Abubakari H. Munna, Nyambilila A. Amuri, Proches Hieronimo, Dino A. Woiso. (2023). Modelling ecological niches of Sclerocarya birrea subspecies in Tanzania under the current and future climates. Silva Fennica vol. 57 no. 3 article id 23009. https://doi.org/10.14214/sf.23009

Keywords: climate change; conservation; GIS; agroforestry; domestication; MaxEnt; protected areas network

Highlights: Tanzania harbors ecological niches of Sclerocarya birrea (S. birrea) subsp. caffra, multifoliata and birrea in the eastern, southern-central-northern, and northeastern part of the country, covering 184 814 km², 139 918 km² and 28 446 km² of Tanzania’s land area, respectively; Ecological niches will contract under future warming climates; Currently, significant parts of ecological niches for Sclerocarya birrea subspecies are beyond Tanzania’s protected areas network.

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The information on ecological niches of the Marula tree, Sclerocarya birrea (A. Rich.) Horchst. subspecies are needed for sustainable management of this tree, considering its nutritional, economic, and ecological benefits. However, despite Tanzania being regarded as a global genetic center of diversity of S. birrea, information on the subspecies ecological niches is lacking. We aimed to model ecological niches of S. birrea subspecies in Tanzania under the current and future climates. Ecological niches under the current climate were modelled by using ecological niche models in MaxEnt using climatic, edaphic, and topographical variables, and subspecies occurrence data. The Hadley Climate Center and National Center for Atmospheric Research's Earth System Models were used to predict ecological niches under the medium and high greenhouse gases emission scenarios for the years 2050 and 2080. Area under the curves (AUCs) were used to assess the accuracy of the models. The results show that the models were robust, with AUCs of 0.85–0.95. Annual and seasonal precipitation, elevation, and soil cation exchange capacity are the key environmental factors that define the ecological niches of the S. birrea subspecies. Ecological niches of subsp. caffra, multifoliata, and birrea are currently found in 30, 22, and 21 regions, and occupy 184 814 km², 139 918 km², and 28 446 km² of Tanzania's land area respectively, which will contract by 0.4–44% due to climate change. Currently, 31–51% of ecological niches are under Tanzania’s protected areas network. The findings are important in guiding the development of conservation and domestication strategies for the S. birrea subspecies in Tanzania.

Munna, Department of Soil and Geological Sciences, Sokoine University of Agriculture, P.O. Box 3008, Morogoro, Tanzania https://orcid.org/0000-0001-8858-0457 E-mail: amabmunna81@gmail.com
Amuri, Department of Soil and Geological Sciences, Sokoine University of Agriculture, P.O. Box 3008, Morogoro, Tanzania https://orcid.org/0000-0003-3092-3458 E-mail: namuri@sua.ac.tz
Hieronimo, Department of Agricultural Engineering, Sokoine University of Agriculture, P.O. Box 3003 Morogoro, Tanzania https://orcid.org/0000-0002-4450-5073 E-mail: phmusigula@gmail.com
Woiso, Department of Biosciences, Sokoine University of Agriculture, P.O. Box 3038 Morogoro, Tanzania E-mail: dino@sua.ac.tz

article id 10441, category Research article

Dipak Mahatara, Amul K. Acharya, Bishnu P. Dhakal, Dipesh K. Sharma, Sunita Ulak, Prashant Paudel. (2021). Maxent modelling for habitat suitability of vulnerable tree Dalbergia latifolia in Nepal. Silva Fennica vol. 55 no. 4 article id 10441. https://doi.org/10.14214/sf.10441

Keywords: rosewood; satisal; distribution mapping; environmental variables; Maxent modelling

Highlights: Dalbergia latifolia is a vulnerable species of Nepal with very few conservation priorities; Habitat suitability modelling for this species is essential to endorse different conservation interventions; 43 presence locations and different environmental variables were retained for model prediction in Maxent; Province 2 was found most suitable habitat for the growth of D. latifolia, with western most province as unsuitable.

Abstract | Full text in HTML | Full text in PDF | Author Info

Dalbergia latifolia Roxb., commonly known as rosewood, is one of the highly valuable tropical timber species of Nepal. The tree species was widely distributed in the past, however, over-exploitation of natural habitat, deforestation, forest conversion for agriculture, illegal logging and the invasion of alien species resulted in the classification of this species as vulnerable by the IUCN (International Union for Conservation of Nature) category. So, the prediction of habitat suitability and potential distribution of the species is required to develop restoration mechanisms and conservation interventions. In this study, we modelled the suitable habitat of D. latifolia over the entire possible range of Nepal using a Maxent model. We compiled 23 environmental variables (19 bioclimatic, 3 topographic and a vegetative layer), however, only 12 least correlated variables along with 43 spatially representative presence locations were retained for model prediction. We used a receiver operating characteristic (ROC) curve to assess the model’s performance and a Jackknife procedure to evaluate the relative importance of predictor variables. The model was statistically significant with an area under the curve (AUC) value of 0.969. The internal Jackknife test indicated that elevation was the most important variable for the model prediction with 71.3% contribution followed by mean temperature of driest quarter (9.8%). The most (>0.6) suitable habitat for the D. latifolia was 235 484 hectares with large sections of area in two provinces whereas, the western most provinces were not suitable for D. latifolia as per Maxent model. The information presented here can provide a framework for nature conservation planning, monitoring and habitat management of this rare and endangered species.

Mahatara, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: honeystar73@gmail.com
Acharya, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: acharya.amulkumar@gmail.com
Dhakal, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: dhakalbp.shorea@gmail.com
Sharma, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: dipeshsharmadiyu2015@gmail.com
Ulak, Forest Research and Training Centre, Government of Nepal, P.O. Box 3339, Babarmahal, Kathmandu 44600, Nepal E-mail: sunitaulak@gmail.com
Paudel, Agriculture Forestry University, P.O. Box 13712 Rampur, Chitwan, Nepal E-mail: prashant.paudel88@gmail.com

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