A Healthy Park Needs Healthy Vegetation: The Story of Gorongosa National Park in the 21st Century

Abstract

Understanding trends or changes in biomass and biodiversity around conservation areas in Africa is important and has economic and societal impacts on the surrounding communities. Gorongosa National Park, Mozambique was established under unique conditions due to its complex history. In this study, we used a time-series of Normalized Difference Vegetation Index (NDVI) to explore seasonal trends in biomass between 2000 and 2016. In addition, vegetation directional persistence was created. This product is derived from the seasonal NDVI time series-based analysis and represents the accumulation of directional change in NDVI relative to a fixed benchmark (2000–2004). Trends in precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) was explored from 2000–2016. Different vegetation covers are also considered across various landscapes, including a comparison between the Lower Gorongosa (savanna), Mount Gorongosa (rainforest), and surrounding buffer zones. Important findings include a decline in precipitation over the time of study, which most likely drives the observed decrease in NDVI. In terms of vegetation persistence, Lower Gorongosa had stronger positive trends than the buffer zone, and Mount Gorongosa had higher negative persistence overall. Directional persistence also varied by vegetation type. These are valuable findings for park managers and conservationists across the world.

An Evaluation of Vegetation Health in and around Southern African National Parks during the 21st Century (2000–2016)

“…However, human populations have often been moved out of national parks and into the buffer zones. Therefore, the landscape in buffer zones is often more affected than in parks [54]. This is supported by our findings when comparing vegetation persistence in and out of parks.…”

Vegetation Dynamics and Climatological Drivers in Ethiopia at the Turn of the Century

“…This methodology enables spatial and temporal specificity by using values at a pixel level and can detect nonlinear trends, which have been noted as an important factor when examining long-term NDVI [13,58]. The DP metric has been applied to evaluate vegetation characteristics, such as the response of drylands to climate variability, changes in biomass in and around protected areas, and identification of regions vulnerable to anthropogenic and environmental causes of change, phenomena that are critical to socioecological resiliency in coupled natural-human systems [35,36,38,59]. The mapped results of this analysis establish which areas exhibit persistent change in NDVI and should therefore be investigated more closely to identify drivers of the observed vegetation dynamics.…”

“…This study uses the NDVI directional ersistence metric to evaluate nonlinear trends in vegetation greenness for the early 21st century across Ethiopia, on a seasonal basis. This metric has been used in a variety of regions to measure vegetation health, ecosystem suitability, and land-cover stability [35][36][37][38].…”

Monitoring of Vegetation Disturbance around Protected Areas in Central Tanzania Using Landsat Time-Series Data

“…The disturbance maps (Figures 5 and 8) highlight the variations in the disturbance patterns and extent across the Ruaha-Rungwa landscape. Although the savannah and overall biophysical environment certainly partially explain the variability in the disturbance patterns [77], differences in management approaches play central roles in explaining the patterns observed in the surroundings of the RKMGR and RNP. The area adjacent to the boundary of the RKMGR is not under legal protection; thus, it is vulnerable to conversion to other land uses that are not compatible with the conservation purpose of the PA.…”