Functional groups based on leaf physiology: are they spatially and temporally robust?
The functional grouping concept, which suggests that complexity in ecosystem function can be simplified by grouping species with similar responses, was tested in the Florida scrub habitat. Functional groups were identified based on how species regulate exchange of carbon and water with the atmosphere as indicated by both instantaneous gas exchange measurements and integrated measures of function (%N, delta13C, delta15N, C:N ratio) in fire-maintained Florida scrub, which was considered the natural state for scrub habitat. Using cluster analysis, five distinct physiologically based functional groups were identified in the fire-maintained scrub and were determined to be distinct clusters and not just arbitrary divisions in a continuous distribution by the non-parametric multivariate analysis of similarities (ANOSIM; R=0.649, P=0.005). These functional groups were tested for robustness spatially, temporally, and with management regime using ANOSIM. The physiological functional groups remained distinct clusters in this broader array of sites (R=0.794, P=0.001) and were not altered by plot differences, primarily, water table depth (R=-0.115, P=0.893) or by the three different management regimes: prescribed burn, mechanically treated and burned, and fire-suppressed (R=0.018, P=0.349). The physiological groupings also remained robust between the two climatically different years, with 1999 being a much wetter year than 2000 (R=-0.027, P=0.725). Easy-to-measure morphological characteristics, if they indicate the same functional groups, would be more practical for scaling and modeling ecosystem processes than detailed gas exchange measurements; therefore, we tested a variety of morphological characteristics as functional indicators. A combination of non-parametric multivariate techniques were used to compare the ability of life form, leaf thickness (LT), and specific leaf area (SLA) classifications to identify the physiologically based functional groups. Life form classifications (ANOSIM; R=0.629, P=0.001) were able to depict the physiological groupings more adequately than either SLA (ANOSIM; R=0.426, P=0.001) or LT (ANOSIM; R=0.344, P=0.001). The ability of life forms to depict the physiological groupings was improved by separating the parasitic Ximenia americana from the shrub category (ANOSIM; R=0.794, P=0.001). Therefore, a life form classification including parasites was determined to be a good indicator of the physiological processes of scrub species and would be a useful method of grouping species for scaling physiological processes to the ecosystem level.
Foster
Tammy E
TE
Department of Biology, University of South Florida, Tampa, FL, 33620, USA. fostete@kscems.ksc.nasa.gov
Brooks
J Renée
JR
D002244:Carbon / Q000378:metabolism; D016000:Cluster Analysis; D017753:Ecosystem; D005431:Florida; D015999:Multivariate Analysis; D009584:Nitrogen / Q000378:metabolism; D018515:Plant Leaves / Q000033:anatomy & histology / Q000145:classification* / Q000502:physiology*; D018521:Plant Physiological Phenomena; D013045:Species Specificity
D002244:Carbon; D009584:Nitrogen