Abstract: The high spatial variability of soil respiration in tropical rainforests is well evaluated, but influences of biotic factors are not clearly understood. This study underlines the influence of tree species characteristics on soil respiration across a 16-monospecific plot design in a tropical plantation of French Guiana. A large variability of soil CO2 fluxes was observed among plots (i.e. 2.8 to 6.8 μmol m(-2) s(-1)) with the ranking being constant across seasons. There were no significant relationships between soil respiration and soil moisture or soil temperature, neither spatially, nor seasonally. The variability of soil respiration was mainly explained by quantitative factors such as leaf litterfall and basal area. Surprisingly, no significant relationship was observed between soil respiration and root biomass. However, the influence of substrate quality was revealed by a strong relationship between soil respiration and litterfall P (and litterfall N, to a lesser extent).

Abstract: Plant phenology characterises the seasonal cyclicity of biological events such as budburst, flowering, fructification, leaf senescence and leaf fall. These biological events are genetically pre-determined but also strongly modulated by climatic conditions, particularly temperature, daylength and water availability. Therefore, the timing of these events is considered as a good indicator of climate change impacts and as a key parameter for understanding and modelling vegetation-climate interactions. In situ observations, empirical or bioclimatic models and remotely sensed time-series data constitute the three possible ways for monitoring the timing of plant phenological events. Remote sensing has the advantage of being the only way of surface sampling at high temporal frequency and, in the case of satellite-based remote sensing, over large regions. Nevertheless, exogenous factors, particularly atmospheric conditions, lead to some uncertainties on the seasonal course of surface reflectance and cause bias in the identification of vegetation phenological events. Since 2005, a network of forest and herbaceous sites has been equipped with laboratory made NDVI sensors to monitor the temporal dynamics of canopy structure and phenology at an intra-daily time step. In this study, we present recent results obtained in several contrasting biomes in France, French Guiana, Belgium and Congo. These sites represent a gradient of vegetation ecosystems: the main evergreen and deciduous forest ecosystems in temperate climate region, an evergreen tropical rain forest in French Guiana, an herbaceous savanna ecosystem in Congo, and a succession of three annual crops in Belgium. In this paper, (1) we provide an accurate description of the seasonal dynamics of vegetation cover in these different ecosystems (2) we identify the most relevant remotely sensed markers from NDVI time-series for determining the dates of the main phenological events that characterize these ecosystems and (3) we discuss the relationships between temporal canopy dynamics and climate factors. In addition to its importance for phenological studies, this ground-based Network of NDVI measurement provides data needed for the calibration and direct validation of satellite observations and products. © 2012 Elsevier Inc.

Abstract: Tank bromeliads form a conspicuous, yet neglected freshwater habitat in Neotropical forests. Recent studies driven by interests in medical entomology, fundamental aspects of bromeliad ecology and experimental research on food webs have, however, prompted increasing interest in bromeliad aquatic ecosystems. As yet, there is nothing in the literature about the life histories and environmental drivers of invertebrate population dynamics in tank bromeliads.
Based on fortnightly samples taken over one year, size frequency plots and individual dry masses allowed us to establish the life cycles and growth rates of the dominant aquatic invertebrates in a common bromeliad species of French Guiana. Linear mixed-effect models and Mantel tests were used to predict changes in density, biomass, and growth rates in relation to temperature, rainfall, humidity and detrital resources.
Annual variations in invertebrate densities and biomasses could be described according to three types of distribution: unimodal, bimodal or almost constant. Despite seasonal variations, precipitation, temperature, relative humidity and detritus concentration accounted significantly for changes in density and biomass, but we found no significant responses in growth rates of most invertebrate species. Species rather displayed non-seasonal life cycles with overlapping cohorts throughout the year. There was also a trend for delayed abundance peaks among congeneric species sharing similar functional traits, suggesting temporal partitioning of available resources.
Beyond novel knowledge, quantitative information on life histories is important to predict food-web dynamics under the influence of external forcing and self-organisation. Our results suggest that changes in species distribution that will affect population dynamics through biotic interactions in space and/or time could have greater effects on food webs and ecosystem functioning than changes in environmental factors per se.

Abstract: Arthropods represent most of global biodiversity, with the highest diversity found in tropical rain forests. Nevertheless, we have a very incomplete understanding of how tropical arthropod communities are assembled. We conducted a comprehensive mass sampling of arthropod communities within three major habitat types of lowland Amazonian rain forest, including terra firme clay, white-sand and seasonally flooded forests in Peru and French Guiana. We examined how taxonomic and functional composition (at the family level) differed across these habitat types in the two regions. The overall arthropod community composition exhibited strong turnover among habitats and between regions. In particular, seasonally flooded forest habitats of both regions comprised unique assemblages. Overall, 17·7% (26 of 147) of arthropod families showed significant preferences for a particular habitat type. We present a first reproducible arthropod functional classification among the 147 taxa based on similarity among 21 functional traits describing feeding source, major mouthparts and microhabitats inhabited by each taxon. We identified seven distinct functional groups whose relative abundance contrasted strongly across the three habitats, with sap and leaf feeders showing higher abundances in terra firme clay forest. Our novel arthropod functional classification provides an important complement to link these contrasting patterns of composition to differences in forest functioning across geographical and environmental gradients. This study underlines that both environment and biogeographical processes are responsible for driving arthropod taxonomic composition while environmental filtering is the main driver of the variance in functional composition. © 2016 British Ecological Society.

Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.