Flora fanerogâmica da Serra Negra, Minas Gerais, Brasil

O presente estudo teve como objetivo caracterizar a flora fanerogâmica da região da Serra Negra localizada no sul da Zona da Mata de Minas Gerais, entre os municípios de Lima Duarte, Rio Preto, Santa Bárbara do Monte Verde e Olaria. Embora considerada de importância biológica alta, esta região não possui nenhum registro anterior de dados florísticos, o que levou ao desenvolvimento deste levantamento, durante o período de 2003 a 2010. A vegetação é caracterizada por um mosaico de formações florestais e campestres onde se destacam os campos rupestres e florestas nebulares em altitudes que variam de 1300 a ca. 1700 m. Um total de 1033 espécies foi encontrado, distribuídas em 469 gêneros e 121 famílias sendo as mais representativas Orchidaceae (115 spp.), Asteraceae 54 spp.), Melastomataceae (56 spp.), Myrtaceae (53 spp.), Fabaceae, Poaceae e Rubiaceae (48 spp. cada), Bromeliaceae (43 spp.), Solanaceae (38 spp.) e Piperaceae (33 spp). Novos registros e endemismos para a flora mineira foram encontrados e 58 espécies estão citadas na lista de espécies ameaçadas de Minas Gerais

Disentangling the role of prefire vegetation vs. burning conditions on fire severity in a large forest fire in SE Spain

Fire severity is a function of dynamic interactions between vegetation and burning conditions. To understand the factors that control it, accurate methods for estimating prefire vegetation structure and composition as well as fire propagation conditions are required. Here we analyzed the spatial variability of fire severity in a mixedseverity fire (3217 ha) that occurred in southeast Spain (Yeste, Albacete) from 27th July to 1th August 2017, burning mostly a pine woodland, including part of an earlier fire in 1994. Fire severity was estimated using three satellite-based indices derived from the Normalized Burn Ratio (NBR) using Sentinel 2 and Landsat 8 images from the dates before and immediately after fire. The field-based Composite Burn Index (CBI) was used for validation. Prefire vegetation conditions and fuel models were derived from LiDAR metrics and other vegetation data. Fire propagation conditions were estimated based on a fire progression map provided by the Forestry Services of Castilla-La Mancha. In addition, hourly fire weather and aligned (i.e., in the sense of the propagating fire-front) slope and wind speed were calculated for each burning period. Regression models using different spectral fire severity indices and their driving factors were obtained applying Boosted Regression Trees (BRTs). Fire severity was highly predicted by both burning conditions and prefire vegetation (mean adjusted R2 [Adj.R2]: 86% ± 0.04 and 68% ± 0.05 for training and validation sets, respectively). Alone, burning conditions explained more variance than LiDAR metrics and vegetation separately. The single variables that contributed most to the models were the rate of spread of the fire-front, biomass proxies (i.e., Leaf Area Index [LAI] and fraction of Photosynthetically Active Radiation [fPAR]) and understory vegetation (i.e., density of LiDAR points 1–2 m). Higher fire severity occurred in areas burning uphill, with a high rate of spread driven by high velocity winds and under high maximum temperature. Fire severity was high in wooded stands that were heterogeneous in height, composed by scattered and small Pinus halepensis trees, with high and homogeneous understory cover. In contrast, lower fire severity occurred in mature stands dominated by tall Pinus pinaster and Pinus nigra trees. There were strong interactions between vegetation, weather, fire-aligned topography and rate of spread. Because vegetation variables were important drivers of fire severity, even under extreme fire weather conditions, fuel management treatments to limit fire severity and, potentially, fire size should be implemented

Multidimensional evaluation of managed relocation

Managed relocation (MR) has rapidly emerged as a potential intervention strategy in the toolbox of biodiversity management under climate change. Previous authors have suggested that MR (also referred to as assisted colonization, assisted migration, or assisted translocation) could be a last-alternative option after interrogating a linear decision tree. We argue that numerous interacting and value-laden considerations demand a more inclusive strategy for evaluating MR. The pace of modern climate change demands decision making with imperfect information, and tools that elucidate this uncertainty and integrate scientific information and social values are urgently needed. We present a heuristic tool that incorporates both ecological and social criteria in a multidimensional decision-making framework. For visualization purposes, we collapse these criteria into 4 classes that can be depicted in graphical 2-D space. This framework offers a pragmatic approach for summarizing key dimensions of MR: capturing uncertainty in the evaluation criteria, creating transparency in the evaluation process, and recognizing the inherent tradeoffs that different stakeholders bring to evaluation of MR and its alternatives.Articl

Multidimensional evaluation of managed relocation

Managed relocation (MR) has rapidly emerged as a potential intervention strategy in the toolbox of biodiversity management under climate change. Previous authors have suggested that MR (also referred to as assisted colonization, assisted migration, or assisted translocation) could be a last-alternative option after interrogating a linear decision tree. We argue that numerous interacting and value-laden considerations demand a more inclusive strategy for evaluating MR. The pace of modern climate change demands decision making with imperfect information, and tools that elucidate this uncertainty and integrate scientific information and social values are urgently needed. We present a heuristic tool that incorporates both ecological and social criteria in a multidimensional decision-making framework. For visualization purposes, we collapse these criteria into 4 classes that can be depicted in graphical 2-D space. This framework offers a pragmatic approach for summarizing key dimensions of MR: capturing uncertainty in the evaluation criteria, creating transparency in the evaluation process, and recognizing the inherent tradeoffs that different stakeholders bring to evaluation of MR and its alternatives.Centre of Excellence for Invasion Biolog