Abstract: Due to habitat fragmentation, resource disruption and pollution, urbanization is one of the most destructive forms of anthropization affecting ecosystems worldwide. Generally, human-mediated perturbations dramatically alter species diversity in urban sites compared to the surroundings, thus influencing the functioning of the entire ecosystem. We investigated the taxonomic and functional diversity patterns of the aquatic macroinvertebrate communities in tank bromeliads by comparing those found in a small Neotropical city with those from an adjacent rural site. Changes in the quality of detrital inputs in relation to lower tree diversity and the presence of synanthropic species are likely important driving forces behind the observed structural changes in the urban site. Leaf-litter processors (i.e., shredders, scrapers) were positively affected in the urban site, while filter-feeders that process smaller particles produced by the activity of the shredders were negatively affected. Because we cannot ascertain whether the decline in filter-feeders is related to food web-mediated effects or to competitive exclusion (Aedes aegypti mosquitoes were present in urban bromeliads only), further studies are necessary to account for the effects of intra-guild competition or inter-guild facilitation. © 2017, Springer Science+Business Media New York.

Abstract: Natural disturbances are the dominant form of forest regeneration and dynamics in unmanaged tropical forests. Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes. In this study, we model the size frequency distribution of natural canopy gaps with a discrete power law distribution. We use a Bayesian framework to introduce and test, using Monte Carlo Markov chain and Kuo-Mallick algorithms, the effect of local physical environment on gap size distribution. We apply our methodological framework to an original light detecting and ranging dataset in which natural forest gaps were delineated over 30 000 ha of unmanaged forest. We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent on floodplains and in wind-exposed areas. In the future, we plan to apply our methodological framework on a larger scale using satellite data. Additionally, although gap size distribution variation is clearly under environmental control, variation in gap size distribution in time should be tested against climate variability. © Author(s) 2017.

Abstract: Over the last decade, distance-based methods have been introduced and then improved in the field of spatial economics to gauge the geographic concentration of activities. There is a growing literature on this theme including new tools, discussions on their specific properties and various applications. However, there is currently no typology of distance-based methods. This paper fills that gap. The proposed classification helps understand all the properties of distance-based methods and proves that they are variations on the same framework. © 2016 Elsevier B.V.

Abstract: Lineages tend to retain ecological characteristics of their ancestors through time. However, for some traits, selection during evolutionary history may have also played a role in determining trait values. To address the relative importance of these processes requires large-scale quantification of traits and evolutionary relationships among species. The Amazonian tree flora comprises a high diversity of angiosperm lineages and species with widely differing life-history characteristics, providing an excellent system to investigate the combined influences of evolutionary heritage and selection in determining trait variation. We used trait data related to the major axes of life-history variation among tropical trees (e.g. growth and mortality rates) from 577 inventory plots in closed-canopy forest, mapped onto a phylogenetic hypothesis spanning more than 300 genera including all major angiosperm clades to test for evolutionary constraints on traits. We found significant phylogenetic signal (PS) for all traits, consistent with evolutionarily related genera having more similar characteristics than expected by chance. Although there is also evidence for repeated evolution of pioneer and shade tolerant lifehistory strategies within independent lineages, the existence of significant PS allows clearer predictions of the links between evolutionary diversity, ecosystem function and the response of tropical forests to global change. © 2016 The Authors.

Abstract: Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain “wall-to-wall” AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values. © 2016 Elsevier B.V.