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International audience; Forests that regrow naturally on abandoned fields are important for restoring biodiversity and ecosystem services, but can they also preserve the distinct regional tree floras? Using the floristic composition of 1215 early successional forests (≤20 years) in 75 human-modified landscapes across the Neotropic realm, we identified 14 distinct floristic groups, with a between-group dissimilarity of 0.97. Floristic groups were associated with location, bioregions, soil pH, temperature seasonality, and water availability. Hence, there is large continental-scale variation in the species composition of early successional forests, which is mainly associated with biogeographic and environmental factors but not with human disturbance indicators. This floristic distinctiveness is partially driven by regionally restricted species belonging to widespread genera. Early secondary forests contribute therefore to restoring and conserving the distinctiveness of bioregions across the Neotropical realm, and forest restoration initiatives should use local species to assure that these distinct floras are maintained.

International audience; Tropical forests disappear rapidly because of deforestation, yet they have the potential to regrow naturally on abandoned lands. We analyze how 12 forest attributes recover during secondary succession and how their recovery is interrelated using 77 sites across the tropics. Tropical forests are highly resilient to low-intensity land use; after 20 years, forest attributes attain 78% (33 to 100%) of their old-growth values. Recovery to 90% of old-growth values is fastest for soil (12 decades). Network analysis shows three independent clusters of attribute recovery, related to structure, species diversity, and species composition. Secondary forests should be embraced as a low-cost, natural solution for ecosystem restoration, climate change mitigation, and biodiversity conservation.

We analyzed the abundance and diversity of Heteromyid and Murid rodents in the Lagos de Montebello National Park and adjacent areas, Chiapas, Mexico. We sampled three habitat types with different degrees of disturbance: pine-oak-liquidambar forest, ecotone and crop farming lands. Habitat types were defined considering characteristics such as heterogeneity, structural complexity and arboreal cover. We obtained ancillary habitat data considered important for small mammal requirements. Data on rodent communities were obtained by capture-mark-recapture between February and October 1996. We made 410 captures in 3820 trap-nights effort. Ten species were recorded, including one endemic with restricted distribution in Chiapas. Mouse diversity in the forest was significantly higher than within the farm lands. A Kendall correlation analysis showed positive relationship between rodent community species richness and habitat heterogeneity. Diversity of rodents was associated with the habitat complexity and structural ...

This report describes the conceptual approach of the CO2FIX V 3.1 model, as well as its implementation and numerous examples. This stand level simulation model is a tool which quantifies the C stocks and fluxes in the forest biomass, the soil organic matter and the wood products chain. Included are also a bioenergy module, a financial module and a carbon accounting module. The model is applicable to many different situations: afforestation projects, agroforestry systems, and selective logging systems. The model is freely available from the web, together with numerous examples. The model has many users. The two earlier versions of the model have been downloaded already almost 2000 times

The present study intends to answer some of the important questions that arise when translating projects that have an ecological potential to mitigate carbon excesses, into actual implementation of these projects in a farmer-dominated landscape. Farm and community forestry projects for greenhouse gas mitigation in such environments would involve numerous participants, a high variety of small-scaled systems spread over large areas, with individual adaptations of general management procedures due to personal interests, local conditions, and previous experiences. In this book the results are presented of a study to estimate the flux of carbon from the terrestrial ecosystems to the atmosphere from the 1970s and 1990s of an intensively impacted and highly fragmented landscape. About 20 x 10 6 MgC were released to the atmosphere during the period of time covered by the study. Approximately 34% of the 1975 vegetation carbon pool disappeared. A feasibility study was carried out to (i) identify farmer preferred and ecologically viable agroforestry/forestry systems and their ex ante carbon sequestration potential; and to (ii) assess the economic potential of carbon offsets of such systems.A total of five land-use systems were considered viable, while farmers presented local adjustments in preferred species, planting arrangements, and rotation times. The carbon sequestration potential varied highly between the systems and the regions (from 26.7 to 338.9 MgC ha -1 ). The total cost of one MgC ha -1 varied between $US 1.84 and 3.98 for the systems selected in the Tzeltal region and between $US 1.47 and 11.15 for the systems in the Tojolabal region. The differences in costs within the same region were due to differences in establishment and opportunity costs, whereas the differences between the two areas were due to differences in the carbon sequestration potential of the regions. The carbon sequestration potential of the Highlands of Chiapas was estimated, based on an incentive program that would stimulate small farmers and rural communities to adopt biomass-accumulating measures, such as agroforestry or improved forest management. It was estimated that 38 × 10 6 MgC could be sequestered for under $US 15 MgC -1 , of which 32 × 10 6 MgC by means of sustainable forest management. The choice of a baseline rate of biomass loss in the "business-as-usual" scenario remains a critical issue to estimate the carbon sequestration potential of forestry.The main sources of uncertainties observed in the calculations of the GHG-offset potential of a forestry project were related to: (i) classification of LU/LC types, with observed differences of up to around 8% in land cover estimations; (ii) estimation of C-stocks within each LU/LC type, with uncertainties varying from around 13 to 34% in total C-stock; (iii) historical evidence of LU/LC changes and related GHG fluxes applied in baselines, giving rise to uncertainties of up to about 16% in the estimation of fluxes, whereas varying baseline assumptions produced differences between 31 and 73% in the C-mitigation calculations, with levels of uncertainty in the differences of up to 74%; and (iv) simulation techniques used to calculate future baseline and project C-fluxes, which generated uncertainties of up to around 10% in overall C-mitigation estimations.A self-reporting system with on-site spot-checks is the most appropriate method to assess the impact on carbon fluxes of a farm-forestry project, which typically include a high diversity of small-scale systems and numerous participants. The monitoring and evaluation procedure outlined in this study, facilitates the collection of field data at low cost, helps to ensure that the systems continue to address the needs of farmers, and gives the farmers an understanding of the value of the service that they are providing.Any method to estimate carbon dynamics has to deal with sources and levels of variability and uncertainties in data. In this dissertation various approaches were used to estimate the impact of variability or uncertainty in data or assumptions. In Chapter 3, the standard deviation of collected biomass data was used as an indicator to estimate the confidence interval of the regional C flux. In Chapter 4, the uncertainty of information was dealt with by varying tree growth due to expected differences in site conditions. In Chapter 5, a sensitivity analysis was used to test the impact of baseline emission assumptions and capital interest rates on the cost of mitigating one Mg carbon. Varying baseline assumptions and carbon transfer parameters within a forest ecosystem was used in Chapter 6 to identify the most important sources of error in the C mitigation estimation of forestry projects.

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5Mg dry massha-1 vs. 21 and 28Mgha-1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.