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Are there consistent grazing indicators in Drylands? Testing plant functional types of various complexity in South Africa's Grassland and Savanna Biomes.

Linstädter A, Schellberg J, Brüser K, Moreno García CA, Oomen RJ, du Preez CC, Ruppert JC, Ewert F - PLoS ONE (2014)

Bottom Line: Traits relate to life history, growth form and leaf width.We found no response consistency, but biome-specific optimum aggregation levels.Its methodological approach may also be useful for identifying ecological indicators in other ecosystems.

View Article: PubMed Central - PubMed

Affiliation: Range Ecology and Range Management Group, Botanical Institute, University of Cologne, Cologne, Germany; Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.

ABSTRACT
Despite our growing knowledge on plants' functional responses to grazing, there is no consensus if an optimum level of functional aggregation exists for detecting grazing effects in drylands. With a comparative approach we searched for plant functional types (PFTs) with a consistent response to grazing across two areas differing in climatic aridity, situated in South Africa's grassland and savanna biomes. We aggregated herbaceous species into PFTs, using hierarchical combinations of traits (from single- to three-trait PFTs). Traits relate to life history, growth form and leaf width. We first confirmed that soil and grazing gradients were largely independent from each other, and then searched in each biome for PFTs with a sensitive response to grazing, avoiding confounding with soil conditions. We found no response consistency, but biome-specific optimum aggregation levels. Three-trait PFTs (e.g. broad-leaved perennial grasses) and two-trait PFTs (e.g. perennial grasses) performed best as indicators of grazing effects in the semi-arid grassland and in the arid savanna biome, respectively. Some PFTs increased with grazing pressure in the grassland, but decreased in the savanna. We applied biome-specific grazing indicators to evaluate if differences in grazing management related to land tenure (communal versus freehold) had effects on vegetation. Tenure effects were small, which we mainly attributed to large variability in grazing pressure across farms. We conclude that the striking lack of generalizable PFT responses to grazing is due to a convergence of aridity and grazing effects, and unlikely to be overcome by more refined classification approaches. Hence, PFTs with an opposite response to grazing in the two biomes rather have a unimodal response along a gradient of additive forces of aridity and grazing. The study advocates for hierarchical trait combinations to identify localized indicator sets for grazing effects. Its methodological approach may also be useful for identifying ecological indicators in other ecosystems.

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Ordination diagrams of herbaceous community composition.Ordinations are based on two alternative procedures (A, B: detrended correspondence analysis, DCA; and C, D: non-metric multidimensional scaling, NMDS). They visualize differences between piosphere plots and pasture plots on commercial farms and communal farms in South Africa’s grassland biome (A, C) and savanna biome (B, D). Close plots feature a similar species composition, remote plots are more dissimilar. Interpretation of ordination axes follows final linear models with PCA-derived composite variables as predictors. In the grassland biome, a gradient of increasing grazing pressure underlies species turnover along the first ordination axes; in the savanna, it is a gradient of mineral nutrient content in the topsoil (0–20 cm). Note that we refrained from interpreting the second DCA axes due to concerns about their interpretability.
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pone-0104672-g002: Ordination diagrams of herbaceous community composition.Ordinations are based on two alternative procedures (A, B: detrended correspondence analysis, DCA; and C, D: non-metric multidimensional scaling, NMDS). They visualize differences between piosphere plots and pasture plots on commercial farms and communal farms in South Africa’s grassland biome (A, C) and savanna biome (B, D). Close plots feature a similar species composition, remote plots are more dissimilar. Interpretation of ordination axes follows final linear models with PCA-derived composite variables as predictors. In the grassland biome, a gradient of increasing grazing pressure underlies species turnover along the first ordination axes; in the savanna, it is a gradient of mineral nutrient content in the topsoil (0–20 cm). Note that we refrained from interpreting the second DCA axes due to concerns about their interpretability.

Mentions: In both biomes, piosphere and pasture plots from the two tenure systems were not clearly separated in the ordination spaces (Figure 2). Both ordination methods rendered essentially similar results. They agreed for the savanna that, along the main ordination axes (DCA 1 and NMDS 1), variation among piosphere plots was higher than that among pasture plots (Figure 2B and 2D). In congruence to our expectations, this reflected steeper environmental gradients close to water points. However, our expectations were not met for the grassland, where variation among pasture plots was also high (Figure 2A and 2C).


Are there consistent grazing indicators in Drylands? Testing plant functional types of various complexity in South Africa's Grassland and Savanna Biomes.

Linstädter A, Schellberg J, Brüser K, Moreno García CA, Oomen RJ, du Preez CC, Ruppert JC, Ewert F - PLoS ONE (2014)

Ordination diagrams of herbaceous community composition.Ordinations are based on two alternative procedures (A, B: detrended correspondence analysis, DCA; and C, D: non-metric multidimensional scaling, NMDS). They visualize differences between piosphere plots and pasture plots on commercial farms and communal farms in South Africa’s grassland biome (A, C) and savanna biome (B, D). Close plots feature a similar species composition, remote plots are more dissimilar. Interpretation of ordination axes follows final linear models with PCA-derived composite variables as predictors. In the grassland biome, a gradient of increasing grazing pressure underlies species turnover along the first ordination axes; in the savanna, it is a gradient of mineral nutrient content in the topsoil (0–20 cm). Note that we refrained from interpreting the second DCA axes due to concerns about their interpretability.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4128714&req=5

pone-0104672-g002: Ordination diagrams of herbaceous community composition.Ordinations are based on two alternative procedures (A, B: detrended correspondence analysis, DCA; and C, D: non-metric multidimensional scaling, NMDS). They visualize differences between piosphere plots and pasture plots on commercial farms and communal farms in South Africa’s grassland biome (A, C) and savanna biome (B, D). Close plots feature a similar species composition, remote plots are more dissimilar. Interpretation of ordination axes follows final linear models with PCA-derived composite variables as predictors. In the grassland biome, a gradient of increasing grazing pressure underlies species turnover along the first ordination axes; in the savanna, it is a gradient of mineral nutrient content in the topsoil (0–20 cm). Note that we refrained from interpreting the second DCA axes due to concerns about their interpretability.
Mentions: In both biomes, piosphere and pasture plots from the two tenure systems were not clearly separated in the ordination spaces (Figure 2). Both ordination methods rendered essentially similar results. They agreed for the savanna that, along the main ordination axes (DCA 1 and NMDS 1), variation among piosphere plots was higher than that among pasture plots (Figure 2B and 2D). In congruence to our expectations, this reflected steeper environmental gradients close to water points. However, our expectations were not met for the grassland, where variation among pasture plots was also high (Figure 2A and 2C).

Bottom Line: Traits relate to life history, growth form and leaf width.We found no response consistency, but biome-specific optimum aggregation levels.Its methodological approach may also be useful for identifying ecological indicators in other ecosystems.

View Article: PubMed Central - PubMed

Affiliation: Range Ecology and Range Management Group, Botanical Institute, University of Cologne, Cologne, Germany; Institute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany.

ABSTRACT
Despite our growing knowledge on plants' functional responses to grazing, there is no consensus if an optimum level of functional aggregation exists for detecting grazing effects in drylands. With a comparative approach we searched for plant functional types (PFTs) with a consistent response to grazing across two areas differing in climatic aridity, situated in South Africa's grassland and savanna biomes. We aggregated herbaceous species into PFTs, using hierarchical combinations of traits (from single- to three-trait PFTs). Traits relate to life history, growth form and leaf width. We first confirmed that soil and grazing gradients were largely independent from each other, and then searched in each biome for PFTs with a sensitive response to grazing, avoiding confounding with soil conditions. We found no response consistency, but biome-specific optimum aggregation levels. Three-trait PFTs (e.g. broad-leaved perennial grasses) and two-trait PFTs (e.g. perennial grasses) performed best as indicators of grazing effects in the semi-arid grassland and in the arid savanna biome, respectively. Some PFTs increased with grazing pressure in the grassland, but decreased in the savanna. We applied biome-specific grazing indicators to evaluate if differences in grazing management related to land tenure (communal versus freehold) had effects on vegetation. Tenure effects were small, which we mainly attributed to large variability in grazing pressure across farms. We conclude that the striking lack of generalizable PFT responses to grazing is due to a convergence of aridity and grazing effects, and unlikely to be overcome by more refined classification approaches. Hence, PFTs with an opposite response to grazing in the two biomes rather have a unimodal response along a gradient of additive forces of aridity and grazing. The study advocates for hierarchical trait combinations to identify localized indicator sets for grazing effects. Its methodological approach may also be useful for identifying ecological indicators in other ecosystems.

Show MeSH
Related in: MedlinePlus