Abstract: In the current global change context, it is urgent to anticipate the fate of tropical forests. This means understanding tree community response to disturbance and the underlying processes. In that respect, we aim here to clarify taxonomic and functional post-disturbance trajectories, and determine the scope of the Intermediate Disturbance Hypothesis (IDH) that remains debated in tropical forests. We analyzed community trajectories following a disturbance gradient from 10 to 60% of above-ground biomass loss in a Neotropical forest over 30 years. We considered trajectories along time of community taxonomic and functional trajectories in terms of richness, evenness, composition, and redundancy. We based on the annual botanical inventories of 75 ha of a Neotropical forest and on large trait datasets comprising seven leaf, stem, and life-history traits. We identified a decoupling between taxonomic composition, differing among communities, and functional composition, similar among communities and convergent in the functional space. The taxonomic diversity followed humped-shaped trajectories along time after disturbance depending on the initial disturbance intensity, which validated the IDH (Intermediate Disturbance Hypothesis). The functional diversity trajectories, however, were homogeneous among plots and dismissed the IDH. We explained this decoupling by the variations in community functional redundancy that mitigated the functional impact of disturbance. Although consistent, the recovery of community composition, diversity, and redundancy remained divergent from the initial state after 30 years. These results acknowledged the need of decades-long cycles without disturbance to ensure community complete recovery.

Abstract: Trait-environment relationships have been described at the community level across tree species. However, whether interspecific trait-environment relationships are consistent at the intraspecific level is yet unknown. Moreover, we do not know how consistent is the response between organ vs. whole-tree level.We examined phenotypic variability for 16 functional leaf (dimensions, nutrient, chlorophyll) and wood traits (density) across two soil types, Ferralitic Soil (FS) vs. White Sands (WS), on two sites for 70 adult trees of Cecropia obtusa Trécul (Urticaceae) in French Guiana. Cecropia is a widespread pioneer Neotropical genus that generally dominates early successional forest stages. To understand how soil types impact resource-use through the processes of growth and branching, we examined the architectural development with a retrospective analysis of growth trajectories. We expect soil types to affect both, functional traits in relation to resource acquisition strategy as already described at the interspecific level, and growth strategies due to resource limitations with reduced growth on poor soils.Functional traits were not involved in the soil response, as only two traits-leaf residual water content and K content-showed significant differences across soil types. Soil effects were stronger on growth trajectories, with WS trees having the slowest growth trajectories and less numerous branches across their lifespan.The analysis of growth trajectories based on architectural analysis improved our ability to characterise the response of trees with soil types. The intraspecific variability is higher for growth trajectories than functional traits for C. obtusa, revealing the complementarity of the architectural approach with the functional approach to gain insights on the way trees manage their resources over their lifetime. Soil-related responses of Cecropia functional traits are not the same as those at the interspecific level, suggesting that the effects of the acting ecological processes are different between the two levels. Apart from soil differences, much variation was found across sites, which calls for further investigation of the factors shaping growth trajectories in tropical forests.

Abstract: In this paper we give a priori error estimates for finite element approximations of linear parabolicproblems with pointwise control and incomplete data. We discretise the optimal control problemby using piecewise linear and continuous finite elements for the space discretisation of the state,and we use the backward Euler scheme for time discretisation. We prove a priori error estimates forthe state, the adjoint-state as well as for the low-regret pointwise optimal control.

Abstract: The rainforests of the Neotropics shelter a vast diversity of plant, animal and microscopic species that provide critical ecosystem goods and services for both local and worldwide populations. These environments face a major crisis due to increased deforestation, pollution, and climate change, emphasizing the need for more effective conservation efforts. The adequate monitoring of these ecosystems has proven a complex and time consuming endeavour, which depends on ever dwindling taxonomic expertise. To date, many species remain undiscovered, let alone described, with otherwise limited information regarding known species population distributions and densities. Overcoming these knowledge shortfalls and practical limitations is becoming increasingly possible through techniques based on environmental DNA (eDNA), i.e., DNA that can be obtained from environmental samples (e.g. tissues, soil, sediment, water, etc.). When coupled with high-throughput sequencing, these techniques now enable realistic, cost-effective, and standardisable biodiversity assessments. This opens up enormous opportunities for advancing our understanding of complex and species-rich tropical communities, but also in facilitating large-scale biomonitoring programs in the neotropics. In this review, we provide a brief introduction to eDNA methods, and an overview of their current and potential uses in both terrestrial and aquatic ecosystems of neotropical rainforests. We also discuss the limits and challenges of these methods for our understanding and monitoring of biodiversity, as well as future research and applied perspectives of these techniques in neotropical rainforests, and beyond. © 2020 Elsevier Ltd

Abstract: For more than a decade, distance-based methods have been widely employed and constantly improved in spatial economics. These methods are a very useful tool for accurately evaluating the spatial distribution of economic activity. We introduce a new distance-based statistical measure for evaluating the spatial concentration of industries. The m function is the first relative density function to be proposed in economics. This tool supplements the typology of distance-based methods recently drawn up by Marcon and Puech (J Econ Geogr 3(4):409–428, 2003). By considering several simulated and real examples, we show the advantages and the limits of the m function for detecting spatial structures in economics. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.