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BackgroundMangrove forest restoration and rehabilitation programs are increasingly undertaken to re-establish ecosystem services in the context of community-based biodiversity conservation. Restoration is returning a habitat to the most natural condition, whereas rehabilitation often focuses on optimising ecosystem services alongside biodiversity. With many different restoration and rehabilitation objectives and techniques existing, it is difficult to assess the general effectiveness of restoration and rehabilitation on biodiversity and ecosystem services. This systematic review protocol presents a methodology that will be used to assess the impacts of mangrove forest restoration and rehabilitation on biodiversity and provisioning ecosystem services in a global context.MethodsThis review will assess studies that have undertaken biodiversity surveys of restored and rehabilitated mangrove forests by comparing them against suitable mature reference mangrove forests within the same region, or surveys prior to degradation of the forest. This review will investigate how the age and initial tree diversity of a restoration or rehabilitation activities determine the effectiveness of these initiatives. Taxa of commercial value to local communities will be assessed to identify whether rehabilitation for optimal ecosystem service provision is likely to conflict with the full restoration of mangrove forests.
<p>Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges “bottom up”, as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated–pre- and post-PPCDAM (“Plano de Ação para Proteção e Controle do Desmatamento na Amazônia”)–the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protecti
Background and AimsIsoprene is the most important volatile organic compound emitted by land plants in terms ofabundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supplyand CO2concentration. A need to quantify these controls has long been recognized. There are already models thatgive realistic results, but they are complex, highly empirical and require separate responses to different drivers.This study sets out to find a simpler, unifying principle.†MethodsA simple model is presented based on the idea of balancing demands for reducing power (derived fromphotosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesisof isoprene. This model’s ability to account for key features in a variety of experimental data sets is assessed.†Key resultsThe model simultaneously predicts the fundamental responses observed in short-term experiments,namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isopreneemission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) amaximum of isoprene emission at low internal CO2concentration (ci) and an asymptotic decline thereafter with in-creasingci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) atemperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity.†ConclusionsA simple model was used to test the hypothesisthat reducing poweravailable to the synthesis pathwayfor isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simpli-city the model explains much in terms of the observed response of isoprene to external drivers as well asthe observeddecoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale
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