Kenya Forestry Research Institute

Ecological filters govern how hemiparasites express functional traits, shaping species persistence and ecosystem dynamics in drylands. We investigated how host identity, elevation, and disturbance influence morphological plasticity in Osyris lanceolata, a facultative hemiparasite of conservation concern in Uganda’s semi-arid Karamoja rangelands. Despite broad host availability, O. lanceolata consistently associated with a core group of woody hosts including Rhus natalensis, Euclea racemosa, and Maytenus senegalensis, reflecting deterministic host-driven trait outcomes (Sørensen greater than 0.70). Elevation, coppicing, and spatial arrangement caused pronounced plasticity in stem number, stem diameter, and leaf area, with trade-offs observed between height and thickness under disturbance. These predictable shifts, influenced by both hosts and the environment, reveal mechanisms of hemiparasite adaptation that support nutrient cycling and dryland community dynamics. Considering host specificity, morphological plasticity, and responses to disturbance, O. lanceolata provides a model for understanding functional ecology in hemiparasitic plants. The findings offer guidance for sustaining O. lanceolata populations and their host networks to maintain resilient dryland ecosystems.

The Taita Hills in southeastern Kenya are a critical biodiversity hotspot within the Eastern Arc Mountains, characterized by a complex mosaic of montane forest fragments, exotic plantations, and agroforestry systems transitioning into semi-arid grasslands and Acacia-Commiphora bushland. This landscape with elevations ranging from approximately 750 m to 2200 m exemplifies competing land-use interests, where a growing population and agricultural expansion have historically driven forest and tree cover loss. Accurate monitoring of these biomass dynamics is essential for quantifying carbon stocks, informing climate mitigation strategies, and guiding contemporary conservation and natural forest regeneration efforts.This study employs an extensive multi-temporal dataset to quantify aboveground biomass (AGB) changes across the Taita Hills and adjacent lowlands. We analyzed data from 38 airborne LiDAR flights conducted between 2014 and 2024, covering 1,600 km², with 650 km² of overlapping coverage for change detection. Field-measured AGB plots (2013–2018) and LiDAR data from 2014/2015 were used to generate a baseline AGB map. A Random Forest model, calibrated on this baseline and LiDAR metrics, was then applied to predict AGB from 2022/2024 acquisitions. These predictions were validated using independent field measurements collected in 2024–2025. Finally, we analyzed annual AGB change rates in relation to high-resolution canopy height model changes, elevation zones, and land cover types to characterize spatial AGB dynamics and identify drivers of gain and loss.Preliminary analysis reveals heterogeneous AGB dynamics across the landscape. The highest positive change rates were observed in young forest plantations, while agroforestry systems exhibited modest gains, indicating successful tree retention and maturation. Notably, native montane forest fragments remained relatively stable, with forest cover losses primarily concentrated within exotic plantations. Conversely, localized AGB reductions were identified in foothill areas and along riverine corridors. The multi-temporal LiDAR approach proved robust for capturing these fine-scale spatial patterns. This ongoing analysis will further refine the magnitude and drivers of decadal carbon stock fluctuations, providing critical evidence for landscape-level conservation and climate mitigation strategies in the region.

Abstract The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.

Non-wood forest products (NWFP) present opportunities for diversifying livelihoods in Kenya especially in the arid and semi-arid lands. This paper examines the current status, investment opportunities, challenges, and potential mitigation measures in key non-wood forest product value chains in Kenya in relation to conservation and sustainable development. It focuses on aloe, gums and resins, dyes and tannins, indigenous fruits and, honey and bee products. The study adopted a desk-based literature review methodology, drawing on research outputs from the Kenya Forestry Research Institute (KEFRI) and other scholarly and policy-related sources. A structured value chain lens was used to examine technological, institutional, and infrastructural factors influencing the development of NWFPs. Key findings focusing on current practices, existing technologies, gaps and inefficiencies, infrastructure bottlenecks and opportunities for upgrading are presented, along with lessons learned and recommendations for improving the development of these value chains. Major challenges identified include technological limitations in harvesting and processing, natural resource availability and degradation issues, inadequate technical capacity and extension services, high investment and operational costs, financial constraints, weak market linkages and value addition, and gaps in policy and legal frameworks. Despite these constraints, the review highlights several investment opportunities. These include the development of forest-based bio-enterprises, the expansion of local and international markets, implementation of certification and quality standards, capacity-building and knowledge transfer programs, increasing demand for forest products, and enhanced governance and support through Kenya's devolved government system. The ongoing review of The Forest Conservation and Management Act of 2016 is also noted as a potential enabler of growth in these sectors. This paper offers valuable insights for investors, researchers, policymakers, farmers, students and other stakeholders aiming to support evidence-based planning and the sustainable commercialization of NWFPs in Kenya.

The wood of 38-year-old Liquidambar styraciflua grown in a provenance trial plot in Kenya was studied to determine its physical and mechanical properties as well as the relationship between the modulus of rupture (MOR) and static modulus of elasticity (MOE) of the timber. Mechanical properties determined were MOE, MOR, compression strength parallel to grain, shear strength parallel to grain and Janka hardness. Physical properties determined were moisture content and specific gravity. Physical and mechanical properties of small clear specimens from the L. styraciflua were determined according to British Standards (BS 373:1957) using the Universal Strength Testing Machine. The results were analysed using R statistical software (Version 4.4.2). Three trees were sampled, one from each of the three best-performing L. styraciflua provenances, from trials established in 1986 in Lugari Forest Station, Kakamega County, in western Kenya. The sampled trees were from Honduras, Nicaragua and Guatemala provenances. Tree 1 (Honduras provenance) had the highest average strength for all the properties tested. Tree 6 (Guatemala provenance) had the lowest average strength for MOE, compression strength parallel to grain and hardness. Tree 3 (Nicaragua provenance) had the lowest average strength for MOR. Trees 3 and 6 had similar average strength for shear parallel to the grain. Variations in the strength of the three trees may have been due to their different specific gravities. Average strength values for MOE, MOR, compression strength parallel to the grain, shear strength parallel to the grain, and Janka hardness were 12,399 MPa, 106.3 MPa, 52.3 MPa, 16.6 MPa and 5.8 kN, respectively. There was a significant correlation (P<0.05) between the MOR and MOE of L. styraciflua; the correlation coefficient was 0.7. Machine strength grading may be suitable for the Liquidambar timber due to its relatively high correlation coefficient. Liquidambar styraciflua from this study had superior properties compared to those of the current plantation species in Kenya; cypress, pines and eucalyptus. This study therefore recommends L. styraciflua as a suitable tree species for plantation growing for sawn timber in Kenya. In Kenya, L. styraciflua provenance trials were conducted at an altitude of 1,600 m above sea level. Provenance trials in lower altitudes could also be established to determine the growing range of L. styraciflua within Kenya. Further research to determine the physical and mechanical properties of graded structural timber from the species is necessary for design purposes. Additional studies are also required to assess the wood’s susceptibility and resistance to biological agents.

ABSTRACT This study evaluated commonly used Normalized Burn Ratio (NBR) and Burned Area Index for Sentinel-2 (BAIS2) spectral indices in mapping burn severity using Sentinel-2 satellite data. We also compared the relationships of Field-Based Index (FBI) and Sentinel-2 derived severity indices. The study was carried out in Aberdare Ranges, a designated world heritage site. The Sentinel-2 data for 2017, 2019 and 2022 pre and post fire season were processed for NBR and BAIS2 using GIS platform. Further, a separability index (M) was used to estimate the effectiveness of spectral indices to discriminate among the burn severity classes. One hundred and sixty-five ground plots distributed in high, moderate and low burn severity classes and unburnt areas were used to develop FBI. Our results indicated that differenced NBR performed better compared to differenced BAIS2 in all severity classes. Nonlinear models described the best relationship between FBI and the Sentinel-2-derived spectral indices. The relationships between FBI and dNBR were more robust than that of FBI and dBAIS2. Our studies demonstrate the usefulness of Sentinel-2 satellite data and the superiority of NBR spectral indices in mapping burn severity. We recommend further studies in various vegetation types of Kenya to support wildfire management.

IntroductionAgroecology is increasingly promoted as a pathway to sustainable food production, aiming to maximize natural resource use while minimizing external inputs with harmful environmental effects. Agroecological practices can enhance farm productivity while ensuring environmental sustainability. However, these practices often require higher initial investments compared to business-as-usual (BAU) practices, and their profitability and relative risks are not well studied. This research evaluates the profitability and risk of adopting agroecological practices among wheat farmers in Ethiopia.MethodsWe conducted a deterministic cost-benefit analysis (CBA) incorporating sensitivity and scenario analysis to evaluate the profitability and relative risks associated with three agroecological practices: certified wheat seed, optimal site-specific inorganic fertilizer application rates, and drainage of waterlogged soils. The analysis considered yield uncertainty, market price fluctuations, and implementation variability to provide robust insights for decision-making.ResultsThe deterministic CBA revealed that among the three practices, the use of certified seeds was the most profitable, with a net present value (NPV) of US$ 2,531 ha–1. This was followed by optimal site-specific inorganic fertilizer application, with an NPV of US$ 2,371 ha–1. Drainage of waterlogged soils yielded the lowest profitability, with an NPV of US$ 2,099 ha–1.DiscussionThe results indicate that certified seeds and optimal fertilizer rates offer higher financial returns, making them attractive investments for wheat farmers. However, profitability alone does not guarantee adoption. Other factors, including social and behavioral aspects, influence farmer decisions. Future research should integrate these dimensions to develop comprehensive strategies for promoting agroecological practices.ConclusionAdopting agroecological practices has clear economic benefits for Ethiopian wheat farmers, with certified seeds emerging as the most profitable option. These findings provide evidence for stakeholders to design targeted interventions that maximize returns while addressing barriers to adoption.