Assessing the ecological condition of streams in a southeastern Brazilian basin using a probabilistic monitoring design.
Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodiversity and habitat. We assessed the ecological condition of streams in a southeastern Brazilian basin. We quantified the percentage of stream length in good, fair, and poor ecological condition according to benthic macroinvertebrate assemblage. We assessed the risk of finding degraded ecological condition associated with degraded aquatic riparian physical habitat condition, watershed condition, and water quality. We describe field sampling and implementation issues encountered in our survey and discuss design options to remedy them. Survey sample sites were selected using a spatially balanced, stratified random design, which enabled us to put confidence bounds on the ecological condition estimates derived from the stream survey. The benthic condition index indicated that 62 % of stream length in the basin was in poor ecological condition, and 13 % of stream length was in fair condition. The risk of finding degraded biological condition when the riparian vegetation and forests in upstream catchments were degraded was 2.5 and 4 times higher, compared to streams rated as good for the same stressors. We demonstrated that the GRTS statistical sampling method can be used routinely in Brazilian rain forests and other South American regions with similar conditions. This survey establishes an initial baseline for monitoring the condition and trends of streams in the region.
Programa de Pós-Graduação em Ecologia, Instituto de Biologia, UFRJ, Ilha do Fundão, Rio de Janeiro, CEP 21941-590, Brazil, jjvingamb@gmail.com.
Juliana
J
Jiménez-Valencia
Philip R
PR
Kaufmann
Ana
A
Sattamini
Riccardo
R
Mugnai
Darcilio Fernandes
DF
Baptista
D000818:Animals; D044822:Biodiversity; D001938:Brazil; D004463:Ecology; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D015233:Models, Statistical; D045483:Rivers / Q000737:chemistry*; D014197:Trees