Regional scale relationships between structure and functioning. The case of the Patagonian steppes.

PARUELO, JM; GOLLUSCIO, RA; GUERSCHMAN, JP; CESA, A; JOUVE, VV; GARBULSKY, MF

GLOBAL ECOLOGY AND BIOGEOGRAPHY

Blackwell

Año: 2004 vol. 13 p. 385 - 395

0960-7447

Aims: 1. To characterize ecosystem functioning by focusing on Aboveground Net Primary Production (ANPP) and, 2. to relate the spatial heterogeneity of both functional and structural attributes to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location:  Western portion of the Patagonian steppes in Argentina (39º 30´ S to 45º 27´ S). Methods: We used remotely sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (Aboveground Net Primary Production and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP.  We built an empirical relationship between the Landsat TM derived Normalized Vegetation Difference Index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PC)). Results:  PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes.  Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semi-deserts, latitude and, to a lesser extent, the number of PCs within an 8x8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8x8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes.  Conclusions: Our results suggest that the spatial patterns of ecosystem functioning, described from ANPP and its temporal variability, result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification.