Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.

Farmer-Managed Natural Regeneration Enhances Rural Livelihoods in Dryland West Africa

Declining agricultural productivity, land clearance and climate change are compounding the vulnerability of already marginal rural populations in West Africa. 'Farmer-Managed Natural Regeneration' (FMNR) is an approach to arable land restoration and reforestation that seeks to reconcile sustained food production, conservation of soils and protection of biodiversity. It involves selecting and protecting the most vigorous stems regrowing from live stumps of felled trees, pruning off all other stems, and pollarding the chosen stems to grow into straight trunks. Despite widespread enthusiasm and application of FMNR by environmental management and development projects, to date, no research has provided a measure of the aggregate livelihood impact of community adoption of FMNR. This paper places FMNR in the context of other agroforestry initiatives, then seeks to quantify the value of livelihood outcomes of FMNR. We review published and unpublished evidence about the impacts of FMNR, and present a new case study that addresses gaps in the evidence base. The case study focuses on a FMNR project in the district of Talensi in the semi-arid Upper East Region in Ghana. The case study employs a Social Return on Investment (SROI) analysis, which identifies proxy financial values for non-economic as well as economic benefits. The results demonstrate income and agricultural benefits, but also show that asset creation, increased consumption of wild resources, health improvements and psycho-social benefits created more value in FMNR-adopting households during the period of the study than increases in income and agricultural yields.