O uso de modelagem de distribuição de espécies para restauração florestal: Uma revisão sistemática

Autores

DOI:

https://doi.org/10.33448/rsd-v10i8.17158

Palavras-chave:

Restauração Ecológica; Maxent; Seleção de Espécies.

Resumo

O objetivo deste trabalho foi realizar uma revisão sistemática da produção científica do uso da modelagem de distribuição de espécies para restauração florestal. As buscas de artigos científicos nas bases de dados Scopus e Web of Science para os últimos 15 anos foram realizadas no mês de dezembro de 2020 utilizando os termos: “ecological modeling” OR “biodiversity modeling” OR “predictive models” OR “niche modeling" OR "habitat models" AND “species distribution” OR "geographic distribution" OR “potential distribution” AND “forest restoration” OR “restoration ecology”. Para as análises estatísticas e gráficos dos dados brutos foi utilizado o pacote Bibliometrix do software R. Os dados brutos foram refinados por meio da seleção dos estudos que atenderam aos seguintes critérios: (i) estudos publicados em revistas científicas com fator de impacto igual ou superior a 2,0; (ii) estudos em que o título ou resumo mencionasse as palavras restauração florestal ou restauração ecológica; (iii) estudos que avaliaram o uso de modelagem de distribuição de espécies como auxílio aos projetos e programas de restauração florestal ou restauração ecológica. Foram encontrados 44 documentos publicados em 30 periódicos científicos com média de 3,91 publicações por ano; 18,55 citações por documento; 197 autores, sendo 3 documentos com autoria única. Assim pode-se concluir que o uso de modelagem de distribuição de espécies para restauração florestal no mundo é muito recente, e no Brasil é incipiente com baixos números de artigos publicados, mas apresenta tendência de crescimento por conta da sua significativa contribuição para melhorar as taxas de sucesso dos projetos de restauração.

Referências

Allen, J. M., & Bradley, B. A. (2016). Out of the weeds? Reduced plant invasion risk with climate change in the continental United States. Biological Conservation, 203, 306-312. https://doi.org/10.1016/j.biocon.2016.09.015

Anderson, R. P., Lew, D., & Peterson, A. T. (2003). Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecological Modelling, 162(3), 211-232. https://doi.org/10.1016/S0304-3800(02)00349-6

Araújo, M. B. & Peterson, A. T. 2012. Uses and misuses of bioclimatic envelope modelling. Ecology, 93: 1527–1539. https://doi.org/10.1890/11-1930.1

Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007

Bradley, B. A., Wilcove, D. S., & Oppenheimer, M. (2010). Climate change increases risk of plant invasion in the Eastern United States. Biological Invasions, 12(6), 1855-1872. https://doi.org/10.1007/s10530-009-9597-y

Brancalion, P. H., & Chazdon, R. L. (2017). Beyond hectares: four principles to guide reforestation in the context of tropical forest and landscape restoration. Restoration Ecology, 25(4), 491-496. https://doi.org/10.1111/rec.12519

Brearley, F. Q. (2011) Below-Ground secondary succession in tropical forests of borneo. Journal of Tropical Ecology, 27, 413–420.

https://doi.org/10.1017/S0266467411000149

Burnside, N. G., Smith, R. F., & Waite, S. (2002). Habitat suitability modelling for calcareous grassland restoration on the South Downs, United Kingdom. Journal of Environmental Management, 65(2), 209-221. https://doi.org/10.1006/jema.2002.0546

Cai, A., Wang, J., Wang, Y., Maclachlan, I. (2019) Spatial optimizations of multiple plant species for ecological restoration of the mountainous areas of north china. Environmental Earth Sciences, 78: 302. https://doi.org/10.1007/s12665-019-8299-8

Cairns, J., 2002. Rationale for restoration. In: Handbook of Ecological Restoration: Vol. 1. Principles of Restoration. Cambridge University Press, Cambridge, UK.

Cancian, L. F. (2012) Modelagem de distribuição geográfica potencial de macrófitas aquáticas em bacias hidrográficas. Tese de doutorado, Universidade Estadual Paulista, Instituto de Biociências de Rio Claro, 2012. Disponível em: <http://hdl.handle.net/11449/100619>.

Carrasco, J., Price, V., Tulloch, V., Mills, M. (2020) Selecting priority areas for the conservation of endemic trees species and their ecosystems in Madagascar considering both conservation value and vulnerability to human pressure. Biodiversity and Conservation, 29, 1841–1854. https://doi.org/10.1007/s10531-020-01947-1

Choi, Y. D., (2004) Theories for ecological restoration in changing environment: toward “futuristic” restoration. Ecological Research, 19, 75–81. https://doi.org/10.1111/rec.13265

Coelho, G. L. N., Carvalho, L. M. T. D., & Gomide, L. R. (2016). Modelagem preditiva de distribuição de espécies pioneiras no Estado de Minas Gerais. Pesquisa Agropecuária Brasileira, 51(3), 207-214. DOI:10.1590/S0100-204X2016000300002

Costa, M. M. (2016) Financiamento para a restauração ecológica no Brasil. Mudanças no Código Florestal Brasileiro: desafios para implementação da nova lei, [S. l.], p. 235–260.

Cote, I., Reynolds, J., (2002) Predictive ecology to the rescue? Science, vol. 298, pp. 1181–1182. DOI:10.1126/science.1079074

Cupertino-Eisenlohr, M. A., Vinícius-Silva, R., Meireles, L. D., Eisenlohr, P. V., Meira-Neto, J. A., & Santos-Gonçalves, A. P. (2017). Stability or breakdown under climate change? A key group of woody bamboos will find suitable areas in its richness center. Biodiversity and Conservation, 26(8), 1845-1861. https://doi.org/10.1007/s10531-017-1332-x

de Castro Pena, J. C., Kamino, L. H. Y., Rodrigues, M., Mariano-Neto, E., & de Siqueira, M. F. (2014). Assessing the conservation status of species with limited available data and disjunct distribution. Biological Conservation, 170, 130-136. https://doi.org/10.1016/j.biocon.2013.12.015

Dybå, T., & Dingsøyr, T. (2008, October). Strength of evidence in systematic reviews in software engineering. In Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (pp. 178-187). https://doi.org/10.1145/1414004.1414034

Felici´Simo, A.M. (2003) Uses of spatial predictive models in forested areas territorial planning. Ciot-IV International Conference on Spatial Planning, pp 1–15.

Ferro, V. G., Lemes, P., Melo, A. S., & Loyola, R. (2014). The reduced effectiveness of protected areas under climate change threatens Atlantic Forest tiger moths. PLoS One, 9(9), e107792. https://doi.org/10.1371/journal.pone.0107792

Florentine, S. K., & Westbrooke, M. E. (2004). Restoration on abandoned tropical pasturelands—do we know enough?. Journal for Nature Conservation, 12(2), 85-94. https://doi.org/10.1016/j.jnc.2003.08.003

García-López, J. M., & Camacho, C. A. (2005, June). Ensayo de un sistema fitoclimático de carácter autoecológico para especies arbóreas forestales en la península ibérica y su aplicación en labores de repoblación forestal. In Congresos Forestales.

G Gaston, A., & Garcia-Vinas, J. I. (2013). Evaluating the predictive performance of stacked species distribution models applied to plant species selection in ecological restoration. Ecological Modelling, 263, 103-108. https://doi.org/10.1016/j.ecolmodel.2013.04.020

Gastón, A., Garcia-Vinas, J. I., Bravo-Fernandez, A. J., López-Leiva, C., Oliet, J. A., Roig, S., & Serrada, R. (2014). Species distribution models applied to plant species selection in forest restoration: are model predictions comparable to expert opinion? New forests, 45(5), 641-653. https://doi.org/10.1007/s11056-014-9427-7

Gastón, A., & García-Viñas, J. I. (2010). Updating coarse-scale species distribution models using small fine-scale samples. Ecological Modelling, 221(21), 2576-2581. https://doi.org/10.1016/j.ecolmodel.2010.07.016

Gelviz-Gelvez, S. M., Pavón, N. P., Illoldi-Rangel, P., & Ballesteros-Barrera, C. (2015). Ecological niche modeling under climate change to select shrubs for ecological restoration in Central Mexico. Ecological Engineering, 74, 302-309. https://doi.org/10.1016/j.ecoleng.2014.09.082

Giacomin, L. L., Kamino, L. H. Y., & Stehmann, J. R. (2014). Speeding up the discovery of unknown plants: a case study of Solanum (Solanaceae) endemics from the Brazilian Atlantic Forest. Boletim do Museu de Biologia Mello Leitão. Nova Série, 35, 121-135.

Guisan, A., & Thuiller, W. (2005). Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8(9), 993-1009. DOI: 10.1111/j.1461-0248.2005.00792.x

Guisan, A., Tingley, R., Baumgartner, J. B., Naujokaitis‐Lewis, I., Sutcliffe, P. R., Tulloch, A. I., ... & Buckley, Y. M. (2013). Predicting species distributions for conservation decisions. Ecology letters, 16(12), 1424-1435. https://doi.org/10.1111/ele.12189

Gutiérrez, J. M. G., & Palomares, O. S. (1994). Estaciones ecológicas de los pinares españoles. Instituto Nacional para la Conservación de la Naturaleza.

Harrell, F. E. (2001) Regression modeling strategies: with applications to linear models, logistic regression and survival analysis. Springer, New York.

Harris, J. A., Hobbs, R. J., Higgs, E., & Aronson, J. (2006). Ecological restoration and global climate change. https://doi.org/10.1111/j.1526-100X.2006.00136.x

Heringer, G., Bueno, M. L., Meira-Neto, J. A., Matos, F. A., & Neri, A. V. (2019). Can Acacia mangium and Acacia auriculiformis hinder restoration efforts in the Brazilian Atlantic Forest under current and future climate conditions? Biological Invasions, 21(9), 2949-2962. https://doi.org/10.1007/s10530-019-02024-7

Hulme P. E. (2009) Trade, transport and trouble: managing invasive species pathways in an era of globalization. Journal of Applied Ecology, 46:10–18. https://doi.org/10.1111/j.1365-2664.2008. 01600.x

Kamino, L. H., Stehmann, J. R., Amaral, S., De Marco Jr, P., Rangel, T. F., de Siqueira, M. F., ... & Hortal, J. (2012). Challenges and perspectives for species distribution modelling in the neotropics. Biology Letters, 8:324–326. https://doi.org/10.1098/rsbl.2011.0942

Lehmann, J. R., Prinz, T., Ziller, S. R., Thiele, J., Heringer, G., Meira-Neto, J. A., & Buttschardt, T. K. (2017). Open-source processing and analysis of aerial imagery acquired with a low-cost unmanned aerial system to support invasive plant management. Frontiers in Environmental Science, 5, 44. https://doi.org/10.3389/fenvs.2017.00044

Lemes, P., Melo, A. S., & Loyola, R. D. (2014). Climate change threatens protected areas of the Atlantic Forest. Biodiversity and Conservation, 23(2), 357-368. https://doi.org/10.1007/s10531-013-0605-2

Martínez‐Ramos, M., Pingarroni, A., Rodríguez‐Velázquez, J., Toledo‐Chelala, L., Zermeño‐Hernández, I., & Bongers, F. (2016). Natural forest regeneration and ecological restoration in human‐modified tropical landscapes. Biotropica, 48(6), 745-757. https://doi.org/10.1111/btp.12382

Mateo, R. G., Gastón, A., María José, A.-F., Juan Ignacio, G.-V., & Saura, S. (2018) Sampling strategies and optimization of species distribution modelling at the landscape scale. Forest Ecology and Management, 410: 104-113. https://doi.org/10.1016/j.foreco.2017.12.046

Meira-Neto, J. A. A., da Silva, M. C. N. A., Tolentino, G. S., Gastauer, M., Buttschardt, T., Ulm, F., & Máguas, C. (2018). Early Acacia invasion in a sandy ecosystem enables shading mediated by soil, leaf nitrogen and facilitation. Biological Invasions, 20(6), 1567-1575. https://doi.org/10.1007/s10530-017-1647-2

Melo, F. P., Pinto, S. R., Brancalion, P. H., Castro, P. S., Rodrigues, R. R., Aronson, J., & Tabarelli, M. (2013). Priority setting for scaling-up tropical forest restoration projects: Early lessons from the Atlantic Forest Restoration Pact. Environmental Science & Policy, 33, 395-404. https://doi.org/10.1016/j.envsci.2013.07.013

Millar, C. I., Stephenson, N. L., & Stephens, S. L. (2007) Climate change and forests of the future: managing in the face of uncertainty. Ecological Applications, 17, 2145–2151.

Oliveira, U., Paglia, A. P., Brescovit, A. D., de Carvalho, C. J., Silva, D. P., Rezende, D. T., ... & Santos, A. J. (2016). The strong influence of collection bias on biodiversity knowledge shortfalls of Brazilian terrestrial biodiversity. Diversity and Distributions, 22(12), 1232-1244. https://doi.org/10.1111/ddi.12489

Oliveira, U., Soares-Filho, B. S., Paglia, A. P., Brescovit, A. D., De Carvalho, C. J., Silva, D. P., ... & Santos, A. J. (2017). Biodiversity conservation gaps in the Brazilian protected areas. Scientific Reports, 7(1), 1-9. https://doi.org/10.1038/s41598-017-08707-2

Pemán García, J., Navarro Cerrillo, R. M., & Serrada Hierro, R. (2006). Species selection guidelines in reforestation. Ruiz de la Torre's contributions. Investigación Agraria. Sistemas y Recursos Forestales (España). f 15:87–102.

Peterson, A. T., Soberón, J., Pearson, R. G., Anderson, R. P., Martínez-Meyer, E., Nakamura, M., & Araújo, M. B. (2011). Ecological niches and geographic distributions (MPB-49). Princeton University Press.

Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 231-259. https://doi.org/10.1016/j.ecolmodel.2005.03.026

Pickering, C., & Byrne, J. (2014). The benefits of publishing systematic quantitative literature reviews for PhD candidates and other early-career researchers. Higher Education Research & Development, 33(3), 534-548. https://doi.org/10.1080/07294360.2013.841651

Ravenscroft, C., Scheller, R. M., Mladenoff, D. J., & White, M. A. (2010). Forest restoration in a mixed‐ownership landscape under climate change. Ecological Applications, 20(2), 327-346. https://doi.org/10.1890/08-1698.1

Renton, M., Shackelford, N., & Standish, R. J. (2012). Habitat restoration will help some functional plant types persist under climate change in fragmented landscapes. Global Change Biology, 18(6), 2057-2070. https://doi.org/10.1111/j.1365-2486.2012.02677.x

Richardson, D. M., & Rejmánek, M. (2011). Trees and shrubs as invasive alien species–a global review. Diversity and distributions, 17(5), 788-809. https://doi.org/10.1111/j.1472-4642.2011.00782.x

Ser. The ser international primer on ecological restoration. Society for Ecological Restoration International, Tucson – USA, 2004.

Team, R. C. (2020). R: A language and environment for statistical computing.

Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future. Human resource development review, 15(4), 404-428. https://doi.org/10.1177/1534484316671606

Tulloch, A. I. T., Sutcliffe, P., Naujokaitis-Lewis, I., Tingley, R., Brotons, L., Ferraz, K., Possingham, H., Guisan, A., & Rhodes, J. R. (2016) Conservation planners tend to ignore improved accuracy of modelled species distributions to focus on multiple threats and ecological processes. Biological Conservation 199: 157-171. https://doi.org/10.1016/j.biocon.2016.04.023

Van Loon, A. H., Soomers, H., Schot, P. P., Bierkens, M. F. P., Griffioen, J., & Wassen, M. J. (2011) Linking habitat suitability and seed dispersal models in order to analyse the effectiveness of hydrological fen restoration strategies. Biological Conservation 144: 1025-1035. https://doi.org/10.1016/j.biocon.2010.12.021

Downloads

Publicado

16/07/2021

Como Citar

AMARAL, L. A.; FERREIRA, R. A.; MANN, R. S. O uso de modelagem de distribuição de espécies para restauração florestal: Uma revisão sistemática. Research, Society and Development, [S. l.], v. 10, n. 8, p. e46610817158, 2021. DOI: 10.33448/rsd-v10i8.17158. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/17158. Acesso em: 23 nov. 2024.

Edição

Seção

Ciências Agrárias e Biológicas