Scenarios of land use and land cover change in the Colombian Amazon to evaluate alternative post-conflict pathways.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
07 02 2023
07 02 2023
Historique:
received:
11
03
2022
accepted:
01
02
2023
entrez:
7
2
2023
pubmed:
8
2
2023
medline:
10
2
2023
Statut:
epublish
Résumé
Pastures and crops have been expanding at an accelerated rate in the forests of the Colombian Amazon since the peace accords were signed in 2016. The rapid loss of tropical rainforests is threatening the integrity of protected areas and connectivity in the Amazon and other natural regions. In the context of the post-conflict stage, a set of land use and land cover change scenarios were constructed for the Colombian Amazon for the year 2040, using expert coherent narratives. Three scenarios were designed: trend, extractivist, and sustainable development. Historic land use change and driving factors were analyzed throughout 14 transitions between the years 2002 and 2016, based on the interpretation of Landsat images and their relationship with 29 driving factors using artificial neural networks. The Markov chain model was calculated for the transitions, and the change allocation model was parameterized to spatially simulate the scenarios. The results showed that the LULC model calibration and validation were satisfactory (0.91). The sustainable development scenario that considers strong policies for the conservation of forests and implementation of sustainable production projects was the option with greater values for conserved forests and secondary vegetation in recovery, adding ~ 42 million hectares by 2040. The other scenarios showed that the Colombian Amazon will lose ~ 2 million hectares of forests in the trend scenario and ~ 4.3 million hectares in the extractivist scenario, based on the reference year (2016). In the trend scenario, pastures and crops could increase by 48%; and, in the extractivist scenario, these would increase by 117%, changing from ~ 3.9 to ~ 8.6 million hectares. We hope that the scientific contribution of this study will be relevant for informed discussion in decision-making and provide a framework for building a peaceful territory.
Identifiants
pubmed: 36750688
doi: 10.1038/s41598-023-29243-2
pii: 10.1038/s41598-023-29243-2
pmc: PMC9905563
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2152Informations de copyright
© 2023. The Author(s).
Références
Armenteras, D., Schneider, L. & Dávalos, L. M. Fires in protected areas reveal unforeseen costs of Colombian peace. Nat. Ecol. Evol. 3, 20–23 (2019).
doi: 10.1038/s41559-018-0727-8
Murillo-Sandoval, P. J. et al. No peace for the forest: Rapid, widespread land changes in the Andes-Amazon region following the Colombian civil war. Glob. Environ. Change. 69, 102283 (2021).
doi: 10.1016/j.gloenvcha.2021.102283
Morales, L. Peace and Environmental Protection in Colombia: Proposals for Sustainable Rural Development. Inter-American Dialogue (Gordon and Betty Moore Foundation, 2017).
Armenteras, D. et al. Curb land grabbing to save the Amazon. Nat. Ecol. Evol. 3, 1497 (2019).
doi: 10.1038/s41559-019-1020-1
Soler, L. S., Kok, K., Camara, G. & Veldkamp, A. Using fuzzy cognitive maps to describe current system dynamics and develop land cover scenarios: A case study in the Brazilian Amazon. J. Land Use Sci. 7, 149–175 (2012).
doi: 10.1080/1747423X.2010.542495
Rodríguez, J. M. et al. Análisis de los cambios de coberturas de la tierra en el periodo 2018 al 2020 en la Amazonia Colombiana. (Instituto Amazónico de Investigaciones Cientificas SINCHI, 2021).
Clerici, N. et al. Deforestation in Colombian protected areas increased during post-conflict periods. Sci. Rep. 10, 1–10 (2020).
doi: 10.1038/s41598-020-61861-y
Armenteras, D., Murcia, U., González, T. M., Barón, O. J. & Arias, J. E. Scenarios of land use and land cover change for NW Amazonia: Impact on forest intactness. Glob. Ecol. Conserv. 17, (2019).
Chhabra, A. et al. Multiple Impacts of Land-Use/Cover Change. In Land-Use and Land-Cover Change: Local Processes and Global Impacts 71–116 (2006). https://doi.org/10.1007/3-540-32202-7 .
Graser, M. et al. Peacebuilding in rural Colombia-a collective perception of the Integrated Rural Reform (IRR) in the department of Caqueta (Amazon). Land 9, 1–17 (2020).
doi: 10.3390/land9020036
Hussain, S., Mubeen, M. & Karuppannan, S. Land use and land cover (LULC) change analysis using TM, ETM+ and OLI Landsat images in district of Okara, Punjab, Pakistan. Phys. Chem. Earth Parts A/B/C 126, 103117 (2022).
Gomes, L. C. et al. Land use and land cover scenarios: An interdisciplinary approach integrating local conditions and the global shared socioeconomic pathways. Land Use Policy 97, 104723 (2020).
doi: 10.1016/j.landusepol.2020.104723
Wassenaar, T. et al. Projecting land use changes in the Neotropics: The geography of pasture expansion into forest. Glob. Environ. Change. 17, 86–104 (2007).
doi: 10.1016/j.gloenvcha.2006.03.007
Verburg, P. H., Kok, K., Pontius, R. G. & Veldkamp, A. Modeling Land-Use and Land-Cover Change BT—Land-Use and Land-Cover Change: Local Processes and Global Impacts. (eds. Lambin, E. F. & Geist, H.) 117–135 (Springer Berlin Heidelberg, 2006). https://doi.org/10.1007/3-540-32202-7_5 .
Bezerra, F. G. S. et al. New land-use change scenarios for Brazil: Refining global SSPs with a regional spatially-explicit allocation model. PLoS ONE 17, 1–17 (2022).
Chang, X., Zhang, F., Cong, K. & Liu, X. Scenario simulation of land use and land cover change in mining area. Sci. Rep. 11, 1–12 (2021).
Colman, C. B., Guerra, A., de Roque, F. O., Rosa, I. M. D. & de Oliveira, P. T. S. Identifying priority regions and territorial planning strategies for conserving native vegetation in the Cerrado (Brazil) under different scenarios of land use changes. Sci. Total Environ. 807, 150998 (2022).
doi: 10.1016/j.scitotenv.2021.150998
IPBES. The methodological assessment report on scenarios and models of biodiversity and ecosystem services. IPBES Methodological Assessment Report on Scenarios and Models of Biodiversity and Ecosystem Services (2016).
Mahmoud, M. et al. A formal framework for scenario development in support of environmental decision-making. Environ. Model. Softw. 24, 798–808 (2009).
doi: 10.1016/j.envsoft.2008.11.010
Sampaio, G. et al. Regional climate change over eastern Amazonia caused by pasture and soybean cropland expansion. Geophys. Res. Lett. 34, 1–7 (2007).
doi: 10.1029/2007GL030612
Ometto, J. & Sampaio, G. Climate change and land use change in Amazonia. Rep. Amaz. Secur. Agenda Proj. 57 (2013).
Staal, A. et al. Hysteresis of tropical forests in the 21st century. Nat. Commun. 11, 1–8 (2020).
doi: 10.1038/s41467-020-18728-7
Cook, C. N., Inayatullah, S., Burgman, M. A., Sutherland, W. J. & Wintle, B. A. Strategic foresight: how planning for the unpredictable can improve environmental decision-making. Trends Ecol. Evol. 29, 531–541 (2014).
doi: 10.1016/j.tree.2014.07.005
Peterson, G. D., Cumming, G. S. & Carpenter, S. R. Scenario planning: A tool for conservation in an uncertain world. Conserv. Biol. 17, 358–366 (2003).
doi: 10.1046/j.1523-1739.2003.01491.x
Schwartz, M. W. et al. Decision support frameworks and tools for conservation. Conserv. Lett. 11, 1–12 (2018).
doi: 10.1111/conl.12385
Tapinos, E. Perceived environmental uncertainty in scenario planning. Futures 44, 338–345 (2012).
doi: 10.1016/j.futures.2011.11.002
Coreau, A., Pinay, G., Thompson, J. D., Cheptou, P. O. & Mermet, L. The rise of research on futures in ecology: Rebalancing scenarios and predictions. Ecol. Lett. 12, 1277–1286 (2009).
doi: 10.1111/j.1461-0248.2009.01392.x
Perz, S., Messina, J. P., Reis, E., Walker, R. & Walsh, S. J. Scenarios of future Amazonian landscapes: Econometric and dynamic simulation models. Geophys. Monogr. Ser. 186, 83–100 (2009).
Alcamo, J. et al. Searching for the future of land: Scenarios from the local to global scale. In Land-Use and Land-Cover Change 137–155 (Springer Berlin Heidelberg, 2006). https://doi.org/10.1007/3-540-32202-7_6 .
Rounsevell, M. D. A. & Metzger, M. J. Developing qualitative scenario storylines for environmental change assessment. Wiley Interdiscip. Rev. Clim. Change. 1, 606–619 (2010).
doi: 10.1002/wcc.63
Charity, S., Dudley, N., Oliveira, D. & Stolton, S. Living Amazon Report 2016. A regional approach to conservation in the Amazon. (WWF Living Amazon Initiative, 2016).
Finer M, M. MAAP #106: DEFORESTATION IMPACTS 4 PROTECTED AREAS IN THE COLOMBIAN AMAZON (2019). Monitoring of the Andean Amazon Project https://maaproject.org/2019/colombia_2019/ (2019).
Murcia, U., Medina, R., Rodríguez, J., Hernández, A. & Castellanos, H. Cambio de uso del suelo: monitoreo de los bosques y otras coberturas de la Amazonia Colombiana, a escala 1:100.000. Cambios multitemporales 2002–2012, con enfansis en el periodo 2007–2012. (Instituto Amazónico de Investigaciones Cientificas SINCHI, 2014).
Eastman, J. R. TerrSet. Geospatial Monitoring and Modeling System. Manual. (ClarkLabs University, 2016).
González Arenas, J. J. et al. Análisis de tendencias y patrones espaciales de deforestación en Colombia. Ideam https://doi.org/10.5194/tc-10-2559-2016 (2011).
Salazar-Cardona, C. A. & Riaño-Umbarila, E. Perfiles urbanos en la Amazonia colombiana. (Instituto Amazónico de Investigaciones Cientificas SINCHI, 2016).
Ideam. Leyenda nacional de coberturas de la tierra. Metodología CORINE Land Cover adaptada para Colombia, escala 1:100.000. Area vol. TH-62-04-1 (2010).
Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
doi: 10.1002/joc.5086
ESRI. ArcGIS [GIS software]. Version 10.7.1 (Environmental Systems Research Institute, Inc., 2019).
SINCHI. Sistema de Información Ambiental Territorial de la Amazonia Colombiana-SIAT-AC. https://siatac.co/ (2020).
PNNC. Sistema Nacional de Áreas Protegidas—SINAP. https://mapas.parquesnacionales.gov.co/ (2020).
Hulley, G. C. et al. The ASTER Global Emissivity Dataset (ASTER GED): Mapping Earth’s emissivity at 100 meter spatial scale. Geophys. Res. Lett. 42, 7966–7976 (2015).
doi: 10.1002/2015GL065564
Fischer, J. & Lindenmayer, D. B. Landscape modification and habitat fragmentation: A synthesis. 265–280 (2007) https://doi.org/10.1111/j.1466-8238.2006.00287.x .
Michalski, F., Peres, C. A. & Lake, I. R. Deforestation dynamics in a fragmented region of southern Amazonia: Evaluation and future scenarios. Environ. Conserv. 35, 93–103 (2008).
doi: 10.1017/S0376892908004864
Castellanos-Mora, L. & Agudelo-Hz, W. Spatial Scenarios of Land Use/Cover Change for the management and conservation of Páramos and Andean Forest in Boyacá, Colombia. In Environment Science Proceeding 9 (MDPI, 2020). https://doi.org/10.3390/IECF2020-08023 .
Sangermano, F., Toledano, J. & Eastman, R. Land cover change in the Bolivian Amazon and its implications for REDD+ and endemic biodiversity. Landsc. Ecol. 27, 571–584 (2012).
doi: 10.1007/s10980-012-9710-y
Tayyebi, A. & Pijanowski, B. C. Modeling multiple land use changes using ANN, CART and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools. Int. J. Appl. Earth Obs. Geoinf. 28, 102–116 (2014).
Mishra, V., Rai, P. & Mohan, K. Prediction of land use changes based on land change modeler (LCM) using remote sensing: A case study of Muzaffarpur (Bihar), India. J. Geogr. Inst. Jovan Cvijic SASA 64, 111–127 (2014).
doi: 10.2298/IJGI1401111M
Mas, J. F. & Flores, J. J. The application of artificial neural networks to the analysis of remotely sensed data. Int. J. Remote Sens. 29, 617–663 (2008).
doi: 10.1080/01431160701352154
Bernetti, I. & Marinelli, N. Evaluation of landscape impacts and land use change: A Tuscan case study for CAP reform scenarios. Aestimum 56, 1–29 (2010).
Camacho Olmedo, M. T., Pontius, R. G., Paegelow, M. & Mas, J.-F. Comparison of simulation models in terms of quantity and allocation of land change. Environ. Model. Softw. 69, 214–221 (2015).
doi: 10.1016/j.envsoft.2015.03.003
Aguejdad, R., Houet, T. & Hubert-Moy, L. Spatial validation of land use change models using multiple assessment techniques: A case study of transition potential models. Environ. Model. Assess. 22, 591–606 (2017).
doi: 10.1007/s10666-017-9564-4
Dzieszko, P. Land-cover modelling using corine land cover data and multi-layer perceptron. Quaest. Geogr. 33, 5–22 (2014).
doi: 10.2478/quageo-2014-0004
Kolb, M. & Galicia, L. Scenarios and story lines: Drivers of land use change in southern Mexico. Environ. Dev. Sustain. 20, 681–702 (2018).
doi: 10.1007/s10668-016-9905-5
Schönenberg, R., Schaldach, R., Lakes, T., Göpel, J. & Gollnow, F. Inter- and transdisciplinary scenario construction to explore future land-use options in southern Amazonia. Ecol. Soc. 22(3), (2017).
Majeed, M. et al. Monitoring of land use–land cover change and potential causal factors of climate change in Jhelum District, Punjab, Pakistan, through GIS and multi-temporal satellite data. Land 10 (2021).
Tope-Ajayi, O. O., Adedeji, O. H., Adeofun, C. O. & Awokola, S. O. Land use change assessment, prediction using remote sensing, and GIS aided Markov chain modelling at Eleyele Wetland area, Nigeria. J. Settl. Spat. Plan. 7, 51–63 (2016).
Camacho-Olmedo, M. T. & Mas, J.-F. Chapter 25. Markov chain. In Geomatic Approaches for Modeling Land Change Scenarios. Lecture Notes in Geoinformation and Cartography (eds. Camacho-Olmedo, M. T., Paegelow, M., Mas, J.-F. & Escobar, F.) 441–445 (Springer Nature, 2018). https://doi.org/10.1007/978-3-319-60801-3 .
Gonzáles, C., Pérez, S., Mateus, A. & Barrera, J. Acuerdos voluntarios de conservación y sostenibilidad en el corazón de la Amazonia: procesos y resultados. (Instituto Amazónico de Investigaciones Cientificas SINCHI, 2019).
Verburg, P. H., Kok, K., Pontius, R. G. & Veldkamp, A. Modeling land-use and land-cover change. In Land-Use and land-Cover Change. Local Processes and Global Impacts (eds. Lambin, E. F. & Geist, H. J.) (2006).
Gholamalifard, M. et al. Application of Kappa Index of Agreement (KIA) for monitoring of land cover changes in coastal areas of Bushehr Province (Time Period 1987–2011). J. Oceanogr. 3, 63–75 (2013).
Chazdon, R. L. & Uriarte, M. The role of natural regeneration in large-scale forest and landscape restoration: Challenge and opportunity. Biotropica 48, 709–715 (2016).
doi: 10.1111/btp.12409
Brancalion, P. H. S. et al. Global restoration opportunities in tropical rainforest landscapes. Sci. Adv. 5, 1–11 (2019).
doi: 10.1126/sciadv.aav3223
Chazdon, R. L. et al. Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics. Sci. Adv. 2, (2016).
Rozendaal, D. M. A. et al. Biodiversity recovery of Neotropical secondary forests. Sci. Adv. 5, (2019).