A comparison of global mangrove maps: Assessing spatial and bioclimatic discrepancies at poleward range limits.

Mangrove distribution maps are used for a variety of applications, ranging from estimates of mangrove extent, deforestation rates, quantify carbon stocks, to modelling response to climate change. There are multiple mangrove distribution datasets, which were derived from different remote sensing data and classification methods, and so there are some discrepancies among these datasets, especially with respect to the locations of their range limits. We investigate the latitudinal discrepancies in poleward mangrove range limits represented by these datasets and how these differences translate climatologically considering factors known to control mangrove distributions. We compare four widely used global mangrove distribution maps - the World Atlas of Mangroves, the World Atlas of Mangroves 2, the Global Distribution of Mangroves, the Global Mangrove Watch. We examine differences in climate among 21 range limit positions by analysing a set of bioclimatic variables that have been commonly related to the distribution of mangroves. Global mangrove maps show important discrepancies in the position of poleward range limits. Latitudinal differences between mangrove range limits in the datasets exceed 5°, 7° and 10° in western North America, western Australia and northern West Africa, respectively. In some range limit areas, such as Japan, discrepancies in the position of mangrove range limits in different datasets correspond to differences exceeding 600 mm in annual precipitation and > 10 °C in the minimum temperature of the coldest month. We conclude that dissimilarities in mapping mangrove range limits in different parts of the world can jeopardise inferences of climatic thresholds. We expect that global mapping efforts should prioritise the position of range limits with greater accuracy, ideally combining data from field-based surveys and very high-resolution remote sensing data. An accurate representation of range limits will contribute to better predicting mangrove range dynamics and shifts in response to climate change.

Drivers of metacommunity structure diverge for common and rare Amazonian tree species.

We analysed the flora of 46 forest inventory plots (25 m x 100 m) in old growth forests from the Amazonian region to identify the role of environmental (topographic) and spatial variables (obtained using PCNM, Principal Coordinates of Neighbourhood Matrix analysis) for common and rare species. For the analyses, we used multiple partial regression to partition the specific effects of the topographic and spatial variables on the univariate data (standardised richness, total abundance and total biomass) and partial RDA (Redundancy Analysis) to partition these effects on composition (multivariate data) based on incidence, abundance and biomass. The different attributes (richness, abundance, biomass and composition based on incidence, abundance and biomass) used to study this metacommunity responded differently to environmental and spatial processes. Considering standardised richness, total abundance (univariate) and composition based on biomass, the results for common species differed from those obtained for all species. On the other hand, for total biomass (univariate) and for compositions based on incidence and abundance, there was a correspondence between the data obtained for the total community and for common species. Our data also show that in general, environmental and/or spatial components are important to explain the variability in tree communities for total and common species. However, with the exception of the total abundance, the environmental and spatial variables measured were insufficient to explain the attributes of the communities of rare species. These results indicate that predicting the attributes of rare tree species communities based on environmental and spatial variables is a substantial challenge. As the spatial component was relevant for several community attributes, our results demonstrate the importance of using a metacommunities approach when attempting to understand the main ecological processes underlying the diversity of tropical forest communities.