Philip J. Platts

Protected Areas: Mixed Success in Conserving East Africa’s Evergreen Forests

In East Africa, human population growth and demands for natural resources cause forest loss contributing to increased carbon emissions and reduced biodiversity. Protected Areas (PAs) are intended to conserve habitats and species. Variability in PA effectiveness and ‘leakage’ (here defined as displacement of deforestation) may lead to different trends in forest loss within, and adjacent to, existing PAs. Here, we quantify spatial variation in trends of evergreen forest coverage in East Africa between 2001 and 2009, and test for correlations with forest accessibility and environmental drivers. We investigate PA effectiveness at local, landscape and national scales, comparing rates of deforestation within park boundaries with those detected in park buffer zones and in unprotected land more generally. Background forest loss (BFL) was estimated at −9.3% (17,167 km2), but varied between countries (range: −0.9% to −85.7%; note: no BFL in South Sudan). We document high variability in PA effectiveness within and between PA categories. The most successful PAs were National Parks, although only 26 out of 48 parks increased or maintained their forest area (i.e. Effective parks). Forest Reserves (Ineffective parks, i.e. parks that lose forest from within boundaries: 204 out of 337), Nature Reserves (six out of 12) and Game Parks (24 out of 26) were more likely to lose forest cover. Forest loss in buffer zones around PAs exceeded background forest loss, in some areas indicating leakage driven by Effective National Parks. Human pressure, forest accessibility, protection status, distance to fires and long-term annual rainfall were highly significant drivers of forest loss in East Africa. Some of these factors can be addressed by adjusting park management. However, addressing close links between livelihoods, natural capital and poverty remains a fundamental challenge in East Africa’s forest conservation efforts.

Delimiting tropical mountain ecoregions for conservation

��������� � �� ���������� SUMMARY Ecological regions aggregate habitats with similar biophysical characteristics within well-defined boundaries, providing spatially consistent platforms for monitoring, managing and forecasting the health of interrelated ecosystems. A major obstacle to the implementation of this approach is imprecise and inconsistent boundary placement. For globally important mountain regions such as the Eastern Arc (Tanzania and Kenya), where qualitative definitions of biophysical affinity are well established, rulebased methods for landform classification provide a straightforward solution to ambiguities in region extent. The method presented in this paper encompasses the majority of both contemporary and estimated preclearance forest cover within strict topographical limits. Many of the species here tentatively considered ‘near-endemic’ could be reclassified as strictly endemic according to the derived boundaries. LandScan and census data show population density inside the ecoregion to be higher than in rural lowlands, and lowland settlement to be most probable within 30 km. This definition should help to align landscape scale conservation strategies in the Eastern Arc and promote new research in areas of predicted, but as yet undocumented, biological importance. Similar methods could work well in other regions where mountain extent is poorly resolved. Spatial data accompany the online version of this article.

Towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world.

Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as ‘lowland tropical forest’ are often used, termed ‘Tier 1 type’ analyses by the Intergovernmental Panel on Climate Change (IPCC). Such estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter, coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method meets the IPCC ‘Tier 2’ reporting standard. We use this method to estimate carbon storage over an area of33.9 million hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92–6.74) Pg C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global studies show a mean carbon storage value of ∼50% of that reported using our regional values, with four of the five studies reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows how such values can be produced for a relatively low investment.

Validating and Linking the GIMMS Leaf Area Index (LAI3g) with Environmental Controls in Tropical Africa

The recent Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g product provides a 30-year global times-series of remotely sensed leaf area index (LAI), an essential variable in models of ecosystem process and productivity. In this study, we use a new dataset of field-based LAITrue to indirectly validate the GIMMS LAI3g product, LAIavhrr, in East Africa, comparing the distribution properties of LAIavhrr across biomes and environmental gradients with those properties derived for LAITrue. We show that the increase in LAI with vegetation height in natural biomes is captured by both LAIavhrr and LAITrue, but that LAIavhrr overestimates LAI for all biomes except shrubland and cropland. Non-linear responses of LAI to precipitation and moisture indices, whereby leaf area peaks at intermediate values and declines thereafter, are apparent in both LAITrue and LAIavhrr, although LAITrue reaches its maximum at lower values of the respective environmental

Land use change and carbon fluxes in East Africa quantified using earth observation data and field measurements

Carbon-based forest conservation requires the establishment of ‘reference emission levels’ against which to measure a country or regions progress in reducing their carbon emissions. In East Africa, landscape-scale estimates of carbon fluxes are uncertain and factors such as deforestation poorly resolved due to a lack of data. In this study, trends in vegetation cover and carbon for East Africa were quantified using moderate-resolution imaging spectroradiometer (MODIS) land cover grids from 2002 to 2008 (500-m spatial resolution), in combination with a regional carbon look-up table. The inclusion of data on rainfall and the distribution of protected areas helped to gauge impacts on vegetation burning (assessed using 1-km spatial resolution MODIS active fire data) and biome trends. Between 2002 and 2008, the spatial extents of forests, woodlands and scrublands decreased considerably and East Africa experienced a net carbon loss of 494 megatonnes (Mt). Most countries in the area were sources of carbon emissions, except for Tanzania and Malawi, where the areal increase of savannah and woodlands counterbalanced carbon emissions from deforestation. Both Malawi and Tanzania contain large areas of planted forest. Vegetation burning was correlated with rainfall (forest only) and differed depending on land management. Freely available global earth observation products have provided ways to achieve rapid assessment and monitoring of carbon change hotspots at the landscape scale.

From local scenarios to national maps: a participatory framework for envisioning the future of Tanzania

Tackling societal and environmental challenges requires new approaches that connect topdown global oversight with bottom-up sub-national knowledge. We present a novel framework for participatory development of spatially-explicit scenarios at national scale that model socio-economic and environmental dynamics by reconciling local stakeholder perspectives and national spatial data. We illustrate results generated by this approach and evaluate its potential to contribute to a greater understanding of the relationship between development pathways and sustainability. Using the lens of land use and land cover changes, and engaging 240 stakeholders representing sub-national (seven forest management Zones) and the national level, we applied the framework to assess alternative development strategies in the Tanzania mainland to the year 2025 - under either a business as usual or a green development scenario. In the business as usual scenario, no productivity gain is expected, cultivated land expands by ca. 2% per year (up to 88,808 km2), with large impacts on woodlands and wetlands. Despite legal protection, encroachment of natural forest occurs along reserve borders. Additional wood demand leads to degradation (i.e. loss of tree cover and biomass) up to 80,426 km2 of wooded land. The alternative green economy scenario envisages decreasing degradation and deforestation with increasing productivity (+10%) and implementation of Payment for Ecosystem Service schemes. In this scenario, cropland expands by 44,132 km2 and the additional degradation is limited to 35,778 km2. This scenario development framework captures perspectives and knowledge across a diverse range of stakeholders and regions. Although further effort is required to extend its applicability, improve users’ equity, and reduce costs the resulting spatial outputs can be used to inform national level planning and policy implementation associated with sustainable development, especially the REDD+ climate mitigation strategy.

In defense of fences

![Figure][1] PHOTOS: (DOGS) ROGER DE LA HARPE/WWW.AFRICAIMAGERY.COM; (ELEPHANTS) LAUREN EVANS/WWW.GEOG.CAM.AC.UK/PEOPLE/L.EVANS AND WWW.SPACEFORGIANTS.ORG Human-driven habitat fragmentation reduces global biodiversity and ecosystem functioning ([ 1 ][2]). R. Woodroffe et al. (“To fence or

The role of traditional coffee management in forest conservation and carbon storage in the Jimma Highlands, Ethiopia

Abstract Ethiopia has lost 90% of its forest extent. Remnant patches in the southwest are often semi-forest coffee (SFC), a system whereby coffee is managed beneath the canopy. Here, we (1) quantify aboveground live carbon (AGC) stored by trees in SFC and other land use types in the Jimma Highlands; and (2) determine coffee farmers’ preference for canopy shade trees, and the resulting differences in carbon storage. We surveyed twenty coffee farmers and assessed thirty-one 1-ha vegetation plots across a 23.6-km transect. The most preferred shade species were Albizia gummifera, Acacia abyssinica, Millettia ferruginea and Cordia africana, which together accounted for 42% AGC in SFC and 12% in natural forests. These species had broad size class distributions, while the least preferred had scant representation in lower size classes. SFC stores significantly more AGC (61.5 ± 25.0 t ha−1, mean ± SE) than woodland, pasture and cropland, significantly less than plantation and slightly less than natural forest (82.0 ± 32.1 t ha−1). If SFC was converted to cropland, then 59.5 t ha−1 would be released, at a social cost of US

Views from two mountains: exploring climate change impacts on traditional farming communities of Eastern Africa highlands through participatory scenarios

2892–4225 ha−1. Carbon-payment schemes (e.g. REDD+) may, therefore, play a role in conserving these forests and associated biodiversity and livelihoods into the future.

Tropical forest canopies and their relationships with climate and disturbance: results from a global dataset of consistent field-based measurements

African mountains are characterized by high levels of biodiversity and provide ecosystem services to millions of people. Due to steep environmental gradients, growing human populations and geographical isolation, these coupled socio-ecological systems are highly vulnerable to climate change impacts. The capacity of local stakeholders to anticipate future changes and to assess their potential impacts is paramount for enhancing adaptation and resilience. Here we apply a participatory scenario development framework in two parts of the Eastern Afromontane Biodiversity Hotspot: Taita Hills in Kenya and Jimma rural area in Ethiopia. In each area, we facilitated local stakeholders in envisioning adaptation scenarios under projected climate changes by mid-21st century, and assessed the potential impacts of these pathways on land use and land cover. In the Taita Hills, under a business-as-usual scenario, human population and activities concentrate at high elevation, triggering cascade effects on remnant forest cover, biodiversity and ecosystem services. Alternative adaptation scenarios envisage reforestation associated with either improved agricultural practices or ecosystem restoration. In the Jimma area, rising temperatures are expected to disrupt traditional coffee production under a business-as-usual scenario, resulting in the loss of coffee-forest canopies and reduction of forest-dependent biodiversity. Alternative adaptation scenarios envisage either expansion of commercial coffee plantations or expansion of agroforestry, including traditional coffee farming. In the both Taita and Jimma, adaptation pathways present trade-offs between provisioning, supporting and regulating services, and between livelihoods and biodiversity conservation. Our findings encourage the use of multidisciplinary, bottom-up approaches for developing locally tailored, climate-smart and sustainable adaptation pathways.