Artificial neural networks;
Benthic invertebrates;
Equitability;
New Zealand;
Spatial scales;
Species richness;
Taieri river;
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摘要:
Although many studies have investigated the influence of environmental patterns on local stream invertebrate diversity, there has been little consistency in reported relationships between diversity and particular environmental variables. Here we test the hypothesis that local stream invertebrate diversity is determined by a combination of factors occurring at multiple spatial scales. We developed predictive models relating invertebrate diversity (species richness and equitability) to environmental variables collected at various spatial scales (bedform, reach and catchment, respectively) using data from 97 sampling sites dispersed throughout the Taieri River drainage in New Zealand. Models based on an individual scale of perception (bedform, reach or catchment) were not able to match predictions to observations (r < 0.26, P > 0.01, between observed and predicted equitability and species richness). In contrast, models incorporating all three scales simultaneously were highly significant (P < 0.01; r = 0.55 and 0.64, between observed and predicted equitability and species richness, respectively). The most influential variables for both richness and equitability were median particle size at the bedform scale, adjacent land use at the reach scale, and relief ratio at the catchment scale. Our findings suggest that patterns observed in local assemblages are not determined solely by local mechanisms acting within assemblages, but also result from processes operating at larger spatial scales. The integration of different spatial scales may be the key to increasing model predictability and our understanding of the factors that determine local biodiversity.
机构:
Univ Fed Rio de Janeiro, Dept Invertebrados, Museu Nacl, Lab Aracnol, BR-20940040 Rio De Janeiro, RJ, BrazilUniv Fed Rio de Janeiro, Dept Invertebrados, Museu Nacl, Lab Aracnol, BR-20940040 Rio De Janeiro, RJ, Brazil
Mugnai, R.
Messana, G.
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机构:
CNR, Ist Studio Ecosistemi, I-50019 Sesto Fiorentino, ItalyUniv Fed Rio de Janeiro, Dept Invertebrados, Museu Nacl, Lab Aracnol, BR-20940040 Rio De Janeiro, RJ, Brazil
Messana, G.
Di Lorenzo, T.
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机构:
CNR, Ist Studio Ecosistemi, I-50019 Sesto Fiorentino, ItalyUniv Fed Rio de Janeiro, Dept Invertebrados, Museu Nacl, Lab Aracnol, BR-20940040 Rio De Janeiro, RJ, Brazil
机构:
Bur Land Management, US Dept Interior, Aquat Monitoring Ctr, Logan, UT 84322 USABur Land Management, US Dept Interior, Aquat Monitoring Ctr, Logan, UT 84322 USA
Vinson, MR
Hawkins, CP
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机构:Bur Land Management, US Dept Interior, Aquat Monitoring Ctr, Logan, UT 84322 USA