Dynamics and sustainable utilization of rangeland ecosystems in arid and semi-arid climates of southern Africa

Snyman, H.A.

doi:10.1006/jare.1998.0387

Cited by 136 publications

(150 citation statements)

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“…Changes in species composition are correlated with a decline in basal cover. Because of lower cover, larger runoff, and soil and nutrient loss, overall productivity declines with increasing degradation, a pattern that is widely found in grasslands Fouché 1991, 1993;Du Preez and Snyman 1993;Milchunas and Lauenroth 1993;O'Connor and Roux 1995;O'Connor and Bredenkamp 1997;Snyman 1998;McNaughton and others 1989;O'Connor and others 2001) and other semiarid vegetation types (Danckwerts and Nel 1989;O'Connor 1994;Hoffman and Ashwell 2001). This decline in production may be primarily caused by basal cover decline, and production per unit of basal cover may not change with degradation.…”

Section: Introductionmentioning

confidence: 97%

“…Mean aboveground net primary production (ANPP) of widely different arid and semiarid systems is strongly correlated with mean annual precipitation (for example, see Sneva and Hyder 1962;Noy-Meir 1973;Lauenroth 1979;McNaughton 1985;Le Houé rou and others 1988;Sala and others 1988a;Paruelo and others 1999). Additional factors that control ANPP include temperature (Christie 1981;Epstein and others 1997), evapotranspiration (Snyman 1998), soil water-holding capacity (Sala and others 1988a;Epstein and others 1997;Snyman 2000), nutrient availability (Chapin 1991;Du Preez and Snyman 1993), species composition (Milchunas and Lauenroth 1993), grazing (O'Connor and Roux 1995;Oesterheld and McNaughton 2000), and fire (Oesterheld and McNaughton 2000). Most of these analyses described the controls of the spatial variability of ANPP.…”

Section: Introductionmentioning

confidence: 99%

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Do Grasslands Have a Memory: Modeling Phytomass Production of a Semiarid South African Grassland

et al. 2004

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We analyzed data sets on phytomass production, basal cover, and monthly precipitation of a semiarid grassland in South Africa for good, medium, and poor rangeland condition (a) to investigate whether phytomass production per unit of basal cover differed among rangeland conditions, (b) to quantify the time scales of a carryover effect from production in previous months, and (c) to construct predictive models for monthly phytomass. Finally, we applied the best models to a 73-year data set of monthly precipitation data to study the long-term variability of grassland production. Our results showed that mean phytomass production per unit of basal cover did not vary significantly among the rangeland conditions-that is, vegetated patches in degraded grassland have approximately the same production as vegetated patches in grassland in good condition. Consequently, the stark decline in production with increasing degradation is a first-order effect of reduced basal area. Current-year precipitation accounted for 64%, 62%, and 36% of the interannual variation in phytomass production for good, medium, and poor condition, respectively. We found that 61%, 68%, and 33%, respectively, of the unexplained variation is related to a memory index that combines mean monthly temperature and a memory of past precipitations. We found a carryover effect in production from the previous 4 years for grassland in good condition and from the previous 1 or 3S month for grassland in medium and poor condition. The memory effect amplified the response of production to changes in precipitation due to alternation of prolonged periods of dry or wet years/months at the time scale of the memory. The interannual variability in phytomass production per unit basal cover (coefficient of variation [CV] ϭ 0.42-0.50 for our 73-year prediction, CV ϭ 0.57-0.71 for the 19-year data) was greater than the corresponding temporal variability in seasonal rainfall (CV ϭ 0.29).

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Do Grasslands Have a Memory: Modeling Phytomass Production of a Semiarid South African Grassland

et al. 2004

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“…Frequently, terrestrial ecosystem diversity is being reduced by replacing indigenous flora with a few crops. The ecological consequences of such transitions have been addressed in several studies focusing on land degradation [1,2,3], losses of macrobiodiversity [4,5], nutrient exhaustion in soils [3], sustainability [6,7] and restoration [8]. Soil microorganisms, including protozoa, fungi, bacteria and archaea, are essential for the proper functioning and sustainability of ecosystems [9,10,11].…”

Section: Introductionmentioning

confidence: 99%

- Discussion on Sustainable Water Technologies for Peri-Urban Areas of Mexico City: Balancing Urbanization and Environmental Conservation

2014

Agricultural Resource Use and Management

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Natural scrublands in semi-arid deserts are increasingly being converted into fields. This results in losses of characteristic flora and fauna, and may also affect microbial diversity. In the present study, the long-term effect (50 years) of such a transition on soil bacterial communities was explored at two sites typical of semi-arid deserts. Comparisons were made between soil samples from alfalfa fields and the adjacent scrublands by two complementary methods based on 16S rRNA gene fragments amplified from total community DNA. Denaturing gradient gel electrophoresis (DGGE) analyses revealed significant effects of the transition on community composition of Bacteria, Actinobacteria, Alpha-and Betaproteobacteria at both sites. PhyloChip hybridization analysis uncovered that the transition negatively affected taxa such as Acidobacteria, Chloroflexi, Acidimicrobiales, Rubrobacterales, Deltaproteobacteria and Clostridia, while Alpha-, Beta-and Gammaproteobacteria, Bacteroidetes and Actinobacteria increased in abundance. Redundancy analysis suggested that the community composition of phyla responding to agricultural use (except for Spirochaetes) correlated with soil parameters that were significantly different between the agricultural and scrubland soil. The arable soils were lower in organic matter and phosphate concentration, and higher in salinity. The variation in the bacterial community composition was higher in soils from scrubland than from agriculture, as revealed by DGGE and PhyloChip analyses, suggesting reduced beta diversity due to agricultural practices. The long-term use for agriculture resulted in profound changes in the bacterial community and physicochemical characteristics of former scrublands, which may irreversibly affect the natural soil ecosystem.

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“…Niederschläge und der Ressourcenverfügbarkeit geprägten Systems zur Degradation von Weideland geführt (Snyman 1998). Die Auswirkungen der Degradation infolge von Überbeweidung oder nicht angepasster Beweidung sind sowohl im bio-physikalischen als auch im sozio-ökonomischen Kontext zu verstehen (Vogt et al 2011; Domptail in Artikel 2;…”

Section: Nutzungsmuster Haben Jedoch In Weiten Teilen Dieses Von Hoheunclassified

Impact of pastoral land use on central Namibian savanna vegetation - Methods for indictor development and perspectives for their application

Wesuls¹

2011

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Dynamics and sustainable utilization of rangeland ecosystems in arid and semi-arid climates of southern Africa

Cited by 136 publications

References 86 publications

Do Grasslands Have a Memory: Modeling Phytomass Production of a Semiarid South African Grassland

Do Grasslands Have a Memory: Modeling Phytomass Production of a Semiarid South African Grassland

- Discussion on Sustainable Water Technologies for Peri-Urban Areas of Mexico City: Balancing Urbanization and Environmental Conservation

Impact of pastoral land use on central Namibian savanna vegetation - Methods for indictor development and perspectives for their application

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