Forest succession in Kibale National Park, Uganda: implications for forest restoration and management

2003 ◽  
Vol 41 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Jeremiah S. Lwanga
Author(s):  
Anu Valtonen ◽  
Eveliina Korkiatupa ◽  
Sille Holm ◽  
Geoffrey Malinga ◽  
Ryosuke Nakadai

Restoration has now emerged as a global priority, with international initiatives such as the “UN Decade on Ecosystem Restoration (2021-2030)”. To fulfil the large-scale global restoration ambitions, an essential step is the monitoring of vegetation recovery after restoration interventions. The aim of this study was to evaluate the utility of remotely-sensed vegetation indices, Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), to monitor the rate of forest regeneration across a tropical forest restoration project area in Kibale National Park, Uganda. As a result, we observed non-linear patterns in NDVI and EVI across the first 25 years of recovery. Both NDVI and EVI increase for the first 10 years of forest regeneration. This “greening” phase could be used as the indicator of successful onset of forest recovery. In particular, the decline of elephant grass, which suppresses the natural regeneration of trees in our area, can be detected as an increase in NDVI. Primary forests differed from the 25-year-old regenerating forests based on the unique combination of low mean and low seasonal variation in EVI. Our results, therefore, suggest that the long-term success of forest restoration could be monitored by evaluating how closely the combination of mean, and degree of seasonal variation in EVI, resembles that observed in the primary forest.


2021 ◽  
pp. 1-11
Author(s):  
Shannon White ◽  
Xinbiao Zhu ◽  
Fanrui Meng ◽  
Scott Taylor ◽  
Charles P.-A. Bourque

Moose (Alces alces L.) browsing in Gros Morne National Park has damaged its balsam fir (Abies balsamea (L.) Mill.)dominated forest. A forest estate model was used to evaluate (i) the impacts of moose browsing and woodcutting on forest succession and (ii) strategies of forest restoration through planting and moose population management. The simulation results show that under current heavy browsing pressure growing stock of balsam fir decreases by 38%, but the area of spruce (Picea mariana (Mill.) BSP and P. glauca (Moench) Voss) increases by 32% over a 100-year planning horizon, compared to that under light browsing scenario which is assumed to be similar to the forest outside the Park due to moose population management. Annual allowable cut (AAC) for the Park’s 19 400 ha domestic harvest area is estimated to be around 120 979 m3 in a light browsing scenario, 21% higher than the sustainable harvest level in a heavy browsing scenario. The model forecasts a 97% reforestation of the Park’s 7 194 ha disturbed area by planting in the heavy browsing scenario, leading to an increase in total forest growing stock by 22% and AAC by 12%. Integration of planting with moose population management could be a more efficient way of restoring forest under high browsing pressure in GMNP.


2021 ◽  
Vol 97 (3) ◽  
pp. 315-325
Author(s):  
Shannon White ◽  
Xinbiao Zhu ◽  
Fanrui Meng ◽  
Scott Taylor ◽  
Charles P.-A. Bourque

Moose (Alces alces L.) browsing in Gros Morne National Park has damaged its balsam fir (Abies balsamea (L.) Mill.)-dominated forest. A forest estate model was used to evaluate (i) the impacts of moose browsing and woodcutting on forest succession and (ii) strategies of forest restoration through planting and moose population management. The simulation results show that under current heavy browsing pressure growing stock of balsam fir decreases by 38%, but the area of spruce (Picea mariana (Mill.) BSP and P. glauca (Moench) Voss) increases by 32% over a 100-year planning horizon, compared to that under light browsing scenario which is assumed to be similar to the forest outside the Park due to moose population management. Annual allowable cut (AAC) for the Park’s 19 400 ha domestic harvest area is estimated to be around 120 979 m3 in a light browsing scenario, 21% higher than the sustainable harvest level in a heavy browsing scenario. The model forecasts a 97% reforestation of the Park’s 7 194 ha disturbed area by planting in the heavy browsing scenario, leading to an increase in total forest growing stock by 22% and AAC by 12%. Integration of planting with moose population management could be a more efficient way of restoring forest under high browsing pressure in GMNP.


2021 ◽  
Vol 14 ◽  
pp. 194008292110147
Author(s):  
Dipto Sarkar ◽  
Colin A. Chapman

The term ‘smart forest’ is not yet common, but the proliferation of sensors, algorithms, and technocentric thinking in conservation, as in most other aspects of our lives, suggests we are at the brink of this evolution. While there has been some critical discussion about the value of using smart technology in conservation, a holistic discussion about the broader technological, social, and economic interactions involved with using big data, sensors, artificial intelligence, and global corporations is largely missing. Here, we explore the pitfalls that are useful to consider as forests are gradually converted to technological sites of data production for optimized biodiversity conservation and are consequently incorporated in the digital economy. We consider who are the enablers of the technologically enhanced forests and how the gradual operationalization of smart forests will impact the traditional stakeholders of conservation. We also look at the implications of carpeting forests with sensors and the type of questions that will be encouraged. To contextualize our arguments, we provide examples from our work in Kibale National Park, Uganda which hosts the one of the longest continuously running research field station in Africa.


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