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Distribution and conservation of species is misestimated if biotic interactions are ignored: the case of the orchid Laelia speciosa

  • 1.

    Elith, J. & Leathwick, J. R. Species distribution models: Ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst 40, 677–697, https://doi.org/10.1146/annurev.ecolsys.110308.120159 (2009).

    Article  Google Scholar 

  • 2.

    Bosso, L. et al. Loss of potential bat habitat following a severe wildfire: a model-based rapid assessment. Int. J. Wildland Fire 27(11), 756–769, https://doi.org/10.1071/WF18072 (2018).

    Article  Google Scholar 

  • 3.

    Guisan, A. & Thuiller, W. Predicting species distribution: Offering more than simple habitat models. Ecol. Lett. 8, 993–1009, https://doi.org/10.1111/j.1461-0248.2005.00792.x (2005).

    Article  Google Scholar 

  • 4.

    Adhikari, D. et al. Ecological niche modeling as a cumulative environmental impact assessment tool for biodiversity assessment and conservation planning: A case study of critically endangered plant Lagerstroemia minuticarpa in the Indian Eastern Himalaya. J environ manage 243, 299–307, https://doi.org/10.1016/j.jenvman.2019.05.036 (2019).

    Article  PubMed  Google Scholar 

  • 5.

    Peterson, A. T. et al. Ecological niches and geographic distributions. Princeton: Princeton University Press (2011).

  • 6.

    Meineri, E., Skarpaas, O. & Vandvik, V. Modeling alpine plant distributions at the landscape scale: Do biotic interactions matter? Ecol. Model. 231, 1–10, https://doi.org/10.1016/j.ecolmodel.2012.01.021 (2012).

    Article  Google Scholar 

  • 7.

    Soberón, J. & Peterson, A. T. Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodiversity Informatics 2, 1–10, https://doi.org/10.17161/bi.v2i0.4 (2005).

    Article  Google Scholar 

  • 8.

    Wisz, M. S. et al. The role of biotic interactions in shaping distributions and realised assemblages of species: Implications for species distribution modelling. Biol. Rev. 88, 15–30, https://doi.org/10.1111/j.1469-185X.2012.00235.x (2013).

    Article  PubMed  Google Scholar 

  • 9.

    Heikkinen, R. K., Luoto, M., Virkkala, R., Pearson, R. G. & Körber, J. H. Biotic interactions improve prediction of boreal bird distributions at macro-scales. Glob. Ecol. Biogeogr. 16, 754–763, https://doi.org/10.1111/j.1466-8238.2007.00345.x (2007).

    Article  Google Scholar 

  • 10.

    Fay, M. F., Pailler, T. & Dixon, K. W. Orchid conservation: making the links. Ann. Bot. 116(3), 377–319, https://doi.org/10.1093/aob/mcv142 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • 11.

    Araújo, M. B. & Luoto, M. The importance of biotic interactions for modelling species distributions under climate change. Glob. Ecol. Biogeogr 16, 743–753, https://doi.org/10.1111/j.1466-8238.2007.00359.x (2007).

    Article  Google Scholar 

  • 12.

    Belmaker, J. et al. Empirical evidence for the scale dependence of biotic interactions. Glob. Ecol. Biogeogr 24, 750–761, https://doi.org/10.1111/geb.12311 (2015).

    Article  Google Scholar 

  • 13.

    Staniczenko, P. P. A., Sivasubramaniam, P., Suttle, K. B. & Pearson, R. G. Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks. Ecol. Lett. 20, 693–707, https://doi.org/10.1111/ele.12770 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  • 14.

    Callaway, R. M., Reinhart, K. O., Moore, G. W., Moore, D. J. & Pennings, S. C. Epiphyte host preferences and host traits: Mechanisms for species-specific interactions. Oecologia 132, 221–230, https://doi.org/10.1007/s00442-002-0943-3 (2002).

    ADS  Article  PubMed  Google Scholar 

  • 15.

    Elith, J., Kearney, M. & Phillips, S. The art of modelling range-shifting species. Methods Ecol. Evol. 1, 330–342, https://doi.org/10.1111/j.2041-210X.2010.00036.x (2010).

    Article  Google Scholar 

  • 16.

    Copenhaver-Parry, P. E. & Bell, D. M. Species interactions weakly modify climate-induced tree co-occurrence patterns. J. Veg. Sci. 29, 52–61, https://doi.org/10.1111/jvs.12597 (2018).

    Article  Google Scholar 

  • 17.

    Araújo, M. B. In Spatial conservation prioritisation: quantitative methods and computational tools 172–184 (Oxford University Press, 2009).

  • 18.

    García-Valdés, R., Zavala, M. A., Araújo, M. B. & Purves, D. W. Chasing a moving target: Projecting climate change-induced shifts in non-equilibrial tree species distributions. J. Ecol. 101, 441–453, https://doi.org/10.1111/1365-2745.12049 (2013).

    Article  Google Scholar 

  • 19.

    Kozlov, M. V. Losses of birch foliage due to insect herbivory along geographical gradients in Europe: A climate-driven pattern? Clim. Change 87, 107–117, https://doi.org/10.1007/s10584-007-9348-y (2008).

    ADS  Article  Google Scholar 

  • 20.

    Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).

    ADS  CAS  Article  Google Scholar 

  • 21.

    Blois, J. L., Zarnetske, P. L., Fitzpatrick, M. C. & Finnegan, S. Climate change and the past, present, and future of biotic interactions. Science 341, 499–504, https://doi.org/10.1126/science.1237184 (2013).

    ADS  CAS  Article  PubMed  Google Scholar 

  • 22.

    Olsen, S. L., Töpper, J. P., Skarpaas, O., Vandvik, V. & Klanderud, K. From facilitation to competition: Temperature‐driven shift in dominant plant interactions affects population dynamics in semi natural grasslands. Glob. Change Biol. 22, 1915–1926, https://doi.org/10.1111/gcb.13241 (2016).

    ADS  Article  Google Scholar 

  • 23.

    Tylianakis, J. M., Didham, R. K., Bascompte, J. & Wardle, D. A. Global change and species interactions in terrestrial ecosystems. Ecol. Lett. 11, 1351–1363, https://doi.org/10.1111/j.1461-0248.2008.01250.x (2008).

    Article  PubMed  Google Scholar 

  • 24.

    Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Courchamp, F. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377, https://doi.org/10.1111/j.1461-0248.2011.01736.x (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  • 25.

    Balmford, A. & Bond, W. Trends in the state of nature and their implications for human well-being. Ecol. Lett. 8, 1218–1234, https://doi.org/10.1111/j.1461-0248.2005.00814.x (2005).

    Article  PubMed  Google Scholar 

  • 26.

    Wang, D., Hao, Y. U. & Wang, J. Impact of climate change on China’s rice production–an empirical estimation based on panel data (1979–2011) from China’s main rice-producing areas. Singapore Economic Review. World Scientific Publishing Co Pte Ltd (2018).

  • 27.

    Davis, M. B. & Shaw, R. G. Range shifts and adaptive responses to Quaternary climate change. Science 292, 673–679, https://doi.org/10.1126/science.292.5517.673 (2001).

    ADS  CAS  Article  PubMed  Google Scholar 

  • 28.

    Suttle, K. B., Thomsen, M. A. & Power, M. E. Species interactions reverse grassland responses to changing climate. Science 315, 640–642, https://doi.org/10.1126/science.1136401 (2007).

    ADS  CAS  Article  PubMed  Google Scholar 

  • 29.

    Bascompte, J., Jordano, P. & Olesen, J. M. Asymmetric coevolutionary networks facilitate biodiversity maintenance. Science 312, 431–433, https://doi.org/10.1126/science.1123412 (2006).

    ADS  CAS  Article  PubMed  Google Scholar 

  • 30.

    Ives, A. R. & Carpenter, S. R. Stability and diversity of ecosystems. Science 317, 58–62, https://doi.org/10.1126/science.1133258 (2007).

    ADS  CAS  Article  PubMed  Google Scholar 

  • 31.

    Ceja-Romero, J. et al. Las plantas epífitas, su diversidad e importancia. Ciencias 91, 35–41 (2008).

    Google Scholar 

  • 32.

    Stanton, D. E. et al. Epiphytes improve host plant water use by microenvironment modification. Funct. Ecol. 28, 1274–1283, https://doi.org/10.1111/1365-2435.12249 (2014).

    Article  Google Scholar 

  • 33.

    van der Putten, W. H., Macel, M. & Visser, M. E. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels. Philos. Trans. Royal Soc. B. 365, 2025–2034, https://doi.org/10.1098/rstb.2010.0037 (2010).

    Article  Google Scholar 

  • 34.

    Zotz, G. & Bader, M. Y. In Progress in Botany. (Springer, 2009).

  • 35.

    Benzing, D. H. Vascular epiphytes. General biology and related biota. Cambridge University Press (1990).

  • 36.

    Cach-Pérez, M. J. et al. Climatic and structural factors influencing epiphytic bromeliad community assemblage along a gradient of water-limited environments in the Yucatan. Trop. Conserv. Sci. 6, 283–302, https://doi.org/10.1177/194008291300600209 (2013).

    Article  Google Scholar 

  • 37.

    Helliker, B. R. & Griffiths, H. Toward a plant-based proxy for the isotope ratio of atmospheric water vapor. Glob. Change Biol. 13, 723–733, https://doi.org/10.1111/j.1365-2486.2007.01325.x (2007).

    ADS  Article  Google Scholar 

  • 38.

    Hágsater, E. et al. Orchids of Mexico. Instituto Chinoin, A.C, México D. F. (2005).

  • 39.

    Ticktin, T., et al. Synthesis of wild orchid trade and demography provides new insight on conservation strategies. Conserv. Lett. e12697, https://doi.org/10.1111/conl.12697 (2020).

  • 40.

    Secretaria de Medio Ambiente y Recursos Naturales. Norma Oficial Mexicana NOM‐059‐ SEMARNAT‐2010, Protección ambiental‐Especies nativas de México de flora y fauna silvestres‐Categorías de riesgo y especificaciones para su inclusión, exclusión o cambio‐Lista de especies en riesgo. México, DF: Diario Oficial (2010).

  • 41.

    Ávila-Díaz, I. & Oyama, K. Conservation genetics of an endemic and endangered epiphytic Laelia speciosa (Orchidaceae). Am. J. Bot. 94, 184–193, https://doi.org/10.3732/ajb.94.2.184 (2007).

    Article  PubMed  Google Scholar 

  • 42.

    Halbinger, F. & Soto-Arenas, M. Laelias of Mexico. México City: Orquídea (Méx.) (1997).

  • 43.

    IUCN (International Union for Conservation of Nature). IUCN red list categories and criteria. Version 3.1. 2nd edition. IUCN, Gland, Switzerland (2012).

  • 44.

    Cruz-Cárdenas, G., López-Mata, L., Villaseñor, J. L. & Ortiz, E. Potential species distribution modeling and the use of principal component analysis as predictor variables. Rev. Mex. Biodiv. 85(1), 188–199, https://doi.org/10.7550/rmb.36723 (2014).

    Article  Google Scholar 

  • 45.

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978, https://doi.org/10.1002/joc.1276 (2005).

    Article  Google Scholar 

  • 46.

    Wei, B. et al. Predicting the current and future cultivation regions of Carthamus tinctorius L. using MaxEnt model under climate change in China. Glob. Ecol. Conserv. 16, e00477, https://doi.org/10.1016/j.gecco.2018.e00477 (2018).

    Article  Google Scholar 

  • 47.

    Phillips, S. J., Dudík, M. & Schapire, R. E. Maxent software for modeling species niches and distributions (2017).

  • 48.

    Warren, D. L., Glor, R. E. & Turelli, M. ENMTools: A toolbox for comparative studies of environmental niche models. Ecography 33, 607–611. (2010).

    Article  Google Scholar 

  • 49.

    Soberón, J., Osorio-Olvera, L. & Peterson, T. Conceptual differences between ecological niche modeling and species distribution modeling. Rev. Mex. Biodivers. 88, 437–441, https://doi.org/10.1016/j.rmb.2017.03.011 (2017).

    Article  Google Scholar 

  • 50.

    Gibson, L. M., Mychajliw, A. M., Leon, Y., Rupp, E. & Hadly, E. A. Using the past to contextualize anthropogenic impacts on the present and future distribution of an endemic Caribbean mammal. Conserv Biol 33(3), 500–510, https://doi.org/10.1111/cobi.13290 (2019).

    CAS  Article  PubMed  Google Scholar 

  • 51.

    Mohammadi, S., Ebrahimi, E., Shahriari Moghadam, M. & Bosso, L. Modelling current and future potential distributions of two desert jerboas under climate change in Iran. Ecological Informatics 52, 7–13, https://doi.org/10.1016/j.ecoinf.2019.04.003 (2019).

    Article  Google Scholar 

  • 52.

    Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151, https://doi.org/10.1111/j.2006.0906-7590.04596.x (2006).

    Article  Google Scholar 

  • 53.

    Hijmans, R. J. & Graham, C. H. The ability of climate envelope models to predict the effect of climate change on species distributions. Glob. Change Biol. 12, 2272–2281, https://doi.org/10.1111/j.1365-2486.2006.01256.x (2006).

    ADS  Article  Google Scholar 

  • 54.

    Kearney, M. R., Wintle, B. A. & Porter, W. P. Correlative and mechanistic models of species distribution provide congruent forecasts under climate change. Conserv. Lett. 3, 203–213, https://doi.org/10.1111/j.1755-263X.2010.00097.x (2010).

    Article  Google Scholar 

  • 55.

    Phillips, S. J. & Dudík, M. Modeling of species distributions with Maxent: New extensions and a comprehensive evaluation. Ecography 31, 161–175, https://doi.org/10.1111/j.0906-7590.2008.5203.x (2008).

    Article  Google Scholar 

  • 56.

    Jiménez-Valverde, A. & Lobo, J. M. Threshold criteria for conversion of probability of species presence to either-or presence-absence. Acta Oecologica 31, 361–369, https://doi.org/10.1016/j.actao.2007.02.001 (2007).

    ADS  Article  Google Scholar 

  • 57.

    Liu, C., White, M. & Newell, G. Selecting thresholds for the prediction of species occurrence with presence only data. J. Biogeogr. 40(4), 778–789, https://doi.org/10.1111/jbi.12058 (2013).

    Article  Google Scholar 

  • 58.

    Peterson, A. T., Papeş, M. & Soberón, J. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Model. 213, 63–72, https://doi.org/10.1016/j.ecolmodel.2007.11.008 (2008).

    Article  Google Scholar 

  • 59.

    Villaseñor, J. L., López-Mata, L., Cruz-Cárdenas, G., Ortiz, E. & Cadena-Rodríguez, J. Modelación de la riqueza y distribución potencial del bosque húmedo de montaña. Informe final SNIB-CONABIO, México D. F. (2015).

  • 60.

    Barve, N. Tool for Partial-ROC. Biodiversity Institute, Lawrence (2008).

  • 61.

    Girardello, M., Griggio, M., Whittingham, M. J. & Rushton, S. P. Identifying important areas for butterfly conservation in Italy. Anim. Conserv. 12, 20–28, https://doi.org/10.1111/j.1469-1795.2008.00216.x (2009).

    Article  Google Scholar 

  • 62.

    Osorio-Olvera, L., Barve, V., Barve, N., Soberón, J. & Falconi, M. ntbox: From getting biodiversity data to evaluating species distribution models in a friendly GUI environment. R package version 0.2.5.4. (2018).

  • 63.

    Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J Appl Ecol 345, 1223–1232, https://doi.org/10.1111/j.1365-2664.2006.01214.x (2006).

    Article  Google Scholar 

  • 64.

    Flato, G. et al. Evaluation of climate models. In Climate change 2013: The physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change 741–866. Cambridge University Press (2013).

  • 65.

    Elith, J., Kearney, M. & Phillips, S. The art of modelling range‐shifting species. Methods Ecol Evol 1, 330–342, https://doi.org/10.1111/j.2041-210X.2010.00036.x (2010).

    Article  Google Scholar 

  • 66.

    ESRI. ArcGIS desktop. Redlands, CA: Environmental Systems Research Institute (2013).

  • 67.

    Wyse, S. V. & Burns, B. R. Do host bark traits influence trunk epiphyte communities? New Zeal. J. Ecol. 35, 296–301 (2011).

    Google Scholar 

  • 68.

    Ávila-Díaz, I., Garibay-Orijel, R., Magaña-Lemus, R. E. & Oyama, K. Molecular evidence reveals fungi associated within the epiphytic orchid Laelia speciosa (HBK) Schltr. Bot. Sci. 91, 523–529, https://doi.org/10.17129/botsci.429 (2013).

    Article  Google Scholar 

  • 69.

    Kottke, I. & Suárez, C. J. P. Mutualistic, root-inhabiting fungi of orchids identification and functional types. Proceedings of the Second Scientific Conference on Andean Orchids 84–99 (2009).

  • 70.

    Zettler, L. W., Sharma, J. & Rasmussen, F. N. Mycorrhizal diversity. In Orchid conservation 205–226 (Natural History Publications, 2003).

  • 71.

    Martos, F. et al. The role of epiphytism in architecture and evolutionary constraint within mycorrhizal networks of tropical orchids. Mol. Ecol. 21, 5098–5109, https://doi.org/10.1111/j.1365-294X.2012.05692.x (2012).

    Article  PubMed  Google Scholar 

  • 72.

    Smith, S. E. & Read, D. Mycorrhizal Symbiosis. Academic Press (2008).

  • 73.

    Hernández-Apolinar, M. Dinámica poblacional de Laelia speciosa (HBK) Schltr (Orchidaceae). Degree Thesis. (Facultad de Ciencias, Universidad Nacional Autónoma de México, 1992).

  • 74.

    Dormann, C. F. et al. Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions. Glob. Ecol. Biogeogr. 27, 1004–1016, https://doi.org/10.1111/geb.12759 (2018).

    Article  Google Scholar 

  • 75.

    Giannini, T. C., Chapman, D. S., Saraiva, A. M., Alves-dos-Santos, I. & Biesmeijer, J. C. Improving species distribution models using biotic interactions: A case study of parasites, pollinators and plants. Ecography 36, 649–656, https://doi.org/10.1111/j.1600-0587.2012.07191.x (2013).

    Article  Google Scholar 

  • 76.

    Meier, E. S. et al. Biotic and abiotic variables show little redundancy in explaining tree species distributions. Ecography 33, 1038–1048, https://doi.org/10.1111/j.1600-0587.2010.06229.x (2010).

    Article  Google Scholar 

  • 77.

    Early, R. & Keith, S. A. Geographically variable biotic interactions and implications for species ranges. Glob. Ecol. Biogeogr. 28, 42–53, https://doi.org/10.1111/geb.12861 (2019).

    Article  Google Scholar 

  • 78.

    Jaeschke, A. et al. Biotic interactions in the face of climate change: A comparison of three modelling approaches. PLoS ONE 7(12), e51472, https://doi.org/10.1371/journal.pone.0051472 (2012).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  • 79.

    Morales-Castilla, I., Matias, M. G., Gravel, D. & Araújo, M. B. Inferring biotic interactions from proxies. Trends Ecol. Evol. 30, 347–356, https://doi.org/10.1016/j.tree.2015.03.014 (2015).

    Article  PubMed  Google Scholar 

  • 80.

    Pearson, R. G., Dawson, T. E., Berry, P. M. & Harrison, P. A. SPECIES: a Spatial Evaluation of Climate Impact on the Envelope of Species. Ecol. Model. 154, 289–300, https://doi.org/10.1016/S0304-3800(02)00056-X (2002).

    Article  Google Scholar 

  • 81.

    Araújo, M. B. & Rozenfeld, A. The geographic scaling of biotic interactions. Ecography 37, 406–415, https://doi.org/10.1111/j.1600-0587.2013.00643.x (2014).

    Article  Google Scholar 

  • 82.

    Campbell, J., Donato, D., Azuma, D. & Law, B. Pyrogenic carbon emission from a large wildfire in Oregon, United States. J. Geophys. Res. 112, G04014, https://doi.org/10.1029/2007JG000451 (2007).

    ADS  CAS  Article  Google Scholar 

  • 83.

    Pyke, G. H., Thomson, J. D., Inouye, D. W. & Miller, T. J. Effects of climate change on phenologies and distribution of bumble bees and the plants they visit. Ecosphere 7(3), 1–19, https://doi.org/10.1002/ecs2.1267 (2016).

    Article  Google Scholar 

  • 84.

    Gudiño, W., Ávila-Díaz, I., Oyama, K. & de la Barrera, E. High-temperature tolerance by the endangered Mexican Mayflower orchid, Laelia speciosa. Trop. Conserv. Sci. 8, 983–991, https://doi.org/10.1177/194008291500800408 (2015).

    Article  Google Scholar 

  • 85.

    Rapp, J. M. & Silman, M. R. Epiphyte response to drought and experimental warming in an Andean cloud forest. F1000Research 3, 1–7, https://doi.org/10.12688/f1000research.3-7.v2 (2014).

    Article  Google Scholar 

  • 86.

    Wagner, K. & Zotz, G. Epiphytic bromeliads in a changing world: the effect of elevated CO2 and varying water supply on growth and nutrient relations. Plant Biol. 20, 636–640, https://doi.org/10.1111/plb.12708 (2018).

    CAS  Article  PubMed  Google Scholar 

  • 87.

    Medina, N. D. Éxito reproductivo en dos poblaciones de Laelia speciosa (HBK) Schltr. (Orchidaceae), en Michoacán, México. Degree thesis. (Facultad de Biología, Universidad Michoacana de San Nicolás de Hidalgo, 2004).

  • 88.

    Urban, M. C., Zarmetske, P. L. & Skelly, D. K. Moving forward: dispersal and species interactions determine biotic responses to climate change. Ann. N. Y. Acad. Sci. 1297, 44–60, https://doi.org/10.1111/nyas.12184 (2013).

    Article  PubMed  Google Scholar 

  • 89.

    Svenning, J.-C. et al. The influence of interspecific interactions on species range expansion rates. Ecography 37, 1198–1209, https://doi.org/10.1111/j.1600-0587.2013.00574.x (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  • 90.

    Anderson, S. C. et al. Improving estimates of population status and trend with superensemble models. Fish Fish 18(4), 732–741, https://doi.org/10.1111/faf.12200 (2017).

    Article  Google Scholar 

  • 91.

    Hof, A. R., Jansson, R. & Nilsson, C. Future climate change will favour non-specialist mammals in the (sub)arctics. PLoS ONE 7, e52574, https://doi.org/10.1371/journal.pone.0052574 (2012).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  • 92.

    Angert, A. L., LaDeau, S. L. & Ostfeld, R. S. Climate change and species interactions: ways forward. Ann. N. Y. Acad. Sci. 1297, 1–7, https://doi.org/10.1111/nyas.12286 (2013).

    ADS  Article  PubMed  Google Scholar 

  • 93.

    Aguilar-Morales, M. A. & López-Escamilla, A. L. Germinación in vitro de Laelia speciosa (Kunth) Schltr., una herramienta para su conservación ex situ. Estudios científicos en el estado de Hidalgo y zonas aledañas 1, 17–24 (2013).

    Google Scholar 

  • 94.

    Menchaca, A. R. G. & Moreno, D. M. Conservación de orquídeas una tarea de todos. (Texcoco, Estado de México, Mex: Universidad Autónoma Chapingo, 2011).

  • 95.

    Mas, J. et al. Evaluación de las tasas de deforestación en Michoacán a escala detallada mediante un método híbrido de clasificación de imágenes SPOT. Madera y Bosques 23, 119–131 (2017).

    Article  Google Scholar 

  • 96.

    Masera, O., Bellon, M. R. & Segura, G. Forest management options for sequestering carbon in Mexico. Biomass Bioener. 8, 357–367, https://doi.org/10.1016/0961-9534(95)00028-3 (1995).

    Article  Google Scholar 

  • 97.

    Secretaria de Medio Ambiente y Recursos Naturales. Informe de la Situación del Medio Ambiente en México, México (2012).

  • 98.

    Smethurst, D. Mountain Geography. Geogr. Rev. 90, 35–56, https://doi.org/10.2307/216174 (2000).

    Article  Google Scholar 

  • 99.

    Jansky, L., Ives, J. D., Furuyashiki, L. & Watanabe, T. Global mountain research for sustainable development. Glob. Environ. Chang. 12, 231–239, https://doi.org/10.1016/S0959-3780(02)00015-8 (2002).

    Article  Google Scholar 

  • 100.

    Velázquez, A., Bocco, G., Romero, F. J. & Vega, A. P. R. A landscape perspective on biodiversity conservation. Mt. Res. Dev. 23, 240–246 (2003). 10.1659/0276-4741(2003)023[0240:ALPOBC]2.0.CO;2.

    Article  Google Scholar 


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