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

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NERC
NERC
NERC
NERC
NERC

£254,260

March 25, 2012

Sept. 25, 2013

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.

Potential Impact:
This study will explicitly confront the conservation policy knowledge gap in relation to the environmental impact of hydropower development in tropical forest watersheds, and we see this as the most important 'scaling-up' by-product of the project. Results will be explicitly communicated to target governmental agencies responsible for both commissioning environmental impact assessment (EIA) studies of large hydroelectric dam projects and subsequently granting formal permission for or rejecting these large engineering projects. The project will also provide a predictive framework, which will culminate in the form of a user-friendly 'analytical toolkit', to ensure that the ecological and demographic impact of future project proposals on the terrestrial biota can be quantitatively evaluated. The study will explicitly inform EletroNorte (the Brazilian Hydropower Development transnational; http://www.eln.gov.br/) on how to best minimize the impact of hydroelectric dams across the Brazilian and Peruvian Amazon, where construction of several additional large dams (>150,000 ha) has been scheduled. A project report will also be made available to the World Bank, as most large hydroelectric projects are funded by mixed national and multilateral capital, contingent upon 'soft' rural development loans. A final report will also be presented to both ICMBio and IBAMA (Brazilian Institute of Natural Resources and Protected Areas; http://www.ibama.gov.br/) as this latter governmental agency holds the ultimate environmental pre-licensing prerogative to either formally approve or reject large energy infrastructure projects, a process that can take several years since the early planning stages of project viability and design. More locally, our results will also be used to inform a number of forest management issues within ICMBio's Uatumã Biological Reserve (which would host the study and manages the Balbina Hydroelectric Dam) as well as to evaluate the biodiversity conservation value of islands created from the Balbina impoundment.

To date, there has been no systematic assessment of the ecological impact of hydroelectric dams in tropical forest regions. Our results and predictive framework in estimating the scale of metacommunity extinction are therefore likely to lead to real conservation impacts, since they will be able to inform both the EIA protocols and the planning process of new hydroelectric dams to be proposed or constructed in Brazilian Amazonia or elsewhere in the lowland tropics. Moreover, the scale of biodiversity erosion resulting from existing dams resulting in an archipelagic landscape can also be estimated using a relatively simple analytical framework, provided that basic biophysical data are made available by the development enterprise. Ultimately, the policy success of this study can be measured in the long-term through (1) the reduction of detrimental impacts on forest biodiversity and forest cover resulting from the hydroelectric sector, and (2) more careful site selection for new hydroelectric dam project proposals, some of which will be inevitably built.

Results from this study will also be disseminated to the wider science community through publications in key conservation biology and ecology journals and talks presented at international meetings.