Dynamics of past forest cover changes and future scenarios with implications for soil degradation in Misiones rainforest, Argentina

被引:3
作者
Rau, Maria Fabiana Navarro [1 ]
Calamari, Noelia Cecilia [2 ]
Mosciaro, Maria Jesus [3 ]
机构
[1] Inst Nacl Tecnol Agr INTA, Inst Suelo Reseros & Caban HB1712WAA, Hurlingham, Buenos Aires, Argentina
[2] Inst Nacl Tecnol Agr INTA, Estacio Expt Paranon, Ruta Nacl 11 km 12, RA-3100 Oro Verde, Entre Rios, Argentina
[3] Inst Nacl Tecnol Agr INTA, Estn Expt Salta, Ruta Nacl 68 km 172, RA-4403 Salta, Argentina
关键词
Dinamica EGO; Future scenarios; LUCC; Soil erosion; Subtropical rainforest; LAND-USE CHANGE; CELLULAR-AUTOMATA MODEL; ATLANTIC FOREST; CLIMATE-CHANGE; AGRICULTURAL EXPANSION; BRAZILIAN AMAZONIA; PROXIMATE CAUSES; URBAN-GROWTH; EROSION; DEFORESTATION;
D O I
10.1016/j.jnc.2023.126391
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Misiones rainforest is one of the most threatened subtropical forests worldwide. Anthropogenic pressure by agriculture and forestry expansion continues transforming landscapes with negative consequences on ecosystem service provision, such as soil erosion control. Understanding how land use and land cover change (LUCC) management, policies, and social factors influenced in the past, allows decision-makers to anticipate potential effects on future land use and soil loss, contributing to the sustainable planning and management of productive activities. We developed three spatially explicit scenarios for Misiones province by 2030 using the Dinamica EGO modeling platform: 1) Business as Usual (BAU), 2) Low Deforestation (ALTlow), and 3) High Deforestation (ALThigh), based on different international and domestic socioeconomic contexts. We used land cover data from 2002 to 2015 as well as biophysical, social-infrastructure, political-administrative factors, and legal restrictions to estimate changes that may occur by 2030. We analyzed magnitude, intensity, and spatial pattern of future forest cover changes through transition rates and a cellular automata allocation model. Moreover, we used the Universal Soil Loss Equation (USLE) integrated into a Geographic Information System (GIS) to determine soil water erosion and soil loss tolerance in each scenario. Our results revealed that around 19% of the remaining native forest would be transformed into either agriculture or cultivated forest by 2030 for all scenarios. In addition, and contrary to that trend, the ALTlow scenario showed a recovery of 3% of native forest. Regarding soil erosion, our study indicated that the mean annual soil loss by 2030 would range from 12.03 to 19.15 t. ha(-1). year(-1) for ALTlow and ALThigh scenarios, respectively. Additionally, between 21% and 31% of Misiones province showed soil loss values higher than tolerance. Our work shows that a 10% decrease in the deforestation rate, compared to the current rate, would lead not only to a recovery of native forest cover, but also to a reduction in soil loss of about 4.5 Mt.yr(-1) by 2030. This study demonstrates the suitability of the applied model to simulate future LUCC processes and provides inputs for decision-making involving natural resource management and the potential impacts of these decisions on ecosystem services. Finally, our results highlight the need for appropriate policies and regulations, especially, in terms of land use change restrictions in areas of high erosion risk.
引用
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页数:14
相关论文
共 126 条
[1]   Biophysical climate impacts of recent changes in global forest cover [J].
Alkama, Ramdane ;
Cescatti, Alessandro .
SCIENCE, 2016, 351 (6273) :600-604
[2]  
Angelsen A., 2007, FOREST COVER CHANGE
[3]  
[Anonymous], 2014, World Soil Resources Report, V106, DOI DOI 10.1017/S0014479706394902
[4]  
[Anonymous], 1993, APPL GEOGRAPHIC INFO
[5]   A re-emerging Atlantic forest? Urbanization, industrialization and the forest transition in Santa Catarina, southern Brazil [J].
Baptista, Sandra R. ;
Rudel, Thomas K. .
ENVIRONMENTAL CONSERVATION, 2006, 33 (03) :195-202
[6]   Lost forever? Ecosystem functional changes occurring after agricultural abandonment and forest recovery in the semiarid Chaco [J].
Basualdo, M. ;
Huykman, N. ;
Volante, J. N. ;
Paruelo, J. M. ;
Pineiro, G. .
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 650 :1537-1546
[7]   Environmental predictors of forest change: An analysis of natural predisposition to deforestation in the tropical Andes region, Peru [J].
Bax, Vincent ;
Francesconi, Wendy .
APPLIED GEOGRAPHY, 2018, 91 :99-110
[8]  
Bertol I., 2000, Revista Brasileira de Ciencia do Solo, V24, P657, DOI 10.1590/S0100-06832000000300018
[9]  
Bonham-Carter G., 1994, GEOGRAPHIC INFORM SY
[10]   Land use and climate change impacts on global soil erosion by water (2015-2070) [J].
Borrelli, Pasquale ;
Robinson, David A. ;
Panagos, Panos ;
Lugato, Emanuele ;
Yang, Jae E. ;
Alewell, Christine ;
Wuepper, David ;
Montanarella, Luca ;
Ballabio, Cristiano .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (36) :21994-22001