Effects of disturbance and landscape structure on the biodiversity value of remnant tropical forest corridors

这项研究将基于社区范围内植物(树木和木本藤本植物)、白天活动的鸟类和非飞行哺乳动物的定量清单，这些植物分布在30个空间独立的残存河岸走廊和10个嵌入大片连续森林的河岸地点。每个站点将抽样多达10个地块，但这将不可避免地取决于走廊斑块的大小。所有地点将使用地理参考的2006年陆地卫星图像(位置误差10m)在3500平方公里的景观多边形内进行预先选择，包括零碎的基质和连续的森林。为了控制区域敏感物种来源种群的差异，所有走廊都将连接到至少1,000公顷的森林斑块，但采样点的位置将明确考虑到这些斑块的距离。在之前的一项研究中，我们在阿尔塔弗洛雷斯塔半径80公里范围内建立了一个由154名土地所有者组成的协作网络，这将极大地便利进入调查地点和调查后勤。将量化物种多样性和物种组成的模式，然后将其与以前对同一区域不同大小森林斑块中的相同分类群的调查(Michalski&Peres 2005，Press，Peres&Michalski 2006，Lees&Peres in Press)进行比较。鸟类和哺乳动物调查将包括全日线横断面普查、哺乳动物足迹调查、相机诱捕、螳螂洞穴计数、有限半径点计数。植物区系清单将以0.25公顷(10 x 250米)的地块为基础。为了重建过去十年中景观结构的变化，所有地点都将通过GPS定位，然后与一年两次的陆地卫星图像时间序列(1996-2006年，最近图像中像素大小为15米)相关联。在现场获得的环境生境变量将包括树木密度、森林断面积、树种组成、郁闭度(使用数字半球照片)、林下密度和树叶的垂直分层。植物鉴定将由一名合作的植物学家进行，并辅之以当地联合国教科文组织植物标本馆已有的植物凭证参考集。此外，将使用从邻近牧场拍摄的数字照片(走廊两侧每块地两张照片)来评估长度为50米的路段的垂直走廊纵断面。森林概况照片将使用我们编制的专用软件进行阈值处理和处理。由此产生的斑块指标(即走廊高度、垂直剖面面积)将与相同地点的森林生境质量有关，使用来自最近陆地卫星图像的像素尺度多光谱数据，这提供了相同走廊水平平面的鸟瞰图。大多数走廊地点是劳动农村的一部分，反复遭受不同形式的人为森林干扰。因此，将采访来自邻近家庭(大型养牛场和小农户)的自愿当地线人，以恢复每个地点结构性和非结构性干扰的历史，包括选择性伐木、野火、放牧和狩猎。将使用一种图像处理技术进一步验证走廊干扰历史，该技术依赖于林隙分数指数(归一化差异分数指数，NDFI)，该指数结合了来自SMA(光谱混合分析)的绿色和非光合作用植被、土壤和阴凉部分，以增强对人为树冠干扰的检测(Souza等人)。2005)。考虑到斑块和景观变量以及场地内的干扰历史，将主要使用广义线性模型和逻辑回归对每个群落的社区范围特性以及单一物种的占有率和丰富度模式进行数据分析。

The study will be based on community-wide quantitative inventories of plants (trees and woody lianas >5 cm in diameter at breast height), diurnal birds, and non-flying mammals at 30 spatially independent remnant riparian corridors and 10 riparian sites embedded within large tracts of continuous forest. As many as 10 plots will be sampled at each site, but this will unavoidably depend on corridor patch size. All sites will be pre-selected using a georeferenced 2006 Landsat image (positional error <10m) within a 3,500 km2 landscape polygon including both the fragmented matrix and continuous forests. To control for differences in source populations of area-sensitive species, all corridors will be connected to forest patches of at least 1,000 ha, but sampling site location will explicitly take into account distance to these patches. During a previous study, we developed a collaborative network of 154 landowners within a 80-km radius of Alta Floresta, which will greatly facilitate access to survey sites and survey logistics. Patterns of species diversity and species composition will be quantified and then compared with previous surveys on the same taxa in variable-sized forest patches in the same region (Michalski & Peres 2005, in press, Peres & Michalski 2006, Lees & Peres in press). Bird and mammal surveys will include diurnal line-transect censuses, surveys of mammal tracks, camera trapping, armadillo burrow counts, limited-radius point-counts. Floristic inventories will be based on 0.25-ha (10 x 250m) plots. To reconstruct changes in landscape structure in the last decade, all sites will be GPS-located and then related to a biannual time series of Landsat images (1996-2006, pixel size = 15 m in recent images). Environmental habitat variables obtained in site will include tree density, forest basal area, tree species composition, canopy cover (using digital hemispherical photographs), understorey density, and vertical stratification of foliage. Plant identification will be conducted by a collaborating botanist, aided by a reference collection of plant vouchers that is already available at the local UNEMAT herbarium. In addition, vertical corridor profiles along sections of 50 m in length will be assessed using digital photos taken from neighbouring pasture sites (two photos per plot along both sides of the corridor). Forest profile photos will be thresholded and processed using a dedicated software that we have compiled. The resulting patch metrics (i.e. corridor height, area of vertical profiles) will then be related to the forest habitat quality of the same sites using pixel-scale multi-spectral data from recent Landsat images, which provides an aerial view of the horizontal plane of the same corridors. Most corridor sites are part of the working countryside and have been subjected to a recurrent history of different forms of anthropogenic forest disturbance. Willing local informants from neighbouring households (large cattle ranches and smallholders) will thus be interviewed to recover the history of structural and non-structural disturbance at each site, including selective logging, wildfires, cattle grazing, and game hunting. Corridor disturbance history will be further verified using an image-processing technique that relies on a gap fraction index (the Normalized Difference Fraction Index, NDFI) which combines the green and non-photosynthetic vegetation, soil and shade fractions derived from SMA (spectral mixture analysis) to enhance the detection of anthropogenic canopy disturbance (Souza et al. 2005). Data analysis of community-wide properties of each assemblage, and the patterns of both occupancy and abundance of single species will be carried out primarily using generalized linear modelling and logistic regressions taking into account patch and landscape variables, as well as the history of disturbance within a site.