Biodiversity is declining from unprecedented land conversions that replace diverse, low-intensity agriculture with vast expanses under homogeneous, intensive production. Despite documented losses of species richness, consequences for β-diversity, changes in community composition between sites, are largely unknown, especially in the tropics. Using a 10-year data set on Costa Rican birds, we find that low-intensity agriculture sustained β-diversity across large scales on a par with forest. In high-intensity agriculture, low local (α) diversity inflated β-diversity as a statistical artefact. Therefore, at small spatial scales, intensive agriculture appeared to retain β-diversity. Unlike in forest or low-intensity systems, however, high-intensity agriculture also homogenised vegetation structure over large distances, thereby decoupling the fundamental ecological pattern of bird communities changing with geographical distance. This ~40% decline in species turnover indicates a significant decline in β-diversity at large spatial scales. These findings point the way towards multi-functional agricultural systems that maintain agricultural productivity while simultaneously conserving biodiversity.

Amplicon based metabarcoding promises rapid and cost-efficient analyses of species composition. However, it is disputed whether abundance estimates can be derived from metabarcoding due to taxon specific PCR amplification biases. PCR-free approaches have been suggested to mitigate this problem, but come with considerable increases in workload and cost. Here, we analyze multilocus datasets of diverse arthropod communities, to evaluate whether amplification bias can be countered by (1) targeting loci with highly degenerate primers or conserved priming sites, (2) increasing PCR template concentration, (3) reducing PCR cycle number or (4) avoiding locus specific amplification by directly sequencing genomic DNA. Amplification bias is reduced considerably by degenerate primers or targeting amplicons with conserved priming sites. Surprisingly, a reduction of PCR cycles did not have a strong effect on amplification bias. The association of taxon abundance and read count was actually less predictable with fewer cycles. Even a complete exclusion of locus specific amplification did not exclude bias. Copy number variation of the target loci may be another explanation for read abundance differences between taxa, which would affect amplicon based and PCR free methods alike. As read abundance biases are taxon specific and predictable, the application of correction factors allows abundance estimates.

Islands harbour evolutionary and ecologically unique biota, which are currently disproportionately threatened by a multitude of anthropogenic factors, including habitat loss, 2568 Biodivers Conserv (2018) 27:2567-2586 1 3 invasive species and climate change. Native forests on oceanic islands are important refugia for endemic species, many of which are rare and highly threatened. Long-term monitoring schemes for those biota and ecosystems are urgently needed: (i) to provide quantitative baselines for detecting changes within island ecosystems, (ii) to evaluate the effectiveness of conservation and management actions, and (iii) to identify general ecological patterns and processes using multiple island systems as repeated 'natural experiments'. In this contribution, we call for a Global Island Monitoring Scheme (GIMS) for monitoring the remaining native island forests, using bryophytes, vascular plants, selected groups of arthropods and vertebrates as model taxa. As a basis for the GIMS, we also present new, optimized monitoring protocols for bryophytes and arthropods that were developed based on former standardized inventory protocols. Effective inventorying and monitoring of native island forests will require: (i) permanent plots covering diverse ecological gradients (e.g. elevation, age of terrain, anthropogenic disturbance); (ii) a multiple-taxa approach that is based on standardized and replicable protocols; (iii) a common set of indicator taxa and community properties that are indicative of native island forests' welfare, building on, and harmonized with existing sampling and monitoring efforts; (iv) capacity building and training of local researchers, collaboration and continuous dialogue with local stakeholders; and (v) long-term commitment by funding agencies to maintain a global network of native island forest monitoring plots.

Aim Understanding how ecological and evolutionary processes together determine patterns of biodiversity remains a central aim in biology. Guided by ecological theory, we use data from multiple arthropod lineages across the Hawaiian archipelago to explore the interplay between ecological (population dynamics, dispersal, trophic interactions) and evolutionary (genetic structuring, adaptation, speciation, extinction) processes. Our goal is to show how communities develop from the dynamic feedbacks that operate at different temporal and spatial scales. Location The Hawaiian islands (19-22°N, 155-160°W).Methods We synthesize genetic data from selected arthropods across the Hawaiian archipelago to determine the relative role of dispersal and in situ differentiation across the island chronosequence. From four sites on three high islands with geological ages ranging from < 1 Ma to 5 Ma, we also generate ecological metrics on plant-herbivore bipartite networks drawn from the literature. We compare the structure of these networks with predictions derived from the principle of maximum information entropy.Results From the perspective of the island chronosequence we show that species at lower trophic levels develop population genetic structure at smaller temporal and spatial scales than species at higher trophic levels. Network nestedness decreases while modularity increases with habitat age. Single-island endemics exhibit more specialization than broadly distributed species, but both show the least specialization in communities on middle-aged substrates. Plant-herbivore networks also show the least deviation from theoretical predictions in middle-aged communities. Main conclusionsThe application of ecological theory to island chronosequences can illuminate feedbacks between ecological and evolutionary processes in community assembly. We show how patterns of population genetic structure, decreasing network nestedness, increasing network modularity and increased specialization shift from early assembly driven by immigration, to in situ diversification after > 1 Myr. Herbivore-plant communities only transiently achieve statistical steady state during assembly, presumably due to incomplete assembly from dispersal in the early stages, and the increasing influence of island ontogeny on older islands.

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Reconciling the relative importance of these processes is hindered by current theory, which tends to focus on a single spatial, temporal or taxonomic scale. We introduce a mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. We demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. We combine our massive eco-evolutionary synthesis simulations (MESS) with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of spatial scales..