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  • Balantak; Bangga_Atas; Bangga_Bawah; Bora; Dolago_Bendung; Dolago_Padang; Hek-Bunta; Indonesia; Kalawara; Kamba; Kayu_Agung; Kolonodale; Kulawi; Lalos; Lamadong; Lambunu; Lampasio; Lemusa; Libok; Mayoa; OBSE; Observation; Ogo_Bayas; Ongka_Persatuan; Palolo; Pandayora; Sausu; Singkoyo; Sionyong; Sulawesi Sea; Tada; Tanamea; Tolae; Tuwa; Waru; Wuasa  (1)
  • Bolivia; Amazon; Deforestation; Proximate causes; Spatial analysis; Multinomial logistic regression  (1)
  • ddc:330
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  • 1
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    Proximate causes of deforestation in the Bolivian lowlands: an analysis of spatial dynamics (2018)
    Springer-Verlag | Berlin/Heidelberg
    Details
    Publication Date: 2021-03-29
    Description: Forests in lowland Bolivia suffer from severe deforestation caused by different types of agents and land use activities. We identify three major proximate causes of deforestation. The largest share of deforestation is attributable to the expansion of mechanized agriculture, followed by cattle ranching and small-scale agriculture. We utilize a spatially explicit multinomial logit model to analyze the determinants of each of these proximate causes of deforestation between 1992 and 2004. We substantiate the quantitative insights with a qualitative analysis of historical processes that have shaped land use patterns in the Bolivian lowlands to date. Our results suggest that the expansion of mechanized agriculture occurs mainly in response to good access to export markets, fertile soil, and intermediate rainfall conditions. Increases in small-scale agriculture are mainly associated with a humid climate, fertile soil, and proximity to local markets. Forest conversion into pastures for cattle ranching occurs mostly irrespective of environmental determinants and can mainly be explained by access to local markets. Land use restrictions, such as protected areas, seem to prevent the expansion of mechanized agriculture but have little impact on the expansion of small-scale agriculture and cattle ranching. The analysis of future deforestation trends reveals possible hotspots of future expansion for each proximate cause and specifically highlights the possible opening of new frontiers for deforestation due to mechanized agriculture. Whereas the quantitative analysis effectively elucidates the spatial patterns of recent agricultural expansion, the interpretation of long-term historic drivers reveals that the timing and quantity of forest conversion are often triggered by political interventions and historical legacies.
    Keywords: Bolivia; Amazon; Deforestation; Proximate causes; Spatial analysis; Multinomial logistic regression ; 551 ; Environment; Geology; Geography (general); Regional/Spatial Science; Climate Change; Nature Conservation; Oceanography
    Language: English
    Type: article , publishedVersion
    Format: application/pdf
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    CITATION GEO-LEO
  • 2
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    Measured daily precipitation sums over Central Sulawesi for the period 1981-1999
    PANGAEA
    Details
    Publication Date: 2023-05-12
    Description: Data compiled within the IMPENSO project. The Impact of ENSO on Sustainable Water Management and the Decision-Making Community at a Rainforest Margin in Indonesia (IMPENSO), http://www.gwdg.de/~impenso, was a German-Indonesian research project (2003-2007) that has studied the impact of ENSO (El Nino-Southern Oscillation) on the water resources and the agricultural production in the PALU RIVER watershed in Central Sulawesi. ENSO is a climate variability that causes serious droughts in Indonesia and other countries of South-East Asia. The last ENSO event occurred in 1997. As in other regions, many farmers in Central Sulawesi suffered from reduced crop yields and lost their livestock. A better prediction of ENSO and the development of coping strategies would help local communities mitigate the impact of ENSO on rural livelihoods and food security. The IMPENSO project deals with the impact of the climate variability ENSO (El Niño Southern Oscillation) on water resource management and the local communities in the Palu River watershed of Central Sulawesi, Indonesia. The project consists of three interrelated sub-projects, which study the local and regional manifestation of ENSO using the Regional Climate Models REMO and GESIMA (Sub-project A), quantify the impact of ENSO on the availability of water for agriculture and other uses, using the distributed hydrological model WaSiM-ETH (Sub-project B), and analyze the socio-economic impact and the policy implications of ENSO on the basis of a production function analysis, a household vulnerability analysis, and a linear programming model (Sub-project C). The models used in the three sub-projects will be integrated to simulate joint scenarios that are defined in collaboration with local stakeholders and are relevant for the design of coping strategies.
    Keywords: Balantak; Bangga_Atas; Bangga_Bawah; Bora; Dolago_Bendung; Dolago_Padang; Hek-Bunta; Indonesia; Kalawara; Kamba; Kayu_Agung; Kolonodale; Kulawi; Lalos; Lamadong; Lambunu; Lampasio; Lemusa; Libok; Mayoa; OBSE; Observation; Ogo_Bayas; Ongka_Persatuan; Palolo; Pandayora; Sausu; Singkoyo; Sionyong; Sulawesi Sea; Tada; Tanamea; Tolae; Tuwa; Waru; Wuasa
    Type: Dataset
    Format: application/zip, 32 datasets
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    DATA PANGAEA
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