What question did this study set out to answer?

This research aims to assess spatio-temporal changes in vegetation cover in Nyungwe National Park from 2013 to 2022.

May 10, 20260 citationsOpen Access

Spatio-Temporal Assessment of Vegetation Cover Changes in Nyungwe National Park, Rwanda (2013–2022): Implications for Conservation Management

Key Points

This research aims to assess spatio-temporal changes in vegetation cover in Nyungwe National Park from 2013 to 2022.
Analyzed MODIS NDVI, climate data, and land surface temperature.
Used Sen's slope estimator and Mann-Kendall test for NDVI trends.
Applied Getis-Ord Gi* hotspot analysis to identify spatial changes.
70.9% of NNP showed significant greening, while 28.1% exhibited significant browning (p<0.05).
NDVI–rainfall correlation was negligible (r=0.075, p=0.836), indicating climate had little impact on NDVI variability.
Identified 4,000 ha of decline coldspots and 11,500 ha of recovery hotspots, with edge areas 1.42 times more likely to have decline pixels (chi-squared=36.2, p<0.001).

Abstract

Abstract: Nyungwe National Park (NNP), Rwanda, sustains a montane forest ecosystem of exceptional biodiversity and carbon significance within the Albertine Rift, yet the drivers of its vegetation changes remain poorly characterized at fine spatial scales. This study presents a spatio-temporal assessment of vegetation cover change across NNP from 2013–2022, integrating MODIS NDVI (MOD13A2), CHIRPS rainfall, and MODIS land surface temperature (LST; MOD11A2). Long-term NDVI trends were quantified using Sen's slope estimator and the Mann-Kendall test; climate–vegetation relationships were assessed through Pearson correlation and OLS multiple regression with lagged analysis; and spatial clustering of change was identified via Getis-Ord Gi* hotspot analysis. MODIS-derived trends were independently validated against Landsat 8 OLI imagery (30 m). Results revealed that 70.9% of NNP exhibited significant greening and 28.1% significant browning, with 98% of pixels showing statistically significant change (p<0.05). Despite moderate interannual rainfall variability (CV=8.20%), NDVI remained exceptionally stable (CV=0.68%) a decoupling ratio of approximately 12:1 underscoring the ecosystem's intrinsic buffering capacity. Climate explained virtually none of this variability: NDVI–rainfall correlation was negligible (r=0.075, p=0.836), and the OLS model was non-significant (R²=0.118, p=0.645; n=10 years). Getis-Ord Gi* analysis identified 4,000 ha of 99%-confidence decline coldspots concentrated within 1 km of the northern and southeastern boundaries, and 11,500 ha of recovery hotspots. Edge zones were 1.42 times more likely to contain decline pixels than core areas (chi-squared=36.2, p<0.001). These findings establish that NNP's montane forest is resilient to normal climate variability and that localised degradation is driven primarily by anthropogenic boundary pressure. The study recommends: (1) improved boundary protection with increased patrol frequency; (2) active restoration targeting 4,000 ha of severe-decline coldspots; and (3) strengthened buffer zone policy with structured community engagement. Keywords: Nyungwe National Park; NDVI; Spatio-temporal vegetation change; MODIS; CHIRPS; Mann-Kendall trend test; Sen's Slope; Getis-Ord Gi*; Hotspot analysis; Edge effects; Climate–vegetation relationship; Conservation management; Albertine Rift. Title: Spatio-Temporal Assessment of Vegetation Cover Changes in Nyungwe National Park, Rwanda (2013–2022): Implications for Conservation Management Author: Mr. Telephosa Bakuriramumwami International Journal of Life Sciences Research ISSN 2348-313X (Print), ISSN 2348-3148 (online) Vol. 14, Issue 2, April 2026 - June 2026 Page No: 12-26 Research Publish Journals Website: www.researchpublish.com Published Date: 06-May-2026 DOI: https://doi.org/10.5281/zenodo.20051117 Paper Download Link (Source) https://www.researchpublish.com/papers/spatio-temporal-assessment-of-vegetation-cover-changes-in-nyungwe-national-park-rwanda-20132022-implications-for-conservation-management

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