• Amazon;
  • climate change;
  • Diplodia mutila;
  • Iriartea deltoidea;
  • Janzen–Connell;
  • plant–climate interactions;
  • plant pathogens;
  • spatial pattern;
  • tree recruitment


1. Climate change predictions in the Amazon have largely focused on carbon–water relations, while the impacts of increased air temperature and reduced precipitation on host–pathogen relationships have not been extensively explored. These relationships are known to affect recruitment of many Amazonian plant species.

2. Host–pathogen relationships are well suited to a dynamical analysis of the effects of climate change due to the direct linkages between pathogen behaviour and abiotic factors such as temperature and rainfall.

3. Seedlings of the palm Iriartea deltoidea experience significant mortality due to infection by the fungus Diplodia mutila. This host–pathogen interaction was examined by combining a semi-analytical model with field data illustrating the temperature sensitivity of D. mutila reproductive rates and I. deltoidea seedling mortality in response to infection.

4. The data–model combination shows that projected climatic shifts in rainfall and temperature for the Amazon region will tend to reduce recruitment by altering pathogen activity and reducing palm fecundity. The magnitude of the reduction is sensitive to the details of the epidemiology of the D. mutila–I. deltoidea host–pathogen system, and ranges from 10% to 56% under plausible scenarios.

5. Although considerable uncertainty remains, the proposed model provides a blueprint for research on one aspect of ecosystem change in future climate models.

6.Synthesis. The study illustrates the potential for ecosystem responses to climate change, which can be investigated through tractable models simple enough to assimilate into climate modelling frameworks. Particular environmental sensitivities in fungal dynamics are identified. The implications of combined plant physiological stress and enhanced pathogenic activity under future climate scenarios are highlighted as critical issues for projecting forest response.