Search

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

Beta diversity patterns are essential for understanding how biological communities are structured. Geographical and environmental factors, as well as species dispersal ability, are important drivers of beta diversity, but their relative importance may vary across spatial scales. In this study, we evaluate whether beta diversity changes across geographical scales and analyse how different drivers affect turnover patterns of native seed plants in an oceanic archipelago, the Azores (Portugal). Using a 500 x 500 m resolution grid, we selected cells that are covered by one of the following habitats: native forest, naturalized vegetation and seminatural pastures. We calculated species turnover at three spatial scales: i) between islands, ii) between cells within each island, and finally iii) between cells of each of the habitats of interest in each island. We then calculated the contribution of dispersal syndromes (endozoochory, epizoochory, hydrochory and anemochory) to turnover at each of the scales. Lastly, we assessed the relationship between geographical and climatic distances and habitat composition with turnover. Turnover was higher at the smallest scale, particularly in seminatural pastures, and decreased with increasing spatial scales, a pattern potentially associated with the historical fragmentation and current patchy distribution of native forest and seminatural habitats in the Azores. Dispersal syndromes and habitat composition had a negligible effect on turnover at all scales. Geographical distance had a positive effect on turnover at all scales, increasing with scale. The relationship between turnover and climatic distance was only significant at the intermediate and small scales in specific islands and habitats. Scale plays an important role at determining the effect of the drivers of turnover, in particular geographical and climatic distance. These results highlight the need to carefully select the scale of analysis when studying turnover patterns, as well as identifying the potential drivers associated with each scale.

The land-sea continuum constitutes a mixing zone where soil microbial communities encounter, via runoff, those inhabiting marine coastal sediment resulting in community coalescence. Here, we propose an experimental approach, mimicking the land-sea continuum, to study the microbial community coalescence events in different situations, by 16S and 18S rRNA genes metabarcoding. The microbial community structure of sediment diverged with the soil inputs. For prokaryotes, phylogenetic enrichment and amplicon sequence variants (ASVs) replacements characterized the community changes in sediment receiving soil inputs. For fungi, despite phylogenetic enrichment was not observed, the fungal ASVs richness was maintained by soil inputs. Comparison of microbial communities revealed ASVs specific to sediment receiving soil inputs, and also ASVs shared with soil and/or runoff. Among these specific ASVs, four bacterial and one fungal ASVs were identified as indicators of coalescence. Our study provides evidences that coalescence involves the mixing of microorganisms and of the environment.

ContextThe conversion of natural land for agriculture is a crippling threat to biodiversity. The effect of this conversion can be minimised by understanding the habitat requirements of local species and incorporating them into agricultural landscapes. Insectivorous bats, which have been shown to control a number of agricultural insect pests, exhibit species-specific responses to the surrounding landscape, tied closely to their morphology and foraging mode. The activity and distribution patterns of bats are therefore influenced by the landscape characteristics. ObjectivesThis study aimed to determine which features in the landscape surrounding rice fields influence the activity levels of insectivorous bats, and at what scales they were most influential.MethodsWe collected acoustic recordings to determine activity levels of seven bat sonotypes in rice fields surrounded by a variety of landcover types in the Nagaon district of Assam, India. Using this, we determined the most important set of features in the surrounding landscape, and the scales at which they were most predictive, for each sonotype. ResultsOur results suggest that variables related to tree cover are the most important predictors of bat activity in rice fields. Distance to nearest forest, area of forest within 1km, distance to nearest forest edge, and landscape heterogeneity influenced all five of the analysed bat sonotypes. Also important were the amount of urban land within 1km, which exerted a negative effect on the activity of one sonotype, and moonlight activity, which negatively influenced the activity levels of one sonotype. ConclusionOur results demonstrate that when in rice fields, bat activity is most influenced by presence and proximity of trees. Increasing tree cover in agricultural landscapes will increase bat activity and likely the level of pest control.

Island biota are in imminent threat from anthropogenic impacts. Of these impacts the negative effects of exotic species on the taxonomic and functional diversity of the local fauna are of particularly major concern. Aside from their impact on the diversity of native fauna, exotics may also have a detrimental effect on native interactions which, in turn, can destabilise ecological networks. Species co-occurrence networks are used to predict ecological interaction networks and utilised as tools to assess environmental impacts on community structure. Here, we investigate the topological differences of the arthropod co-occurrence networks among native forest fragments from seven Azorean islands and reveal the influence of the abiotic environment and exotic species on these networks. We found that co-occurrence networks were sensitive to environmental and community dissimilarities, showing a clear separation between islands and pinpointed differences between indigenous and exotic networks. Most exotics are little connected and exotic networks have a large proportion of unconnected species. The resulting decreased connectance and the increased modularity with the increase of the proportions of exotics in the networks suggests that most exotics have too low prevalence to show associations with other species, and only a few dominants drive co-occurrences. Moreover, the proportion of negative links, as indicators of competition, did not increase with the increase of exotics in the habitats, suggesting that exotics occupied empty niches when they colonised native forest remnants. However, when the theoretical networks consisting of only indigenous species were investigated both the number of negative associations and modularity increased with the increase of exotics, suggesting obscure competition and processes of network degradation. Since our study provides ample evidence for the usefulness of co-occurrence network analysis in studying island ecosystems, we recommend the use of this tool for ecosystem assessments, early warning systems and decision making in island biodiversity conservation.Significance statementGlobal anthropogenic biodiversity decline affects islands to a disproportionately greater extent than other ecosystems. One major cause of declining island biodiversity is the spread of exotic species which may overcompete and replace native biota. In this study, we show, by using arthropod species co-occurrence networks from the Azorean archipelago, that species association patterns reflect both abiotic and biotic impacts and that the increasing proportion of exotics in an ecosystem seemingly has little impact on association networks at large. However, when the effects on the association network of solely indigenous species were scrutinised, signs of network degradation were observed, suggesting an obscure, and most likely slow, negative impact of exotics on native arthropod assemblages. This disintegration of the co-occurrence networks can be the first sign of disappearing interaction links which, in turn, may jeopardise ecosystem function and can lead to regime shifts. In this work, we used a unique long-term dataset collected across the islands of the Azorean archipelago with standardised methodology. We built on the deep knowledge gathered over two decades on the ecology of species, as well as on the ongoing processes shaping the islands’ arthropod fauna, yet took a novel methodological approach and disentangled hidden ecological processes of great ecological and conservation concern.

A dramatic insect decline has been documented on the grasslands and forests of European or North American mainland. Yet, other parts of the world and other ecosystems remain much less studied with unknown patterns. Using a unique time-series dataset, we investigate recent trends on abundance and richness of arthropods sampled in Azorean native forest over 6 years (2013–2018). We test the hypothesis that biodiversity erosion drivers are changing the diversity and relative species abundance structure (species abundance distribution, SAD) of endemics, native non‐endemics and exotic species over time. We also examine temporal trends in abundance for each individual species. In contrast with mainland studies, we observed no decline in overall arthropod diversity, but a clear increase in the diversity of exotic arthropods and some evidence of a tendency for decreasing abundance for some endemic species. We also document stronger species turnover for exotic species, but no specific changes in the SAD. We argue that many changes, particularly in unique systems such as islands, will be noticed not at the richness but mostly at compositional level. Special attention should be given to exotic species which are known to be one of the major drivers of biodiversity erosion on islands. European Commission; Portuguese FCT-NETBIOME-ISLANDBIODIV (0003/2011); Portuguese National Funds, through FCT - Fundacão para a Ciência e a Tecnologia (UID/BIA/00329/2013-2020); Direcção Regional do Ambiente - PRIBES (LIFE17 IPE/PT/000010); Direcção Regional do Ambiente - LIFE-BETTLES (LIFE18 NAT_PT_000864); AZORESBIOPORTAL - PORBIOTA (ACORES-01-0145-FEDER-000072) info:eu-repo/semantics/publishedVersion

International audience

AIM: Habitat diversity has been linked to the diversity and structure of island communities, however, little is known about patterns and processes within habitats. Here we aim to determine the contributions of habitat type and inferred dispersal frequency to the differences in taxonomic structure between assemblages in the same island habitat. LOCATION: The Macaronesian archipelagos (Azores, Madeira, the Canary Islands and Cabo Verde). TAXON: Spiders (Araneae). METHODS: We established forest and dry habitat sites (each with five plots) on two islands per archipelago. We collected spiders using standardised sampling protocols. We tested the differences in beta diversity separately for each habitat and for each inferred category of ballooning (an aerial dispersal strategy) frequency across geographic scales through nested non-parametric permutational multivariate analyses of variance. We then tested whether ballooning and habitat influenced heterogeneity in species composition (dispersion in beta diversity) in the two habitat types. We analysed the effects of habitat and ballooning on species abundance distribution (SAD) and rarity by fitting Gambin models and evaluating the contribution of ballooning categories to SAD. RESULTS: Communities of the same archipelago and habitat were taxonomically more similar, and beta diversity increased with geographic scale, being greater in dry habitats. There was greater species replacement among assemblages in dry habitats than in forests, with greater differences for rare ballooners. There were no differences in SAD between habitats although dry habitat sites seemed to harbour more species with low abundances (rare species) than forests. MAIN CONCLUSIONS: Habitat type does not only condition the differences between spider assemblages of the same habitat but also the scale at which they occur. These differences may be determined by the heterogeneity in the physical structure of each habitat as well as how much this structure facilitates aerial dispersal (ballooning), and should be considered in theories/hypotheses on island community assembly as well as in conservation strategies. The Government of the Canary Islands, Grant/Award Number: SE-12/02, SE-12/03 and SE-12/04; Fundação para a Ciência e a Tecnologia, Grant/Award Number: FCT-PTDC/BIABIC/0054/2014, DL57/2016/CP1375/CT0003 and UIDB/00329/2020-2024; FEDER, Grant/Award Number: 0003/2011 info:eu-repo/semantics/publishedVersion

Islands have been disproportionately affected by the current biodiversity crisis. In island biotas, one of the most recurrent anthropic alterations is species introduction. Invasion of exotic species may represent a major threat for island biotas, because invasive species may change species composition and simplify community dynamics. We investigated diversity patterns of native and introduced species in native and exotic forests of Terceira Island (Azores, Portugal) by using diversity profiles based on Hill numbers. Use of diversity profiles allows for a complete characterization of the community diversity because they combine information on species richness, rarity, and dominance. We found that native forest remnants are crucial for the maintenance of endemic Azorean arthropod diversity. However, we also found that some lowland patches of exotic forests can sustain populations of rare endemic species. Our findings reinforce the importance of the few and small remnants of native forests, which are a pillar to the conservation of Azorean endemic arthropods. However, areas occupied by exotic forests, whether they are large and contiguous or small and isolated, close to native forests, or embedded in a matrix of agriculture activities, can also play a role in the conservation of native species, including endemics. Field work for 2020 and N.T. were funded by Secretaria Regional do Ambiente e Alterações Climáticas—LIFE-BETTLES (LIFE18 NAT_PT_000864) (2020). This manuscript was also partly financed by Portuguese FCT-NETBIOME–ISLANDBIODIV grant 0003/2011 (between 2012 and 2015), Portuguese National Funds, through FCT–Fundação para a Ciência e a Tecnologia, within the project UID/BIA/00329/2013–2020, the project from Direcção Regional do Ambiente—LIFE IP AZORES NATURA (LIFE17 IPE/PT/000010) (2019), AZORESBIOPORTAL–PORBIOTA (ACORES-01-0145- FEDER-000072) (2019). The Natural Park of Terceira (Azores) provided the necessary authorization for sampling. info:eu-repo/semantics/publishedVersion

The spatial distribution and seasonal variations of atmospheric iodine (I), selenium (Se) and caesium (Cs) depositions remain unclear and this precludes adequate inputs for biogeochemical models. We quantified total concentrations and fluxes of these elements in rainfalls from 27 monitoring sites in France with contrasted climatic conditions; monthly measurements were taken over one year (starting in 2016/09). Since speciation of I and Se can impact their behaviour in the environment, analysis of their inorganic compounds was also conducted. Our results showed that annual I concentrations in rainfall were much higher than those of Se and Cs (annual means = 1.56, 0.044 and 0.005 μg L-1, respectively). The annual iodine concentrations were highly positively correlated with those of marine elements (i.e. Na, Cl and Mg), involving higher I concentrations under oceanic climate than for transition, continental and mountainous ones. Furthermore, common patterns were found between Se concentrations and both marine and terrestrial components consistent with the various sources of Se in atmosphere. The association of Cs with two anthropogenic components (i.e. NH4+ and NO3-) used in agriculture supports the hypothesis of its terrestrial origin (i.e. from atmospheric dusts) in rainfall. We found higher rainfall concentrations of I during the warmest months for all climates. However, no specific seasonal trend occurred for Se and Cs. On annual average, rainfall contained mostly unidentified selenium compounds (inorganic Se proportions = 25-54%) and equal proportions of inorganic and unidentified I compounds. Concentrations of iodate were higher under oceanic climate consistent with an iodine marine-origin. We thank the technical staff of RENECOFOR-ONF for providing samples for this study as well as datasets other than those for iodine, selenium and caesium. This work was financed by the Region Nouvelle Aquitaine and the Agence Nationale de la Recherche with funds allocated in the Investissements d'Avenir' framework program under the reference ANR11-RSNR-0002. The authors thank Vicki Moore for English language assistance. The authors would like to thank Guy Pernot from the computer graphics Unit of Andra for his help in maps edition. info:eu-repo/semantics/publishedVersion

International audience; Species distributions have been profoundly affected by past climate change, and are expected to change considerably in response to future environmental change. To better apprehend how future climate change is likely to affect genetic diversity in marine populations, it is essential to first evaluate the processes that have shaped the current distribution of genetic diversity in the sea. The honeycomb worm is a reef-building polychaete that hosts high biodiversity. Here we show that the genetic diversity in populations of S. alveolata is highest towards the edges of the current species range and lowest at its center. Pleistocene glacial cycles likely led to extirpations of S. alveolata from central populations in the Bay of Biscay, with coalescent-based estimates of post-glacial colonization dating to the beginning of the Holocene interglacial, from 10,000 to 14,000 years ago. Meanwhile, populations in the Irish Sea and English Channel likely persisted in glacial refugia since the Eemian interglacial, 120,000 years ago. Northern populations host at least two sets of divergent haplotypes, indicating that two refugia possibly existed in the north, with Ireland being a likely second refugium. Within biogeographic regions, populations were overall well-connected, but strong genetic differentiation suggests that little exchange occurs between regions. These two unexpected reservoirs of genetic diversity at the range edges deserve greater attention as warming temperatures threaten trailing edge populations, while greater climatic variability threatens leading edge populations.

The widespread use of silver nanoparticles (AgNPs) in consumer products that release Ag throughout their life cycle has raised potential environmental concerns. AgNPs primarily accumulate in soil through the spreading of sewage sludge (SS). In this study, the effects of direct exposure to AgNPs or indirect exposure via SS contaminated with AgNPs on the earthworm Eisenia fetida and soil microbial communities were compared, through 3 scenarios offering increasing exposure concentrations. The effects of Ag speciation were analyzed by spiking SS with AgNPs or AgNO₃ before application to soil. SS treatment strongly impacted Ag speciation due to the formation of Ag₂S species that remained sulfided after mixing in the soil. The life traits and expression of lysenin, superoxide dismutase, cd-metallothionein genes in earthworms were not impacted by Ag after 5 weeks of exposure, but direct exposure to Ag without SS led to bioaccumulation of Ag, suggesting transfer in the food chain. Ag exposure led to a decrease in potential carbon respiration only when directly added to the soil. The addition of SS had a greater effect on soil microbial diversity than the form of Ag, and the formation of Ag sulfides in SS reduced the impact of AgNPs on E. fetida and soil microorganisms compared with direct addition. This study was funded by the ANSES in the ETNA2 project context and by a grant from the University of Lille and the SMRE doctoral school. 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.’

AIM: Research on the response of species richness to area and environmental heterogeneity so far has not addressed possible effects of species’ differences in ecological specialization. Herein we provide a new metric, ‘ecorichness’, in an attempt to fill this gap. LOCATION: Aegean islands (Greece). TAXON: Terrestrial isopods. METHODS: ‘Ecorichness’ estimates an island's biodiversity by integrating species richness and the specialists-generalists spectrum. We calculated ‘ecorichness’ for terrestrial isopods from 43 Aegean islands based on the habitats they exploit. ‘Ecorichness’ then was regressed on area, habitat diversity and the K-parameter of the Choros model using linear and quadratic models, compared based on AICc. A reduced data set, without halophilous species and coastal habitats, as well as an alternative description of habitat diversity, also was explored. The small island effect (SIE) thresholds identified using both a path analysis approach and piecewise continuous linear models were compared to the area of maximum ‘ecorichness’. RESULTS: ‘Ecorichness’ response to area and habitat heterogeneity was best fitted by quadratic models with peaks located at an area similar to the SIE threshold identified by path analysis. Different measures of habitat diversity produced similar patterns. Exclusion of coastal species and habitats shows that the response of ‘ecorichness’ to area is mostly shaped by the increasing contribution of specialists in the assemblages of larger islands. MAIN CONCLUSIONS: ‘Ecorichness’ facilitates exploration of the role of ecological specialization in shaping community patterns. It can be applied to different community data sets, whenever habitat range exploitation can be quantified. Results from the case study accord with previous suggestions that the relative contribution of generalists and specialists differs between small and large island communities. info:eu-repo/semantics/publishedVersion

Ecology, biogeography and conservation biology, among other disciplines, often rely on species identity, distribution and abundance to perceive and explain patterns in space and time. Yet, species are not independent units in the way they interact with their environment. Species often perform similar roles in networks and their ecosystems, and at least partial redundancy or difference of roles might explain co-existence, competitive exclusion or other patterns reflected at the community level. Therefore, considering species traits, that is, the organisms’ functional properties that interact with the environment, might be of utmost importance in the study of species relative abundances. Several descriptive measures of diversity, such as the species-area relationship (SAR) and the species abundance distribution (SAD), have been used extensively to characterize the communities and as a possible window to gain insight into underlying processes shaping and maintaining biodiversity. However, if the role of species in a community is better assessed by their functional attributes, then one should also study the SAR and the SAD by using trait-based approaches, and not only taxonomic species. Here we merged species according to their similarity in a number of traits, creating functional units, and used these new units to study the equivalent patterns of the SAR and of the SAD (functional units abundance distributions - FUADs), with emphasis on their spatial scaling characteristics. This idea was tested using data on arthropods collected in Terceira island, in the Azorean archipelago. Our results showed that diversity scales differently depending on whether we use species or functional units. If what determines species communities’ dynamics is their functional diversity, then our results suggest that we may need to revaluate the commonly assumed patterns of species diversity and, concomitantly, the role of the underlying processes. SA was financed by the Fundacao para a Ciencia e a Tecnologia project PTDC/BIA-BIC/5558/2014. LB-A was financed by the Portuguese national funds through FCT-Fundacao para a Ciencia e a Tecnologia, I.P., under the Norma Transitoria-DL57/2016/CP1440/CT0022. info:eu-repo/semantics/publishedVersion

Ecological systems are the quintessential complex systems, involving numerous high-order interactions and non-linear relationships. The most used statistical modeling techniques can hardly accommodate the complexity of ecological patterns and processes. Finding hidden relationships in complex data is now possible using massive computational power, particularly by means of artificial intelligence and machine learning methods. Here we explored the potential of symbolic regression (SR), commonly used in other areas, in the field of ecology. Symbolic regression searches for both the formal structure of equations and the fitting parameters simultaneously, hence providing the required flexibility to characterize complex ecological systems. Although the method here presented is automated, it is part of a collaborative human–machine effort and we demonstrate ways to do it. First, we test the robustness of SR to extreme levels of noise when searching for the species-area relationship. Second, we demonstrate how SR can model species richness and spatial distributions. Third, we illustrate how SR can be used to find general models in ecology, namely new formulas for species richness estimators and the general dynamic model of oceanic island biogeography. We propose that evolving free-form equations purely from data, often without prior human inference or hypotheses, may represent a very powerful tool for ecologists and biogeographers to become aware of hidden relationships and suggest general theoretical models and principles. PC and VB were supported by Kone Foundation. PB and FR were partly funded by the project FCT-PTDC/BIABIC/119255/2010 - Biodiversity on oceanic islands: toward a unified theory. LC was supported by FCT through LASIGE Research Unit, ref. UIDB, UIDP/00408/2020. SM acknowledges support from the European Commission through Horizon 2020 Marie Sklodowska-Curie Actions (MSCA) individual fellowships (Grant no. 882221). 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

© 2020 by the authors., Phylogenetic relatedness is a key diversity measure for the analysis and understanding of how species and communities evolve across time and space. Understanding the nonrandom loss of species with respect to phylogeny is also essential for better-informed conservation decisions. However, several factors are known to influence phylogenetic reconstruction and, ultimately, phylogenetic diversity metrics. In this study, we empirically tested how some of these factors (topological constraint, taxon sampling, genetic markers and calibration) affect phylogenetic resolution and uncertainty. We built a densely sampled, species-level phylogenetic tree for spiders, combining Sanger sequencing of species from local communities of two biogeographical regions (Iberian Peninsula and Macaronesia) with a taxon-rich backbone matrix of Genbank sequences and a topological constraint derived from recent phylogenomic studies. The resulting tree constitutes the most complete spider phylogeny to date, both in terms of terminals and background information, and may serve as a standard reference for the analysis of phylogenetic diversity patterns at the community level. We then used this tree to investigate how partial data affect phylogenetic reconstruction, phylogenetic diversity estimates and their rankings, and, ultimately, the ecological processes inferred for each community. We found that the incorporation of a single slowly evolving marker (28S) to the DNA barcode sequences from local communities, had the highest impact on tree topology, closely followed by the use of a backbone matrix. The increase in missing data resulting from combining partial sequences from local communities only had a moderate impact on the resulting trees, similar to the difference observed when using topological constraints. Our study further revealed substantial differences in both the phylogenetic structure and diversity rankings of the analyzed communities estimated from the different phylogenetic treatments, especially when using non-ultrametric trees (phylograms) instead of time-stamped trees (chronograms). Finally, we provide some recommendations on reconstructing phylogenetic trees to infer phylogenetic diversity within ecological studies., This study was supported by the project BIODIV ISLAND-CONT (Biodiversity drivers on islands and continents–706482) funded by Marie Sklodowska-Curie Individual Fellowships (H2020-MSCA-IF-2015) to the first author N.M.-H. The research was additionally funded by four other projects that provided the material collected: 1. ERA-Net Net-Biome research framework, financed through Portuguese FCT-NETBIOME grant 0003/2011 (P.A.V.B.). 2. ERA-Net Net-Biome financed through Canary Islands Government ACIISI grants SE-12/02, SE-12/03, SE-12/04 (B.C.E.), co-financed by FEDER. 3. FCT MACDIV–FCT-PTDC/BIABIC/0054/2014 (P.A.V.B.,B.C.E., P.C., I.R.A., F.R., O.S.P., A.V.). 4. Organismo Autónomo de Parques Nacionales Spain (OAPN #485/2012) (M.A.A.). Additional support was provided by grant 2017SGR83 from the Catalan Government to M.A.A. M.D. was supported by an APIF PhD fellowship from the University of Barcelona. J.L.-F. was supported by a Juan de la Cierva Fellowship (FJCI-2015-23723). I.R.A. was funded by Portuguese funds through FCT–Fundação para a Ciência e a Tecnologia, I.P., under the Norma Transitória–DL57/2016/CP1375/CT0003. Open access funding provided by University of Helsinki.

Peatlands store ∼ 20 %–30 % of the global soil organic carbon stock and are an important source of dissolved organic carbon (DOC) for inland waters. Recent improvements for in situ optical monitoring revealed that the DOC concentration in streams draining peatlands is highly variable, showing seasonal variation and short and intense DOC concentration peaks. This study aimed to statistically determine the variables driving stream DOC concentration variations at seasonal and event scales. Two mountainous peatlands (one fen and one bog) were monitored in the French Pyrenees to capture their outlet DOC concentration variability at a high-frequency rate (30 min). Abiotic variables including precipitation, stream temperature and water level, water table depth, and peat water temperature were also monitored at high frequency and used as potential predictors to explain DOC concentration variability. Results show that at both sites DOC concentration time series can be decomposed into a seasonal baseline interrupted by many short and intense peaks of higher concentrations. The DOC concentration baseline is driven, at the seasonal scale, by peat water temperature. At the event scale, DOC concentration increases are mostly driven by a rise in the water table within the peat at both sites. Univariate linear models between DOC concentration and peat water temperature or water table increases show greater efficiency at the fen site. Water recession times were derived from water level time series using master recession curve coefficients. They vary greatly between the two sites but also within one peatland site. They partly explain the differences between DOC dynamics in the studied peatlands, including peat porewater DOC concentrations and the links between stream DOC concentration and water table rise within the peatlands. This highlights that peatland complexes are composed of a mosaic of heterogeneous peat units distinctively producing or transferring DOC to streams.

Peatlands store about 20 % of the global soil organic carbon stock and are an important source of dissolved organic carbon (DOC) for inland waters. Recent improvements for in situ optical monitoring revealed that the DOC concentration in streams draining peatlands is highly variable, showing seasonal variation and short and intense DOC concentration peak periods. This study aimed to determine the variables driving stream DOC concentration variations at seasonal and event scales. Two mountainous peatlands (one fen and one bog) were monitored in the French Pyrenees to capture their outlet DOC concentration variability at a high frequency rate (30 min). Abiotic variables including precipitation, stream temperature and water level, water table depth and peat water temperature were also monitored at high frequency and used as potential predictors to explain DOC concentration variability. Results show that at both sites, DOC concentration time series can be decomposed into a seasonal baseline interrupted by many short and intense peaks of higher concentrations. The DOC concentration baseline is driven, at the seasonal scale, by peat water temperature. At the event scale, DOC concentration increases are mostly driven by water table increases within the peat at both sites. Univariate linear models between DOC concentration and peat water temperature or water table increases show greater efficiency at the fen site. Water recession times were derived from water level time series using master recession curve coefficients. They vary greatly between bog and fen but also within one peatland site. They partly explain the differences between DOC dynamics in the studied peatlands, including porewater DOC concentrations and the links between stream DOC concentration and water table rise. This highlights that peatland complexes are composed of a mosaic of heterogeneous peat units distinctively producing or transferring DOC to streams.

International audience; The increase in species richness with island area (ISAR) is a well-established global pattern, commonly described by the power model, the parameters of which are hypothesized to vary with system isolation and to be indicative of ecological process regimes. We tested a structural equation model of ISAR parameter variation as a function of taxon, isolation, and archipelago configuration, using a globally distributed dataset of 151 ISARs encompassing a range of taxa and archipelago types. The resulting models revealed a negative relationship between ISAR intercept and slope as a function of archipelago species richness, in turn shaped by taxon differences and by the amount and disposition of archipelago area. These results suggest that local-scale (intra-archipelago) processes have a substantial role in determining ISAR form, obscuring the diversity patterns predicted by island theory as a function of archipelago isolation. These findings have implications for the use and interpretation of ISARs as a tool within biogeography, ecology, and conservation.