Predicting the ecological consequences of mega hydroelectric dams on vertebrate assemblages in lowland tropical forests

建造大型水电大坝是当前造成低地热带森林生境丧失的最重要因素之一，而低地热带森林每单位洪泛面积产生的水电兆瓦数比率非常低。迄今为止，在巴西亚马逊河流域建造的9座巨型水电站大坝至少淹没了662 000公顷的原始森林，到2022年还将再建造10座大型大坝。水电能源部门促使森林动植物群和植物群普遍受到侵蚀，因为大片森林变成了嵌在不适宜的淡水基质中的岛屿，而且邻近水库地区的森林砍伐率很高。鉴于水电投资不断增加，评估巨型水坝对森林生物多样性持久性的影响已成为热带森林保护的一个高度优先研究事项。位于亚马逊河中部的巴尔比纳水电站（Balbina Hydroelectric Dam，BHD）对环境的影响被广泛认为是灾难性的;在建设时（1986年），估计电力供应的50%现在是以236，000公顷的连续森林为代价产生的，这些森林减少到约3，500个岛屿的群岛。然而，这种实验景观提供了一个独特的机会，研究生物对栖息地破碎化和隔离的反应。除了长期的放松时间，与其他分散的景观相比，巴尔比纳大坝还具有几个优势，包括大量复制的岛屿，均匀的栖息地矩阵，有效的保护免受伐木和狩猎，以及管理水库区域的Uatumã生物保护区的部分后勤支持。在这里，我们建议研究陆生和树栖脊椎动物种群（哺乳动物，鸟类和爬行动物）如何应对巴尔比纳水库景观结构的急剧隔离后的变化，以及森林干扰和森林隔离的协同作用。将在32个地点进行定量调查，采用七种抽样技术：样线普查、点计数、相机诱捕、跟踪调查、封闭跟踪站、犰狳洞穴计数以及昼夜动物区系的自动数字记录。物种持久性和群落结构的模式将被量化，并与生境结构和组成（森林断面积，冠层空隙率，冠层高度，林下密度，活/死树密度和植物多样性）和不同的补丁和景观指标（岛屿的大小，形状，隔离，土地覆盖）。将利用数字半球照片和高分辨率卫星图像对森林树冠断裂进行评估。本研究将记录在一个真正的湖泊岛屿系统内的脊椎动物组合的局部灭绝模式，并预测整个巴尔比纳群岛的物种丰富度和组成，使用修改后的物种面积关系。使用“分析工具包”，从这项研究的结果也将告知施工前的环境影响评估和许可标准的计划水力发电大坝预计为其他亚马逊河流域，提供大坝的位置和最高水位是已知的，数字高程（DE）数据的上游淹没区可以提供。这将有助于制定一个预测框架，利用该框架可以对一系列拟议的水电大坝项目地点的水力发电和生物多样性侵蚀之间的权衡进行评估。

The construction of major hydroelectric dams is one of the most important current drivers of habitat loss in lowland tropical forests, where the ratio of megawatts of hydropower produced per unit of flooded area is notoriously low. At least 662,000 ha of primary forests were inundated by the nine mega-hydroelectric dams constructed to date across the Brazilian Amazon, and 10 additional major dams will be built by 2022. The hydroelectric energy sector promotes widespread erosion of forest fauna and flora due to conversion of large tracts of forest into islands embedded within a unsuitable freshwater matrix and high deforestation rates throughout the neighbouring reservoir areas. Given escalating investments in hydropower, assessing the effects of mega-dams on forest biodiversity persistence has become a high research priority in tropical forest conservation. The environmental impact of the Balbina Hydroelectric Dam (BHD) in the Central Amazon has been widely considered to be disastrous; <50% of the estimated power supply at the time of construction (1986) is now generated at the expense of 236,000ha of continuous forests that were reduced to an archipelago of ~3,500 islands. However, this experimental landscape provides a unique opportunity to examine biotic responses to habitat fragmentation and isolation. In addition to the long-term relaxation time, the Balbina Dam presents several advantages compared to other fragmented landscapes including a large number of replicate islands, a homogeneous habitat matrix, effective protection from logging and hunting, and partial logistical support from the Uatumã Biological Reserve which manages the reservoir area. Here, we propose to examine how both terrestrial and arboreal vertebrate populations (mammals, birds and reptiles) respond to drastic post-isolation alteration in landscape structure in the Balbina reservoir, and the synergistic interaction of forest disturbance and forest isolation. Quantitative surveys will be conducted at 32 sites using a combination of seven sampling techniques: line-transect censuses, point-counts, camera trapping, track-surveys, enclosed track stations, armadillo burrow counts, and automated digital recordings of the diurnal and nocturnal fauna. Patterns of species persistence and community structure will be quantified and related to habitat structure and composition (forest basal area, canopy gap fraction, canopy height, understorey density, density of live/dead trees and floristic diversity) and different patch and landscape metrics (island size, shape, isolation, land cover). Forest canopy fracture will be assessed using digital hemispherical photographs coupled with high resolution satellite images. This study will document the patterns of local extinction in vertebrate assemblages within a true lacustrine island system and predict species richness and composition across the entire Balbina archipelago using modified species-area relationships. Using an 'analytical toolkit', results from this study will also inform pre-construction environmental impact assessments and licensing standards of planned hydroelectric dams projected for other Amazonian river basins, provided that the dam location and maximum water-level are known and digital elevation (DE) data for the upstream flooded area can be made available. This will allow the development of a predictive framework with which the tradeoffs between hydropower generation and biodiversity erosion can be evaluated for a range of proposed hydroelectric dam project sites.