Hierarchical Sampling Design Research Articles

Benthic communities influence coral seeding success at fine spatial scales

The deployment of engineered substrates seeded with newly settled corals is a technique being developed to increase the numbers of juvenile corals on reefs with the goal of improving reef resilience in response to climate warming. Using a hierarchical sampling design, we explored the spatial scales at which seeded coral (spat) survival and growth varied in situ and investigated the environmental drivers of seeded spat success in the southern inshore Great Barrier Reef. After 10 months, variation in spat survival and size was greatest at the smallest spatial scale (1–2 m) (27 and 11% of variation, respectively), indicating the scale at which the main drivers of post‐settlement survival and growth are occurring. Crustose coralline algae (CCA) cover on seeding units prior to deployment was a significant driver of short‐ and long‐term spat survival (22% of variation). Survival of Acropora millepora and A. muricata spat did not differ according to benthic community variation. Increasing cover of branching Acropora corals was correlated with decreased survival and the size of Montipora aequituberculata spat, although CCA cover on plugs remained the most influential factor determining survival. Interspecific variation in spat survival and size and higher survival and size in the side‐facing orientation of the seeding units suggest natural variation in response to the seeding method, warranting further experiments to refine species selection and deployment methods prior to upscaling. High within‐site variation in seeded spat survival and size highlights the need for future studies of ecological factors driving post‐settlement mortality at fine spatial scales.

Landscape heterogeneity can partially offset negative effects of habitat loss on mammalian biodiversity in agroecosystems

Abstract Intensive, large‐scale agriculture promotes the conversion of natural habitats and diversified crops into monocultures, decreasing both native vegetation cover and landscape heterogeneity, leading to landscape simplification. Yet, a key knowledge gap persists on the relative impacts of the loss of native vegetation and landscape heterogeneity on biodiversity. Addressing this gap is pressing to support policies that conciliate agricultural production and biodiversity conservation and to move forward some scientific controversies, as the ‘land sharing versus land sparing’ and ‘habitat loss versus fragmentation’ debates. Through a hierarchical sampling design that maximised variation, while minimising correlation, between landscape heterogeneity and native vegetation cover, we recorded the occurrence of medium and large‐bodied mammals in native vegetation and agricultural areas of 55 landscapes in a global conservation hotspot and a key commodity production area—the Brazilian Savanna, Cerrado. We compared simple, additive and interactive models to investigate the effects of landscape heterogeneity and native vegetation cover on richness and composition of native and invasive mammals. Native and invasive mammal communities were affected by both native vegetation cover and landscape heterogeneity, although the effects of the first was stronger than the later. Both aspects had positive effects on native species richness and negative effects on invasive species richness, indicating that the loss of native vegetation and the reduction in landscape heterogeneity lead to biotic homogenisation. Yet, while landscape heterogeneity benefited most native species, the direction of its effect varied among invasive species and depended on native vegetation cover. Synthesis and applications. Besides reducing habitat loss, avoiding landscape homogenisation is key for conciliating agricultural production and biodiversity conservation, pointing to the relevance of policies encouraging crop diversification. As increasing landscape heterogeneity can in part compensate the negative effects of losing native habitat on biodiversity in agroecosystems, policies can gain feasibility by adjusting the balance between native vegetation cover and landscape heterogeneity according to what best suits local restraints and demands.

Pollen Variability of Alnus glutinosa (L.) Gaerth. (Betulaceae) from Southern Range Edge Populations in Northern Morocco

Moroccan populations of Alnus glutinosa (L.) Gaerth. (Betulaceae) are found at the southern limit of the species’ range and are represented by tetraploid cytotypes with no available pollen data. The objective of this study was to assess the morphological and morphometric variability of the pollen, specifically focusing on pollen diameters and the number of apertures. To achieve this, we sampled 11 populations that are representative of the Moroccan distribution area of this species. We employed a hierarchical sampling design (11 populations, 10 trees per population, and from 30 to 300 pollen grains per tree, depending on the character measured) to examine different levels of variability: interpopulation, intrapopulation, and intraindividual. The results demonstrate that there is no discernible difference in the morphology or size of the pollen among the Moroccan tetraploid populations. However, we observed a high degree of intraspecific variability in pollen morphometric traits, but most of this variability is associated with the intraindividual level.

The multivariate-Tweedie: a self-weighting likelihood for age and length composition data arising from hierarchical sampling designs

Abstract Weighting data appropriately in stock assessment models is necessary to diagnose model mis-specification, estimate uncertainty, and when combining data sets. Age- and length-composition data are often fitted using a multinomial distribution and then reweighted iteratively, and the Dirichlet-multinomial (“DM”) likelihood provides a model-based alternative that estimates an additional parameter and thereby “self-weights” data. However, the DM likelihood requires specifying an input sample size (ninput), which is often unavailable and results are sensitive to ninput. We therefore introduce the multivariate-Tweedie (MVTW) as alternative with three benefits: (1) it can identify both overdispersion (downweighting) or underdispersion (upweighting) relative to the ninput; (2) proportional changes in ninput are exactly offset by parameters; and (3) it arises naturally when expanding data arising from a hierarchical sampling design. We use an age-structured simulation to show that the MVTW (1) can be more precise than the DM in estimating data weights, and (2) can appropriately upweight data when needed. We then use a real-world state-space assessment to show that the MVTW can easily be adapted to other software. We recommend that stock assessments explore the sensitivity to specifying DM, MVTW, and logistic-normal likelihoods, particularly when the DM estimates an effective sample size approaching ninput.

Hay meadows' overriding effect shapes ground beetle functional diversity in mountainous landscapes

AbstractMountain regions are hotspots of biodiversity, and are particularly sensitive to human activities and global changes. Characterizing biodiversity using trait‐based approaches may improve the understanding of the evolutionary and mechanistic basis of ecological patterns in species distribution. The investigation of trait–environment relationships, however, is challenging, especially when a hierarchical sampling design is used, as this may lead to misidentification of associations. Here, we investigate how functional traits in ground beetles (Coleoptera: Carabidae), a taxon often used as a bioindicator of climate and environmental changes, vary with environmental features in a mountainous landscape. The study was conducted in the Stelvio National Park (Central Italian Alps), collecting individuals with pitfall traps deployed within plots (small spatial scale), located along altitudinal transects (large spatial scale). To investigate the trait–environment association, we used double constrained correspondence analysis, which permits the selection of important traits and environmental variables while accounting for the hierarchical structure of the sampling design. The trait–environment association was largely one‐dimensional, with hay meadow acting as main environmental driver, negatively related to brachypterous wing‐form (indicator of poor dispersal ability) and, to a lesser extent, to specialized diet and (only for the large scale) body length. Secondarily, these traits were related negatively to soil pH and, for the larger spatial scale, positively to canopy cover and elevation. Double constrained correspondence analysis with specialized permutation schemes for statistical testing was effective and robust to analyze the data of the hierarchical sampling.

Sampling errors and variability in video transects for assessment of reef fish assemblage structure and diversity.

Video monitoring is a rapidly evolving tool in aquatic ecological research because of its non-destructive ability to assess fish assemblages. Nevertheless, methodological considerations of video monitoring techniques are often overlooked, especially in more complex sampling designs, causing inefficient data collection, processing, and interpretation. In this study, we discuss how video transect sampling designs could be assessed and how the inter-observer variability, design errors and sampling variability should be quantified and accounted for. The study took place in the coastal areas of the Galapagos archipelago and consisted of a hierarchical repeated-observations sampling design with multiple observers. Although observer bias was negligible for the assessment of fish assemblage structure, diversity and counts of individual species, sampling variability caused by simple counting/detection errors, observer effects and instantaneous fish displacement was often important. Especially for the counts of individual species, sampling variability most often exceeded the variability of the transects and sites. An extensive part of the variability in the fish assemblage structure was explained by the different transects (13%), suggesting that a sufficiently high number of transects is required to account for the within-location variability. Longer transect lengths allowed a better representation of the fish assemblages as sampling variability decreased by 33% if transect length was increased from 10 to 50 meters. However, to increase precision, including more repeats was typically more efficient than using longer transect lengths. The results confirm the suitability of the technique to study reef fish assemblages, but also highlight the importance of a sound methodological assessment since different biological responses and sampling designs are associated with different levels of sampling variability, precision and ecological relevance. Therefore, besides the direct usefulness of the results, the procedures to establish them may be just as valuable for researchers aiming to optimize their own sampling technique and design.

Positive and negative effects of land abandonment on butterfly communities revealed by a hierarchical sampling design across climatic regions.

Land abandonment may decrease biodiversity but also provides an opportunity for rewilding. It is therefore necessary to identify areas that may benefit from traditional land management practices and those that may benefit from a lack of human intervention. In this study, we conducted comparative field surveys of butterfly occurrence in abandoned and inhabited settlements in 18 regions of diverse climatic zones in Japan to test the hypotheses that species-specific responses to land abandonment correlate with climatic niches and habitat preferences. Hierarchical models that unified species occurrence and habitat preferences revealed that negative responses to land abandonment were associated with species that have cold climatic niches and use open habitats, suggesting that species negatively impacted by land abandonment will decline more due to future climate warming. Maps representing species gains and losses due to land abandonment, which were created from the model estimates, showed similar geographical patterns, but some areas exhibited high species losses relative to gains. Our hierarchical modelling approach was useful for scaling up local-scale effects of land abandonment to a macro-scale assessment, which is crucial to developing spatial conservation strategies in the era of depopulation.

Metal(loid) accumulation in the leaves of the grey mangrove (Avicennia marina): Assessment of robust sampling requirements and potential use as a bioindicator

This study assessed the appropriate sampling design required for quantifying variability in metal accumulation in the leaf tissues of A. marina, a dominant mangrove inhabiting Australian estuaries, by applying a hierarchical nested sampling design to sample mangroves at various levels of biological and spatial hierarchies (leaf, branch, tree, site). It was revealed that most variation in metal accumulation occurred among trees and branches, with insignificant variation between sites and among leaves. We also examined the accumulation of metal (loid)s in the leaf tissues collected from six locations across the Georges River estuary in southern Sydney, which differ in metal contamination history. Prospect Creek and Salt Pan Creek were the most contaminated locations, which exceeded sediment quality guideline values for Cu (66.71 ± 2.18 μg/g), Zn (317.14 ± 46.14 μg/g) and Pb (81.02 ± 2.79 μg/g). All metal(loid) concentrations in leaf tissues were much lower than their concentrations in sediment, but essential metals exhibited greater mobility. Out of 10 metal(loid)s, Mn, Co and Pb in leaves showed linear relationships (R2 = 0.28–0.47) with sediment, indicating that mangrove leaves may be used as a bioindicator of environmental loads for these metals.

Determining Plant Diversity within Interconnected Natural Habitat Remnants (Ecological Network) in an Agricultural Landscape: A Matter of Sampling Design?

In intensively used and human-modified landscapes, biodiversity is often confined to remnants of natural habitats. Thus, identifying ecological networks (ENs) necessary to connect these patches and maintain high levels of biodiversity, not only for conservation but also for the effective management of the landscape, is required. However, ENs are often defined without a clear a-priori evaluation of their biodiversity and are seldom even monitored after their establishment. The objective of this study was to determine the adequate number of replicates to effectively characterize biodiversity content of natural habitats within the nodes of an EN in north-eastern Italy, based on vascular plant diversity. Plant communities within habitat types of the EN’s nodes were sampled through a hierarchical sampling design, evaluating both species richness and compositional dissimilarity. We developed an integrated method, consisting of multivariate measures of precision (MultSE), rarefaction curves and diversity partitioning approaches, which was applied to estimate the minimum number of replicates needed to characterize plant communities within the EN, evaluating also how the proposed optimization in sampling size affected the estimations of the characteristics of habitat types and nodes of the EN. We observed that reducing the total sampled replicates by 85.5% resulted to sufficiently characterize plant diversity of the whole EN, and by 72.5% to exhaustively distinguish plant communities among habitat types. This integrated method helped to fill the gap regarding the data collection to monitor biodiversity content within existing ENs, considering temporal and economic resources. We therefore suggest the use of this quantitative approach, based on probabilistic sampling, to conduct pilot studies in the context of ENs design and monitoring, and in general for habitat monitoring.

Implications of Genetic Structure for Aquaculture and Cultivar Translocation of the Kelp Ecklonia radiata in Northern New Zealand

The fast expansion of the global seaweed aquaculture industry has created an interest in translocating seedlings cultivated from wild type brood stock. However, such translocations must be applied with caution as introduced cultivars can reduce genetic structure and diversity of wild populations. An understanding of the genetic structure and connectivity of target species is required to guide decision making around aquaculture translocation activities. In this study we used 14 microsatellite loci in a three-level hierarchical sampling design to analyze the genetic structure and connectivity of the native kelp Ecklonia radiata across 12 sites among four geographic regions (Northland, Bay of Plenty, Gisborne, and Wellington) in the North Island of New Zealand. Our aim was to provide guidance for translocation of cultivars to prevent the introduction of locally absent genotypes of E. radiata. Strong genetic structure and low geneflow were observed at all hierarchical levels, indicating the presence of multiple genetically distinct sub-populations. On a regional scale, high genetic differentiation was found between the Wellington region and the other three regions (FST = 0.407–0.545), and within regions most sites were significantly different (measured by pairwise FST) with high relatedness found between individuals within sites (mean 28.2% ± 0.7 SE). Bayesian modeling and redundancy analysis showed a high degree of genetic clustering and indicate that ocean currents and other factors that have resulted in biogeographical breaks along the coast are likely to be the main factors shaping genetic structure and connectivity of E. radiata on the North Island, rather than isolation by distance. Based on these findings, we recommend that that cultivars of E. radiata should not be translocated outside their area of origin to avoid introducing locally absent genotypes to local sub-populations.

Components of plant diversity as ecological indicators reflecting the effects of conservation management and degradation in different climatic conditions

AbstractAdditive partitioning of species diversity is a valuable approach for quantifying the spatial patterns of biodiversity sampled in hierarchically scaled studies. This approach may provide key insights into vegetation community restoration following terrestrial ecosystems degradation in different climatic conditions. The scale‐dependence of plant diversity in relation to different plant functional groups (e.g., herbaceous and woody) is still little understood. This research aims to investigate the influence of management options (protected vs. non‐protected) and climatic conditions (semiarid vs. Mediterranean) on different components of diversity in both herbaceous and woody species derived from local and regional scales (i.e., plot and site, respectively). In the studied areas, a total of 64 plots (1000 m2) at local scale and 128 micro‐plots (1 m2) among 16 sites at regional scale were selected for sampling the woody and herbaceous species data, respectively, by using a hierarchical sampling design. Diversity components of local (α1, β1) and regional (α2, β2) scales were extracted according to additive partitioning method. Differences in diversity component (α1, α21, β1 and β2) and floristic composition between management options and climatic conditions were evaluated using GLMM and DCA. The results indicate that all components of total species (both herbaceous and woody) diversity (α1, α2, β1 and β2) were significantly influenced by management options (p < 0.05) with greater values in the protected areas than the non‐protected areas. However, the climatic conditions only had significant effects on β2, with greater values in the Mediterranean compared to semi‐arid areas. Moreover, the separate analysis of herbaceous and woody species indicated that management options have a greater significant effect on different diversity components compared to the climatic condition. Detrended correspondence analysis showed that floristic variations along the axes are strongly affected by management in both climatic conditions. This indicates that protection measures mostly increased plant species diversity at the local and regional scales, which is independent of the climatic condition.

PoolTestR: An R package for estimating prevalence and regression modelling for molecular xenomonitoring and other applications with pooled samples

Pooled testing (also known as group testing), where diagnostic tests are performed on pooled samples, has broad applications in the surveillance of diseases in animals and humans. An increasingly common use case is molecular xenomonitoring (MX), where surveillance of vector-borne diseases is conducted by capturing and testing large numbers of vectors (e.g. mosquitoes). The R package PoolTestR was developed to meet the needs of increasingly large and complex molecular xenomonitoring surveys but can be applied to analyse any data involving pooled testing. PoolTestR includes simple and flexible tools to estimate prevalence and fit fixed- and mixed-effect generalised linear models for pooled data in frequentist and Bayesian frameworks. Mixed-effect models allow users to account for the hierarchical sampling designs that are often employed in surveys, including MX. We demonstrate the utility of PoolTestR by applying it to a large synthetic dataset that emulates a MX survey with a hierarchical sampling design.

Environmental DNA reveals the fine-grained and hierarchical spatial structure of kelp forest fish communities

Biodiversity is changing at an accelerating rate at both local and regional scales. Beta diversity, which quantifies species turnover between these two scales, is emerging as a key driver of ecosystem function that can inform spatial conservation. Yet measuring biodiversity remains a major challenge, especially in aquatic ecosystems. Decoding environmental DNA (eDNA) left behind by organisms offers the possibility of detecting species sans direct observation, a Rosetta Stone for biodiversity. While eDNA has proven useful to illuminate diversity in aquatic ecosystems, its utility for measuring beta diversity over spatial scales small enough to be relevant to conservation purposes is poorly known. Here we tested how eDNA performs relative to underwater visual census (UVC) to evaluate beta diversity of marine communities. We paired UVC with 12S eDNA metabarcoding and used a spatially structured hierarchical sampling design to assess key spatial metrics of fish communities on temperate rocky reefs in southern California. eDNA provided a more-detailed picture of the main sources of spatial variation in both taxonomic richness and community turnover, which primarily arose due to strong species filtering within and among rocky reefs. As expected, eDNA detected more taxa at the regional scale (69 vs. 38) which accumulated quickly with space and plateaued at only ~ 11 samples. Conversely, the discovery rate of new taxa was slower with no sign of saturation for UVC. Based on historical records in the region (2000–2018) we found that 6.9 times more UVC samples would be required to detect 50 taxa compared to eDNA. Our results show that eDNA metabarcoding can outperform diver counts to capture the spatial patterns in biodiversity at fine scales with less field effort and more power than traditional methods, supporting the notion that eDNA is a critical scientific tool for detecting biodiversity changes in aquatic ecosystems.

Micro on a macroscale: relating microbial-scale soil processes to global ecosystem function.

Soil microorganisms play a key role in driving major biogeochemical cycles and in global responses to climate change. However, understanding and predicting the behavior and function of these microorganisms remains a grand challenge for soil ecology due in part to the microscale complexity of soils. It is becoming increasingly clear that understanding the microbial perspective is vital to accurately predicting global processes. Here, we discuss the microbial perspective including the microbial habitat as it relates to measurement and modeling of ecosystem processes. We argue that clearly defining and quantifying the size, distribution and sphere of influence of microhabitats is crucial to managing microbial activity at the ecosystem scale. This can be achieved using controlled and hierarchical sampling designs. Model microbial systems can provide key data needed to integrate microhabitats into ecosystem models, while adapting soil sampling schemes and statistical methods can allow us to collect microbially-focused data. Quantifying soil processes, like biogeochemical cycles, from a microbial perspective will allow us to more accurately predict soil functions and address long-standing unknowns in soil ecology.

Variation in fouling assemblages associated with prop roots of Rhizophora mangle L. in the Caribbean: The role of neutral and niche processes

AbstractThe discussion about the drivers that govern the spatial patterns of diversity has been focussed on two seemingly independent models: (1) neutral dynamics, mediated by larval supply and dispersal limitations, and (2) niche processes, mainly environmental control. However, metacommunity theory assumes that drivers evoked by both models (niche and neutral) might act simultaneously, but at different spatial scales, in shaping assemblage composition and structure. In this study, we use communities inhabiting prop roots of the Caribbean mangrove Rhizophora mangle L. as a model system to test hypotheses about the role of environmental control and neutral dynamics as potential synergic drivers at multiple spatial scales. For this, environmental, biological and spatial data were obtained from the southern Caribbean under a hierarchical sampling design that includes (1) mangrove systems distanced apart by hundreds of km, (2) sectors within each mangrove systems separated by a few km, (3) sites within each sector separated by tens of metres and (4) neighbouring roots in a site. Non‐parametric multivariate statistics were used to describe, link and test the environmental, biological and spatial patterns. In general, we found that environmental filtering, principally salinity and supply of energy/nutrients, could be the primary filters that sustain differences in composition and structure of the assemblages at the spatial scale of mangrove systems. At local spatial scales, shallow depths (<1 m) seem to be a critical environmental filter for these assemblages. Beyond this environmental filter, it seems that the distribution and abundance of species might be more affected by neutral processes. However, we detect a wide diversity of spatiotemporal trends of species distribution and abundance. These results support the conclusion that niche and neutral processes act simultaneously, affecting species and individuals, rather than as general drivers affecting the whole metacommunity.

Variations in coralligenous assemblages from local to biogeographic spatial scale

The present study aims at contributing to the knowledge of the spatial variability of coralligenous reefs through the evaluation of patterns ranging from local to biogeographic scale around the island of Sardinia. The coralligenous reef assemblages of six areas were studied through a hierarchical sampling design: three sites per area were selected, in each site three plots were sampled and in each plot ten photographic samples were collected. The structure of coralligenous reefs across closed biogeographic regions is described, highlighting that nearly pristine assemblages, although characterized by similar high diversity, can be either dominated by animals, such as gorgonians and bryozoans, or macroalgae. The observed variations seem largely related to biogeographic patterns rather than spatial distance, supporting the need to identify specific reference conditions to assess the ecological quality of this habitat depending on the biogeographic area to be monitored.

Molecular approaches reveal weak sibship aggregation and a high dispersal propensity in a non-native fish parasite.

Inferring parameters related to the aggregation pattern of parasites and to their dispersal propensity are important for predicting their ecological consequences and evolutionary potential. Nonetheless, it is notoriously difficult to infer these parameters from wildlife parasites given the difficulty in tracking these organisms. Molecular‐based inferences constitute a promising approach that has yet rarely been applied in the wild. Here, we combined several population genetic analyses including sibship reconstruction to document the genetic structure, patterns of sibship aggregation, and the dispersal dynamics of a non‐native parasite of fish, the freshwater copepod ectoparasite Tracheliastes polycolpus. We collected parasites according to a hierarchical sampling design, with the sampling of all parasites from all host individuals captured in eight sites spread along an upstream–downstream river gradient. Individual multilocus genotypes were obtained from 14 microsatellite markers, and used to assign parasites to full‐sib families and to investigate the genetic structure of T. polycolpus among both hosts and sampling sites. The distribution of full‐sibs obtained among the sampling sites was used to estimate individual dispersal distances within families. Our results showed that T. polycolpus sibs tend to be aggregated within sites but not within host individuals. We detected important upstream‐to‐downstream dispersal events of T. polycolpus between sites (modal distance: 25.4 km; 95% CI [22.9, 27.7]), becoming scarcer as the geographic distance from their family core location increases. Such a dispersal pattern likely contributes to the strong isolation‐by‐distance observed at the river scale. We also detected some downstream‐to‐upstream dispersal events (modal distance: 2.6 km; 95% CI [2.2–23.3]) that likely result from movements of infected hosts. Within each site, the dispersal of free‐living infective larvae among hosts likely contributes to increasing genetic diversity on hosts, possibly fostering the evolutionary potential of T. polycolpus.

No overall effect of urbanization on nest-dwelling arthropods of great tits (Parus major).

Urbanization has been shown to strongly affect community composition of various taxa with potentially strong shifts in ecological interactions, including those between hosts and parasites. We investigated the effect of urbanization on the composition of arthropods in nests of great tits in Flanders, Belgium. These nests contain taxonomically and functionally diverse arthropod communities including parasites, predators, detritivores and accidental commensals. Using a standardized hierarchical sampling design with subplots (200 m × 200 m) nested in plots (3 km × 3 km) of varying urbanization levels, we collected arthropods from nests of resident great tits after the young had fledged. Arthropods were extracted, identified to Primary Taxonomical Groups (PTG) and counted. Using generalized linear mixed models (GLMMs) we found diverging effects of urbanization on PTG occurrences and abundances at various levels, but we did not find an overall signal in arthropod diversity or richness. Also, visual inspection of non-metric multidimensional scaling (NMDS) plots did not reveal any community differences between urbanization levels at plot or subplot scales. Land use and environmental variables at different distances around nestboxes did not contribute much to the variation between communities. Our results indicate that arthropod nestbox communities are generally not adversely affected by urbanization, and even city gardens and parks harbor comparable communities to forests and suburban areas. We thus found no evidence for a parasite release effect due to urbanization, nor an increased risk of parasitism in human-dominated environments.

Taxonomic and functional homogenisation of macroinvertebrate communities in recently intermittent Alpine watercourses

Abstract Mountain streams in southwestern European Alps are currently shifting from perennial to intermittent flow due to the combined effects of climate change and local anthropogenic pressures. Given that flow intermittency is a recently documented phenomenon in the Alps, only scattered studies have investigated functional and taxonomical diversity of benthic invertebrate communities in recently intermittent Alpine streams. We used a hierarchical sampling design to investigate patterns in taxonomic and functional diversity of benthic invertebrate communities in 13 recently intermittent Alpine streams in north‐west Italy. in April 2017, we sampled benthic communities in two reaches of each stream with different hydrological conditions: a control reach, with permanent flow; and an intermittent reach, which recently experienced non‐flow periods in summer. We tested for the response of taxonomic richness at multiple spatial scales by partitioning total diversity into the average richness of local communities and the richness due to variation among local communities both within and among reaches. By partitioning total diversity (γ) into its local (α) and turnover (β) components we showed a decrease in local and regional species richness both within and among reaches, whereas variation among communities was significantly lower in intermittent reaches at the reach scale only. The analysis of multidimensional trait space of macroinvertebrate communities in reaches with different hydrological conditions revealed a significant reduction of functional diversity, dispersion, and evenness in intermittent reaches. There was trait overdispersion in intermittent reaches, as these hosted both typical Alpine taxa and organisms adapted to flow intermittency. In particular, we observed the replacement of taxa with aquatic respiration and those preferring medium‐ to fast‐flowing oligotrophic waters by taxa adapted to lentic habitats, air breathing and with larval dormancy phases. These results indicate that recent flow intermittency has caused drastic changes in benthic invertebrate communities in Alpine streams. Our work highlights the importance of integrating taxonomic and functional diversity to thoroughly assess the impacts of flow intermittency.

Msocc: Fit and analyse computationally efficient multi‐scale occupancy models in r

Abstract Environmental DNA (eDNA) sampling is a promising tool for the detection of rare and cryptic taxa, such as aquatic pathogens, parasites and invasive species. Environmental DNA sampling workflows commonly rely on multi‐stage hierarchical sampling designs that induce complicated dependencies within the data. This complex dependence structure can be intuitively modelled with Bayesian multi‐scale occupancy models. However, current software for such models are computationally demanding, impeding their use. We present an r package, msocc, that implements a data augmentation strategy to fit fully Bayesian, computationally efficient multi‐scale occupancy models. The msocc package allows users to fit multi‐scale occupancy models, to estimate and visualize posterior summaries of site, sample and replicate‐level occupancy, and to compare different models using Bayesian information criterion. Additionally, we provide a supplemental web application that allows users to investigate study design for multi‐scale occupancy models and acts as a graphical user interface to the msocc package. The utility of the msocc package is illustrated on a published dataset and the functions in msocc are compared to the primary Bayesian toolkit for multi‐scale occupancy modelling, eDNAoccupancy, using various computational benchmarks. These benchmarks indicate that msocc is capable of fitting models 50 times faster than eDNAoccupancy. We hope that access to software that efficiently fits, analyses and conducts study design investigations for multi‐scale occupancy models facilitates their implementation by the research and wildlife management communities.