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Replication data for: Estimating aboveground tree biomass in three different miombo woodlands and associated land use systems in Malawi

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Title Replication data for: Estimating aboveground tree biomass in three different miombo woodlands and associated land use systems in Malawi
 
Identifier https://doi.org/10.34725/DVN/24926
 
Creator Kuyah, Shem
Sileshi, Gudeta W.
Njoloma, Joyce
Mng’omba, Simon
Neufeldt, Henry
 
Publisher World Agroforestry - Research Data Repository
 
Description Trees outside forests support smallholder farmers’ livelihoods and play a critical role in the global carbon cycle. However, their contribution to climate change mitigation through carbon storage is not obvious because of limited information regarding their extent, and inadequate methods for biomass quantification. This study evaluated the distribution of aboveground biomass (AGB) in three 100 km2 benchmark sites in Kasungu, Salima, and Neno districts in Malawi. In 67 sample plots covering 37 cultivated fields and 30 woodland plots, a total of 2481 trees were inventoried over 6 ha. Tree species documented were 56 in Kasungu, 35 in Salima and 33 in Neno. The corresponding values of the Shannon diversity index and its standard error (SE) were 3.45 (0.01) for Kasungu, 2.78 (0.01) for Salima and 2.73 (0.01) for Neno. The three most dominant species in terms of biomass were Faidherbia albida (47.8%), Piliostigma thonningii (11%), and Mangifera indica (9%), all found in cultivated fields. Large trees with diameter at breast height (DBH) greater than 40 cm formed only 3% of the total population inventoried in Salima, but held over 80% of the biomass. These high biomass trees were hardly found in Kasungu and Neno. Smaller trees (DBH less than 10 cm) dominated all the sites, representing 93% of all the trees measured. These stock 14, 1, and 67% of the biomass in Kasungu, Salima, and Neno, respectively. The biomass estimates established in this study provide a useful reference against which future estimates ca
n be compared, and sets a baseline for calculating changes in carbon stocks over time.
 
Subject Agricultural Sciences