Data from: Is environmental legislation conserving tropical stream faunas? a large-scale assessment of local, riparian and catchment-scale influences on Amazonian stream fish
Leal, Cecília G., Federal University of Lavras, Lancaster University
Barlow, Jos, Lancaster University
Gardner, Toby, Museu Paraense Emílio Goeldi
Hughes, Robert M., Oregon State University
Leitão, Rafael P., Universidade Federal de Minas Gerais
Mac Nally, Ralph, University of Canberra, La Trobe University
Kaufmann, Philip R., Environmental Protection Agency
Ferraz, Silvio F. B., University of Sao Paulo
Zuanon, Jansen, National Institute of Amazonian Research
de Paula, Felipe R., Universidade Federal de Mato Grosso
Ferreira, Joice, Federal University of Amazonas
Thomson, James R., Federal University of Lavras
Lennox, Gareth D., Lancaster University
Dary, Eurizângela P., Universidade Federal de Mato Grosso
Röpke, Cristhiana P., Federal University of Amazonas
Pompeu, Paulo S., Federal University of Lavras
Gardner, Toby A., Stockholm Environment Institute
Published Sep 27, 2018 on Dryad.
Cite this dataset
Leal, Cecília G. et al. (2018). Data from: Is environmental legislation conserving tropical stream faunas? a large-scale assessment of local, riparian and catchment-scale influences on Amazonian stream fish [Dataset]. Dryad. https://doi.org/10.5061/dryad.d5k7p
1.Agricultural expansion and intensification are major threats to tropical biodiversity. In addition to the direct removal of native vegetation, agricultural expansion often elicits other human-induced disturbances, many of which are poorly addressed by existing environmental legislation and conservation programmes. This is particularly true for tropical freshwater systems, where there is considerable uncertainty about whether a legislative focus on protecting riparian vegetation is sufficient to conserve stream fauna.
2.To assess the extent to which stream fish are being effectively conserved in agricultural landscapes, we examined the spatial distribution of assemblages in river basins to identify the relative importance of human impacts at instream, riparian, and catchment scales, in shaping observed patterns. We used an extensive dataset on the ecological condition of 83 low-order streams distributed in three river basins in the eastern Brazilian Amazon.
3.We collected and identified 24,420 individual fish from 134 species. Multiplicative diversity partitioning revealed high levels of compositional dissimilarity (DS) among stream sites (DS = 0.74 to 0.83) and river basins (DS = 0.82), due mainly to turnover (77.8 to 81.8%) rather than nestedness. The highly heterogeneous fish faunas in small Amazonian streams underscore the vital importance of enacting measures to protect forests on private lands outside of public protected areas.
4.Instream habitat features explained more variability in fish assemblages (15-19%) than riparian (2-12%), catchment (4-13%) or natural covariates (4-11%). Although grouping species into functional guilds allowed us to explain up to 31% of their abundance (i.e. for nektonic herbivores), individual riparian- and catchment-scale predictor variables that are commonly a focus of environmental legislation explained very little of the observed variation (partial R2 values mostly < 5%).
5.Policy implications. Current rates of agricultural intensification and mechanisation in tropical landscapes are unprecedented, yet the existing legislative frameworks focusing on protecting riparian vegetation seem insufficient to conserve stream environments and their fish assemblages. To safeguard the species-rich freshwater biota of small Amazonian streams, conservation actions must shift towards managing whole basins and drainage networks, as well as agricultural practices in already-cleared land.
Fish species and functional guild composition, and environmental predictor variables from Amazonian streams
This is the complete dataset used in the manuscript. It includes fish species composition per stream site, functional guild composition per stream site and environmental predictor variables per stream site. For dataset descriptions see the file 'README.docx'.