Abstract: Around the world, the human-induced collapses of populations and species have triggered a sixth mass extinction crisis, with rare species often being the first to disappear. Although the role of species diversity in the maintenance of ecosystem processes has been widely investigated, the role of rare species remains controversial. A critical issue is whether common species insure against the loss of functions supported by rare species. This issue is even more critical in species-rich ecosystems where high functional redundancy among species is likely and where it is thus often assumed that ecosystem functioning is buffered against species loss. Here, using extensive datasets of species occurrences and functional traits from three highly diverse ecosystems (846 coral reef fishes, 2,979 alpine plants, and 662 tropical trees), we demonstrate that the most distinct combinations of traits are supported predominantly by rare species both in terms of local abundance and regional occupancy. Moreover, species that have low functional redundancy and are likely to support the most vulnerable functions, with no other species carrying similar combinations of traits, are rarer than expected by chance in all three ecosystems. For instance, 63% and 98% of fish species that are likely to support highly vulnerable functions in coral reef ecosystems are locally and regionally rare, respectively. For alpine plants, 32% and 89% of such species are locally and regionally rare, respectively. Remarkably, 47% of fish species and 55% of tropical tree species that are likely to support highly vulnerable functions have only one individual per sample on average. Our results emphasize the importance of rare species conservation, even in highly diverse ecosystems, which are thought to exhibit high functional redundancy. Rare species offer more than aesthetic, cultural, or taxonomic diversity value; they disproportionately increase the potential breadth of functions provided by ecosystems across spatial scales. As such, they are likely to insure against future uncertainty arising from climate change and the ever-increasing anthropogenic pressures on ecosystems. Our results call for a more detailed understanding of the role of rarity and functional vulnerability in ecosystem functioning. © 2013 Mouillot et al.

Abstract: Dispersal is usually associated with the spread of invasive species, but it also has two opposing effects, one decreasing and the other increasing the probability of establishment. Indeed, dispersal both slows population growth at the site of introduction and increases the likelihood of surrounding habitat being colonized. The connectivity of the introduction site is likely to affect dispersal, and, thus, establishment, according to the dispersal behaviour of individuals. Using individual-based models and microcosm experiments on minute wasps, we demonstrated the existence of a hump-shaped relationship between connectivity and establishment in situations in which individual dispersal resembled a diffusion process. These results suggest that there is an optimal level of connectivity for the establishment of introduced populations locally at the site of introduction, and regionally over the whole landscape.

Abstract: Key message: In French Guiana, the leaf and cambium phenologies should not be considered only as exogenous-driven processes, as the dry season, but also as endogenous-driven, as tree development stage. Abstract: Studies of the periodicity of wood formation provide essential data on tree age and on factors that control tree growth. The aim of this work was to investigate cambial phenology and its relation with leaf phenology and climatic seasonality in two briefly deciduous tropical rainforest species belonging to the genus Parkia. Wood microcores were collected every 15 days from April 2009 to February 2012 from five trees of each species. The microcores were stained with cresyl violet acetate to facilitate counting the number of cells in the cambial zone, in the radial enlargement zone and wall-thickening zone. At the same time, we observed leaf shedding pattern in the crown of the same trees. In both species, cambial activity was significantly reduced during the leafless period. In P. nitida, these two concomitant events were observed during the dry season whereas in P. velutina they can occur anytime in the year with no apparent link with seasonality. In conclusion, the period of reduced cambial activity in some tropical rainforest trees may be independent of rainfall seasonality and not necessarily follow an annual cycle. It appears that leaf phenology is a good proxy to estimate cambial activity. © 2015, Springer-Verlag Berlin Heidelberg.

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: Reliable above-ground biomass (AGB) estimates are required for studies of carbon fluxes and stocks. However, there is a huge lack of knowledge concerning the precision of AGB estimates and the sources of this uncertainty. At the tree level, the tree height is predicted using the tree diameter at breast height (DBH) and a height sub-model. The wood-specific gravity (WSG) is predicted with taxonomic information and a WSG sub-model. The tree mass is predicted using the predicted height, the predicted WSG and the biomass sub-model. Our models were inferred with Bayesian methods and the uncertainty propagated with a Monte Carlo scheme. The uncertainties in the predictions of tree height, tree WSG and tree mass were neglected sequentially to quantify their contributions to the uncertainty in AGB. The study was conducted in French Guiana where long-term research on forest ecosystems provided an outstanding data collection on tree height, tree dynamics, tree mass and species WSG. We found that the uncertainty in the AGB estimates was found to derive primarily from the biomass sub-model. The models used to predict the tree heights and WSG contributed negligible uncertainty to the final estimate. Considering our results, a poor knowledge of WSG and the height-diameter relationship does not increase the uncertainty in AGB estimates. However, it could lead to bias. Therefore, models and databases should be used with care. This study provides a methodological framework that can be broadly used by foresters and plant ecologist. It provides the accurate confidence intervals associated with forest AGB estimates made from inventory data. When estimating region-scale AGB values (through spatial interpolation, spatial modelling or satellite signal treatment), the uncertainty of the forest AGB value in the reference forest plots has to be taken in account. We believe that in the light of the Reducing Emissions from Deforestation and Degradation debate, our method is a crucial step in monitoring carbon stocks and their spatio-temporal evolution. © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.