The role of land tenure in conservation of tree and shrub species diversity in miombo woodlands of southern Malawi

Mwase, Weston F.; Bjørnstad, Åsmund; Bokosi, James M.; Kwapata, M.B.; Stedje, Brita

doi:10.1007/s11056-006-9029-0

Cited by 22 publications

(17 citation statements)

References 11 publications

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“…Hyde and Seve (1993) quantified forest establishment, suggesting government plantations added 30 km 2 y −1 by 1985 and private smallholders added 11 km 2 y −1 by 1990. However, although there has been much forest establishment, it is unlikely the new forested areas would have the same levels of biodiversity as remaining original forests (Mwase et al 2007). …”

Section: Change In Forest Areamentioning

confidence: 99%

Deforestation since independence: a quantitative assessment of four decades of land-cover change in Malawi

Bone

Parks

Hudson

et al. 2016

Southern Forests: a Journal of Forest Science

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Land cover has changed rapidly across the tropics over the past century; however, detailed historical information describing the extent and possible drivers of such change is widely lacking. Here, we constructed a history of land-cover change at the district level in Malawi over a 37-year period from 1972 to 2009, the immediate post-colonial phase. Overall, there was a loss of 12 760 km 2 (36%) of original forested area but also 11 161 km 2 of new forest establishment, resulting in a relatively modest overall net loss of 1 599 km 2 (5%). We correlated changes in deforestation and forest establishment with changes in socio-economic variables derived from spatially explicit data from the same time period. Deforestation was positively correlated with (in order of influence) changes in male school attendance, sex ratio, population density, hospital bed numbers, protected areas and dependency rate, but negatively correlated with changes in cattle density; forest establishment broadly showed the inverse relationships with the same variables. Although direct drivers of deforestation are well known for Malawi and much of Africa, the significance of socio-economic variables within this study can help to understand the underlying social pressures behind such drivers. In particular, development, population pressure and demographic factors are important predictors of deforestation rate within our study area.

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Section: Change In Forest Areamentioning

confidence: 99%

Deforestation since independence: a quantitative assessment of four decades of land-cover change in Malawi

Bone

Parks

Hudson

et al. 2016

Southern Forests: a Journal of Forest Science

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“…Tanzania have the highest rate (1.16%) of deforestation and forest degradation in Africa, estimated to be 403,000 ha annually [26,30]. The challenge is more pronounced in miombo woodlands, if compared to other forest biomes [14,[31][32][33][34]. Deforestation and forest degradation is occurring significantly even in the reserved forests [35,36].…”

Section: International Journal Of Forestry Researchmentioning

confidence: 99%

Management, Growth, and Carbon Storage in Miombo Woodlands of Tanzania

Lupala

Lusambo

Ngaga

2014

International Journal of Forestry Research

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Despite the local livelihoods support function provided by miombo woodlands of Tanzania under participatory forest management, its growth still has potential for carbon storage and sequestration attractive to REDD+ initiatives. This study has revealed the average growth to be significant, despite the local community livelihoods support function. However, climate change mitigation strategy needs to be more innovative to optimize carbon storage and local livelihoods' potentials in forest-dependent communities like miombo woodlands. Carbon credits resulting from the increased carbon stock and sequestration should contribute to sustainable development. This should also help promote participatory forest management and secure miombo woodland products and services upon which billions of people depend.

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“…Statistics on woodland cover in the miombo countries continue to show a decline in cover, both nationally (Table 1) and in many case study areas (e.g. Luoga et al 2005;Mwase et al 2007). Woodland loss is largely driven by two major processes: land clearing for agriculture, and wood extraction for energy.…”

Section: Introductionmentioning

confidence: 99%