Exploring the benefits of inoculated cowpeas under different climatic conditions in Namibia.

Cowpeas (Vigna uniculata L. Walp) are grown by many smallholder farmers in sub-Saharan Africa for food and their ability to fix nitrogen even under stress. Their performance depends on the indigenous rhizobial strains that live in symbiotic association with the roots; it can be enhanced if the seeds are inoculated with more effective ones. Data of the effectiveness of the technique under a variety of climatic conditions is rare. Here, we thus use a model to upscale two field experiments conducted in Namibia to include different climate change scenarios. The simulations show that non-inoculated cowpeas have mean yields of 0.5 t/ha and inoculated cowpeas 1 t/ha. If climatic conditions are favorable (cool and wet), estimated yield differences increase to over 1 t/ha. In dry years (< 200 mm), the average yield difference is only 0.1 t/ha. In the far future (2080-2100), instances of dry and hot years will increase. Using inoculated cowpea seeds instead of non-inoculated ones thus does not benefit farmers as much then as in the near future (2030-2050). In conclusion, using cowpea seeds inoculated with an efficient rhizobial strain can significantly increase yields under varying climatic conditions, but yield advantages decrease markedly in very dry and hot years.

New tools for old problems - comparing drone- and field-based assessments of a problematic plant species.

Plant species that negatively affect their environment by encroachment require constant management and monitoring through field surveys. Drones have been suggested to support field surveyors allowing more accurate mapping with just-in-time aerial imagery. Furthermore, object-based image analysis tools could increase the accuracy of species maps. However, only few studies compare species distribution maps resulting from traditional field surveys and object-based image analysis using drone imagery. We acquired drone imagery for a saltmarsh area (18 ha) on the Hallig Nordstrandischmoor (Germany) with patches of Elymus athericus, a tall grass which encroaches higher parts of saltmarshes. A field survey was conducted afterwards using the drone orthoimagery as a baseline. We used object-based image analysis (OBIA) to segment CIR imagery into polygons which were classified into eight land cover classes. Finally, we compared polygons of the field-based and OBIA-based maps visually and for location, area, and overlap before and after post-processing. OBIA-based classification yielded good results (kappa = 0.937) and agreed in general with the field-based maps (field = 6.29 ha, drone = 6.22 ha with E. athericus dominance). Post-processing revealed 0.31 ha of misclassified polygons, which were often related to water runnels or shadows, leaving 5.91 ha of E. athericus cover. Overlap of both polygon maps was only 70% resulting from many small patches identified where E. athericus was absent. In sum, drones can greatly support field surveys in monitoring of plant species by allowing for accurate species maps and just-in-time captured very-high-resolution imagery.

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 km(2) 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.