Variation by Geographic Scale in the Migration-Environment Association: Evidence from Rural South Africa

"Scholarly understanding of human migration's environmental dimensions has greatly advanced in the past several years, motivated in large part by public and policy dialogue around 'climate migrants'. The research presented here advances current demographic scholarship both through its substantive interpretations and conclusions, as well as its methodological approach. We examine temporary rural South African outmigration as related to household-level availability of proximate natural resources. Such 'natural capital' is central to livelihoods in the region, both for sustenance and as materials for market-bound products. The results demonstrate that the association between local environmental resource availability and outmigration is, in general, positive: households with higher levels of proximate natural capital are more likely to engage in temporary migration. In this way, the general findings support the 'environmental surplus' hypothesis that resource security provides a foundation from which households can invest in migration as a livelihood strategy. Such insight stands in contrast to popular dialogue, which tends to view migration as a last resort undertaken only by the most vulnerable households. As another important insight, our findings demonstrate important spatial variation, complicating attempts to generalize migration-environment findings across spatial scales. In our rural South African study site, the positive association between migration and proximate resources is actually highly localized, varying from strongly positive in some villages to strongly negative in others. We explore the socio-demographic factors underlying this 'operational scale sensitivity'. The cross-scale methodologies applied here offer nuance unavailable within more commonly used global regression models, although also introducing complexity that complicates story-telling and inhibits generalizability." (author's abstract

How free-ranging ungulates with differing water dependencies cope with seasonal variation in temperature and aridity

Large mammals respond to seasonal changes in temperature and precipitation by behavioural and physiological flexibility. These responses are likely to differ between species with differing water dependencies. We used biologgers to contrast the seasonal differences in activity patterns, microclimate selection, distance to potential water source and body temperature of the water-independent gemsbok (Oryx gazella gazella) and water-dependent blue wildebeest (Connochaetes taurinus), free-living in the arid Kalahari region of Botswana. Gemsbok were more active nocturnally during the hot seasons than in the cold-dry season, while wildebeest showed no seasonal difference in their nocturnal activity level. Both species similarly selected shaded microclimates during the heat of the day, particularly during the hot seasons. Wildebeest were further than 10 km from surface water 30% or more of the time, while gemsbok were frequently recorded >20 km from potential water sources. In general, both species showed similar body temperature variation with high maximum 24-h body temperature when conditions were hot and low minimum 24-h body temperatures when conditions were dry, resulting in the largest amplitude of 24-h body temperature rhythm during the hot-dry period. Wildebeest thus coped almost as well as gemsbok with the fairly typical seasonal conditions that occurred during our study period. They do need to access surface water and may travel long distances to do so when local water sources become depleted during drought conditions. Thus, perennial water sources should be provided judiciously and only where essential

Conservation during times of change : correlations between birds, climate and people in South Africa

CITATION: Van Rensburg, B. J., et al. 2004. Conservation during times of change : correlations between birds, climate and people in South Africa. South African Journal of Science, 100(5-6):266-272.The original publication is available at https://journals.co.za/Few studies have investigated the ability of national conservation networks to adapt to changes in underlying environmental drivers (such as precipitation) and their consequences for factors such as human density and species richness patterns. In this article, the South African avifauna is used as the basis for such analysis to ascertain the likely extent of current, and future, anthropogenic impacts on priority conservation areas. We show that human population pressure is high in or around most of these priority areas and is likely to increase, given the magnitude of post-climate change estimated from predicted changes in precipitation and relationships between species richness, human densities, and rainfall. Although additional conservation areas, such as the Important Bird Area (IBA) network, are likely to introduce valuable flexibility to conservation management, only limited options are available for such expansions, and the conservation value of these areas is likely to be compromised by changing climate. Ultimately, a more integrated conservation approach is needed for effective conservation policies. Such an approach should confer adequate protection on current reserves and emphasize sustainable utilization of non-reserve areas.https://journals.co.za/content/sajsci/100/5-6/EJC96257Publisher's versio

Mean biomass increase (Mg ha^-1) at sites under varying wood extraction pressures.

<p>n is the number of 25 m x 25 m grid cells in each rangeland.</p><p>Mean biomass increase (Mg ha^-1) at sites under varying wood extraction pressures.</p

Height-specific biomass change as a function of relative height change per grid cell.

<p>Height categories are a) 1–3 m, b) 3–5 m and c) 5–10 m for rangelands of high, intermediate and low wood extraction pressure. There were no data for the 5–10 m height class in the high wood extraction rangeland and the >10 m height class for all rangelands as there were no grid cells with an average height over 10 m. Grid cell size: 25 m x 25 m.</p

Height-specific biomass change as a function of relative change in canopy cover per grid cell.

<p>Height categories are a) 1–3 m, b) 3–5 m and c) 5–10 m for rangelands of high, intermediate and low wood extraction pressure. There were no data for the 5–10 m height class in the high wood extraction rangeland and the >10 m height class for all rangelands as there were no grid cells with an average height over 10 m. Grid cell size: 25 m x 25 m.</p

Study sites in Bushbuckridge municipality, located in the South African Lowveld.

<p>Sites are classified (from west to east) as low, high and intermediate wood extraction pressure based on the number of households and people utilising each rangeland. Settlements that utilise each rangeland are shown, including the names of the major settlements, as well as the location of the gabbro intrusions in the predominantly granitic landscape.</p

Height-specific subcanopy returns (%) (mean ± standard deviation) for 2008 and 2012.

<p>Wood extraction levels are: a) high (n = 102 cells), b) intermediate (n = 291 cells), and c) low wood extraction (n = 1654 cells). Contribution of height class change (subcanopy returns) to total change (total vegetation column) (%) is the black bar represented by values on the secondary axis. e.g. In the high wood extraction rangeland, 79% of the change in the total vegetation column was attributable to the 1–3 m height class.</p

Site-specific biomass models derived from field allometry and LiDAR metric linear regression.

<p>In the model equations, y refers to the plot-level (25 m x 25 m) biomass estimate (kg/625 m²) and x to the LiDAR-derived H x CC predictor metrics, where H is plot-averaged height (> 1.5 m) and CC is the proportion of canopy cover (> 1.5 m in height) per plot. Root mean square error (RMSE) was reported in Mg ha^-1 for ease of interpretation and n is number of 25 m x 25 m plots.</p><p>Site-specific biomass models derived from field allometry and LiDAR metric linear regression.</p