Abstract: Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015. The collation of biodiversity datasets with broad taxonomic and biogeographic extents is necessary to understand historical declines and to project – and hopefully avert – future declines. We describe a newly collated database of more than 1.6 million biodiversity measurements from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world.

Abstract: The survey of plant and animal populations is central to undertaking field ecology. However, detection is imperfect, so the absence of a species cannot be determined with certainty. Methods developed to account for imperfect detectability during surveys do not yet account for stochastic variation in detectability over time or space. When each survey entails a fixed cost that is not spent searching (e.g., time required to travel to the site), stochastic detection rates result in a trade-off between the number of surveys and the length of each survey when surveying a single site. We present a model that addresses this trade-off and use it to determine the number of surveys that: 1) maximizes the expected probability of detection over the entire survey period; and 2) is most likely to achieve a minimally-acceptable probability of detection. We illustrate the applicability of our approach using three practical examples (minimum survey effort protocols, number of frog surveys per season, and number of quadrats per site to detect a plant species) and test our model's predictions using data from experimental plant surveys. We find that when maximizing the expected probability of detection, the optimal survey design is most sensitive to the coefficient of variation in the rate of detection and the ratio of the search budget to the travel cost. When maximizing the likelihood of achieving a particular probability of detection, the optimal survey design is most sensitive to the required probability of detection, the expected number of detections if the budget were spent only on searching, and the expected number of detections that are missed due to travel costs. We find that accounting for stochasticity in detection rates is likely to be particularly important for designing surveys when detection rates are low. Our model provides a framework to do this. © 2014 Moore et al.

Abstract: Tank bromeliads are good models for understanding how climate change may affect biotic associations. We studied the relationships between spiders, the epiphytic tank bromeliad, Aechmea bracteata, and its associated ants in an inundated forest in Quintana Roo, Mexico, during a drought period while, exceptionally, this forest was dry and then during the flooding that followed. We compared spider abundance and diversity between “Aechmea-areas” and “control areas” of the same surface area. We recorded six spider families: the Dipluridae, Ctenidae, Salticidae, Araneidae, Tetragnathidae and Linyphiidae among which the funnel-web tarantula, Ischnothele caudata, the only Dipluridae noted, was the most abundant. During the drought period, the spiders were more numerous in the Aechmea areas than in the control areas, but they were not obligatorily associated with the Aechmea.
During the subsequent flooding, the spiders were concentrated in the A. bracteata patches, particularly those sheltering an ant colony. Also, a kind of specificity existed between certain spider taxa and ant species, but varied between the drought period and subsequent flooding. We conclude that climatic events modulate the relationship between A. bracteata patches and their associated fauna. Tank bromeliads, previously considered only for their ecological importance in supplying food and water during drought, may also be considered refuges for spiders during flooding. More generally, tank bromeliads have an important role in preserving non-specialized fauna in inundated forests.

Abstract: Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mg ha-1) at spatial scales ranging from 5 to 250 m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial “dilution” bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Abstract: Ants (Hymenoptera: Formicidae) represent a taxonomically diverse group of arthropods comprising nearly 13,000 extant species. Sixteen ant subfamilies have individuals that possess a stinger and use their venom for purposes such as a defence against predators, competitors and microbial pathogens, for predation, as well as for social communication. They exhibit a range of activities including antimicrobial, haemolytic, cytolytic, paralytic, insecticidal and pain-producing pharmacologies. While ant venoms are known to be rich in alkaloids and hydrocarbons, ant venoms rich in peptides are becoming more common, yet remain understudied. Recent advances in mass spectrometry techniques have begun to reveal the true complexity of ant venom peptide composition. In the few venoms explored thus far, most peptide toxins appear to occur as small polycationic linear toxins, with antibacterial properties and insecticidal activity. Unlike other venomous animals, a number of ant venoms also contain a range of homodimeric and heterodimeric peptides with one or two interchain disulfide bonds possessing pore-forming, allergenic and paralytic actions. However, ant venoms seem to have only a small number of monomeric disulfide-linked peptides. The present review details the structure and pharmacology of known ant venom peptide toxins and their potential as a source of novel bioinsecticides and therapeutic agents.