Ensemble forecasting shifts in climatically suitable areas for Tropidacris cristata (Orthoptera: Acridoidea: Romaleidae)
Article first published online: 31 MAR 2010
© 2010 The Authors. Journal compilation © 2010 The Royal Entomological Society
Insect Conservation and Diversity
Volume 3, Issue 3, pages 213–221, August 2010
How to Cite
DINIZ-FILHO, J. A. F., NABOUT, J. C., BINI, L. M., LOYOLA, R. D., RANGEL, T. F., NOGUES-BRAVO, D. and ARAÚJO, M. B. (2010), Ensemble forecasting shifts in climatically suitable areas for Tropidacris cristata (Orthoptera: Acridoidea: Romaleidae). Insect Conservation and Diversity, 3: 213–221. doi: 10.1111/j.1752-4598.2010.00090.x
- Issue published online: 7 JUL 2010
- Article first published online: 31 MAR 2010
- Accepted 19 February 2010 First published online 1 April 2010 Editor: Raphael K. Didham Associate editor: Robert Ewers
- Climate change;
- ensemble forecasting;
- niche models;
- variance partition
Abstract. 1. The effects of climate change on species’ ranges have been usually inferred using niche-based models creating bioclimatic envelopes that are projected into geographical space. Here, we apply an ensemble forecasting approach for niche models in the Neotropical grasshopper Tropidacris cristata (Acridoidea: Romaleidae). A novel protocol was used to partition and map the variation in modelled ranges due to niche models, Atmosphere-Ocean Global Circulation Models (AOGCM), and emission scenarios.
2. We used 112 records of T. cristata and four climatic variables to model the species’ niche using five niche models, four AOGCMs and two emission scenarios. Combinations of these effects (50 cross-validations for each of the 15 subsets of the environmental variables) were used to estimate and map the occurrence frequencies (EOF) across all analyses. A three-way anova was used to partition and map the sources of variation.
3. The projections for 2080 show that the range edges of the species are likely to remain approximately constant, but shifts in maximum EOF are forecasted. Suitable climatic conditions tend to disappear from central areas of Amazon, although this depends on the AOGCM and the niche model. Most of the variability around the mapped consensus projections came from using distinct niche models and AOGCMs.
4. Although our analyses are restricted to a single species, they provide new conceptual and methodological insights in the application of ensemble forecasting and variance partition approaches to understand the origins of uncertainty in studies assessing species responses to climate change in the tropics.