Climatic and oceanic associations with daily rainfall extremes over southern Africa

Changes in climate variability and, in particular, changes in extreme climate events are likely to be of far more significance for environmentally vulnerable regions than changes in the mean state. It is generally accepted that sea-surface temperatures (SSTs) play an important role in modulating rainfall variability. Consequently, SSTs can be prescribed in global and regional climate modelling in order to study the physical mechanisms behind rainfall and its extremes. Using a satellite-based daily rainfall historical data set, this paper describes the main patterns of rainfall variability over southern Africa, identifies the dates when extreme rainfall occurs within these patterns, and shows the effect of resolution in trying to identify the location and intensity of SST anomalies associated with these extremes in the Atlantic and southwest Indian Ocean. Derived from a Principal Component Analysis (PCA), the results also suggest that, for the spatial pattern accounting for the highest amount of variability, extremes extracted at a higher spatial resolution do give a clearer indication regarding the location and intensity of anomalous SST regions. As the amount of variability explained by each spatial pattern defined by the PCA decreases, it would appear that extremes extracted at a lower resolution give a clearer indication of anomalous SST regions

Community Capacity for Implementing Clean Development Mechanism Projects Within Community Forests in Cameroon

There is a growing assumption that payments for environmental services including carbon sequestration and greenhouse gas emission reduction provide an opportunity for poverty reduction and the enhancement of sustainable development within integrated natural resource management approaches. Yet in experiential terms, community-based natural resource management implementation falls short of expectations in many cases. In this paper, we investigate the asymmetry between community capacity and the Land Use Land Use Change Forestry (LULUCF) provisions of the Clean Development Mechanism within community forests in Cameroon. We use relevant aspects of the Clean Development Mechanism criteria and notions of “community capacity” to elucidate determinants of community capacity needed for CDM implementation within community forests. The main requirements are for community capacity to handle issues of additionality, acceptability, externalities, certification, and community organisation. These community capacity requirements are further used to interpret empirically derived insights on two community forestry cases in Cameroon. While local variations were observed for capacity requirements in each case, community capacity was generally found to be insufficient for meaningful uptake and implementation of Clean Development Mechanism projects. Implications for understanding factors that could inhibit or enhance community capacity for project development are discussed. We also include recommendations for the wider Clean Development Mechanism/Kyoto capacity building framework

Global Assessment Report on Disaster Risk Reduction 2019

The Global Assessment Report on Disaster Risk Reduction (GAR) is the flagship report of the United Nations on worldwide efforts to reduce disaster risk

Vegetation structure and effects of human use of Dambos ecosystem in northern Mozambique

Original research articleThe Niassa National Reserve (NNR) is the most extensive conservation area in Mozambique and the third largest in Africa, encompassing 42,000 km2 of endemic miombo vegetation. Dambos wetlands occur within the wooded grassland and grassland vegetation of NNR and provide a wide range of Ecosystem Services (ES), including life support for animal species, regulation of water flow and prevention of soil erosion. It also generates income for the livelihoods of local communities by providing land for agriculture and harvesting of non-timber products. The dynamics of these ecosystems is poorly understood despite the contribution of the dambos to global biodiversity and ES. This research is the first preliminary assessment of the vegetation structure and composition of six dambos within NNR, selected using Google Earth, MODIS satellite images and an exploratory field visit. Field data collection was performed using a two-stage systematic sampling approach, along transect lines of 100 10m (0.1 ha), perpendicular to the dambos' flow. Square plots of 0.25m2 were established for grass survey within the transects where grass vegetation was measured, counted and identified. Data were analyzed with R software. The sociological position of each species was analyzed with regard to the vertical structure while for horizontal structure, the abundance, dominance, frequency and Importance Value Index (IVI) were determined. In order to understand the differences between dambos, evenness (H) and reciprocal of Simpson's heterogeneity index (Hill's N2) were calculated. Principal Coordinates Analysis (PCoA) and Cluster Analysis were also used to characterize the surveyed species communities. A total of 58 transects (5.8 ha) and 336 subplots were assessed, recording 110 woody and 73 grass species, respectively. The most common tree species were Vitex doniana, Burkea africana, Syzygium cordatum and Annona senegalensis, while for grass vegetation the most abundant species were Andropogon eucomus and Helictotrichon turgidulum. According to the IVI, the most dominant tree and shrub species were V. doniana, Pseudolachnostylis maprouneifolia, A. senegalensis and S. cordatum. Homogeneity (Hill's N2 ¼18.92) and evenness (H¼ 4.27) were, on average, low in all dambos. Dambo 2 was the most heterogeneous (Hill's N2 ¼18.21) while dambo 1 was the least heterogeneous (Hill's N2 ¼ 5.71). Dambo 6 was most equitable (H¼ 1.35) whereas dambo 2 the least equitable (H¼ 3.72). Using species abundance and based on PCoA and cluster analysis, four main groups of dambos were identified based mainly on the water gradient, with data variation captured by the first three axes reaching almost 83%. The p-value (0.42), suggested no significant differences between species communities in the dambos, and thus, human disturbances appear not to be enough to modify dambos microenvironment. Accordingly, the results suggest that human activities, at this level, do not necessarily affect the structure and diversity of dambos in the NNR. The results also suggest that the species A. senegalensis, Combretum psidioides, Crossopteryx febrifuga, Protea nitida, P. maprouneifolia and S. cordatum can be used as indicator dambo species in NNR, with high likelihood of occurrenceinfo:eu-repo/semantics/publishedVersio

Africa and the global carbon cycle

The African continent has a large and growing role in the global carbon cycle, with potentially important climate change implications. However, the sparse observation network in and around the African continent means that Africa is one of the weakest links in our understanding of the global carbon cycle. Here, we combine data from regional and global inventories as well as forward and inverse model analyses to appraise what is known about Africa's continental-scale carbon dynamics. With low fossil emissions and productivity that largely compensates respiration, land conversion is Africa's primary net carbon release, much of it through burning of forests. Savanna fire emissions, though large, represent a short-term source that is offset by ensuing regrowth. While current data suggest a near zero decadal-scale carbon balance, interannual climate fluctuations (especially drought) induce sizeable variability in net ecosystem productivity and savanna fire emissions such that Africa is a major source of interannual variability in global atmospheric CO(2). Considering the continent's sizeable carbon stocks, their seemingly high vulnerability to anticipated climate and land use change, as well as growing populations and industrialization, Africa's carbon emissions and their interannual variability are likely to undergo substantial increases through the 21st century

Fire regimes and variability in aboveground woody biomass in miombo woodland

This study combined a process-based ecosystem model with a fire regime model to understand the effect of changes in fire regime and climate pattern on woody plants of miombo woodland in African savanna. Miombo woodland covers wide areas in Africa and is subject to frequent anthropogenic fires. The model was developed based on observations of tree topkill rates in individual tree size classes for fire intensity and resprouting. Using current and near-future climate patterns, the model simulated the dynamics of miombo woodland for various fire return intervals and grass cover fractions, allowing fire intensity to be estimated. There was a significant relationship between aboveground woody biomass and long-term fire regimes. An abrupt increase in fire intensity and/or fire frequency applied as a model forcing led to reduced long-term average aboveground woody biomass and mean tree size. Fire intensity increased with increasing living grass biomass (which provides increased flammable fuel), thereby affecting the relationship between fire regime and tree size, creating a demographic bottleneck on the route to tree maturity. For the current fire regime in miombo woodland, with a fire return interval of about 1.6-3 years, the model-predicted fire intensity lower than 930-1700 kW m-1 is necessary to maintain today's aboveground woody biomass under current climate conditions. Future climate change was predicted to have a significant positive effect on woody plants in miombo woodland associated with elevated CO2 concentration and warming, allowing woody plants to survive more effectively against periodic fires

Impact of Climate Change on Life in Africa

An article from the World Wide Fund for Nature (WWF)url:www.panda.org/climat

Development of a MIOMBO woodland dynamics model in Zambezian Africa using Malawi as a case study

A path model was developed to characterize the effects of climate on succession of miombo dry forests of Zambezian Africa using Malawi as a case study. The model, called MIOMBO, is based on the FORSKA Version I gap model of forest succession by Prentice and Leemans (1990). The FORSKA model was modified to include the effects of moisture and fire; and how these affect processes of establishment, survival, growth and development. The impacts that four different GCM scenarios for a CO2 doubling might have on dynamics of a number of miombo species were analyzed. Preliminary results show a gradual increase in the basal area of the more mesic species. This result is consistent with what might be expected with increased precipitation. Tree growth and development data with associated detailed climatic data are lacking and severely limit the ability to define quantitatively how species are influenced by given levels of environmental factors (such as climate and nutrient factors), and how they might respond to seasonal changes in climate variability