Mau Forest, a major forest reserve in Kenya, has experienced anthropogenic disturbances through encroachment and forest fires. This study aimed at comparing the soil carbon stocks in different forest management types as well as how seasonal climatic changes influence its dynamics. The study was undertaken in the Eastern Mau block (Sururu) which forms part of the greater Mau Forest Complex. The forest management interventions have been in place for over 15 years with disturbed (fire) natural forest experiencing fires in 2005, 2007, and 2014 while cypress plantations were established in 1994. A nested experimental design was used in data collection, where thirty-two sample plots were nested into four blocks each measuring 100 m² delineated by forest management types (disturbed by fire, natural forest, undisturbed natural forest, plantation, and glades). In each plot, data on soil carbon stocks, soil bulk density, soil moisture, and temperature were collected for both dry and wet seasons. Data collection was carried out between November 2015 and December 2016. The results indicated that there were no significant differences in the carbon stocks among the forest management types (F₄,₁₆ = 0.61, ). However, seasonal weather changes significantly affected the amount of carbon stocks among the forest management types (F₄,₁₆ = 0.61, ). The undisturbed natural forest had the highest mean soil carbon stocks, while the plantation forest had the lowest as follows: undisturbed natural forest (135.17 ± 35.99.0 Mg·C^−ha), disturbed natural forest by fire (134.52 ± 38.11 Mg·C^−ha), glades (122.4 ± 64.9 Mg·C^−ha), and plantation forest (116.51 ± 39.77 Mg·C^−ha). Furthermore, the undisturbed natural forest management had the highest bulk density (0.66 g/cm³), while the disturbed (fire) natural forest had the lowest (0.59 g/cm³). These values were low compared to most normal mineral soils which have a bulk density of between 1.0 g/cm³ and 1.5 g/cm³. There was a significant ( ) relationship between seasonal weather (temperature) changes and soil carbon stocks under different forest management types with the relationship being stronger in soils under glades (r² = 0.62) and weak in the undisturbed natural forest (r² = 0.26). In conclusion, forest disturbances have an impact on soil carbon stocks, and for effective management of forest towards climate stabilization, then disturbance should be minimized if not avoided.

This study quantified the influence of temperature, atmospheric relative humidity, and seasonal and tidal variability on soil CO₂ and CH₄ fluxes in mangrove ecosystems on the Southern Swamp and the Pate Islands of the Lamu Archipelago, Kenya. The field measurements were conducted during wet and dry seasons and at varying tidal heights for 2 consecutive years (2023 and 2024). Because measurements were repeatedly collected from permanent plots, mixed-effects models accounting for the repeated sampling structure were used as the primary inferential analyses, while Spearman’s rank correlations and Mann–Whitney U were used to characterize unadjusted bivariate associations and group differences. In the unadjusted analysis, CO₂ fluxes were significantly higher during the dry season than during the wet season (median 3.72 versus 1.91 µmol CO₂ m⁻² s⁻¹; p = 0.020). However, season was not a significant independent predictor of CO₂ flux in the adjusted mixed-effects model. Similarly, CH₄ flux showed a significant positive bivariate association with temperature and a significant negative association with tidal height. In the adjusted mixed-effects model, temperature remained significantly associated with CH₄ flux (β = 2.961, p = 0.045, 95% CI: 0.410–6.064), whereas tidal height was no longer significant. Atmospheric relative humidity did not show a significant independent effect on either gas, and mangrove block showed no significant independent main effect. Overall, the findings indicate that temperature was the principal measured environmental predictor independently associated with CH₄ flux, whereas the observed dry-season increase in CO₂ flux and negative tidal-height association with CH₄ represented unadjusted patterns that were not retained as significant independent main effects after accounting for covariates and repeated measurements. These results underscore the importance of distinguishing exploratory bivariate patterns from adjusted effects when assessing environmental controls on greenhouse gas fluxes in mangrove ecosystems.

Mangrove ecosystems are globally recognized for their exceptional capacity to sequester and store carbon, regulate coastal processes, and support biodiversity and local livelihoods. However, increasing anthropogenic disturbances continue to degrade mangrove ecosystems. Moreover, there remains inadequate understanding of how intact, disturbed, and restored mangrove systems differ in their capacity to store soil organic carbon (SOC) under varying geomorphological and hydrological conditions. This study examined the influence of disturbance, community types and blocking management approaches on SOC stocks in mangroves of the Lamu Archipelago, Kenya, with emphasis on intact, disturbed, and restored sites across different ecological settings. Soil cores were collected from Pate Island and Southern Swamp mangrove ecosystems at depths of 0–50 cm to determine soil bulk density and total organic carbon stocks. Data were analysed using non-parametric statistical tests and linear mixed-effects models to assess variations in SOC stocks across forest disturbance categories, mangrove community types, sediment depths, and mangrove blocks. The mixed-effects model revealed significant effects of forest disturbance status (LR χ² = 120.843, p < 0.001), sediment depth (LR χ² = 78.612, p < 0.001), mangrove community type (LR χ² = 8.248, p = 0.004), and mangrove blocks (LR χ² = 18.973, p < 0.001) on SOC stocks. Post-hoc comparisons indicated significantly higher SOC stocks in intact mangroves than in disturbed and restored mangroves (p < 0.001), with no significant difference between disturbed and restored ecosystems (p = 0.188). SOC stocks varied significantly across sediment depths, with the highest stocks recorded at 0–10 cm and the lowest at 30–40 cm. Fringing mangroves exhibited significantly higher SOC stocks than overwash communities (p = 0.004), while Pate Island recorded significantly higher stocks than Southern Swamp (p < 0.001). These findings demonstrate that forest disturbance, mangrove community type, sediment depth, and spatial variability significantly influence SOC storage, highlighting the importance of conserving intact mangroves, strengthening restoration efforts, and incorporating ecological variability into blue carbon accounting and climate change mitigation strategies in Kenya.

Mangrove ecosystems are significant blue carbon sinks but can also act as sources of greenhouse gases, particularly carbon dioxide (CO₂) and methane (CH₄), due to complex sediment biogeochemical processes. This study quantified the influence of seasonal and tidal variability on soil–atmosphere CO₂ and CH₄ fluxes in mangrove ecosystems of the Lamu Archipelago, Kenya. Field measurements were conducted across wet and dry seasons and varying tidal heights, alongside key environmental parameters including temperature and humidity. Non-parametric statistical analyses revealed that CH₄ fluxes were significantly influenced by temperature variability (p < 0.05), whereas CO₂ fluxes were significantly associated with humidity (p < 0.05). Both gases exhibited significant seasonal variation (p < 0.05), with elevated CO₂ emissions during the dry season and higher CH₄ emissions during the wet season, reflecting shifts between aerobic and anaerobic sediment conditions. Tidal height exerted a significant effect on both CO₂ and CH₄ fluxes (p < 0.05), underscoring the role of tidal inundation in regulating redox dynamics and gas exchange processes. These findings demonstrate the strong coupling between climatic and meteorological parameters in controlling mangrove GHG fluxes and highlight the importance of incorporating temporal variability into blue carbon assessments. The study provides empirical data to refine greenhouse gas inventories and improve the representation of tropical coastal wetlands in climate models and mitigation frameworks.