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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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Response of plant aggregations to management and soil conditions in the grassland (A) and in the savanna biome (B).For each plant aggregation, bars denote the proportion of explained variance (given as effect sizes, η2) in best-fitting linear models, associated with biome-specific principal components and land tenure. Parameters are ordered by their effect sizes, starting with the grazing-related principal component. Arrows facing upwards indicate a positive response to increased grazing, and arrows facing downwards indicate a negative response. Note that negative or positive responses to grazing cannot be assigned to ordination axes. DCA 1 = plot scores on first DCA axis. For abbreviations of PFTs, refer to Table 2.
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pone-0104672-g003: Response of plant aggregations to management and soil conditions in the grassland (A) and in the savanna biome (B).For each plant aggregation, bars denote the proportion of explained variance (given as effect sizes, η2) in best-fitting linear models, associated with biome-specific principal components and land tenure. Parameters are ordered by their effect sizes, starting with the grazing-related principal component. Arrows facing upwards indicate a positive response to increased grazing, and arrows facing downwards indicate a negative response. Note that negative or positive responses to grazing cannot be assigned to ordination axes. DCA 1 = plot scores on first DCA axis. For abbreviations of PFTs, refer to Table 2.

Mentions: In the grassland biome, the grazing-related PC explained the highest proportion of species turnover along the first axis of the two ordination procedures (DCA 1: 43%, NMDS 1: 29%; see Figure 3), followed by a variable group reflecting mineral nutrients (PC 2) and a PC reflecting changes in silt and P content of the topsoil (PC 5; see Tables S2 and S3 for details of final linear models). Unexpectedly, the most important predictor for species turnover in the savanna was not grazing pressure (PC 2; explained variance only 6%) but a gradient in mineral nutrients (PC 3; explained variance 25%). Other soil parameters (PC 5 related to topsoil clay, and PC 4 to silt and Fe content) were of minor importance. In both biomes, community composition in the savanna (DCA 1) was not explained by differences in land tenure. To substantiate our claim that certain ordination axes reflected a grazing gradient, we performed correlations between these axes and reciprocal distances to the water point, as this estimate reflects grazing intensity better than distance [56]. In the grassland, both DCA 1 and NMDS 1 showed a strong positive correlation to reciprocal distance (p<0.001). Coefficients of determination (r2) indicated that reciprocal distance explained 23.4 % of variation in DCA 1 and 21.9 % of variation in NMDS 1. In the savanna, a strong negative correlation was found between NMDS 2 and reciprocal distance (explained variance 53.6 %; p<0.001).


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)

Response of plant aggregations to management and soil conditions in the grassland (A) and in the savanna biome (B).For each plant aggregation, bars denote the proportion of explained variance (given as effect sizes, η2) in best-fitting linear models, associated with biome-specific principal components and land tenure. Parameters are ordered by their effect sizes, starting with the grazing-related principal component. Arrows facing upwards indicate a positive response to increased grazing, and arrows facing downwards indicate a negative response. Note that negative or positive responses to grazing cannot be assigned to ordination axes. DCA 1 = plot scores on first DCA axis. For abbreviations of PFTs, refer to Table 2.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0104672-g003: Response of plant aggregations to management and soil conditions in the grassland (A) and in the savanna biome (B).For each plant aggregation, bars denote the proportion of explained variance (given as effect sizes, η2) in best-fitting linear models, associated with biome-specific principal components and land tenure. Parameters are ordered by their effect sizes, starting with the grazing-related principal component. Arrows facing upwards indicate a positive response to increased grazing, and arrows facing downwards indicate a negative response. Note that negative or positive responses to grazing cannot be assigned to ordination axes. DCA 1 = plot scores on first DCA axis. For abbreviations of PFTs, refer to Table 2.
Mentions: In the grassland biome, the grazing-related PC explained the highest proportion of species turnover along the first axis of the two ordination procedures (DCA 1: 43%, NMDS 1: 29%; see Figure 3), followed by a variable group reflecting mineral nutrients (PC 2) and a PC reflecting changes in silt and P content of the topsoil (PC 5; see Tables S2 and S3 for details of final linear models). Unexpectedly, the most important predictor for species turnover in the savanna was not grazing pressure (PC 2; explained variance only 6%) but a gradient in mineral nutrients (PC 3; explained variance 25%). Other soil parameters (PC 5 related to topsoil clay, and PC 4 to silt and Fe content) were of minor importance. In both biomes, community composition in the savanna (DCA 1) was not explained by differences in land tenure. To substantiate our claim that certain ordination axes reflected a grazing gradient, we performed correlations between these axes and reciprocal distances to the water point, as this estimate reflects grazing intensity better than distance [56]. In the grassland, both DCA 1 and NMDS 1 showed a strong positive correlation to reciprocal distance (p<0.001). Coefficients of determination (r2) indicated that reciprocal distance explained 23.4 % of variation in DCA 1 and 21.9 % of variation in NMDS 1. In the savanna, a strong negative correlation was found between NMDS 2 and reciprocal distance (explained variance 53.6 %; p<0.001).

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