Understanding the dynamics in the forest-farm transition
Download as PPTX, PDF0 likes269 views
The document discusses the dynamics of forest-farm transitions in the Nile-Congo sentinel landscape and their role in landscape restoration efforts. It highlights the impact of land degradation due to population growth and economic activities and outlines the establishment of sentinel landscapes for monitoring land health and ecosystem services. The conclusion emphasizes the importance of data-driven research and stakeholder engagement for effective restoration strategies and better management of landscape resources.
Understanding the dynamics in the forest-farm transition
- 1. Understanding the dynamics in the forest-farm transition to inform landscape restoration in the Nile- Congo Sentinel Landscape Clement Okia ICRAF Uganda c.okia@cgiar.org
- 2. Presentation outline 1. Introduction 2. Why forest-farm transition 3. The Sentinel landscapes 4. Progress made 5. Supporting restoration initiatives 6. Conclusion
- 3. Introduction • Growing human population and the increasing global demand for food and energy are the major driving forces behind land degradation in Africa (UNEP, 2006). • Forest degradation in SSA is largely driven by immediate economic gains from forest-related activities (Mogaka et al., 2001). • Land use change undermines the capacity of ecosystems to sustain the provision of ecosystems services (Foley et al. 2005).
- 4. Why Forest-farm transition • Forest-farm transitions concern long-term observed changes • Well-managed forest-farm transitions can sustainably provide environmental services- stable societies. • Have demonstrated impact on hydrological cycles, soil conservation, climate change, & biodiversity conservation • Well-managed forest-farm transitions also increase carbon sequestration.
- 5. Sentinel landscape under FTA • “sentinel” – term borrowed from the health sector - used to describe a community from which in- depth data are gathered and the resulting analysis is used to inform programs and policies affecting a larger geographic area. • For FTA- a sentinel landscape is defined as an entity that meets the following four criteria: – Existing data for baseline and historical – FTA partners interested to co-locate research in this landscape – Variation along a contiguous forest transition curve (geographical and issues bound landscapes) – Existence of a network of reliable partners on the ground that FTA can add value to
- 6. Set up of Sentinel Landscapes under FTA • Central to FTA work is the establishment of a series of sentinel landscapes • Located in contrasting biophysical and cultural scenarios around the world • Used to monitor, assess and learn from long term trends of: – drivers and processes that lead to changes in the presence of trees in forests and outside forests, – consequences of these changes in the provision of livelihoods, conservation of natural resources and provision of other ecosystem services to society, and – innovations and changes needed to reduce tree cover loss and to stimulate active planting and restoration of trees and forests in the landscape (landscape restoration).
- 7. FTA Sentinel Landscapes Network • 10 Sentinel Landscapes (2012-2014) • 4 Sentinel Sites per Landscape • 10 Villages per Sentinel Site • 160 Sampling Points per Sentinel Site • 300 Households per Sentinel Site
- 8. Nile-Congo Sentinel Landscape - 4 Sentinel Sites Four countries (4 sentinel sites) 1. Uganda – Mt. Elgon 2. Kenya – The Mau Forest 3. Rwanda – Gishwati 4. Eastern DRC – Lake Kivu • Each Sentinel site is 10x10 km2 with a buffer area of 30X30 km2
- 9. 4 parts of the work flow 1. Land Degradation Surveillance Framework 2. Village level baselines 3. Household surveys 4. Tree inventories on a cohort of farms from the household survey
- 10. Sentinel landscapes Baseline data To collect a set of standardized variables, both socio-economic and biophysical .. … to assess the relationship between livelihoods and land health in forested landscapes, which have been exposed to various forms of land-use change.
- 11. Progress made • Land health surveys conducted in Mt. Elgon, the Mau forest and Gishwati sites • Village and Household baseline surveys in two sites http://landscapeportal.org:3838/slExplorer/
- 12. Land Degradation Surveillance Framework (LDSF) • A spatially stratified, randomized sampling design, developed to provide a biophysical baseline at landscape level • Also a monitoring and evaluation framework for assessing processes of land degradation and effectiveness of restoration measures, over time. • Each LDSF site has 160 plots that are randomly stratified among 16 sampling clusters. • Thus for each sentinel site 160x2x16=320 standard soil samples are collected
- 13. Land Degradation Surveillance Framework
- 14. Village survey in 10 villages
- 15. Research questions 1. What are the institutional settings that favor the utilization of forest resources in ways which result in more equitable sharing of benefits? 2. What are the factors that induce people to value the ecosystem services of trees and manage the landscape to provide them? 3. What are the conditions that allow farmers to significantly capitalize on tree products and benefit from them?
- 16. • 10 villages - randomly selected for each sentinel site • Objective is to ensure that the sum of all selected Villages (sample) represents the entire livelihood variation of the sentinel site • Villages are located within a 30x30 km2 radius from the center of the LDSF site Village level baseline
- 17. Village level baseline cont’d • 5 villages are located within the core sentinel site (10x10 km2) to ensure that we have a collection of both biophysical and socio-economic samples.
- 18. A minimum of at least 30% of the houses within each village should be achieved. A randomized sample obtained by getting a list of all HHS from the village heads prior to sampling then using a random number generator. Household survey
- 19. Use of the ODK system for direct data capture
- 20. Requires careful selection and training of enumerators
- 21. Meetings with local leaders in the Mau Sentinel site – securing political buy-in before intensive data collection
- 22. The benefit is a large set of data collected and cleaned simultaneously – transferred to data verse
- 23. • Soil erosion by water is an important indicator of land degradation – modeling erosion prevalence for each site and variations between sampling clusters. • Tree (woody vegetation) densities determined and compared between plots and sites. • Infiltration capacity -important indicator of land health due to its role in terms of regulating the hydrological functioning of the system. Infiltration curves for sites will be produced to highlight the variations. • Further analysis will combine key indicators of land and soil health, including soil properties. • Also, linkages with key socio-economic indicators at both household and village levels will be explored. Key indicators monitored
- 24. Sites in Nile-Congo are mostly cultivated > 70%
- 25. Sites in Nile-Congo have lowest tree cover presenting opportunities for agroforestry
- 26. Except for Kericho, erosion is more prevalent in Gishwati and Mt Elgon sites
- 27. Tree diversity is higher in uncultivated sites (Kericho)
- 28. Soil Organic Matter- Mt. Elgon Ug
- 29. FLR in Nile-Congo SL • Need to build on Landscape observatories under CRP II • Countries in the region have made firm commitments to Bonn challenge/ AFRI100 • Rwanda 2M ha; Kenya 5.1M ha; Uganda 2.5M ha; DR Congo 8 M ha Plus Ethiopia 15M ha • ROAM assessments are almost complete • Agroforestry and farm wood lots are a priority • Focus on Forests, trees, farm and settlement dynamics
- 30. ROAM in Rwanda (GoR, 2014) • Identified 2.25M ha and government committed 2M ha for restoration • Interventions should target 1.5M ha • In particular targeting agroforestry on both flat and sloping land, • Also improved silviculture and establishment of protective forests on steep sloping land and in riparian zones
- 31. Kenya’s restoration options (GoK, 2016) 1. Reforestation and rehabilitation of degraded natural forests 2. Agroforestry and woodlots on cropland 3. Commercial tree and bamboo plantations 4. Tree-based buffers along waterways, wetlands and roads 5. Silvo-pastoral and rangeland restoration
- 32. Uganda’s most preferred FRL options, GoU, 2016 # Zone Area for restoration (Ha) Preferred restoration option 1 Afro-montane 691,161.1 Natural regeneration & AF 2 Karamoja 1,775,156.2 Woodlots 3 Lake Victoria Crescent 394,491.0 Agroforestry 4 Northern Moist 2,631,314.7 Woodlots & agroforestry 5 South East Lake Kyoga Flood Plain 393,639.5 Agroforestry 6 Southwest Rangelands 1,154,340.1 Woodlots 7 Western Mid-Altitude 1,039,519.5 Agroforestry Total (2.5 million ha of this is committed) 8,079,622.10 Agroforestry is singled out as having a high likelihood of creating benefits that far outweigh the costs of FLR compared to other options. But which AF interventions will be promoted and how will progress be monitored Can we present SL as an approach to systematically achieve FLR and monitor progress
- 33. Land health surveillance for Understanding the dynamics in the forest-farm transition • Identifying land constraints and targeting land mgt options in smallholder farming systems in Nile-Congo SL Key issues to address: 1) Determine baseline conditions for monitoring and assessing land management impact and ecosystem health over time (done) 2) Describe land health patterns in different land uses, associated degradation drivers and heir implications over short, medium and long-term horizons (land degradations hot spots) 3) Evaluate the contribution of trees on farms to livelihoods and ecosystem processes 4) Develop and test site-specific agroforestry and other SLM interventions (wider stakeholder engagement).
- 34. Conclusion SL approach allows for long-term research where existing data sets and partnerships can be used to monitor the impacts of landscape restoration at a wider scale . The use of field-tested and standardized research protocols allows regional/global comparative studies of forest transition stages, economic and demographic conditions, and biophysical determinants of environmental services and livelihood options. The key driver of the approach should be to develop and test technical solutions (options) to aid forest landscape restoration at local level Then facilitate the scaling-out and scaling-up of such options and experiences.