Drivers of bird species richness within moist high-altitude grasslands in eastern South Africa

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

Data from: Dynamic multi-species occupancy models reveal individualistic habitat preferences in a high-altitude grassland bird community

Moist, high-altitude grasslands of eastern South African harbour rich avian diversity and endemism. This area is also threatened by increasingly intensive agriculture and land conversion for energy production. This conflict is particularly evident at Ingula, an Important Bird and Biodiversity Area located within the least conserved high-altitude grasslands and which is also the site of a new Pumped Storage Scheme. The new management seeks to maximise biodiversity through manipulation of the key habitat variables: grass height and grass cover through burning and grazing to make habitat suitable for birds. However, different species have individual habitat preferences, which further vary through the season. We used a dynamic multi-species occupancy model to examine the seasonal occupancy dynamics of 12 common grassland bird species and their habitat preferences. We estimated monthly occupancy, colonisation and persistence in relation to grass height and grass cover throughout the summer breeding season of 2011/12. For majority of these species, at the beginning of the season occupancy increased with increasing grass height and decreased with increasing grass cover. Persistence and colonisation decreased with increasing grass height and cover. However, the 12 species varied considerably in their responses to grass height and cover. Our results suggest that management should aim to provide plots which vary in grass height and cover to maximise bird diversity. We also conclude that the decreasing occupancy with increasing grass cover and low colonisation with increasing grass height and cover is a results of little grazing on our study site. We further conclude some of the 12 selected species are good indicators of habitat suitability more generally because they represent a range of habitat needs and are relatively easy to monitor

Birds_veg_plot data seasons all rvsn

Grassland birds recorded across the 19 plots in 2010-12 across all seasons and vegetation for summers onl

Habitat use, distribution and breeding ecology of the globally threatened Rudd’s Lark and Botha’s Lark in eastern South Africa

Habitat use and breeding ecology of the threatened and poorly known Rudd’s Lark Heteromirafra ruddi were studied in south-eastern Mpumalanga, South Africa, from October 2002 to April 2004. Data were also collected incidentally on the equally poorly known Botha’s Lark Spizocorys fringillaris. Rudd’s Larks establishing territories at the start of the summer breeding season selected grassland of lower than average height. Although grass in these territories had reached average height by the late breeding season, grassland selected by birds could still be distinguished from unoccupied grassland using a combination of other habitat variables. Botha’s Lark was encountered less frequently than Rudd’s Lark, but was always encountered along transects that also held Rudd’s Lark, indicating a degree of overlap in habitat selection. However, the two species appeared to differ in nest site selection; Rudd’s Lark nests were most frequently built in unburned grass and Botha’s Lark nests on recently burned land. First egg dates of 93 Rudd’s Lark nests ranged from late October to late March, with peak laying in January and February. Most clutches were of three eggs, and both incubation and nesting periods appear long for a lark, at 13–14 d and  13 d, respectively, for both species. Average nesting success, estimated using an extension of the Mayfield method, was around 30%, but showed a significant decline as the breeding season progressed and was lowest during the peak nesting period. Clutch size was significantly smaller in Botha’s Lark (median = 2) and nesting took place significantly earlier, largely on land recently burned. Botha’s Larks largely abandoned the study area after a short and possibly curtailed breeding season. Predation was the main cause of nest loss in both species and examination of the remains of dummy eggs identified mongooses, rodents and snakes as the main predators. Late burning of grassland might shorten the potential breeding season of Rudd’s Lark and lead to a peak of nesting that coincides with high predator numbers. The earlier nesting of Botha’s Lark suggests that this species may have been even more severely affected by a shortening of the breeding season. A model of Rudd’s Lark potential distribution confirms previous suggestions that there might be a population of the species in the north-eastern Free State and identifies possible new sites elsewhere. Ostrich 2009, 80(1): 19–2

Data from: Drivers of bird species richness within moist high-altitude grasslands in eastern South Africa

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

Comparison of grass height during the three summers of survey at Ingula (2006/07, 2007/08 and 2010/11).

<p>Year is treated as a fixed effect and transect as a random effect. <b>Bold</b> vertical lines represent the estimated means according to the best model (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0162609#pone.0162609.t002" target="_blank">Table 2</a>).</p

Comparison of influence of fire on grass cover along transects that were burned and those that were not burned at Ingula using summer data for three years (2006/7, 2007/08 and 2010/11).

<p>Year is a treated as a fixed effect and transect as a random effect. <b>Bold</b> vertical lines show the estimated means according to the best model (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0162609#pone.0162609.t001" target="_blank">Table 1</a>).</p

Comparison of total bird species richness (combining birds that prefer heavy grazing with birds that prefer light grazing) at Ingula using data from summer surveys only.

<p>Year is treated as a fixed effect and transect as a random effect. <b>Bold</b> bars represent the estimated means.</p

Ingula vegtn transects 2006,2007,2010_PLOS2016

Ingula vegtn transects 2006,2007,2010_PLOS201