- Email: [email protected]
Simulating ecosystem functioning of tropical mountainous cloud forests in southern Ecuador
Ecological Modelling 239 (2012) 1–2
Contents lists available at SciVerse ScienceDirect
Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel
Editorial
Simulating ecosystem functioning of tropical mountainous cloud forests in southern Ecuador
Tropical mountainous cloud forests belong to the most diverse ecosystems on earth. If you ask scientists which features characterize these ecosystems, then the answers are as diverse as is the flora and fauna within them: persistent cloud cover, reduced solar radiation due to cloud cover, distinctly structured vegetation forms, suppressed evapotranspiration as a consequence of high relative humidity, stripping of clouds by tree canopies and resulting large amount of throughfall, reduced canopy heights, high rainfall rates, gnarled tree trunks at increasing altitudes, substantial epiphyte biomass, moss-covered stems, organic rich and typically wet soils, and – last but not least – extremely high biodiversity with a paramount endemism (Bruijnzeel et al., 2011). Despite their intrinsic value, tropical mountainous cloud forests are under high pressure, mainly due to expanding infrastructure and agriculture as well as climate change (Foster, 2001; Peh et al., 2011). While timber harvesting and clearing for large scale farming are one of the most dominant reasons in tropical lowland forests, deforestation in tropical mountainous cloud forests is mainly caused by population growth and the associated pressure to produce food and feed by local farming and pastoralism. Yet not much is known about the specific loss rate of tropical mountainous cloud forests, which was reported to be even higher than that of tropical lowland forests in the period 1981–1990 (Doumenge et al., 1995). Given the overall high loss rates of tropical forests mainly in South America and Africa as of today (FAO, 2010) it can be concluded that tropical mountainous cloud forests are still lost at high rates. From all South American countries, Ecuador has the highest annual loss rate of tropical rain forests (including cloud forests) with 1.89% in the reporting period of 2005–2010 (FAO, 2010). This, in combination with an almost unmatched high biodiversity found in the tropical Andes (Myers et al., 2000), were major reasons for the Deutsche Forschungsgemeinschaft to establish two structured Research Units FOR 402 (1999–2006) and FOR 816 (2007–2013) focusing on the biodiversity and sustainable management of mountain ecosystems in Southern Ecuador (www.tropicalmountainforest.org). While much effort has been put into research of biodiversity and its functionality in the past years of the Research Unit, recently we have also begun to investigate the drivers of ecosystem functioning. In this special section, we report on the outcome of four studies that focus on modelling the water cycle, plant competition, landslides, and forest regrowth in the San Francisco catchment of southern Ecuador.
0304-3800/$ – see front matter © 2012 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.ecolmodel.2012.05.027
Water is one of the dominant drivers of tropical mountainous cloud forests. However, understanding the rainfall-runoff generation in these ecosystems is still limited (Crespo et al., 2012). This is partly due to extreme environmental conditions which hinder experimental field work and limited available data such as on hydro-geological conditions. Therefore, to better understand the rainfall-runoff process and to test whether available hydrological models are capable of predicting runoff generation, Plesca et al. (2012) utilized an ensemble of hydrological models to simulate the highly dynamic discharge of the San Francisco catchment. Land clearing in southern Ecuador is often done to create pastures for extensive livestock grazing and dairy by planting the Setaria sphacelata grass. As in many areas of the tropics, weed infestation is a common threat to such pastures. In the case of southern Ecuador, the southern bracken fern (Pteridium arachnoideum) overgrows pastures shortly after their establishment as the result of the current pasture management system with recurrent burning of pastures. Silva et al. (2012) developed a model to investigate and better understand the competition between these two dominant species. Landslides are a typical phenomenon of tropical mountainous rainforests. In contrast to public perception, these landslides not only occur in areas of anthropogenic disturbances, but are also commonly observed in pristine forests. But what are the driving factors of these landslides? Vorpahl et al. (2012) developed a set of phenomenological models to reveal drivers and predictors of landslides and made clear that the vegetation itself is an important trigger of landslide generation. Based on the observation that landslides are a common type of disturbances in these ecosystems, Dislich and Huth (2012) stepped further and investigate how primary succession is developing on such landslides. They compiled a process-based dynamic forest model to study forest recovery on these natural succession plots. Apart from investigations of biomass and species composition on the local level of landslide disturbed sites, they also provide insights on how landslides affect biomass stocks and forest productivity on the landscape scale. Hopefully, modelling the drivers of ecosystem functioning in tropical mountainous cloud forests can help to better understand the key processes that lead to the establishment of the extraordinary biodiversity observed in these fascinating ecosystems. Given the rapid changes in ecosystem structure that are currently going on, not only due to global change but also due local changes, such modeling tools will facilitate to develop improved and sustainable
2
Editorial / Ecological Modelling 239 (2012) 1–2
management plans for safeguarding this valuable ecosystem and its services in the future. References Bruijnzeel, L.A., Scatena, F.N., Hamilton, L.S., 2011. Tropical Montane Cloud Forests: Science for Conservation and Management. Cambridge University Press, Cambridge, 740 pp. Crespo, P., Bücker, A., Feyen, J., Vaché, K.B., Frede, H.G., Breuer, L., 2012. Preliminary evaluation of the runoff processes in a remote montane cloud forest basin using Mixing Model Analysis and Mean Transit Time. Hydrological Processes, http://dx.doi.org/10.1002/hyp.8382. Dislich, C., Huth, A., 2012. Modelling the impact of shallow landslides on forest structure in tropical montane forests. Ecological Modelling 239, 40– 53. Doumenge, C., Gilmour, D., Ruiz Perez, M., Blockhus, J., 1995. Tropical montane cloud forests: conservation status and management issues. In: Hamilton, L.S., Juvik, J.O., Scatena, F.N. (Eds.), Tropical Montane Cloud Forests. Springer, New York, pp. 24–37. FAO, 2010. Global Forest Resources Assessment 2010, FAO Forestry Paper 163. Food and Agriculture Organization of the United Nations, Rome. 340 pp. Foster, P., 2001. The potential negative impacts of global climate change on tropical montane cloud forests. Earth-Science Reviews 55, 73–106. Myers, N., Mittermeier, R.A., Mittermeier, C.G., Da Fonseca, G.A.B., Kent, J., 2000. Biodiversity hotspots for conservation priorities. Nature 403, 853– 858.
Peh, K.S.H., Soh, M.C.K., Sodhi, N.S., Laurance, W.F., Ong, D.J., Clements, R., 2011. Up in the clouds: is sustainable use of tropical montane cloud forests possible in Malaysia? BioScience 61, 27–38. Plesca, I., Timbe, E., Exbrayat, J.-F., Windhorst, D., Kraft, P., Crespo, P., Vaché, K.B., Frede, H.-G., Breuer, L., 2012. Model intercomparison to explore catchment functioning: results from a remote montane tropical rainforest. Ecological Modelling 239, 3–13. Silva, B., Roos, K., Voss, I., König, N., Rollenbeck, R., Scheibe, R., Beck, E., Bendix, J., 2012. Simulating canopy photosynthesis for two competing species of an anthropogenic grassland community in the Andes of southern Ecuador. Ecological Modelling 239, 14–26. Vorpahl, P., Elsenbeer, H., Märker, M., Schröder, B., 2012. How can statistical models help to determine driving factors of landslides? Ecological Modelling 239, 27–29.
Lutz Breuer ∗ Research Centre for BioSystems, Land Use and Nutrition (IFZ), Institute for Landscape Ecology and Resources Management, Justus-Liebig-Universität Gießen, Germany ∗ Tel.:
+49 641 9937395; fax: +49 641 9937389. E-mail address: [email protected]
Contents lists available at SciVerse ScienceDirect
Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel
Editorial
Simulating ecosystem functioning of tropical mountainous cloud forests in southern Ecuador
Tropical mountainous cloud forests belong to the most diverse ecosystems on earth. If you ask scientists which features characterize these ecosystems, then the answers are as diverse as is the flora and fauna within them: persistent cloud cover, reduced solar radiation due to cloud cover, distinctly structured vegetation forms, suppressed evapotranspiration as a consequence of high relative humidity, stripping of clouds by tree canopies and resulting large amount of throughfall, reduced canopy heights, high rainfall rates, gnarled tree trunks at increasing altitudes, substantial epiphyte biomass, moss-covered stems, organic rich and typically wet soils, and – last but not least – extremely high biodiversity with a paramount endemism (Bruijnzeel et al., 2011). Despite their intrinsic value, tropical mountainous cloud forests are under high pressure, mainly due to expanding infrastructure and agriculture as well as climate change (Foster, 2001; Peh et al., 2011). While timber harvesting and clearing for large scale farming are one of the most dominant reasons in tropical lowland forests, deforestation in tropical mountainous cloud forests is mainly caused by population growth and the associated pressure to produce food and feed by local farming and pastoralism. Yet not much is known about the specific loss rate of tropical mountainous cloud forests, which was reported to be even higher than that of tropical lowland forests in the period 1981–1990 (Doumenge et al., 1995). Given the overall high loss rates of tropical forests mainly in South America and Africa as of today (FAO, 2010) it can be concluded that tropical mountainous cloud forests are still lost at high rates. From all South American countries, Ecuador has the highest annual loss rate of tropical rain forests (including cloud forests) with 1.89% in the reporting period of 2005–2010 (FAO, 2010). This, in combination with an almost unmatched high biodiversity found in the tropical Andes (Myers et al., 2000), were major reasons for the Deutsche Forschungsgemeinschaft to establish two structured Research Units FOR 402 (1999–2006) and FOR 816 (2007–2013) focusing on the biodiversity and sustainable management of mountain ecosystems in Southern Ecuador (www.tropicalmountainforest.org). While much effort has been put into research of biodiversity and its functionality in the past years of the Research Unit, recently we have also begun to investigate the drivers of ecosystem functioning. In this special section, we report on the outcome of four studies that focus on modelling the water cycle, plant competition, landslides, and forest regrowth in the San Francisco catchment of southern Ecuador.
0304-3800/$ – see front matter © 2012 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.ecolmodel.2012.05.027
Water is one of the dominant drivers of tropical mountainous cloud forests. However, understanding the rainfall-runoff generation in these ecosystems is still limited (Crespo et al., 2012). This is partly due to extreme environmental conditions which hinder experimental field work and limited available data such as on hydro-geological conditions. Therefore, to better understand the rainfall-runoff process and to test whether available hydrological models are capable of predicting runoff generation, Plesca et al. (2012) utilized an ensemble of hydrological models to simulate the highly dynamic discharge of the San Francisco catchment. Land clearing in southern Ecuador is often done to create pastures for extensive livestock grazing and dairy by planting the Setaria sphacelata grass. As in many areas of the tropics, weed infestation is a common threat to such pastures. In the case of southern Ecuador, the southern bracken fern (Pteridium arachnoideum) overgrows pastures shortly after their establishment as the result of the current pasture management system with recurrent burning of pastures. Silva et al. (2012) developed a model to investigate and better understand the competition between these two dominant species. Landslides are a typical phenomenon of tropical mountainous rainforests. In contrast to public perception, these landslides not only occur in areas of anthropogenic disturbances, but are also commonly observed in pristine forests. But what are the driving factors of these landslides? Vorpahl et al. (2012) developed a set of phenomenological models to reveal drivers and predictors of landslides and made clear that the vegetation itself is an important trigger of landslide generation. Based on the observation that landslides are a common type of disturbances in these ecosystems, Dislich and Huth (2012) stepped further and investigate how primary succession is developing on such landslides. They compiled a process-based dynamic forest model to study forest recovery on these natural succession plots. Apart from investigations of biomass and species composition on the local level of landslide disturbed sites, they also provide insights on how landslides affect biomass stocks and forest productivity on the landscape scale. Hopefully, modelling the drivers of ecosystem functioning in tropical mountainous cloud forests can help to better understand the key processes that lead to the establishment of the extraordinary biodiversity observed in these fascinating ecosystems. Given the rapid changes in ecosystem structure that are currently going on, not only due to global change but also due local changes, such modeling tools will facilitate to develop improved and sustainable
2
Editorial / Ecological Modelling 239 (2012) 1–2
management plans for safeguarding this valuable ecosystem and its services in the future. References Bruijnzeel, L.A., Scatena, F.N., Hamilton, L.S., 2011. Tropical Montane Cloud Forests: Science for Conservation and Management. Cambridge University Press, Cambridge, 740 pp. Crespo, P., Bücker, A., Feyen, J., Vaché, K.B., Frede, H.G., Breuer, L., 2012. Preliminary evaluation of the runoff processes in a remote montane cloud forest basin using Mixing Model Analysis and Mean Transit Time. Hydrological Processes, http://dx.doi.org/10.1002/hyp.8382. Dislich, C., Huth, A., 2012. Modelling the impact of shallow landslides on forest structure in tropical montane forests. Ecological Modelling 239, 40– 53. Doumenge, C., Gilmour, D., Ruiz Perez, M., Blockhus, J., 1995. Tropical montane cloud forests: conservation status and management issues. In: Hamilton, L.S., Juvik, J.O., Scatena, F.N. (Eds.), Tropical Montane Cloud Forests. Springer, New York, pp. 24–37. FAO, 2010. Global Forest Resources Assessment 2010, FAO Forestry Paper 163. Food and Agriculture Organization of the United Nations, Rome. 340 pp. Foster, P., 2001. The potential negative impacts of global climate change on tropical montane cloud forests. Earth-Science Reviews 55, 73–106. Myers, N., Mittermeier, R.A., Mittermeier, C.G., Da Fonseca, G.A.B., Kent, J., 2000. Biodiversity hotspots for conservation priorities. Nature 403, 853– 858.
Peh, K.S.H., Soh, M.C.K., Sodhi, N.S., Laurance, W.F., Ong, D.J., Clements, R., 2011. Up in the clouds: is sustainable use of tropical montane cloud forests possible in Malaysia? BioScience 61, 27–38. Plesca, I., Timbe, E., Exbrayat, J.-F., Windhorst, D., Kraft, P., Crespo, P., Vaché, K.B., Frede, H.-G., Breuer, L., 2012. Model intercomparison to explore catchment functioning: results from a remote montane tropical rainforest. Ecological Modelling 239, 3–13. Silva, B., Roos, K., Voss, I., König, N., Rollenbeck, R., Scheibe, R., Beck, E., Bendix, J., 2012. Simulating canopy photosynthesis for two competing species of an anthropogenic grassland community in the Andes of southern Ecuador. Ecological Modelling 239, 14–26. Vorpahl, P., Elsenbeer, H., Märker, M., Schröder, B., 2012. How can statistical models help to determine driving factors of landslides? Ecological Modelling 239, 27–29.
Lutz Breuer ∗ Research Centre for BioSystems, Land Use and Nutrition (IFZ), Institute for Landscape Ecology and Resources Management, Justus-Liebig-Universität Gießen, Germany ∗ Tel.:
+49 641 9937395; fax: +49 641 9937389. E-mail address: [email protected]