Pattern of forest recovery and carbon stock following shifting cultivation in Manipur, North-East India

Modeling LULC using Multi-Layer Perceptron Markov change (MLP-MC) and identifying local drivers of LULC in hilly district of Manipur, India

Identification and prediction of future land use and land cover (LULC) changes and their drivers are required for land resources management, formulation of better policy, practicing sustainable management strategies, and modeling future LULC. The present study has focused on the prediction of future LULC and assessment of local drivers of LULC change in the hill agroecosystem Senapati district of Manipur, Northeast India. The prediction of future LULC for 2029 was achieved based on LULC data of 1999, 2009, and 2019 satellite data using multi-layer perceptron Markov change (MLP-MC) of Land Change Modeler (LCM). The socio-economic survey and field observation were performed to identify local drivers of LULC changes in the study area. The total area covered by open and dense forests in 2029 was 69.06% of the total geographical area of the district, a slight increase from the 2019 assessment of 61.01 km². The drivers of LULC were categorized by assigning rank. The proximate drivers directly influence land use dynamics, such as increases in the settlement area, firewood collection, and construction. The underlying drivers-population growth and poverty-have also indirectly influenced LULC change in the district. It was observed that the livelihoods of local communities depend on forest products and agriculture. Therefore, the study finding will help create a future LULC information database and identification of local drivers of LULC. It will encourage the communities to participate in proper land resource management and create awareness for the sustainable use of the land.

Forests, Farms, and Fallows: The Dynamics of Tree Cover Transition in the Southern Part of the Uluguru Mountains, Tanzania

Forests and woodlands remain under threat in tropical Africa due to excessive exploitation and inadequate management interventions, and the isolated success stories of tree retention and tree cover transition on African agricultural land are less well documented. In this study, we characterize the status of tree cover in a landscape that contains forest patches, fallows, and farms in the southern part of Uluguru Mountains. We aimed to unveil the practices of traditional tree fallow system which is socially acceptable in local settings and how it provides a buffering effects to minimize forest disturbances and thus represents an important step towards tree cover transition. We assessed land cover dynamics for the period of 1995 to 2020 and compared tree stocking for forest patches, fallows, and farms. We found that tree biomass carbon stocks were 56 ± 5 t/ha in forest patches, 33 ± 7 t/ha in fallows, and 9 ± 2 t/ha on farms. In terms of land cover, farms shrank at intensifying rates over time for the entire assessment period of 1995–2020. Forest cover decreased from 1995–2014, with the reduction rate slowing from 2007–2014 and the trend reversing from 2014–2020, such that forest cover showed a net increase across the entire study period. Fallow consistently and progressively increased from 1995–2020. We conclude that traditional tree fallows in the study site remain a significant element of land management practice among communities, and there appears to be a trend towards intensified tree-based farming. The gains in fallowed land represent an embracing of a traditional land management system that supports rotational and alternate uses of cropping space as well as providing a buffering effect to limit over-exploitation of forests. In order to maximize tree cover and carbon stocks in the farm landscape, this well-known traditional tree fallow system can be further optimized through the incorporation of additional innovations.