Dataset Information

Protected areas and regional avian species richness in South Africa.

ABSTRACT: Protected areas are generally regarded as essential for the long-term maintenance of biodiversity. Evidence for their effectiveness in this regard is, however, somewhat equivocal. Here, we document the relationship between the proportion of protected land and species richness in a region, both with and without taking spatial variation in environmental energy availability into account. Using the South African avifauna as a case study, we find that total and threatened species richness exhibit modest increases with the proportion of protected land. While the protected area network should be expanded, it is essential that conservation efforts also focus on maintaining biodiversity in the wider unprotected landscape that supports high species richness.

SUBMITTER: Evans KL

PROVIDER: S-EPMC1618914 | biostudies-literature | 2006 Jun

REPOSITORIES: biostudies-literature

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Protected areas and regional avian species richness in South Africa.

Evans Karl L KL Rodrigues Ana S L AS Chown Steven L SL Gaston Kevin J KJ

Biology letters 20060601 2

Protected areas are generally regarded as essential for the long-term maintenance of biodiversity. Evidence for their effectiveness in this regard is, however, somewhat equivocal. Here, we document the relationship between the proportion of protected land and species richness in a region, both with and without taking spatial variation in environmental energy availability into account. Using the South African avifauna as a case study, we find that total and threatened species richness exhibit mod ...[more]

PMID: 17148358

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Project description:Moist high-altitude grasslands in South Africa are renowned for high avifaunal diversity and are priority areas for conservation. Conservation management of these areas conflicts with management for other uses, such as intensive livestock agriculture, which requires annual burning and leads to heavy grazing. Recently the area has become target for water storage schemes and renewable electricity energy projects. There is therefore an urgent need to investigate environmental factors and habitat factors that affect bird species richness in order to optimise management of those areas set aside for conservation. A particularly good opportunity to study these issues arose at Ingula in the eastern South African high-altitude grasslands. An area that had been subject to intense grazing was bought by the national power utility that constructed a pumped storage scheme on part of the land and set aside the rest for bird conservation. Since the new management took over in 2005 the area has been mostly annually burned with relatively little grazing. The new management seeks scientific advice on how to maintain avian species richness of the study area. We collected bird occurrence and vegetation data along random transects between 2006 and 2010 to monitor the impact of the new management, and to study the effect of the habitat changes on bird species richness. To achieve these, we convert bird transect data to presence only data to investigate how bird species richness were related to key transect vegetation attributes under this new grassland management. First we used generalised linear mixed models, to examine changes in vegetation grass height and cover and between burned and unburned habitats. Secondly, we examined how total bird species richness varied across seasons and years. And finally we investigated which habitat vegetation attributes were correlated with species richness of a group of grassland depended bird species only. Transects that were burned showed a larger decrease in vegetation cover compared to transects that were not burned. Grass height increased over time. Bird species richness was highest in summer compared to other seasons and increased over time. Overall bird species richness increased over the three summer surveys but species richness of birds that prefer heavily grazed habitat showed little change over the three years. Changes in bird species richness were best explained by the model with grass height for combined species richness of grassland depended birds but also for birds that prefer heavy grazing when treated alone. On one hand birds that prefer moderate grazing were best explained by a null model. However, overall bird species richness was better positively correlated to grass height than grass cover or dead grass. We conclude that frequent burning alone with relatively reduced grazing led to higher but less dense grass, which benefited some species and disadvantaged others. We suggest that management of this grassland use combination of fire and grazing and leave some areas unburned to accommodates birds of various habitat needs.

Project description:For decades, ecologists have measured habitat attributes in the field to understand and predict patterns of animal distribution and abundance. However, the scale of inference possible from field measured data is typically limited because large-scale data collection is rarely feasible. This is problematic given that conservation and management typical require data that are fine grained yet broad in extent. Recent advances in remote sensing methodology offer alternative tools for efficiently characterizing wildlife habitat across broad areas. We explored the use of remotely sensed image texture, which is a surrogate for vegetation structure, calculated from both an air photo and from a Landsat TM satellite image, compared with field-measured vegetation structure, characterized by foliage-height diversity and horizontal vegetation structure, to predict avian density and species richness within grassland, savanna, and woodland habitats at Fort McCoy Military Installation, Wisconsin, USA. Image texture calculated from the air photo best predicted density of a grassland associated species, grasshopper sparrow (Ammodramus savannarum), within grassland habitat (R(2)?=?0.52, p-value <0.001), and avian species richness among habitats (R(2)=?0.54, p-value <0.001). Density of field sparrow (Spizella pusilla), a savanna associated species, was not particularly well captured by either field-measured or remotely sensed vegetation structure variables, but was best predicted by air photo image texture (R(2)=?0.13, p-value?=?0.002). Density of ovenbird (Seiurus aurocapillus), a woodland associated species, was best predicted by pixel-level satellite data (mean NDVI, R(2)=?0.54, p-value <0.001). Surprisingly and interestingly, remotely sensed vegetation structure measures (i.e., image texture) were often better predictors of avian density and species richness than field-measured vegetation structure, and thus show promise as a valuable tool for mapping habitat quality and characterizing biodiversity across broad areas.

Dataset Information

Protected areas and regional avian species richness in South Africa.

Publications

Protected areas and regional avian species richness in South Africa.

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