Rainfed Farming Systems in South Africa

Hardy, M.B.; Dziba, Luthando; Kilian, Willem; Tolmay, J.P.C.

doi:10.1007/978-1-4020-9132-2_16

Cited by 10 publications

(12 citation statements)

References 8 publications

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“…Rainfall is a crucial determinant for crop growth, especially in areas where no irrigation practices are conducted and rainfed agriculture is dominating, which accounts for most parts of South Africa [73]. Detection of different responses to rainfall on grassland and communal and commercial cropland as well as analysis of correlation between rainfall and vegetation productivity and vegetation condition were conducted to detect areas according to their rainfall-vegetation dependency.…”

Section: Precipitation and Vegetation-how Close Is The Link?mentioning

confidence: 99%

Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

et al. 2017

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Eastern Cape Province in South Africa has experienced extreme drought events during the last decade. In South Africa, different land management systems exist belonging to two different land tenure classes: commercial large scale farming and communal small-scale subsistence farming. Communal lands are often reported to be affected by land degradation and drought events among others considered as trigger for this process. Against this background, we analyzed vegetation response to drought in different land management and land tenure systems through assessing vegetation productivity trends and monitoring the intensity, frequency and distribution of the drought hazard in grasslands and communal and commercial croplands during drought and non-drought conditions.

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Section: Precipitation and Vegetation-how Close Is The Link?mentioning

confidence: 99%

Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

et al. 2017

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“…50%) is produced in the year-round and winter rainfall regions (ca. 55-80% of rainfall between April and September) along the southern and southwestern coasts (Hardy et al, 2011). Maize plantings and production average 31 000 km 2 and 10 000 kt, respectively, while wheat extent and production is 8200 km 2 and 2300 kt, respectively (Anonymous, 2009).…”

Section: Background and Model Overviewmentioning

confidence: 99%

“…We focused on South Africa, a regionally and globally important agricultural power that is the world's 9th largest maize producer and sub-Saharan Africa's 2nd largest wheat grower (FAO, 2012). Although it is semiarid, most (85%) of South African maize and wheat is rainfed (Hardy et al, 2011). Some climate scenarios show that South Africa will become both drier and hotter (IPCC, 2007), which could cause substantial production losses.…”

Section: Introductionmentioning

confidence: 99%

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches

Estes

Beukes

Bradley

et al. 2013

Global Change Biology

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Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were -3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EM-MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM-MM comparisons to provide a fuller picture of crop-climate response uncertainties.

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“…Maize and wheat are South Africa's 2 dominant staple crops by production area and consumption (Bradley et al ), and South Africa is a regionally and globally important producer of these 2 crops (Estes et al ). Despite having a semiarid climate, more than 85% of South African maize and wheat production is rainfed and occurs on commercial farms (Hardy et al ; Bradley et al ). Maize is mostly grown in the summer rainfall zones in the northeastern part of the country (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…This assumption is based on several factors, including South Africa's recent agricultural history. Up until the late 1980s, government subsidies promoted maize and wheat farming in marginally productive areas (Hardy et al ). Following the removal of subsidies, cereal farming retreated toward more climatically suitable areas (Hardy et al ), such that most of the high potential arable land is cultivated (Wessels et al ).…”

Section: Methodsmentioning

confidence: 99%

Using Changes in Agricultural Utility to Quantify Future Climate‐Induced Risk to Conservation

Estes

Paroz

Bradley

et al. 2013

Conservation Biology

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Much of the biodiversity-related climate change impacts research has focused on the direct effects to species and ecosystems. Far less attention has been paid to the potential ecological consequences of human efforts to address the effects of climate change, which may equal or exceed the direct effects of climate change on biodiversity. One of the most significant human responses is likely to be mediated through changes in the agricultural utility of land. As farmers adapt their practices to changing climates, they may increase pressure on some areas that are important to conserve (conservation lands) whereas lessening it on others. We quantified how the agricultural utility of South African conservation lands may be altered by climate change. We assumed that the probability of an area being farmed is linked to the economic benefits of doing so, using land productivity values to represent production benefit and topographic ruggedness as a proxy for costs associated with mechanical workability. We computed current and future values of maize and wheat production in key conservation lands using the DSSAT4.5 model and 36 crop-climate response scenarios. Most conservation lands had, and were predicted to continue to have, low agricultural utility because of their location in rugged terrain. However, several areas were predicted to maintain or gain high agricultural utility and may therefore be at risk of near-term or future conversion to cropland. Conversely, some areas were predicted to decrease in agricultural utility and may therefore prove easier to protect from conversion. Our study provides an approximate but readily transferable method for incorporating potential human responses to climate change into conservation planning.

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Rainfed Farming Systems in South Africa

Cited by 10 publications

References 8 publications

Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

Drought Dynamics and Vegetation Productivity in Different Land Management Systems of Eastern Cape, South Africa—A Remote Sensing Perspective

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches

Using Changes in Agricultural Utility to Quantify Future Climate‐Induced Risk to Conservation

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