Divergent vegetation response to increasing grazing pressure in arid and semi-arid rangelands in Argentina

doi:10.1016/j.jaridl.2026.01.007

Journal of Arid Land

2026, Vol. 18

Issue (1): 84-100 DOI: 10.1016/j.jaridl.2026.01.007 CSTR: 32276.14.JAL.20250074

Research article

Divergent vegetation response to increasing grazing pressure in arid and semi-arid rangelands in Argentina

Dianela Alejandra CALVO¹, Juan José GAITÁN²^,³, Juan Manuel ZEBERIO¹, Ana Inés CASALINI⁴, Guadalupe PETER¹^,²^,^*(

)

¹Universidad Nacional de Río Negro, Sede Atlántica, CEANPa, Viedma 8500, Argentina
²Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires 1425, Argentina
³Universidad Nacional de Luján, Luján 6700, Argentina
⁴Wildlife Conservation Society, Buenos Aires 1005, Argentina

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Abstract

The connection between climatic factors and grazing is essential for maintaining ecosystem function and vegetation productivity. This study examined the impact of grazing intensity on vegetation across a broad climatic gradient spanning the Espinal, Argentine Low Monte, and Patagonian Steppe ecoregions of Argentina. The research was carried out at eight sampling sites with radial grazing gradients generated around artificial water sources (piospheres), exhibiting two contrasting response patterns of vegetation to grazing pressure. One of the response patterns shows a typical vegetation response to grazing that the vegetation productivity increases with the distance to the water sources (decreasing grazing intensity). The second pattern is found in drier regions, where vegetation presents an inverse productivity response that vegetation productivity is higher near water sources (high grazing intensity) due to increased shrub cover. Vegetation productivity was measured using the Normalized Difference Vegetation Index (NDVI). Vegetation patch structure and cover were determined for each site with high, medium, and low grazing intensities. Results indicated that shrub cover is the primary driver of vegetation productivity, showing contrasting responses to grazing intensity between the two identified patterns. While NDVI proved to be a reliable proxy for shrub cover and total vegetation cover (R²>0.70), it failed to reflect grass cover dynamics. Furthermore, mean annual temperature was more strongly correlated with vegetation cover changes, while grazing intensity significantly altered vegetation patch structure and soil cover distribution. Specifically, in drier regions, high grazing intensity led to larger patches while, in wetter regions, it led to smaller patches (fragmentation). Shrubs, with their deeper roots and drought tolerance, were less preferred and more resistant to grazing in arid environments and thrived under grazing pressure in these arid conditions. Our results underscored the need for adaptive management strategies in grazing systems. Traditional approaches may require significant adjustments, as the efficacy of management hinges on the interplay of specific climatic conditions and the varied responses of vegetation. Furthermore, effective conservation efforts should prioritize the recognition and protection of shrubs given their critical contribution to ecosystem function and biodiversity. Ultimately, this research provides a valuable framework to understand the complex dynamics between grazing and vegetation in arid and semi-arid environments, highlighting that sustainable grazing practices should be tailored to account for both climatic variables and the unique characteristics of different plant communities.

Key words： grazing intensity vegetation productivity piospheres shrub encroachment climate change Patagonian Steppe

Received: 01 March 2025 Published: 31 January 2026

Corresponding Authors: ^*Guadalupe PETER (E-mail: gpeter@unrn.edu.ar)

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	Dianela Alejandra CALVO
	Juan José GAITÁN
	Juan Manuel ZEBERIO
	Ana Inés CASALINI
	Guadalupe PETER

Cite this article:

Dianela Alejandra CALVO, Juan José GAITÁN, Juan Manuel ZEBERIO, Ana Inés CASALINI, Guadalupe PETER. Divergent vegetation response to increasing grazing pressure in arid and semi-arid rangelands in Argentina. Journal of Arid Land, 2026, 18(1): 84-100.

URL:

http://jal.xjegi.com/10.1016/j.jaridl.2026.01.007 OR http://jal.xjegi.com/Y2026/V18/I1/84

Fig. 1 Location of the study area and distribution of the sampling sites (piospheres)

Table 1 Details of the sampling sites

Fig. 2 Graphical representation of grazing intensity versus distance to the artificial water source and the corresponding transect design. HGI, high grazing intensity; MGI, medium grazing intensity; LGI, low grazing intensity.

Fig. 3 Graphical representation of patch intercept sampling. CC, compound closed; SC, simple closed; CO, compound open; SO, simple open.

Fig. 4 Variation in the cover of each functional group and soil cover type among different grazing intensities in piospheres under Pattern 1 (a) and Pattern 2 (b). Pattern 1 showed an increase in Normalized Difference Vegetation Index (NDVI) with distance from the artificial water source, indicating a negative response of vegetation productivity to the pressure exerted by livestock; Pattern 2 showed an inverse response with a decrease in NDVI as the distance to the water source increased. Different letters indicate statistically significant differences (P<0.050) among intensities for the cover of each functional group and soil cover type. Bars are standard error. Significances marked with ^* belong to a statistically distinct group.

Table 2 Statistics of vegetation and soil cover at three grazing intensities under two vegetation response patterns

Fig. 5 Relationship of NDVI with total vegetation cover, shrub cover, and grass cover

Fig. 6 Principal component analysis (PCA) of grazing intensities in the space defined by patch structure variables under Pattern 1 (a) and Pattern 2 (b). PC, principal component.

Fig. 7 Relationships between the CovD of different vegetation types with AI (a), MAP (b), PET (c), and MAT (d). AI, aridity index; MAP, mean annual precipitation; PET, potential evapotranspiration; MAT, mean annual temperature. CovDS, CovDG, and CovDT indicate the difference in cover (CovD) determined for shrubs, grasses, and total vegetation, respectively.


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