Skip to main content
Log in

Assessment of causes and future deforestation in the mountainous tropical forest of Timor Island, Indonesia

  • Published:
Journal of Mountain Science Aims and scope Submit manuscript

Abstract

The Mutis-Timau Forest Complex, one of the remaining mountainous tropical forest areas in Timor Island, eastern Indonesia that covers an area of 31,984 ha, tends to decrease gradually. Efforts to secure mountain forest functions and counteract the negative impact of declining forest areas are often constrained by data uncertainty on factors contributing to deforestation. For this reason, this study attempts to develop models of deforestation and predict future deforestation in the Mutis-Timau Forest Complex. We constructed models of deforestation that describe the relationship between deforestation and factors contributing to deforestation using spatial statistical models. In this model, we used the deforestation data for the 1987–2017 period obtained from a previous study as dependent variables and the potential causes of deforestation generated from Geographic Information System spatial analysis as independent variables. Using the probability of deforestation derived from the model, we predicted future deforestation under two different scenarios, namely, business-as-usual (as the reference scenario) and reducing emission from deforestation and forest degradation. Our findings showed that a positive relationship exists between probability of deforestation, distance to the settlement, and population density variables, whereas a negative relationship exists between likelihood of deforestation, elevation, slope, distance to the road, distance to the savanna, and forest management unit variables. During the 2017–2030 period, under the business-as-usual scenario, the Mutis-Timau Forest Complex will lose 1327.65 ha in forest area with an annual deforestation rate of 0.54%. Meanwhile, under the reducing emission from deforestation and forest degradation scenario, the overall forest loss was estimated to be 1237.11 ha with an annual deforestation rate of 0.50%. The predicted area of avoided deforestation in 2017–2030 under the reducing emission from deforestation and forest degradation scenario was 90.54 ha. Such data and information are important for the Mutis-Timau Forest Complex authority in prioritizing actions for combating deforestation and designing appropriate forest-related policies and supporting data for reducing emission from deforestation and forest degradation programme or other incentive schemes in reducing deforestation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Agarwal C, Green GM, Grove JM, et al. (2002) A Review and Assessment of Land-Use Change Models: Dynamics of Space, Time, and Human Choice. Gen. Tech. Rep. NE-297. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. pp 1–61. https://doi.org/10.2737/NE-GTR-297

    Google Scholar 

  • Ahmad A, Saleh MB, dan Rusolono T (2016) Model Spasial Deforestasi di KPHP Poigar, Provinsi Sulawesi Utara. Jurnal Penelitian Kehutanan Wallacea 5 (2): 159–169. (In Indonesia)

    Article  Google Scholar 

  • Alcamo J (2008) Introduction: the Case for Scenarios of The Environment. In: J. Alcamo (ed.), Developments in Integrated Environmental Assessment: Environmental Futures-The practice of Environmental Scenario Analysis. Amsterdam: Elsevier. pp 1–12. https://doi.org/10.1016/S1574-101X(08)00401-8

    Google Scholar 

  • Apan AA, Peterson JA (1998) Probing Tropical Deforestation: The use of GIS and statistical analysis of georeferenced data. Applied Geography 18(2): 137–152. https://doi.org/10.1016/S0143-6228(98)00004-6

    Article  Google Scholar 

  • Bavaghar MP (2015) Deforestation Modelling using logistic regression and GIS. Journal of Forest Science 61(5):193–199. https://doi.org/10.17221/78/2014-JFS

    Article  Google Scholar 

  • BMKG-Badan Meteorologi, Klimatologi dan Geofisika (2019) Data Iklim Online - Pusat Database - BMKG [Climate Data Online]. https://doi.org/dataonline.bmkg.go.id/home (Accessed on 11 May 2019) (In Indonesia)

    Google Scholar 

  • BPS-Badan Pusat Statistik (2016) Persentase Rumah Tangga Menurut Provinsi dan Bahan Bakar Utama untuk Memasak Tahun 2001, 2007–2016 [Percentage of Households by Province and Main Fuel for Cooking in 2001, 2006–2017]. https://doi.org/www.bps.go.id/statictable/2014/09/10%2000:00:00 /1364/persentase-rumah-tangga-menurut-provinsi-dan-bahan-bakar-utama-untuk-memasak-tahun-2001-2007-2016. html (Accessed on 01 August 2018) (In Indonesia)

    Google Scholar 

  • Briassoulis H (2000) Analysis of land use change: theoretical and modelling approaches. The Web Book of Regional Science (ed. S. Loveridge). Regional Research Institute, West Virginia University. Available online at: https://doi.org/www.rri.wvu.edu/WebBook/Briassoulis/contents.htm (Accessed on 01 July 2018)

    Google Scholar 

  • Bush J (2011) Constructing reference levels for REDD+: Strenghts and limitations of economic modeling. UNFCCC SBSTA Expert Meeting on Reference Levels November 2011. Bonn, Germany. https://doi.org/www.forestcarbonpartnership.org/sites/fcp/files/Documents/PDF/Nov2011/Reference%20levels%20workshop%20FCPF%2011%209%2011.pdf (Accessed on 01 August 2018)

    Google Scholar 

  • Chakravarty S, Ghosh S, Suresh C (2011) Deforestation: Causes, Effects and Control Strategies. In: D. D. C. A. Okia (ed.), Global Perspectives on Sustainable Forest Management. pp 3–29. https://doi.org/10.5772/33342

    Google Scholar 

  • Coe MT, Marthews TR, Costa MH, et al. (2013) Deforestation and climate feedbacks threaten the ecological integrity of south-southeastern Amazonia. Philosophical Transactions of the Royal Society B 368: 20120155. https://doi.org/10.1098/rstb.2012.0155 ESRI — Environmental Systems Research Institute (2016) ArcGIS Release 10.4.1. Redlands, CA.

    Article  Google Scholar 

  • Elz I, Tansey K, Page SE, et al. (2015) Modelling Deforestation and Land Cover Transition of Tropical Peatland in Sumatra, Indonesia Using Remote Sensed Land Cover Data Set. Land 4: 670–687. https://doi.org/10.3390/land4030670

    Article  Google Scholar 

  • Farida WR, Triono T, Handayani TH, et al. (2005) Pemilihan Jenis Tumbuhan Sumber Pakan dan Tempat Bersarang Kuskus (Phalanger sp.) di Cagar Alam Gunung Mutis, NTT [Feed Plants Selection and Nesting Site of Cuscus (Phalanger sp.) in the Gunung Mutis Nature Reserve, East Nusa Tenggara]. Biodiversitas, Vol 6, No.1, pp. 50–54. https://doi.org/dx.doi.org/10.13057/biodiv/d060110 (In Indonesia)

    Article  Google Scholar 

  • Fisher L, Moeliono I, Wodicka S (2003) The Nusa Tenggara Upland, Indonesia: Multiple-site lessons in conflict management. In: D. Buckles (ed.), Cultivating Peace — Conflict and Collaboration in Nature Resources Management. Ottawa, Canada: International Development Research Center (IDRC). Available online at: https://doi.org/lib.icimod.org/record/10360/files/1344.pdf, accessed on 01 August 2018.

    Google Scholar 

  • FORCLIME — Forest and Climate Change Programme (2015) Frequently Ask Questions (FAQ) Forest Management Unit (FMU). https://doi.org/www.forclime.org/documents/Brochure/English/FAQ%20FMU_English.pdf, accessed on 08 May 2019.

    Google Scholar 

  • Gaveau DLA, Linkie M, Suyadi, et al. (2009) Three decades of deforestation in southwest Sumatra: Effects of coffe prices, law enforcement and rural poverty. Biological conservation 142: 597–605. https://doi.org/10.10016/j.biocon.2008.11.024

    Article  Google Scholar 

  • Geist HJ, Lambin EF (2002) Proximate Causes and Underlying Driving Forces of Tropical Deforestation. BioScience 52(2): 142–150. https://doi.org/10.1641/0006-3568(2002)052[0143:PCAUDF]2.0.CO;2

    Article  Google Scholar 

  • Geist HJ, Lambin EF (2001) What drives tropical deforestation? A meta-analysis of proximate and underlying causes of deforestation based on subnational case study evidence. LUCC International Project IV. International Human Dimensions Programme on Global Environmental Change (IHDP) V. International Geosphere-Biosphere Programme (IGHP) VI. LUCC Report Series 4. pp 1–116.

    Google Scholar 

  • Geoghegan J (1998) “Socializing the Pixel” and “Pixelizing the Social” in Land-Use and Land-Cover Change. People and Pixels: Linking Remote Sensing and Social Science. National Academy Press. Whasington DC. pp 1–256. https://doi.org/10.17226/5963

    Google Scholar 

  • Haliuc A, Feurdean A, Mindrescu M, et al. (2018) Impact of forest loss in the eastern Carpathian Mountain: linking remote sensing and sediment changes in a mid-altitude catchment (Red lake, Romania). Regional Environmental Change. https://doi.org/10.1007/s10113-018-1416-5

    Google Scholar 

  • Haggith M, Iv S, Muetzelfeldt RI, et al. (2003) Modelling Decision-making in Rural Communities at the Forest Margin. Small-scale Forest Economics, Management and Policy 2(2): 241–258.

    Google Scholar 

  • Hosmer DW, Lemeshow S (2000) Applied Logistic Regression (2nd Edition). John Wiley and Sons, Inc., New York. USA. pp 1–375. https://doi.org/10.1002/0471722146

    Book  Google Scholar 

  • Hosonuma N, Herold M, De Sy V, et al. (2012) An Assessment of deforestation and forest degradation drivers in developing countries. Environmental Research Letter 7: 044009. https://doi.org/10.1088/1748-9326/7/4/044009

    Article  Google Scholar 

  • Howell S, Bastiansen E (2015) REDD+ in Indonesia 2010-2015: Report of a Collaborative Anthropological Research Programme. Department of Social Anthropology University of Oslo. Norwegia. pp 1–25

    Google Scholar 

  • Hoyos L, Cabido M, Cingolani A. (2018) A multivariate approach to study drivers of land-cover changes through remote sensing in the Dry Chaco of Argentina. ISPRS International Journal of Geo-Information 7(5): 170. https://doi.org/10.3390/ijgi7050170

    Article  Google Scholar 

  • Htun NZ, Mizoue N, Yoshida S (2013) Changes in Determinants of Deforestation and Forest Degradation in Popa Mountain Park, Central Myanmar. Environmental Management 51: 423–434. https://doi.org/10.1007/s00267-012-9968-5.

    Google Scholar 

  • Huettner M, Lemans R, Kok K, et al. (2009) A comparison of baseline methodologies for ‘Reducing Emissions from Deforestation and Degradation’. Carbon Balance and Management (4): 4. https://doi.org/10.1186/1750-0680-4-4

    Google Scholar 

  • IBM Corp. (2015) IBM SPSS Regression 23. Armonk, NY: IBM Corp. https://doi.org/public.dhe.ibm.com/software/analytics/spss/documentation/statistics/23.0/en/client/Manuals/IBM_SPSS_Regression.pdf (Accessed on 01 March 2019)

    Google Scholar 

  • Kaimovitz D, Angelsen A (1998) Economic model of deforestation: A review. Central for International Forestry Research, Bogor. Indonesia. https://doi.org/10.17528/cifor/000341

    Google Scholar 

  • Kanade R, John R (2018) Topographical influence on recent deforestation and degradation in the Sikkim Himalaya in India; Implications for conservation of East Himalayan broadleaf forest. Applied Geography: 85–93. https://doi.org/10.1016/j.apgeog.2018.02.004

    Google Scholar 

  • KLHK — Kementerian Lingkungan Hidup dan Kehutanan. Direktorat Jenderal Pengendalian Perubahan. Direktorat Inventarisasi GRK dan Monitoring, Pelaporan, Verifikasi (2018). Laporan Inventarisasi Gas Rumah Kaca, Monitoring, Pelaporan, dan Verifikasi Nasional Tahun 2017 [National Report of Greenhouse Gas Inventory Report and Monitoring, Reporting and Verification in 2017]. Kementerian Lingkungan Hidup dan Kehutanan, Jakarta, Indonesia (In Indonesia)

    Google Scholar 

  • Koomen E, Stillwell J (2007) Modelling land use: Theories and methods. In Koomen, E., Stilwell, J., Bakema, A., and Scholten, H.J. (Eds.). Modelling Land-Use Change: Progress and Applications. Geo Journal Library 90: 1–21.

    Google Scholar 

  • Kurniadi R, Purnomo H, Wijayanto H, et al. (2017) Model Pengelolaan Ternak di Sekitar Hutan Gunung Mutis dan Dampaknya terhadap Kelestarian Hutan [Livestock Management Models around Mt. Mutis Forest and Its Impact on Forest Sustainability]. Jurnal Ilmu Kehutanan, 11: 156–172. (In Indonesia)

    Article  Google Scholar 

  • Kissinger G, Herold M, De Sy V (2012) Drivers of Deforestation and Forest Degradation: A Synthesis Report for REDD+ Policymakers. Lexeme Consulting, Vancouver Canada. pp 1–46.

    Google Scholar 

  • Lentz C, Malo M, Bowe M (1998) Environmental Management in Gunung Mutis. International Association for the Study of Common Property, 10–14 June. Vancouver, Canada.

    Google Scholar 

  • Linkie M, Rood E, Smith RJ (2010) Modelling the effectiveness of Enforcement strategies for avoiding tropical deforestation in Kerinci Seblat National Park, Sumatra. Biodiversity Conservation 19: 973–984. https://doi.org/10.1007/s10531-009-9754-8

    Article  Google Scholar 

  • Linkie M, Smith RJ, Williams NL (2004) Mapping and predicting deforestation patterns in the lowlands of Sumatra. Biodiversity and Conservation 13: 1809–1818.

    Article  Google Scholar 

  • Mardiastuti A (2012) The role of UN_REDD in the Development of REDD+ in Indonesia, Vol. III: Highlight of REDD+ Related Projects in Indonesia. Kemenhut RI, UN-REDD, FAO, UNDP, UNEP. Jakarta, Indonesia. pp 1–96.

    Google Scholar 

  • Mertens B, Lambin EF (2000) Land-Cover-Change Trajectories in Southern Cameroon. Annals of Association of American Geographers 90(3): 467–494.

    Article  Google Scholar 

  • Mertens B, Kaimowitz D, Puntodewo A, et al. (2004) Modelling Deforestation at Distinct Geographic Scales and Time Periods in Santa Cruz, Bolivia. International Regional Science Review 27(3): 271–296. https://doi.org/10.1177/0160017604266027

    Article  Google Scholar 

  • Mon MS, Mizoue N, Htun NZ, et al. (2012) Estimating forest canopy density of tropical mixed deciduous vegetation using Landsat data: a comparison of three classification approaches. International Journal of Remote Sensing 33(4): 1042–1057. https://doi.org/10.1080/01431161.2010.549851

    Article  Google Scholar 

  • NRC-National Research Council (2013) Advancing Land Change Modeling: Opportunities and Research Requirements. Washington, DC: National Academies Press. pp 1–142

    Google Scholar 

  • Parker DC, Manson SM, Janssen MA, et al. (2002) Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change?: A Review Forthcoming. Workshop on Agent-Based Models of Land Use (Nag 56406), 75. https://doi.org/10.1111/1467-8306.9302004

    Article  Google Scholar 

  • Pedraza C, Clerici N, Forero CF, et al. (2018) Zero Deforestation Agreement Assessment at Farm Level in Columbia Using ALOS PALSAR. Remote Sensing. https://doi.org/10.3390/rs10091464

    Google Scholar 

  • Price MF, Gratzer G, Duguma LA, et al. (Eds) (2011) Mountain Forests in a Changing World — Realizing Values, addressing challenges. Published by FAO/MPS and SDC, Rome.

    Google Scholar 

  • Pujiono E, Sadono R, Hartono, et al. (2019) A three decades assessment of forest cover change in the mountanious tropical forest of Timor island, Indonesia. Journal of Tropical Forest Management 25(1): 51–64. https://doi.org/10.7226/jtfm.5.1.51

    Google Scholar 

  • Pujiono E, Lee WK, Kwak DA, et al. (2011) Assessing the extent and rate of deforestation in the mountanious tropical forest. Korean Journal of Remote Sensing 27(3): 315–328. https://doi.org/10.7780/kjrs.2011.27.3.315

    Article  Google Scholar 

  • Purwanto J, Rusolono T, Prasetyo LB (2015) Spatial Model of Deforestation in Kalimantan from 2000 to 2013. Journal of Tropical Forest Management 21 (3): 110–118. https://doi.org/10.7226/jtfm.21.3.110

    Google Scholar 

  • Serneels S, Lambin EF (2001) Proximate causes of land-use change in Narok District, Kenya: a spatial statistical model. Agriculture, Ecosystems and Environment 85: 65–81. https://doi.org/10.1016/S0167-8809(01)00188-8

    Article  Google Scholar 

  • Shu GN (2003) Detection and analysis of land cover dynamics in moist tropical rainforest of South Cameroon. Master Thesis, International Institute for Geo-Information Science and Earth Observation, Enshede, The Netherland.

    Google Scholar 

  • Sumanto SE, Pujiono E (2009) Pengelolaan sumber daya alam secara tradisional di Timor Barat: Studi sosio-ekologi di Kabupaten Timor Tengah Selatan [Traditional nature resources management: a socio-ecological study in Timor Tengah Selatan district] s. Info Sosial dan Ekonomi Kehutanan 9(3): 179–186. (In Indonesia)

    Google Scholar 

  • Suwarno A, Hein L, Sumarga E (2015) Governance, Decentralisation and Deforestation: The Case of Central Kalimantan Province, Indonesia. Quarterly Journal of International Agriculture 54(1): 77–100.

    Google Scholar 

  • Swart R (2016) Monitoring 40 Years of land Use Change in the Mau Forest Complex, Kenya. Thesis. Wageningen University, Wageningen, The Netherland.

    Google Scholar 

  • Tacconi L (2003) Fires in Indonesia: Causes, Cost and Policy Implications. CIFOR Occasional Paper No. 38. CIFOR, Bogor-Indonesia. https://doi.org/www.cifor.org/publications/pdf_files/OccPapers/OP-038.pdf (Accessed on 16 May 2019)

    Google Scholar 

  • Tole L (2002) An estimate of forest cover extent and change in Jamaica using Landsat MSS data. International Journal of Remote Sensing 23(1): 91–106. https://doi.org/10.1080/01431160010014837

    Article  Google Scholar 

  • Turner BL II, Skole D, Sanderson S, et al. (1995) Land-Use and Land-Cover Change; Science/Research Plan. IGBP Report No.35, HDP Report No.7. IGBP and HDP, Stockholm and Geneva.

    Google Scholar 

  • United Nation-REDD PROGRAMME (2010) FAQs: What is REDD? https://doi.org/www.unredd.net/index.php?view=download&alias=6207-un-redd-faqs-and-answers-june-2010-1-6207&category_slug=additional-resources-1312&option=com_docm_an&Itemid=134, accessed on 03 August 2018.

    Google Scholar 

  • Verburg PH, Schot PP, Dijst MJ, et al. (2004) Land-use change modelling: current practice and research priorities. Geo Journal 61: 309–324.

    Google Scholar 

  • Wang C and Myint S (2016) Environmental concerns of deforestation in Myanmar 2001–2010. Remote Sensing 8(9): 728. https://doi.org/10.3390/rs8090728

    Article  Google Scholar 

  • Wijaya PA, Saleh MB, Tiryana T (2015) Spatial Model of Deforestation in Jambi Province for the Period 1990–2011. Journal of Tropical Forest Management 21 (3): 128–137. https://doi.org/10.7226/jtfm.21.3.128

    Google Scholar 

  • World Bank (2016) The Cost of Fire: an Economic Analysis of Indonesia’s 2015 Fire Crisis. Indonesia Sustainable Landscapes Knowledge Note: 1. the Government of Norway and the Embassy of Denmark through the World Bank’s REDD+ Support Facility (RSF). The World Bank, Jakarta-Indonesia. https://doi.org/pubdocs.worldbank.org/en/643781465442350600/Indonesia-forest-fire-notes.pdf, accessed on 16 May 2019.

    Google Scholar 

  • Wulandari R (2011) Pemodelan Spasial Deforestasi di Pulau Lombok, Nusa Tenggara Barat, Periode 2000–2010 [Spatial Modelling of Deforestation in Lombok Island, Nusa Tenggara Barat for the period of 2000–2010]. Skripsi, Institut Pertanian Bogor, Bogor, Indonesia. (In Indonesian)

    Google Scholar 

Download references

Acknowledgement

This study is funded by the Ministry of Environment and Forestry Republic of Indonesia through the research funding assistance program. We express our gratitude to BBKSDA NTT, the local government of TTU - TTS districts and people of the Mutis Timau forest fringe villages for research permit and assistance in data collection. We thank to Muhammad Alif K. Sahide for comments on an earlier version of the manuscript in Scientific Writing Workshop organized by Faculty of Forestry Universitas Gadjah Mada. We are also grateful to Badan Penerbit dan Publikasi Universitas Gadjah Mada and Enago for language editing service.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ronggo Sadono.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pujiono, E., Sadono, R., Hartono et al. Assessment of causes and future deforestation in the mountainous tropical forest of Timor Island, Indonesia. J. Mt. Sci. 16, 2215–2231 (2019). https://doi.org/10.1007/s11629-019-5480-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11629-019-5480-1

Keywords

Navigation