COS 57-10
Functional trait-based research in agroecology: Progress and prospects

Wednesday, August 12, 2015: 11:10 AM
301, Baltimore Convention Center
Adam R. Martin, Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
Marney E. Isaac, Department of Physical and Environmental Science, University of Toronto-Scarborough, Toronto, ON, Canada

In recent years there has been considerable expansion in agroecological research, but many argue this discipline could further benefit from theoretical advances that provide appropriate predictive capability, or allow for the development and testing of generalized hypotheses on crop responses to environmental change. Studies focused on plant functional traits may provide such a framework, but to date this approach – which has been critical for understanding ecological patterns and processes in natural plant communities – has not been widely adopted in agroecological research, policy, or practice. While there is a long history of evaluating the causes and consequences of variation in crop “agronomic” or “domestication” traits, few agroecological studies have focused on functional plant traits as commonly envisioned in the ecology or evolutionary biology literature. Here, we concisely review the potential applications of functional-trait based approaches to agroecological research, illustrating its strengths and applications through our field studies on leaf trait variation in shade-coffee agroforestry systems in Costa Rica and Nicaragua. Through meta-analyses of global functional trait databases, we also highlight knowledge key gaps that when addressed, may provide new insights into agroecological dynamics across multiple spatial and temporal scales.


Our analyses show that leaf trait syndromes (i.e. the “leaf economics spectrum” (LES)) commonly used to describe functional variation among species in natural systems, also describe functional variation among coffee plants at farm and regional scales. Moreover, we find that variation in coffee LES traits is significantly correlated with key management goals, namely plant-level reproductive output. At fine spatial scales (i.e. farm level), LES traits are best predicted by local environmental conditions (i.e. light availability), while across regional scales temperature and precipitation best explain intraspecific variation in coffee LES traits. Evaluating similar questions in other crops might be facilitated by meta-analyses of large functional trait databases, most notably the TRY database. However we found that in TRY, LES trait data is available for less than 20 of the world’s 79 most widespread crop species; the crops that are represented are generally associated with ≤ 3 individual observations for a given trait. While there are novel contributions that can be made by functional-trait based approaches to agroecological research, our results suggest that that more field studies on crop functional trait variation, coupled with consolidation of crop trait data into global traits databases, are key in advancing trait-based agroecology.