolfe, Jared D., Chapman, Philip M., Daly, Benjamin G., Sorensen, Marjorie C., Neu, Alexander, Ford, Michael A., Mayhew, Rebekah J., Fabio Silveira, Luis, Kelly, David J., Annorbah, Nathaniel N. D., Pollock, Henry S., Grabowska‐Zhang, Ada M., McEntee, Jay P., Carlos T. Gonzalez, Juan, Meneses, Camila G., Muñoz, Marcia C., Powell, Luke L., Jamie, Gabriel A., Matthews, Thomas J., Johnson, Oscar, Brito, Guilherme R. R., Zyskowski, Kristof, Crates, Ross, Harvey, Michael G., Jurado Zevallos, Maura, Hosner, Peter A., Bradfer‐Lawrence, Tom, Maley, James M., Stiles, F. Gary, Lima, Hevana S., Provost, Kaiya L., Chibesa, Moses, Mashao, Mmatjie, Howard, Jeffrey T., Mlamba, Edson, Chua, Marcus A. H., Li, Bicheng, Gómez, M. Isabel, García, Natalia C., Päckert, Martin, Fuchs, Jérôme, Ali, Jarome R., Derryberry, Elizabeth P., Carlson, Monica L., Urriza, Rolly C., Brzeski, Kristin E., Prawiradilaga, Dewi M., Rayner, Matt J., Miller, Eliot T., Bowie, Rauri C. K., Lafontaine, René‐Marie, Scofield, R. Paul, Lou, Yingqiang, Somarathna, Lankani, Lepage, Denis, Illif, Marshall, Neuschulz, Eike Lena, Templin, Mathias, Dehling, D. Matthias, Cooper, Jacob C., Pauwels, Olivier S. G., Analuddin, Kangkuso, Fjeldså, Jon, Seddon, Nathalie, Sweet, Paul R., DeClerck, Fabrice A. J., Naka, Luciano N., Brawn, Jeffrey D., Aleixo, Alexandre, Böhning‐Gaese, Katrin, Rahbek, Carsten, Fritz, Susanne A., Thomas, Gavin H., Schleuning, Matthias (2022): AVONET: morphological, ecological and geographical data for all birds. Ecology Letters 25 (3): 581-597, DOI: 10.1111/ele.13898, URL: http://dx.doi.org/10.1111/ele.13898

AIM: The aim was to identify the primary drivers of compositional change in breeding bird assemblages over a 40-year period. LOCATION: Britain. TIME PERIOD: From 1970 to 2010. MAJOR TAXA STUDIED: Birds. METHODS: Using morphological trait measurements and a dataset of presence-absence data for British breeding birds surveyed in 10 km × 10 km hectads during two time periods, we calculated temporal taxonomic and functional beta diversity for each hectad alongside the change in species richness, mean nearest taxon distance (MNTD) and mean pairwise distance (MPD). We also estimated potential drivers of beta diversity, including climatic and land-use and land-cover (LULC) change variables, elevation and assemblage species richness in 1970 (1970rich). We used random forest regressions to test which variables best explained compositional change in the assemblages. We also assessed spatial taxonomic and functional change by analysing multiple-site beta diversity and pairwise dissimilarities between time periods. RESULTS: Initial (1970) species richness was the most important predictor (highest importance score) across all models, with areas characterized by higher initial richness experiencing less assemblage change overall. The coordinates included to capture spatial autocorrelation in the data were also important predictors of change. Most cli-mate and LULC variables had relatively low explanatory power; elevation and average temperature were the most influential. All metrics increased slightly with increasing elevation, except for species richness change and MPD, which decreased. MAIN CONCLUSIONS: The composition of British breeding bird assemblages changed substantially between 1970 and 2010. Spatial heterogeneity increased, both taxonomically and functionally. We show evidence that hectads with larger assemblages have been buffered from temporal diversity change and that those at higher elevations changed more in composition than those at lower elevations. Overall, coarse-resolution climate and LULC explained only small to moderate amounts of variation, suggesting that stochastic assembly change or finer-scale drivers might be drivers of temporal changes in assemblage composition. British Trust for Ornithology (BTO). info:eu-repo/semantics/publishedVersion

[EN] Species abundance distributions (SADs) link species richness with species abundances and are an important tool in the quantitative analysis of ecological communities. Niche-based and sample-based SAD models predict different spatial scaling properties of SAD parameters. However, empirical research on SAD scaling properties is largely missing. Here we extracted percentage cover values of all occurring vascular plants as proxies of their abundance in 1725 10-m(2) plots from the GrassPlot database, covering 47 regional data sets of 19 different grasslands and other open vegetation types of the Palaearctic biogeographic realm. For each plot, we fitted the Weibull distribution, a model that is able to effectively mimic other distributions like the log-series and lognormal, to the species-log abundance rank order distribution. We calculated the skewness and kurtosis of the empirical distributions and linked these moments, along with the shape and scale parameters of the Weibull distribution, to plot climatic and soil characteristics. The Weibull distribution provided excellent fits to grassland plant communities and identified four basic types of communities characterized by different degrees of dominance. Shape and scale parameter values of local communities on poorer soils were largely in accordance with log-series distributions. Proportions of subdominant species tended to be lower than predicted by the standard lognormal SAD. Successive accumulation of plots of the same vegetation type yielded nonlinear spatial scaling of SAD moments and Weibull parameters. This scaling was largely independent of environmental correlates and geographic plot position. Our findings caution against simple generalizations about the mechanisms that generate SADs. We argue that in grasslands, lognormal-type SADs tend to prevail within a wider range of environmental conditions, including more extreme habitats such as arid environments. In contrast, log-series distributions are mainly restricted to comparatively species-rich communities on humid and fertile soils. We thank all vegetation scientists who carefully collected the plant diversity data and contributed them to GrassPlot. The Eurasian Dry Grassland Group (EDGG) and the International Association for Vegetation Science (IAVS) supported the EDGG field workshops, which generated a core part of the GrassPlot data. The Bavarian Research Alliance (via the BayIntAn scheme) and the Bayreuth Center of Ecology and Environmental Research (BayCEER) funded the initial GrassPlot workshop during which the database was established (grants to Jurgen Dengler). Werner Ulrich acknowledges support from the Polish National Science Centre (Grant 2017/27/B/NZ8/00316). Idoia Biurrun and Juan Antonio Campos were partly supported by the Basque Government (IT936-16). Goffredo Filibeck was partly supported by the MIUR initiative "Department of Excellence" (Law 232/2016) granted to DAFNE. Peter Torok was supported by the NKFIH K 119225 and K 137573 projects and the HAS Momentum Program during the manuscript preparation. Franz Essl appreciates funding by the Austrian Science Foundation FWF (Grant I 3757-B29).

Islands have fascinated biologists since the days of Charles Darwin and Alfred Russel Wallace and before, providing the inspiration for substantial theoretical development that has advanced our understanding of global biodiversity patterns and the mechanisms that underpin them. As such, they are often termed 'natural laboratories', providing the ideal setting to study the interface between ecology, evolution and conservation. Part of this fascination no-doubt arises from islands harboring a disproportionate amount of global biodiversity given the amount of land-mass they occupy (roughly 15-20% of global terrestrial species present in just 3.5% of global land), including large numbers of endemic forms not found anywhere else. Interestingly, more than 25% of human languages, many of which are also threatened with extinction, are also to be found on islands. In this primer, we provide an overview of the field of island biogeography, splitting it into three main sections. First, we explore some of the reasons that make islands, and the species that have evolved on them, unique and scientifically rewarding study systems for ecologists and biogeographers. Second, we delve into the key island biogeography works in order to provide an introductory summary of some of the main theoretical models developed to explain species diversity patterns on islands. Unfortunately, as well as representing captivating environments to study, islands are also highly threatened systems. As such, we end with an overview of the drivers and impacts of anthropogenic environmental change on islands, providing examples of some of the extraordinary island species that humans have driven extinct.

Human activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbances affect the shape of macroecological patterns, and analyzing these patterns can provide insights into how ecosystems are affected by land use change. The Maximum Entropy Theory of Ecology (METE) simultaneously predicts many of these patterns using a set of ecological state variables: the number of species, the number of individuals, and the total metabolic rate. The theory9s predictions have been shown to be successful across habitats and taxa in undisturbed natural ecosystems, although previous tests of METE in relation to disturbance have focused primarily on systems where the state variables are changing relatively quickly. Here, we assess predictions of METE applied to a different type of disturbance: land use change. We use METE to simultaneously predict the species abundance distribution (SAD), the metabolic rate distribution of individuals (MRDI), and the species--area relationship (SAR) and compare these predictions to arthropod data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: 1. native forest, 2. exotic forest, 3. semi-natural pasture, and 4. intensive pasture. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture consistently provided the worst fit. The intensive pasture is intermediately well fit for the SAD and MRDI, and comparatively well fit for the SAR, though the residuals are not normally distributed. The direction of failure of the METE predictions at the pasture sites is likely due to the hyper-dominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium and the changing management practices throughout the year, leading to greater heterogeneity in composition and complex dynamics that violate METE9s assumption of static state variables. The comparative better fit for the intensive pasture could then result from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux.

AIM: The positive relationship between species richness and area-the species-area relationship (SAR)-is a key principle in ecology. Previous studies show large variation in the SAR across taxa collectively indicating the necessity of a taxon-focused approach to accurately evaluate biodiversity scaling patterns. Ants are ideal for this given their global distribution and role in ecosystem functioning. Using data from insular ant communities, this study quantified and investigated various attributes of ant SARs and reviewed the SAR literature for ant faunas, world-wide, to identify specific areas for improvement. LOCATION: Islands around the world. TAXON: Ants (Hymenoptera: Formicidae). METHODS: We aggregated data on species richness and island characteristics from previous studies on ant SARs to evaluate effects of climate, biogeographic realm, and latitude on slope values from these studies. A multimodel inference approach was used to determine the form of the different SARs, and whether there were any differences between mainland and insular SARs. We also assessed differences between mainland and insular SAR slopes and intercepts. To seek a general slope coefficient for ants, we used a mixed-effect model. Finally, we tested for potential thresholds in the global insular SAR using piecewise regression models. RESULTS: There was a negative relationship between SAR slopes and precipitation in both mainland and insular SARs, while SAR slopes and intercept values were higher in mainland compared to insular systems. Strong evidence of thresholds emerged in the global insular SAR. Finally, a general slope of 0.16 was observed for insular systems, which is lower than found in previous studies. MAIN CONCLUSIONS: A taxon-focused approach proves to showcase unexpected patterns in the SAR. Ant diversity increases faster across area in mainland areas compared to true islands. The influences of climate and biogeographic realms on the ant SAR warrant deeper study. Our review highlights knowledge gaps in the ant SAR that also extend to other taxa, such as the effects of nonnative species on the SAR. info:eu-repo/semantics/publishedVersion

Aim: In fresh waters, most biogeographical understanding of how extreme events such as drought modify biodiversity and ecosystem functioning derives from static, spatial comparisons of ecological communities, between intact and disturbed sites or along stress gradients. Impacts of drought on the development of ecological communities over time remain poorly resolved, with information on parallel trends in community structure and function particularly scarce. In theory, drought could progressively eliminate both species and functional traits, rendering communities increasingly taxonomically and functionally nested subsets of their pre-existing counterparts. Alternatively, drought could create new niche opportunities, producing a continuous turnover of species and traits, or simply constrain natural community succession. Location: Dorset, UK. Taxon: Aquatic invertebrates. Methods: We studied temporal changes in community structure and function in artificial streams over 2 years, comparing drought (frequent drying) with control (constant flow) conditions. Temporal beta diversity was partitioned into turnover and nestedness components, calculated using both presence–absence and abundance data, and analysed using time-lag and null modelling approaches. Results: Community development was comparable taxonomically under control and drought conditions, driven primarily by temporal turnover of species. Under control conditions, corresponding trends in functional composition were not apparent, and species turnover was characterized by the progressive replacement of some species by others of equivalent abundance. By contrast, species turnover in disturbed communities was accompanied by both functional turnover and greater loss of individuals, indicating that new colonists were not equivalent, either functionally or numerically, to those they replaced. Furthermore, functional dissimilarities between time points were greatest under drought, and more similar in magnitude to taxonomic dissimilarities, implying that drying reduced the stability and redundancy of functional attributes. Main conclusion: A shift to drier climate could disrupt the natural development of stream community structure, and undermine functional stability, at local and biogeographical scales, with potentially significant consequences for ecosystem services provisioning in fresh waters.

Aim: The species abundance distribution (SAD) is a fundamental pattern in macroecology. Understanding how SADs vary spatially, and identifying the variables that drive any change, is important from a theoretical perspective because it enables greater understanding of the factors that underpin the relative abundance of species. However, precise knowledge on how the form of SADs varies across large (continental) scales is limited. Here, we use the shape parameter of the gambin distribution to assess how meta-community-scale SAD shape varies spatially as a function of various climatic variables and dataset characteristics. Location: Eastern North America (ENA). Time period: Present day. Major taxa studied: Trees. Methods: Using an extensive continental-scale dataset of 863,930 individual trees in plots across ENA sampled using a standardized method, we use a spatial regression framework to examine the effect of temperature and precipitation on the form of the SAD. We also assess whether the prevalence of multimodality in the SAD varies spatially across ENA as a function of temperature and precipitation, in addition to other sample characteristics. Results: We found that temperature, precipitation and species richness can explain two-thirds of the variation in tree SAD form across ENA. Temperature had the largest effect on SAD shape, and it was found that increasing temperature resulted in more logseries-like SAD shapes (i.e. SADs with a relatively higher proportion of rarer species). We also found spatial variation in SAD multimodality as a function of temperature and species richness. Main conclusions: Our results indicate that temperature is a key environmental driver governing the form of ENA tree meta-community-scale SADs. This finding has implications for our understanding of local-scale variation in tree abundance and suggests that niche factors and environmental filtering are important in the structuring of ENA tree communities at larger scales. (Less)

The study of species abundance distributions (SADs) needs a precise modeling of their drivers and ecological implications. We introduce the two-parameter Weibull distribution as a versatile tool to fit various kinds of observed SADs and to compare observed and theoretically expected values at the species level. We show that the shape and the scale parameter of this distribution have precise ecological interpretations, the first being a measure of the excess of either rare or common species, and the second as a quantification of the proportion of persistent species in the focal community. Applying the Weibull model to 534 global tree communities we demonstrate that plots of the parameters of the Weibull distribution demark ecologically impossible species abundance distributions. This promises new insight into the ecological constraints on community assembly.

QUESTIONS: Which environmental factors influence fine-grain beta diversity of vegetation and do they vary among taxonomic groups? LOCATION: Palaearctic biogeographic realm. METHODS: We extracted 4,654 nested-plot series with at least four different grain sizes between 0.0001 m² and 1,024 m² from the GrassPlot database, covering a wide range of different grassland and other open habitat types. We derived extensive environmental and structural information for these series. For each series and four taxonomic groups (vascular plants, bryophytes, lichens, all), we calculated the slope parameter (z-value) of the power law species–area relationship (SAR), as a beta diversity measure. We tested whether z-values differed among taxonomic groups and with respect to biogeographic gradients (latitude, elevation, macroclimate), ecological (site) characteristics (several stress–productivity, disturbance and heterogeneity measures, including land use) and alpha diversity (c-value of the power law SAR). RESULTS: Mean z-values were highest for lichens, intermediate for vascular plants and lowest for bryophytes. Bivariate regressions of z-values against environmental variables had rather low predictive power (mean R² = 0.07 for vascular plants, less for other taxa). For vascular plants, the strongest predictors of z-values were herb layer cover (negative), elevation (positive), rock and stone cover (positive) and the c-value (U-shaped). All tested metrics related to land use (fertilization, livestock grazing, mowing, burning, decrease in naturalness) led to a decrease in z-values. Other predictors had little or no impact on z-values. The patterns for bryophytes, lichens and all taxa combined were similar but weaker than those for vascular plants. CONCLUSIONS: We conclude that productivity has negative and heterogeneity positive effects on z-values, while the effect of disturbance varies depending on type and intensity. These patterns and the differences among taxonomic groups can be explained via the effects of these drivers on the mean occupancy of species, which is mathematically linked to beta diversity. The Bavarian Research Alliance (via the BayIntAn scheme) and the Bayreuth Center of Ecology and Environmental Research (BayCEER) funded the initial GrassPlot workshop during which the database was established and the current paper was initiated (grants to JDe). WU acknowledges support from the Polish National Science Centre (grant 2017/27/B/NZ8/00316). IB, JAC and IG-M were funded by the Basque Government (IT936-16). GF carried out the research in the frame of the MIUR initiative "Department of excellence" (Law 232/2016). SBa was supported by the GINOP-2.3.2-15-2016-00019 project. CM was supported by the Czech Science Foundation (grant no. 19-28491X) and the Basque Government (IT936-16). ID was supported by the Polish National Science Centre (grant DEC-2013/09/N/NZ8/03234) and by a Swiss Government Excellence Scholarship for Postdocs (ESKAS No. 2019.0491). MJ was supported by the Slovak Academy of Sciences (grant VEGA 02/0095/19). AN was supported by a " Master Plan Project" in the University of Mazandaran, Iran. DS was supported by the Czech Science Foundation (grant no. 20-29554X). AK, IV and DV were supported by the National Research Foundation of Ukraine (project no. 2020.01/0140). JDo was supported by the Czech Science Foundation (GA17-19376S) and LTAUSA18007 info:eu-repo/semantics/publishedVersion

Large body size, the defining characteristic of "charismatic megafauna," is often viewed as the most significant correlate of higher public interest in species. However, common, local species (many of which are not large) can also generate public interest. We explored the relative importance of body size versus local occurrence in patterns of online interest in birds using a large sample of digital human-wildlife interactions (367 million Wikipedia pageviews) that included more than 10,000 bird species and a range of cultural and geographic contexts (represented by 25 Wikipedia language editions). We compared interest in Wikipedia, as measured by pageviews, with a bird's body size and its regional observation frequency (using data from ). We found that local species (i.e., those that occur in the wild in the country responsible for the majority of a Wikipedia language edition's pageviews) attract more pageviews than global species. Both body size and observation frequency had a positive correlation with Wikipedia pageviews across languages, but eBird observation frequency explained more of the variance in pageviews on average. In a model that included both observation frequency and body size, observation frequency was a significantly better predictor of pageviews than body size in 24 of 25 languages. Our results demonstrate that the opportunity to encounter birds in the wild is a significant correlate of increased online interest in birds across multiple linguistic and geographic contexts. This relationship provides insight into why some species attract greater interest than others and emphasizes the overlooked potential of common species in conservation marketing. info:eu-repo/semantics/publishedVersion

An increasing number of studies have focused on identifying thresholds in the species–area relationship (SAR). The most common approach in such studies is to use piecewise regression models. While a few software packages are available for fitting piecewise models, these resources are general regression packages (i.e., they are not specifically designed for the analysis of SAR data) and tend to only provide functions for fitting a subset of the piecewise models proposed in the SAR literature. Given the large number of SAR studies now fitting piecewise models, there is a need for a software package that provides functions for fitting a range of piecewise models, including continuous, left-horizontal and discontinuous models in addition to supplementary functions for analysing model fits, in the context of SAR data. To this end, we provide a set of functions for fitting six piecewise regression models to SAR data, calculating confidence intervals around the breakpoint estimates (for certain models), comparing the models using various information criteria, and plotting the resultant model fits. Here, we present these functions and illustrate them using a selection of empirical datasets. These functions are implemented in the freely available and open-source R package ‘sars.’

QUESTION: To better understand the influence of deep-time diversification on extant plant communities, we assessed how community dissimilarity increases with spatial and climatic distances at multiple taxonomic ranks (species, genus, family, and order) in angiosperm trees. We tested the prediction that the dissimilarity–distance relationship should change across taxonomic ranks depending on the deep-time diversification in different biogeographical regions reflecting geohistories and geographical settings. LOCATION: Global. METHODS: Using a data set of plot-based surveys across the globe (861 plots), we compiled a community composition matrix comprising 21,455 species, 2,741 genera, 240 families, and 57 orders. We then calculated Sørensen's pairwise dissimilarity (βsor), and its turnover (βsim) and nestedness (βsne) components, among plots within seven biogeographical regions. Finally, we modeled the relationships between the biotic dissimilarities and the spatial/climatic distances at each taxonomic rank, and compared them among regions. RESULTS: βsor and βsim increased with increasing spatial and climatic distance in all biogeographical regions: βsim was dominant in all biogeographical regions in general, while βsne showed relatively high contributions to total dissimilarity in the temperate regions with historically unstable climatic conditions. The βsim-distance curve was more saturated at smaller spatial scales in the tropics than in the temperate regions. In general, the curves became flatter at higher taxonomic ranks (order or family), with the exception of Africa, North America, and Australia, pointing to region-specific geographical constraints. CONCLUSIONS: Compositional dissimilarity was generally shaped through the abrupt turnover of species along spatial/climatic gradients. The relatively high importance of the nestedness component in the temperate regions suggests that historical dispersal filters related to extinction/colonization may play important roles. Region-specific changes in the turnover and nestedness components across taxonomic ranks suggest differential imprints of historical diversification over deep evolutionary time in shaping extant diversity patterns in each biogeographical region. Financial support was provided by the Japan Society for the Promotion of Science (no. 20H03328), the Program for Advancing Strategic International Networks to Accelerate the Circulation of Talented Researchers by the Japan Society for the Promotion of Science and the Environment Research and Technology Development fund (JPMEERF20184002) of the Ministry of the Environment, Japan. info:eu-repo/semantics/publishedVersion

Spatial variation in community composition may be driven by a variety of processes, including environmental filtering and dispersal limitation. While work has been conducted on the relative importance of these processes on various taxa and at varying resolutions, tests using high-resolution empirical data across large spatial extents are sparse. Here, we use a dataset on the presence/absence of breeding bird species collected at the 10 km × 10 km scale across the whole of Britain. Pairwise spatial taxonomic and functional beta diversity, and the constituent components of each (turnover and nestedness/richness loss or gain), were calculated alongside two other measures of functional change (mean nearest taxon distance and mean pairwise distance). Predictor variables included climate and land use measures, as well as a measure of elevation, human influence, and habitat diversity. Generalized dissimilarity modeling was used to analyze the contribution of each predictor variable to variation in the different beta diversity metrics. Overall, we found that there was a moderate and unique proportion of the variance explained by geographical distance per se, which could highlight the role of dispersal limitation in community dissimilarity. Climate, land use, and human influence all also contributed to the observed patterns, but a large proportion of the explained variance in beta diversity was shared between these variables and geographical distance. However, both taxonomic nestedness and functional nestedness were uniquely predicted by a combination of land use, human influence, elevation, and climate variables, indicating a key role for environmental filtering. These findings may have important conservation implications in the face of a warming climate and future land use change.

The necessity to restore rainforest habitats degraded by anthropogenic fires is widely recognized, however, research on restoration approaches has mainly centred on the recovery of forest structural complexity. There is insufficient evidence on the efficacy of restoration methods in the recovery of the faunal diversity and features linked to key ecosystem functions. We assessed the taxonomic diversity and functional trait structure of bird assemblages in undisturbed primary forest and fire-affected habitats undergoing natural regeneration, as well as areas of assisted natural regeneration, in Nyungwe National Park, Rwanda. We compiled bird occurrence data from point-count sampling, and obtained morphological traits for all species in our assemblages using measurements taken from wild birds and museum specimens. We found marked differences in species composition between primary forest habitats and regenerating forest, with similarity increasing over time since perturbation. Taxonomic diversity was higher in primary forest, and similar between the two restoration approaches. Functional diversity was lower in assisted naturally regenerated habitats, although separate analyses within dietary guilds revealed no differences across habitats. Among desired restoration outcomes, tree species diversity was the leading positive driver of avian species diversity, fern coverage exerted negative effects, while canopy cover had a positive but weak influence. Our findings underscore the importance of preventing anthropogenic fires in tropical rainforest since their impacts on ecological processes are not easily reversed, as shown by the lack of improvement in avian diversity metrics under assisted naturally regeneration in relation to natural regeneration. We stress the need to document both floral and faunal recovery in order to aid informed decision-making on restoration methods. This work was supported by the Commonwealth Scholarship Commission, National Geographic Society (WW-086EC-17, 4472), the British Ecological society (EA17/1169) and Christ Church College, University of Oxford. Measurement of morphological traits was funded by Natural Environment Research Council grant nos. NE/I028068/1 and NE/P004512/1 (J.A.T.). info:eu-repo/semantics/publishedVersion

AIM: The small-island effect (SIE) describes a different relationship between island area and species richness on smaller compared to larger islands. The pattern has recently gained widespread support. However, few studies have attempted to identify the actual mechanisms driving the SIE. Here, we use a phylogenetic community framework to study the SIE, based on the assumption that if the dominant assembly processes differ between small and large islands, patterns of phylogenetic community structure should shift across the area and habitat diversity gradient. LOCATION: The Aegean Archipelago, Greece. TAXON: Plants. METHODS: We used a large dataset of 3,262 vascular plant species distributed across 173 islands, in combination with a species-level phylogeny. The phylogenetic community structure of each island was calculated using a null modelling framework and was quantified using effect sizes (ES); negative values indicating phylogenetic clustering and positive values overdispersion. Habitat diversity, species richness, phylogenetic diversity (PD) and ES values were regressed against log10-transformed area and we tested for a SIE using piecewise regression models. We also assessed differences in taxonomic and phylogenetic composition between small and large islands using a beta diversity framework. RESULTS: We found evidence of a SIE using species richness, PD and phylogenetic community structure (ES values). Small islands displayed low variation in habitat diversity and tended to be more phylogenetically clustered, while large islands shifted from phylogenetic clustering towards phylogenetic overdispersion with increasing area and habitat diversity. In addition, we showed that phylogenetic composition tended to be more similar between small islands than expected. MAIN CONCLUSION: Overall, our results provide an example of a SIE in the analysis of island phylogenetic community structure, and point to a role of habitat diversity in driving the SIE more generally. College of Life and Environmental Sciences (University of Birmingham). info:eu-repo/semantics/publishedVersion

Recently, a 2018 study by Ulrich et al. introduced the Weibull distribution as a flexible approach to model the distribution of species abundances in ecological communities. They pointed to possible limitations in the realized parameter spaces of this distribution as possibly indicating ecological constraints on species abundances. Here, we explore this question in detail using three large global data sets on quantitatively assessed plant, invertebrate, and vertebrate communities. By fitting the Weibull distribution to these communities, we confirm that only a minor amount of the possible ranges in the scale and the shape parameters of the Weibull distribution are realized. Shapes of distributions become more similar across taxa with increasing species richness and average abundances. This finding points to stochastic explanations for species abundance shapes, possibly linked to local colonization and extinction dynamics. We introduce the Weibull survival time parameter as a way to define the proportion of rare species in a community. This proportion increased with increasing species richness. Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of Science; National Science Center, Poland (UMO-2017/27/B/NZ8/00316) info:eu-repo/semantics/publishedVersion

Investigating the structure of ecological networks can help unravel the mechanisms promoting and maintaining biodiversity. Recently, Strona and Veech 2015 (A new measure of ecological network structure based on node overlap and segregation. – Methods Ecol. Evol. 6: 907–915) introduced a new metric (Ɲ, pronounced ‘nos’), that allows assessment of structural patterns in networks ranging from complete node segregation to perfect nestedness, and that also provides a visual and quantitative assessment of the degree of network modularity. The Ɲ metric permits testing of a wide range of hypotheses regarding the tendency for species to share interacting partners by taking into account ecologically plausible species interactions based on constraints such as trophic levels and habitat preference. Here we introduce NOS, a software suite (including a web interface freely accessible at  http://nos.alwaysdata.net , an executable program, and Python and R packages) that makes it possible to exploit the full potential of this method. Besides computing node overlap and segregation (Ɲ), the software provides different functions to automatically identify a set of possible resource–consumer interactions in food webs based on trophic levels. As an example of application, we analyzed two well-resolved high-latitude marine food webs, showing that an explicit a priori consideration of trophic levels is fundamental for a proper assessment of food web structure.

The destruction of forest for agricultural expansion has created a vast estate of human-modified land in tropical regions. One group of organisms that are particularly vulnerable to the loss of forest habitat are insectivorous birds. Despite this, few conservation strategies have been identified for this group in human-modified landscapes. We survey the use of 104 isolated trees by insectivorous birds in rural Assam, India. We used an information theoretic model comparison approach to determine the important variables driving insectivorous bird diversity within these isolated trees. Our work demonstrates that the conservation of large trees in human-modified landscapes may play an important role in maintaining bird diversity and ecological function beyond the forest edge. More specifically, we found that isolated Ficus trees hold assemblages with particularly high insectivore abundance, richness and functional diversity when compared to other isolated fruit and large trees. We argue that, where present, Ficus trees should be actively conserved in human-modified landscapes to maintain the composition of insectivore communities in a “Ficus first” strategy.

Analysis of a unique global data set reveals how the species diversity of birds is affected by the properties of archipelagos and offers a way to test an influential theory. Has this improved our understanding of island biodiversity patterns? Evidence from archipelagos worldwide confirms an influential theory.

Background: Although the species-urban green area relationship (SARu) has been analyzed worldwide, the global consistency of its parameters, such as the fit and the slope of models, remains unexplored. Moreover, the SARu can be explained by 20 different models. Therefore, our objective was to evaluate which models provide a better explanation of SARus and, focusing on the power model, to evaluate the global heterogeneity in its fit and slope. Methods: We tested the performance of multiple statistical models in accounting for the way in which species richness increases with area, and examined whether variability in model form was associated with various methodological and environmental factors. Focusing on the power model, we analyzed the global heterogeneity in the fit and slope of the models through a meta-analysis. Results: Among 20 analyzed models, the linear model provided the best fit to the most datasets, was the top ranked model according to our efficiency criterion, and was the top overall ranked model. The Kobayashi and power models were the second and third overall ranked models, respectively. The number of green areas and the minimum number of species within a green area were the only significant variables explaining the variation in model form and performance, accounting for less than 10% of the variation. Based on the power model, there was a consistent overall fit (r 2 = 0.50) and positive slope of 0.20 for the species richness increase with area worldwide. Conclusions: The good fit of the linear model to our SARu datasets contrasts with the non-linear SAR frequently found in true and non-urban habitat island systems; however, this finding may be a result of the small sample size of many SARu datasets. The overall power model slope of 0.20 suggests low levels of isolation among urban green patches, or alternatively that habitat specialist and area sensitive species have already been extirpated from urban green areas. Fil: Levau, Lucas M.. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ecología, Genética y Evolución; Argentina Fil: Ruggiero, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentina Fil: Matthews, Thomas J.. Universidade dos Açores; Portugal. University of Birmingham; Reino Unido Fil: Bellocq, Maria Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ecología, Genética y Evolución; Argentina

AIM: One of the main applications of the island species–area relationship (SAR) is to predict species richness in areas of habitat too large to be sampled, but there are few clear guidelines for choosing an appropriate model for this purpose. We therefore aimed to test whether a multi‐model averaging approach could improve the accuracy of predictions made by extrapolating the ISAR. Specifically, we compared the performance of multi‐model averaging with that of the default ISAR model of choice, the power model, in predicting species richness in large habitat islands. LOCATION: Global TAXA: Vertebrates, invertebrates and plants METHODS: We removed the largest islands from 120 habitat island datasets, and fitted both the power model and a multi‐model average curve (averaging the predictions of up to 20 ISAR models) to this filtered dataset. We then assessed the accuracy of both approaches in predicting the species richness of the largest island in the original dataset using the log error of extrapolation (LEE) metric. A generalized additive regression modelling framework was used to determine whether any dataset characteristics could explain variation in the LEE values for the power model (LEE‐POW). RESULTS: The power model gave the more accurate richness predictions for 58% of the analysed datasets and the multi‐model averaged curve gave the more accurate predictions for the remaining 42%. Both the power models (61% of LEE‐POW values were positive) and the multi‐model averaged curve (60% were positive) had a slightly greater tendency to over predict the observed richness. The confidence intervals were also on average narrower for the power model predictions (median 95% confidence interval width = 18 species) than for the multi‐model averaged curve predictions (median 95% confidence interval width = 78). The range in island areas and richness values explained a small amount of the variation in LEE‐POW. MAIN CONCLUSIONS: Contrary to expectation, multi‐model averaging was less accurate than the power model in the majority of cases, and thus does not appear to be a panacea for uncertainty in model choice when extrapolating the ISAR. However, further research is urgently needed to evaluate the performance of a multi‐model averaging approach at larger spatial scales.