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Monitoring Forest-Savanna Dynamics in the Guineo-Congolian Transition Area of the Centre Region of Cameroon

Abstract : Understanding the effects of global change (combining anthropic and climatic pressures) on biome distribution needs innovative approaches allowing to address the large spatial scales involved and the scarcity of available ground data. Characterizing vegetation dynamics at landscape to regional scale requires both a high level of spatial detail (resolution), generally obtained through precise field measurements, and a sufficient coverage of the land surface (extent) provided by satellite images. The difficulty usually lies between these two scales as both signal saturation from satellite data and ground sampling limitations contribute to inaccurate extrapolations. Airborne laser scanning (ALS) data has revolutionized the trade-off between spatial detail and landscape coverage as it gives accurate information of the vegetation’s structure over large areas which can be used to calibrate satellite data. Also recent satellite data of improved spectral and spatial resolutions (Sentinel 2) allow for detailed characterizations of compositional gradients in the vegetation, notably in terms of the abundance of broad functional/optical plant types. Another major obstacle comes from the lack of a temporal perspective on dynamics and disturbances. Growing satellite imagery archives over several decades (45 years; Landsat) and available computing facilities such as Google Earth Engine (GEE) provide new possibilities to track long term successional trajectories and detect significant disturbances (i.e. fire) at a fine spatial detail (30m) and relate them to the current structure and composition of the vegetation. With these game changing tools our objective was to track long-term dynamics of forest-savanna ecotone in the Guineo-Congolian transition area of the Central Region of Cameroon with induced changes in the vegetatio structure and composition within two contrasted scenarios of anthropogenic pressures: 1) the Nachtigal area which is targeted for the dam construction and subject to intense agricultural activities and 2) the Mpem et Djim National Park (MDNP) which has no management plan. The maximum likelihood classification of the Spot 6/7 image aided with the information from the canopy height derived from ALS data discriminated the vegetation types within the Nachtigal area with good accuracy (96.5%). Using field plots data in upscaling aboveground biomass (AGB) form field plots estimates to the satellite estimates with model-based approaches lead to a systematic overestimation in AGB density estimates and a root mean squared prediction error (RMSPE) of up to 65 Mg.ha−1 (90%), whereas calibration with ALS data (AGBALS) lead to low bias and a drop of ~30% in RMSPE (down to 43 Mg.ha−1, 58%) with little effect of the satellite sensor used. However, these results also confirm that, whatever the spectral indices used and attention paid to sensor quality and pre-processing, the signal is not sufficient to warrant accurate pixel wise predictions, because of large relative RMSPE, especially above (200–250 Mg.ha−1). The design-based approach, for which average AGB density values were attributed to mapped land cover classes, proved to be a simple and reliable alternative (for landscape to region level estimations), when trained with dense ALS samples. AGB and species diversity measured within 74 field inventory plots (distributed along a savanna to forest successional gradient) were higher for the vegetation located in the MDNP compared to their pairs in the Nachtigal area. The automated unsupervised long-term (45 years) land cover change monitoring from Landsat image archives based on GEE captured a consistent and regular pattern of forest progression into savanna at an average rate of 1% (ca. 6 km².year-1). No fire occurrence was captured for savanna that transited to forest within five years of monitoring. Distinct assemblages of spectral species are apparent in forest vegetation which is consistent with the age of transition. As forest gets older AGBALS recovers at a rate of 4.3 Mg.ha-1.year-1 in young forest stands (< 20 years) compared to 3.2 Mg.ha-1.year-1 recorded for older forest successions (≥ 20 years). In savannas, two modes could be identified along the gradient of spectral species assemblage, corresponding to distinct AGBALS levels, where woody savannas with low fire frequency store 50% more carbon than open grassy savannas with high fire frequency. At least two fire occurrences in five years is found to be the fire regime threshold below which woody savannas start to dominate over grassy ones. Four distinct plant communities were found distributed along a fire frequency gradient. However the presence of fire-sensitive pioneer forest species in all scenarios of fire frequencies (from low to high fire frequencies) would suggest that the limiting effect of fire on woody vegetation is not sufficient to hinder woody encroachment in the area bringing therefore sufficient humidity required for the establishment of pioneer forest saplings within open savannas. These results have implications for carbon sequestration and biodiversity conservation policies. The maintenance of the savanna ecosystem in the region would require active management actions, and contradicts reforestation goals (REDD+, Bonn challenge, etc.).
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Submitted on : Wednesday, April 13, 2022 - 11:48:06 AM
Last modification on : Thursday, April 21, 2022 - 3:27:54 AM


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Le Bienfaiteur Sagang Takougoum. Monitoring Forest-Savanna Dynamics in the Guineo-Congolian Transition Area of the Centre Region of Cameroon. Ecosystems. Université de Yaoundé 1 (Cameroun), 2022. English. ⟨tel-03528875⟩



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