Fragmentation Increases Impact of Wind Disturbance on Forest Structure and Carbon Stocks in a Western Amazonian Landscape

Tropical second-growth forests could help mitigate climate change, but the degree to which their carbon potential is achieved will depend on exposure to disturbance. Wind disturbance is common in tropical forests, shaping structure, composition, and function, and influencing successional trajectories. However, little is known about the impacts of extreme winds in fragmented landscapes, though second-growth forests are often located in mosaics of forest, pasture, cropland, and other land cover types. Though indirect evidence suggests that fragmentation increases risk of wind damage, few studies have found such impacts following severe storms. In this study, we ask whether fragmentation and forest type (old vs. second growth) were associated with variation in wind damage after a severe convective storm in a fragmented production landscape in western Amazonia. We applied linear spectral unmixing to Landsat 8 imagery from before and after the storm, and combined it with field observations of damage to map wind effects on forest structure and biomass (Figure 4, 5). We also used Landsat 8 imagery to map land cover with the goals of identifying old- and second-growth forest and characterizing fragmentation. We used these data to assess variation in wind disturbance across 95,596 hectares of forest, distributed over 6,110 patches. We find that fragmentation is significantly associated with wind damage, with damage severity higher at forest edges and in edgier, more isolated patches (Figure 7). Damage was more severe in old-growth than in second-growth forests, but this effect was weaker than that of fragmentation (Figure 8). These results illustrate the importance of considering spatial configuration and landscape context in planning tropical forest restoration and predicting carbon sequestration in second-growth forests. Future research should address the mechanisms behind these results, to minimize wind damage risk in second-growth forests so their carbon potential can be maximally achieved

Wild Meat

The meat of wild animals is a crucial part of the diets of millions of families in the tropics and subtropics. It is often the most accessible and sustainable source of protein and micronutrients and can also be a significant source of revenue for many people. Enabling these people, mostly the poor, to continue consuming wildlife in a sustainable manner — while reducing the impacts of overhunting on animal populations — are the main challenges facing researchers and policymakers. Since 2011, the research and policy initiatives led by the Bushmeat Research Initiative (the BRI-CIFOR team), in conjunction with many partners and collaborators worldwide, have made substantial contributions to this topic. These efforts increase the understanding of the current levels and trends of wild meat extraction and of the importance of this wild meat to consumers. The BRI-CIFOR team has generated important new data of wild meat use across a diverse number of environments worldwide. This publication presents some of the key FTA outputs on wild meat; over the last decade these efforts have contributed to inform science, policy and practice

North Tropical Atlantic influence on western Amazon fire season variability

The prevailing wet climate in the western Amazon is not favorable to the natural occurrence of fires. Nevertheless, the current process of clearing of humid forests for agriculture and cattle ranching has increased the vulnerability of the region to the spread of fires. Using meteorological stations precipitation and the Moderate Resolution Spectroradiometer (MODIS) Active-Fires (AF) during 2000-2009, we show that fire anomalies vary closely with July-August-September (JAS) precipitation variability as measured by the Standardized Precipitation Index (SPI). The precipitation variability is, in turn, greatly determined by sea surface temperature (SST) anomalies in the North Tropical Atlantic (NTA). We develop a linear regression model to relate local fire activity to an index of the NTA-SST. By using seasonal forecasts of SST from a coupled model, we are able to predict anomalous JAS fire activity as early as April. We applied the method to predict the severe 2010 JAS season, which indicated strongly positive seasonal fire anomalies within the 95% prediction confidence intervals in most western Amazon. The spatial distribution of predicted SPI was also in accordance with observed precipitation anomalies. This three months lead time precipitation and fire prediction product in the western Amazon could help local decision makers to establish an early warning systems or other appropriate course of action before the fire season begins

North Tropical Atlantic influence on western Amazon fire season variability

The prevailing wet climate in the western Amazon is not favorable to the natural occurrence of fires. Nevertheless, the current process of clearing of humid forests for agriculture and cattle ranching has increased the vulnerability of the region to the spread of fires. Using meteorological stations precipitation and the Moderate Resolution Spectroradiometer (MODIS) Active-Fires (AF) during 2000-2009, we show that fire anomalies vary closely with July-August-September (JAS) precipitation variability as measured by the Standardized Precipitation Index (SPI). The precipitation variability is, in turn, greatly determined by sea surface temperature (SST) anomalies in the North Tropical Atlantic (NTA). We develop a linear regression model to relate local fire activity to an index of the NTA-SST. By using seasonal forecasts of SST from a coupled model, we are able to predict anomalous JAS fire activity as early as April. We applied the method to predict the severe 2010 JAS season, which indicated strongly positive seasonal fire anomalies within the 95% prediction confidence intervals in most western Amazon. The spatial distribution of predicted SPI was also in accordance with observed precipitation anomalies. This three months lead time precipitation and fire prediction product in the western Amazon could help local decision makers to establish an early warning systems or other appropriate course of action before the fire season begins

Decadal covariability of Atlantic SSTs and western Amazon dry-season hydroclimate in observations and CMIP5 simulations

The unusual severity and return time of the 2005 and 2010 dry-season droughts in western Amazon is attributed partly to decadal climate fluctuations and a modest drying trend. Decadal variability of western Amazon hydroclimate is highly correlated to the Atlantic sea surface temperature (SST) north-south gradient (NSG). Shifts of dry and wet events frequencies are also related to the NSG phase, with a 66% chance of 3+ years of dry events per decade when NSG > 0 and 19% when NSG < 0. The western Amazon and NSG decadal covariability is well reproduced in general circulation models (GCMs) historical (HIST) and preindustrial control (PIC) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). The HIST and PIC also reproduce the shifts in dry and wet events probabilities, indicating potential for decadal predictability based on GCMs. Persistence of the current NSG positive phase favors above normal frequency of western Amazon dry events in coming decades

Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use

Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù

Forest-linked livelihoods in a globalized world.

Forests have re-taken centre stage in global conversations about sustainability, climate and biodiversity. Here, we use a horizon scanning approach to identify five large-scale trends that are likely to have substantial medium- and long-term effects on forests and forest livelihoods: forest megadisturbances; changing rural demographics; the rise of the middle-class in low- and middle-income countries; increased availability, access and use of digital technologies; and large-scale infrastructure development. These trends represent human and environmental processes that are exceptionally large in geographical extent and magnitude, and difficult to reverse. They are creating new agricultural and urban frontiers, changing existing rural landscapes and practices, opening spaces for novel conservation priorities and facilitating an unprecedented development of monitoring and evaluation platforms that can be used by local communities, civil society organizations, governments and international donors. Understanding these larger-scale dynamics is key to support not only the critical role of forests in meeting livelihood aspirations locally, but also a range of other sustainability challenges more globally. We argue that a better understanding of these trends and the identification of levers for change requires that the research community not only continue to build on case studies that have dominated research efforts so far, but place a greater emphasis on causality and causal mechanisms, and generate a deeper understanding of how local, national and international geographical scales interact.This work was funded by the UK’s Department for International Development (grant number 203516-102) and governed by the University of Michigan’s Institutional Review Board (HUM00092191). JAO acknowledges the 520 support of a European Union FP7 Marie Curie international outgoing fellowship (FORCONEPAL). LVR was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (Grant agreement No. 853222 FORESTDIET). AJB acknowledges the support of an Australian Research Council Australia Laureate Fellowship (grant number 525 FL160100072). LBF acknowledges support from the European Union Marie Curie global fellowship (CONRICONF). PM was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement No 677140 MIDLAND)