The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Multispecies and Multiscale Conservation Planning: Setting Quantitative Targets for Red‐Listed Lichens on Ancient Oaks

Abstract: Species occurrence in a habitat patch depends on local habitat and the amount of that habitat in the wider landscape. We used predictions from empirical landscape studies to set quantitative conservation criteria and targets in a multispecies and multiscale conservation planning effort. We used regression analyses to compare species richness and occurrence of five red‐listed lichens on 50 ancient oaks (Quercus robur; 120–140 cm in diameter) with the density of ancient oaks in circles of varying radius from each individual oak. Species richness and the occurrence of three of the five species were best explained by increasing density of oaks within 0.5 km; one species was best explained by the density of oaks within 2 km, and another was best predicted by the density of oaks within 5 km. The minimum numbers of ancient oaks required for “successful conservation” was defined as the number of oaks required to obtain a predicted local occurrence of 50% for all species included or a predicted local occurrence of 80% for all species included. These numbers of oaks were calculated for two relevant landscape scales (1 km² and 13 km²) that corresponded to various species responses, in such a way that calculations also accounted for local number of oaks. Ten and seven of the 50 ancient oaks surveyed were situated in landscapes that already fulfilled criteria for successful conservation when the 50% and 80% criteria, respectively, were used to define the level of successful conservation. For cost‐efficient conservation, oak stands in the landscapes most suitable for successful conservation should be prioritized for conservation and management (e.g., grazing and planting of new oaks) at the expense of oak stands situated elsewhere.     

Ammonia emissions from a broiler farm: spatial variability of airborne concentrations in the vicinity and impact on adjacent woodland

Agricultural NH₃ emissions affect air quality and influence the nitrogen cycle. In the subject study, NH₃ emissions from a broiler farm and the resulting atmospheric concentrations in the immediate vicinity during three growing cycles have been quantified. Additionally, vegetation along a transect in an adjacent woodland was analysed. The emissions were as high as 10 kg NH₃ h⁻¹ and the atmospheric concentrations ranged between 33 and 124 μg NH₃ m⁻³ per week in the immediate vicinity. Measurements of the atmospheric concentrations over 7 weeks showed a substantial decline of mean concentrations (based on a 3-week average) from ∼13 to <3 μg NH₃ m⁻³, at 45- and 415-m distance from the farm. Vegetation surveys showed that nitrophilous species flourished when they grew closest to the farm (their occurrence sank proportionately with distance). A clearly visible damage of pine trees was observed within 200 m of the farm; this illustrated the significant impact of NH₃ emissions from agricultural sources on the sensitive ecosystem.