Native woody vegetation in central Argentina: Classification of Chaco and Espinal forests

Question

What are the composition and spatial patterns of native woody plant communities in the southern Great Chaco and Espinal?

Location

Córdoba Province, central Argentina, an area of ca. 161,000 km².

Methods

We collected 351 geo‐referenced relevés representative of the geographic, topographic and ecological variation of the Chaco and Espinal woody vegetation in central Argentina. The relevés were classified into vegetation types using the hierarchical ISOPAM method. Forest and shrubland types were described on the basis of diagnostic species occurrences and their distribution in relation to environmental factors. A map of the actual vegetation derived from remote‐sensed images (Landsat) and field data was used to describe the current distribution and abundance of the different vegetation types.

Results

The classification of the 351 plots × 837 species matrix revealed two major clusters comprising seven woody vegetation types corresponding to Chaco lowland and mountain forests and shrublands, Espinal forests and edaphic vegetation. The most important gradients in woody vegetation types are related to elevation, temperature and rainfall variables.

Conclusions

Subtropical seasonally dry woody plant communities from the southern extreme of the Great Chaco and Espinal forests were described for the first time based on complete floristic data. Our results show that lowland Chaco native forests, as well as replacement communities, are still present in its southern distribution range and are well distinguishable from other vegetation types such as the Espinal and mountain forests. Overall, extensive Espinal forests have almost disappeared while Chaco vegetation is highly fragmented and degraded.

     

Factors influencing above‐ground and soil seed bank vegetation diversity at different scales in a quasi‐Mediterranean ecosystem

Questions

Are factors influencing plant diversity in a fire‐prone Mediterranean ecosystem of southeast Australia scale‐dependent?

Location

Heathy woodland, Otways region, Victoria, southeast Australia

Methods

We measured patterns of above‐ground and soil seed bank vegetation diversity and associated them with climatic, biotic, edaphic, topographic, spatial and disturbance factors at multiple scales (macro to micro) using linear mixed effect and generalized dissimilarity modelling.

Results

At the macro‐scale, we found species richness above‐ground best described by climatic factors and in the soil seed bank by disturbance factors. At the micro‐scale we found species richness best described above‐ground and in the soil seed bank by disturbance factors, in particular time‐since‐last‐fire. We found variance in macro‐scale β‐diversity (species turnover) best explained above‐ground by climatic and disturbance factors and in the soil seed bank by climatic and biotic factors.

Conclusions

Regional climatic gradients interact with edaphic factors and fire disturbance history at small spatial scales to influence species richness and turnover in the studied ecosystem. Current fire management regimes need to incorporate key climatic–disturbance–diversity interactions to maintain floristic diversity in the studied system.

     

Structural and functional mapping of geosigmeta in Atlantic coastal marshes (France) using a satellite time series

Geosynphytosociology deals with the study of combinations of vegetation series – or geosigmeta – within landscape. Its main advantage is to assess conservation status based on vegetation dynamics. However, this field-based approach has not been widely applied, because local surveys are not representative of spatio-temporal landscape complexity, which leads to uncertainties and errors for geosigmeta structural and functional mapping. In this context, satellite time series appear as relevant data for monitoring vegetation dynamics. This article aims to assess the contribution of an annual satellite time series for geosigmeta structural and functional mapping. The study area, which focuses on the French Atlantic coast (4630 km²), includes salt, brackish, sub-brackish and fresh marshes. A structural vegetation map was derived from the classification of an annual time series of 38 MODIS images validated with field surveys. The functional vegetation map was derived from the annual Integral of Normalized Difference Vegetation Index (NDVI-I), as an indicator of above-ground net primary production. Results show that geosigmeta were successfully mapped at a scale of 1:250,000 with an overall accuracy of 82.9%. The geosigmeta functional map highlights a strong gradient from the lowest NDVI-I values in salt marshes to the highest values in fresh marshes.