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The following is the established format for referencing this article:
Newton, A. C., L. Cayuela, C. Echeverría, J. J. Armesto, R. F. Del Castillo, D. Golicher, D. Geneletti, M. Gonzalez-Espinosa, A. Huth, F. López-Barrera, L. Malizia, R. Manson, A. Premoli, N. Ramírez-Marcial, J. Rey Benayas, N. Rüger, C. Smith-Ramírez, and G. Williams-Linera. 2009. Toward integrated analysis of human impacts on forest biodiversity: lessons from Latin America. Ecology and Society 14(2): 2. [online] URL: http://www.ecologyandsociety.org/vol14/iss2/art2/


Toward Integrated Analysis of Human Impacts on Forest Biodiversity: Lessons from Latin America

Adrian C. Newton 1, Luis Cayuela 2, Cristian Echeverría 3, Juan J. Armesto 4, Rafael F. Del Castillo 5, Duncan Golicher 6, Davide Geneletti 7, Mario Gonzalez-Espinosa 8, Andreas Huth 9, Fabiola López-Barrera 10, Lucio Malizia 11, Robert Manson 10, Andrea Premoli 12, Neptali Ramírez-Marcial 8, José-Maria Rey Benayas 13, Nadja Rüger 9, Cecilia Smith-Ramírez 4 and Guadalupe Williams-Linera 10

1Centre for Conservation Ecology and Environmental Change, Bournemouth University, 2Departamento de Ecología, Universidad de Alcalá, 3Universidad de Concepción, 4Pontificia Universidad Católica de Chile, 5CIIDIR, Instituto Politécnico Nacional, 6El Colegio de la Frontera Sur, 7Università degli Studi di Trento, 8ECOSUR, 9UFZ, 10Instituto de Ecología, 11Fundación Proyungas, 12Universidad Nacional del Comahue, 13Universidad de Alcalá


Although sustainable forest management (SFM) has been widely adopted as a policy and management goal, high rates of forest loss and degradation are still occurring in many areas. Human activities such as logging, livestock husbandry, crop cultivation, infrastructural development, and use of fire are causing widespread loss of biodiversity, restricting progress toward SFM. In such situations, there is an urgent need for tools that can provide an integrated assessment of human impacts on forest biodiversity and that can support decision making related to forest use. This paper summarizes the experience gained by an international collaborative research effort spanning more than a decade, focusing on the tropical montane forests of Mexico and the temperate rain forests of southern South America, both of which are global conservation priorities. The lessons learned from this research are identified, specifically in relation to developing an integrated modeling framework for achieving SFM. Experience has highlighted a number of challenges that need to be overcome in such areas, including the lack of information regarding ecological processes and species characteristics and a lack of forest inventory data, which hinders model parameterization. Quantitative models are poorly developed for some ecological phenomena, such as edge effects and genetic diversity, limiting model integration. Establishment of participatory approaches to forest management is difficult, as a supportive institutional and policy environment is often lacking. However, experience to date suggests that the modeling toolkit approach suggested by Sturvetant et al. (2008) could be of value in such areas. Suggestions are made regarding desirable elements of such a toolkit to support participatory-research approaches in domains characterized by high uncertainty, including Bayesian Belief Networks, spatial multi-criteria analysis, and scenario planning.

Key words: biodiversity conservation; environmental modeling; landscape ecology; Latin America; spatial analysis; sustainable forest management


Over the past two decades, sustainable forest management (SFM) has become a global environmental issue, reflecting widespread concern about high rates of forest loss and degradation. This is illustrated by the development of international policy initiatives such as the Convention on Biological Diversity (CBD), the Forest Principles of Agenda 21, the United Nations Forum on Forests (UNFF), and the many processes developing criteria and indicators for SFM (Newton 2007a, Nussbaum and Simula 2005, Wiersum 1995). Despite these initiatives, progress toward SFM has been very limited (Rametsteiner and Simula 2003), and high rates of forest loss and degradation are still being reported in many areas (Food and Agriculture Organization (FAO) 2006).

SFM can be considered as a form of integrated land-use planning, which requires integration of social, economic, and environmental information (Nussbaum and Simula 2005). Sturtevant et al. (2007) note that to achieve SFM, tools for supporting strategic landscape planning are required that address specific questions and use local information, while making use of existing models and techniques. As the socioeconomic and environmental relationships associated with SFM are complex, no single model or tool is likely to suffice. Consequently Sturtevant et al. (2007) propose a “toolkit” approach, involving selection of a range of pre-existing models from a model toolkit, each appropriate for use at a particular scale and domain. Implementation of this approach presents the challenge of integrating the different information produced by such models, across a range of scales. Sturtevant et al. (2007) suggest that this may be achieved by the use of “meta-models” (defined as “models derived from other models”; Urban et al. 1999), in which models are loosely coupled by using output from one as input to another.

The toolkit approach arose from studies of boreal forested ecosystems in North America (e.g., Fall et al. 2004, Sturtevant et al. 2004, Gustafson et al. 2006). This raises the question of whether such an approach might be of value to forests in other areas with very different characteristics. Many developing countries are currently experiencing high rates of forest loss and degradation as a result of over-exploitation and conversion of forest to other land uses (Newton 2007b, FAO 2006, Millennium Ecosystem Assessment (MEA) 2005). In such circumstances, SFM may appear to be a very distant prospect, with timber effectively being mined rather than sustainably harvested. Land-use planning may be very limited or even entirely lacking, reflecting limited institutional capacity, and a lack of an appropriate legislative framework, financial resources, and political will. Use of scientific information or decision-support tools of any kind in such situations is currently rare. These conditions prevail in many forest areas of global conservation importance, such as the biodiversity hotspots identified by Myers et al. (2000). In such areas, tools and approaches for supporting implementation of SFM are urgently required.

This paper summarizes the experience gained by an international collaborative research effort spanning more than a decade, which focused on the tropical montane forests of Mexico and the temperate rain forests of southern South America. These forest types have previously been neglected by researchers, despite their global conservation importance. Both types are characterized by high species richness and endemism, and are consequently recognized as global conservation priorities, being listed as biodiversity “hotspots” (Myers et al. 2000) and as priority ecoregions (Dinerstein et al. 1995). The objective of the research was to investigate the impacts of human activities on forest biodiversity, with the aim of informing the development of SFM approaches. Research results are summarized by Newton (2007b). The current paper identifies the lessons learned from this research, specifically in relation to developing an integrated modeling framework for achieving SFM. Reference is also made to an ongoing research initiative in the same geographic areas, focusing on restoration of dryland forests (Newton 2008a), in which many of the same partners are involved. In each case, research has primarily focused on forest areas that are being subjected to some form of human use, namely those areas lying outside protected area networks. As noted by Lindenmayer and Franklin (2002), the future conservation of forest biodiversity will depend largely on how such unprotected forest areas are managed.


Study Areas

Research was undertaken in Mexico, in the states of Veracruz, Oaxaca, and Chiapas, and in the southern cone of South America (Chile and Argentina) (Appendix 1). Despite differing in their floristic composition, moist forests in these areas are structurally similar, including both coniferous and broadleaved tree species. Climatic conditions are also broadly similar, being humid (mean annual rainfall >2000 mm) and temperate in character (mean annual temperatures 10–20°C). In Mexico, upper montane forests cover less than 1% of the land surface of the country, but contain about 12% of the country’s 30 000 plant species, some 30% of which are endemic (Rzedowski 1996). The temperate rain forests of southern South America (“Valdivian” forests of Chile and Argentina) are home to more than 900 vascular plant species, including 60 tree species, over 90% of which are endemic (Arroyo et al. 1995).

Forests in each of the study areas play a major role in supporting the livelihoods of rural communities, but face similar pressures resulting from human activities, including clearance for agriculture, browsing by livestock, human-set fires, timber logging, and fuelwood extraction. Typically, current land cover is a mosaic of remnant patches of degraded native primary forest, secondary forest, plantations, pastures, agricultural crops, and human settlements. In Chiapas and Oaxaca, land tenure is generally communal, whereas in the other study areas, most land is privately owned. Further details of the study areas are provided in Appendix 1. It should be noted that progress toward sustainable harvesting of forest products from natural forests has been very limited in all of the study areas.

Analytical Framework

A conceptual model was developed at the outset of the research, to provide an analytical framework for the research activities and to support integration of results. The model is based on the assumption that the conservation of biodiversity depends on the maintenance of key ecological processes, which determine the composition and structure of biological communities and patterns of genetic variation (Fig. 1). In areas subjected to human use, the main factor determining the scope for biodiversity conservation is the extent to which these processes are influenced by patterns of land use. Areas where deforestation is occurring at a high rate are generally characterized by conversion of forest to agricultural land uses, such as crop cultivation and grazing, often in addition to logging and the use of fire. Clearance of forest for agriculture leads to a decline in forest area and fragmentation of forest habitat. Remnant patches of forest may be further degraded by extraction of forest products, and by alteration of environmental conditions in newly created forest edges. Human activities may have impacts both at the landscape scale and the scale of individual forest patches, influencing habitat characteristics and ecological processes at these different scales (Fig. 1).

Research activities were organized as a series of themes, each addressing an individual aspect of the overall objective of SFM (Fig. 2). Research actions focused primarily on conservation of forest biodiversity as a key component of sustainable management approaches, but to date have not examined the full range of environmental and socioeconomic aspects that SFM encompasses. Integration of research results required information flow between research themes, and was achieved using a variety of different modeling approaches (Table 1). Research outputs were also designed to support the development and implementation of policies relating to SFM, through the development of decision-support tools and management recommendations. Details of the research methods adopted for each of these themes are presented below, with particular reference to the modeling tools employed.


The pattern of forest loss was examined in four study areas by producing maps of forest cover from Landsat satellite images and aerial photographs, using a geographic information system (GIS). Two of these study areas are located in Mexico (Chiapas and Veracruz) and two in Chile (Rio Maule-Cobquecura, “Maule”; and Los Muermos–Ancud, “Muermos”). Forest maps were produced from images obtained at different times during the past three decades, which were classified using results from field surveys, and used to estimate annual deforestation rates (Cayuela et al. 2006a,c, Echeverría et al. 2006, 2007a). Landscape spatial indices were computed using FRAGSTATS (version 3.3) (McGarigal et al. 2002). Results indicated that substantial deforestation has occurred in each of the study areas in recent decades (Fig. 3; Cayuela et al. 2006a,c, Echeverría et al. 2006, 2007a). For example, in Chiapas, by 2000 forest area had declined to less than one-third of its value in 1975. Between 1975 and 1990, the forest loss rate was 1.5% yr-1, whereas between 1990 and 2000, this rate increased to 6.1% yr-1. In Maule, 67% of the native forest existing in 1975 had disappeared by 2000, equivalent to an annual deforestation rate of 4.4% yr-1. Most of the forest loss occurred in the period 1975–1990, at a deforestation rate of 5.0% yr-1. In Muermos, approximately 23% of native forest present in 1976 had disappeared by 1999, at an annual forest loss of 1.1% yr-1. In Veracruz, loss of native forest occurred at a rate of 2.0% yr-1.

In each study area, deforestation was accompanied by substantial forest fragmentation (Cayuela et al. 2006a,c, Echeverría et al. 2006, 2007a,b). The mean size of forest patches declined progressively, displaying most rapid decline in Chiapas (Fig. 4a). This was accompanied by an increase in patch density, with rate of change again most pronounced in Chiapas (Fig. 4b). However, in Maule, patch density declined during 1990–2000. This reflected the fact that deforestation had been so severe that little forest was left to be divided into smaller patches. In all study areas, these changes were associated with a decrease in the percentage of area accounted for by the largest patch, a decrease in total interior area of forest patches, and an increase in the isolation of forest patches.

Both forest loss and fragmentation were explored using statistical and rule-based modeling approaches, to examine the spatial dynamics of forest cover at the landscape scale and the potential influence of different drivers. For example, Echeverría et al. (2008) used both spatially explicit logistic regression and a GIS-based land-use change model (GEOMOD) to examine the pattern of forest loss and fragmentation in southern Chile during the past three decades. Both modeling approaches showed consistent and complementary results with respect to the drivers that were most related to deforestation. Results indicated that between 1976 and 1999, forest loss has occurred mainly from the edges of small fragments situated on gentle slopes (<10°) and located far away from rivers, the latter finding relating to the fact that clearance of forests is legally prohibited in areas close to rivers or with high flood risk (Echeverría et al. 2008). GEOMOD was able to correctly classify 88% of grid cells based on decision rules relating to slope, distance to rivers, and a nearest-neighbor deforestation rule. These results indicated that forest logging and clearance for crops and pasture land are the main human activities associated with the changes in the spatial configuration of forest cover (Echeverría et al. 2008). Similarly, Wilson et al. (2005) used classification tree and regression analyses to analyze conversion of native forest in southern Chile to plantations of exotic species. Results indicated that significant variables associated with this conversion included soil type, slope, altitude, distance to roads, and distance to towns.


The characteristics of habitat edges are influenced by patterns of land use surrounding forest fragments and can have a major impact on biodiversity by affecting ecological processes such as dispersal, establishment, survival, and growth (Harper et al. 2005). A large number of studies have examined such impacts, and have identified a wide variety of responses. Ries et al. (2004) and Harper et al. (2005) both present conceptual models of edge effects based on reviews of the results obtained by previous investigations. However, progress toward developing quantitative predictive models for edge effects has been limited to date.

We undertook 22 field-based studies comparing forest edge and forest interior habitats (Table 2, López-Barrera et al. 2007a). From the 34 response variables considered, 19 resulted in a positive edge effect (i.e., higher values of the response variable in the edge vs. forest), nine in a negative edge effect, and six recorded no edge effect. Edge effects were detected on a wide variety of processes, including seed rain, avian nest predation, seed germination, seed removal, and predation (Table 2). From all of the response variables tested in three different study regions, only tree seedling growth and survival exhibited consistent responses in all regions, displaying higher values in edges.

Our results were consistent with some hypotheses presented previously. For example, as predicted by Harper et al. (2005), we found that the magnitude of edge effects was greater at edges with more pronounced contrasts. High and low contrast edges produced different responses in seed removal and seed dispersal across edges (López-Barrera et al. 2005, 2007b, Guzman-Guzman & Williams-Linera 2006), seedling herbivory (López-Barrera et al. 2006), seed germination (López-Barrera and Newton 2005), diversity and abundance of small mammals, and edge microclimate (López-Barrera et al. 2007a). Edge type affected animal movement, with low-contrast edges enhancing small-mammal dispersal of seeds from the forest edge into adjacent old fields, whereas high-contrast edges tended to concentrate seed dispersal along edges (López-Barrera et al. 2007a).

However, our finding that edge effects are widespread in tropical montane and temperate rain forests contradicts Harper et al. (2005), who hypothesized that edge effects are more likely to be pronounced in lowland tropical forests, where air temperatures and solar radiation are higher and cloud cover lower. Furthermore, we demonstrated that a number of factors modulate the intensity, direction, and type of edge effect recorded. Such factors were recorded in 40% of our studies that recorded an edge effect, and included both the distribution and characteristics of species, edge orientation with respect to biotic or abiotic fluxes, and season or year of study. For example, changes in the distribution of seed predators and dispersers along the forest-edge gradient affected the processes of seed predation and dispersal (Díaz et al. 1999, López-Barrera 2003, López-Barrera et al. 2005, 2006, 2007a,b, Guzmán-Guzmán and Williams-Linera 2006). These edge effects were determined by factors such as species, degree of canopy opening and the occurrence of mast-seeding years.

Another key finding was that edge effects were influenced by human disturbance within forest fragments, such as collection of firewood and livestock browsing. Most previous studies of edge effects compared well-preserved forest fragments with a highly disturbed surrounding matrix, ignoring the potential occurrence of human disturbance within forest fragments (Harper et al. 2005). Our results indicate that edge effects are more difficult to detect and are probably less ecologically important in forests subjected to such disturbance.


Although the loss and fragmentation of forest area are generally considered to be the most important causes of biodiversity loss, further losses can occur because of human disturbance within remnant forest fragments. In the study areas considered here, the following forms of anthropogenic disturbance were chronic and widespread: logging of timber, fuelwood cutting, browsing by livestock, and development of infrastructure (principally roads) (Ramírez-Marcial et al. 2001, Aravena et al. 2002, Galindo-Jaimes et al. 2002, Williams-Linera 2002). Human-set fires were also a common feature, except in Veracruz.

Substantial impacts of human disturbance on forest stand structure and composition were identified by analysis of gradients of disturbance in four study areas, using regression analyses (Newton et al. 2007), and by analysis of field data derived from successional chronosequences in Oaxaca, Mexico (del Castillo and Blanco-Macías 2007). These results were supported by modeling exercises exploring dynamics of montane forests in Chiapas, where the long-term dynamics of forest stands were explored using Markovian stochastic models (Zavala et al. 2007). Transition matrices were used to evaluate the probability of replacement of canopy-tree species by other species, based on their ecological characteristics and regeneration patterns, which were determined using results from field surveys. Results indicated the potential for competitive exclusion of pines (Pinus spp.) and oaks (Quercus spp.) by shade-tolerant broadleaved tree species in the absence of human disturbance, but also highlighted the influence of environmental variables (such as rainfall availability) on successional trajectories.

In addition, also in Chiapas, an individual tree-based gap model was parameterized using field data, and used to examine the process of forest recovery following disturbance (Golicher and Newton 2007). Results indicated that the recovery rate of tropical montane forest following human disturbance is very low, even when a source of colonists is assumed to exist nearby. Simulations suggested that it may take several hundred years to re-establish a canopy dominated by shade-tolerant tree species (Fig. 5). In forests subjected to recurrent disturbance, such tree species may become locally extinct. These results were further supported by simulations performed with the process-based forest growth model FORMIND (Köhler and Huth 1998, Köhler et al. 2001) for tropical montane forest in Veracruz, where relatively slow-growing, shade-tolerant canopy tree species did not achieve steady-state basal area until around ca. 300 years after disturbance (Rüger et al. 2008). Modeling results from temperate rain forest in Chile also indicated slow recovery following human disturbance (Rüger et al. 2007b). When long-term dynamics of a forest in Chiloé (Chile) following a clearfell was simulated over a 1500-year period, including natural medium-scale disturbances (e.g., windthrows), total basal area reached a steady state after 200 years (Fig. 6). However, the basal area of some species attained a steady state only after 1000 years.

Statistical analyses of field data together with remote-sensing imagery also identified interactions between forest fragmentation and anthropogenic disturbance within forest patches. For example, in southern Chile, significant negative relationships were found between patch size and indicators of human disturbance such as the number of animal trails, counts of feces produced by livestock, and the number of cut tree stumps (Echeverría et al. 2007b).


The impact of forest fragmentation on tree species richness was explored using regression models, by relating the results of floristic surveys to different measures of forest fragmentation derived from analysis of remote-sensing imagery. For example, in southern Chile, data from 63 sampling plots distributed in 51 forest fragments with different spatial attributes were sampled. Results indicated that the area, core area, edge length, and proximity of forest fragments were all negatively associated with mean species richness of pioneer species, and positively associated with richness of forest interior species. Patch size was the most important attribute influencing different measures of species composition, being significantly related to the abundance of tree and shrub species associated with interior and edge habitats (Echeverría et al. 2007b).

In Chiapas, we identified all tree species within 204 field plots (each 1000 m2) and measured different environmental, human disturbance-related, and spatial variables using remote sensing and GIS data (Cayuela et al. 2006d). To obtain a predictive model of α tree diversity (Fisher’s alpha) based on selected explanatory variables, we used a generalized linear model with a gamma error distribution. Mantel tests of matrix correspondence were used to determine whether similarities in floristic composition were correlated with similarities in the explanatory variables. The model for α diversity explained 44% of the overall variability, of which most was related to precipitation, temperature, normalized difference vegetation index (NDVI), and canopy cover. These results were used to identify and assign conservation priority to unexplored areas with potentially high tree diversity (Cayuela et al. 2006d).


Genetic variation is rarely considered in analyses of SFM, despite being widely acknowledged as a key component of biodiversity. To assess the potential impacts of forest loss on genetic diversity, patterns of genetic variation within selected tree species were analyzed using molecular markers. Results revealed an unexpectedly high degree of population differentiation in many species (Table 3). In the 10 species investigated by random amplification of polymorphic DNA (RAPD), the mean percentage of genetic variation recorded between populations was 19.4%, reaching a maximum of 54.8% in the endemic vine Berberidopsis corallina. Hamrick et al. (1992), in a review of isozyme analyses of 195 woody perennial plants, reported an overall mean value of 8.4% differentiation among populations, less than half the value recorded here with DNA markers. Perhaps significantly, most species surveyed by Hamrick et al. (1992) were north-temperate or lowland-tropical in origin. Evidence suggests that tropical montane and south temperate rainforest trees display very different biogeographic and evolutionary histories, characterized by relatively limited post-glacial migration and long-term isolation between populations (Newton et al. 2002, Premoli et al. 2002, 2007). High population differentiation implies that relatively high losses of genetic variation are likely to have occurred as a result of deforestation, although the lack of baseline data makes these losses difficult to estimate with precision.

Forest fragmentation can also affect genetic variation within species, by influencing processes of gene flow, inbreeding, and genetic drift (Fig. 1). Several of the species examined, notably Pinus chiapensis, Berberidopsis corallina, and Pilgerodendron uviferum displayed relatively low intraspecific genetic variation (Table 3), suggesting that fragmentation, and consequent isolation of populations, may be reducing genetic variation within these species. Analyses of mating system in several populations of the threatened conifer Pinus chiapensis revealed inbreeding depression in relatively small, isolated populations, resulting in low seed germination (Premoli et al. 2007). The most detailed analysis of fragmentation effects on genetic variation was undertaken with the bird-pollinated tree Embothrium coccineum. Seedling growth correlated positively with the number of alleles, indicating a deleterious effect of inbreeding. However, as a result of the foraging behaviour of bird pollinators, higher outcrossing rates were recorded in smaller forest fragments than in larger patches, reducing the risk of inbreeding in the former (Mathiasen et al. 2007). These results indicate that fragmentation can have positive effects on gene flow in some species, by influencing animal behavior and plant–animal interactions.


The potential for sustainable harvesting of timber and fuelwood was assessed using the process-based forest-growth model FORMIND in central Veracruz and in Chiloé. Simulation results show that both forest types have potential for sustained wood production (Rüger et al. 2007b, 2008). Estimated potential harvests of up to 12 m³ ha-1 yr-1 for Mexican montane cloud forest and up to 13 m³ ha-1 yr-1 for Chilean temperate rain forest are substantially lower than growth rates of plantations of Eucalyptus spp. or Pinus radiata, which reach mean annual volume increments of 40 and 30 m³ ha-1, respectively (Ugalde and Pérez 2001). However, simulated annual volume increments are relatively high compared with those predicted for various tropical lowland forests, which range between 1 and 4 m³ ha-1 (Huth and Ditzer 2001, Kammesheidt et al. 2002, van Gardingen et al. 2003). However, harvesting the forests at such high rates has a strong impact on the size structure and species composition of the forests. For both forest types, an ecological index measuring the similarity of the simulated logged forest to undisturbed old-growth forest consistently decreased linearly with increasing levels of wood extraction (Fig. 7). Moreover, FORMIND simulations indicated that even at low logging intensities, the number of large trees markedly decreases over the long term. As a consequence, forest structure becomes simplified and habitat value is reduced (Rüger et al. 2007b).

Similarly, exploration of the individual tree-based gap model (PINQUE) in Chiapas suggested that the potential exists for sustainable timber harvesting (Golicher and Newton 2007). However, the harvesting regime adopted has a major impact on both forest structure and composition. Following harvesting or forest clearance, pines will initially tend to dominate the forest canopy, but in the absence of any further disturbance, oaks will tend to dominate after a period of approximately 70 years (Fig. 5). However, if subjected to recurrent disturbance equivalent to timber cutting, pine dominance within the stands (as indicated by basal area values) may continue indefinitely. A regime of less intensive use, involving disturbance of small patches, creates a forest that is heterogeneous in structure in which either pines or oaks may dominate.

In addition, population viability analyses (PVA) based on the use of transition matrix models were used to examine the potential impact of harvesting on the populations of selected tree species. For example, Bekessy et al. (2004) used a spatially structured metapopulation model based on transition matrices to examine harvesting impacts on the threatened conifer Araucaria araucana, together with other disturbances including fire, timber harvesting, and volcanic activity. Results indicated that the species has very limited ability to recover after disturbance, although seed harvesting appeared to be having relatively little effect on population viability compared with the other forms of disturbance assessed.


We established experimental restoration trials on 33 sites within six study areas (Gonzalez-Espinosa et al. 2007). Most experiments focused on establishment of native tree species on former agricultural land, or floristic enrichment of impoverished secondary stands (Alvarez-Aquino et al. 2004), and were analyzed using standard statistical approaches (such as ANOVA). Results indicate that establishment of native tree species can be achieved through a variety of means, including artificial establishment and/or encouragement of natural regeneration, in a wide range of site conditions. A range of factors were found to influence the growth and survival of established trees, including light availability, soil conditions, and drainage. Most importantly, establishment of shade-tolerant tree species was often enhanced by the presence of other plants, emphasizing the importance of facilitation as an establishment mechanism and highlighting the importance of understanding successional processes when developing forest restoration practices.

Experimental investigations were complemented by forest modeling simulations, using PINQUE and FORMIND. Results indicated that these forests take a great deal of time to recover following disturbance. Whereas structural characteristics such as total stem number, basal area, or leaf area index recover rapidly, variables characterizing old-growth conditions such as late-successional species composition or the number of large trees require a timescale of centuries to re-establish (Golicher and Newton 2007, Rüger et al. 2007a,b, 2008).


The analytical framework underpinning this research initiative (Fig. 2) was designed to support the integration of research results to provide support to decision makers, with the overall goal of assisting progress toward SFM. Many of the individual research activities produced outputs of value to this process. In particular, the production of map-based research outputs using GIS greatly facilitated data integration and presentation in a form that could readily be understood by decision makers. Statistical models of the spatial dynamics of forest cover were integrated with species distribution data, and were used to identify areas of actual or potential biodiversity loss, and thereby to identify priorities for conservation action (Wilson et al. 2005, 2007, Cayuela et al. 2006a,b,c,d, Echeverría et al. 2007a, 2008, Rey Benayas et al. 2007). Similarly, information on genetic variation was used to identify management priorities (Premoli et al. 2007), and recommendations for sustainable harvesting were developed based on models of stand dynamics (Rüger et al. 2007a) and tree population dynamics (Bekessy et al. 2004). Research results were also used to develop and test indicators, which could be used to monitor progress toward SFM (Newton et al. 2007).

Two other analytical approaches were employed with the specific aim of integrating research results and communicating findings to decision makers (Appendix 2). Firstly, Bayesian belief networks (BBN) were used to analyze and explore expert knowledge regarding the threats to forest biodiversity within the study areas and to develop projections regarding likely future trends (Miles et al. 2007). This method is particularly applicable to this kind of domain, characterized by high uncertainty and dependence on expert knowledge (Newton 2009). Model output, presented in the form of probabilities associated with different outcomes, can readily be used to provide a type of risk assessment, in this case relating to the likelihood of future biodiversity loss as a result of unsustainable land-use practices.

Secondly, scenarios were developed exploring potential future trends in forest biodiversity, in relation to different management interventions and policy developments (Miles et al. 2007). Scenario planning is increasingly being recognized as a useful tool for developing conservation management approaches under such uncertain conditions (Newton 2007a). A scenario can be defined in this context as an account of a plausible future. In this case, scenarios were informed by results obtained from the different research activities, including model outputs. In this way, scenario building offers a tool for integration of data, models, and other evidence (such as experimental results) in a way that links closely to the needs of decision makers by providing a tool for exploring the potential impacts of different management and policy interventions. The approach was also used to identify priorities for management action (Miles et al. 2007).


Sturtevant et al. (2007) suggest that although developed primarily for North American boreal forests, the SFM toolkit approach should be applicable to other socioeconomic and ecological contexts. Our results support this contention, as a variety of modeling approaches developed for north-temperate forests have successfully been applied to a range of forest areas in Latin America. However, the situation in these areas is very different from that prevailing in many north-temperate countries. Our research results indicated that high rates of forest loss have occurred in each of the study areas during recent decades. The annual rates of deforestation recorded generally fall within the range of values typical for areas undergoing rapid change in forest cover: 2% to 5% (Lambin et al. 2003). However, the rate of forest loss recorded in Chiapas during the period 1990–2000 (6.1% yr-1) is exceptionally high, exceeding that (6% yr-1) recorded for lowland deciduous forest in eastern Santa Cruz, Bolivia in the mid 1990s (Steininger et al. 2001), thought to be one of the highest deforestation rates reported anywhere in the world. In general, forest loss was associated with conversion to either crop or pasture lands by smallholders, or as in the case of Chile, conversion to plantation forestry, processes neglected by previous reviews (Lambin et al. 2001, 2003). Forest loss has been accompanied by substantial fragmentation. For example, over the last three decades, total core area of forest patches declined by 96% and 90% in Maule and Chiapas, respectively, whereas mean proximity of forest fragments declined by 98.7% and 98.6%, respectively (Rey Benayas et al. 2007).

Within the forest fragments that remain, human disturbance was found to be chronic and widespread. Forest patches are being subjected to tree cutting, browsing by livestock, construction of roads and tracks, and human-set fire, often in combination. Such disturbance has a negative impact on tree species richness (Ramírez-Marcial et al. 2001, Aravena et al. 2002, Galindo-Jaimes et al. 2002, Cayuela et al. 2006b,d, Echeverría et al. 2007a,b, Rey Benayas et al. 2007). In Chiapas and Oaxaca, the forests have been subjected to human disturbance over a prolonged period, as traditional land use involved shifting agriculture followed by land abandonment, providing opportunities for the forest to recover. However, this traditional form of land use is now being abandoned, and increasingly agriculture is being intensified in fixed locations through the use of fertilizers, limiting opportunities for forest recovery. Our results also provide clear evidence of interactions between fragmentation and other anthropogenic impacts. For example, in Muermos, southern Chile, intensity of browsing by livestock and harvesting of trees for timber were found to be higher in smaller forest fragments (Echeverría et al. 2007b). As forest fragments decline in area, they become more accessible to both people and livestock, resulting in a positive feedback between forest loss, fragmentation, and degradation. As a result, remnant forest patches become increasingly dominated by early successional species, and old-growth forest areas are progressively eliminated from the landscape (Cayuela et al. 2006b,d, Echeverría et al. 2007a,b).

Approaches to SFM in areas experiencing rapid forest loss will necessarily differ from those typically being adopted in north-temperate countries, where forest areas are relatively stable and management efforts are often supported by a strong legislative framework, institutional capacity, and substantial financial resources. The areas of Latin America that we investigated lack such an enabling environment for SFM. The main priorities are to prevent further forest loss and degradation and to address the degradation that has already occurred, for example, through management interventions aimed at forest restoration. Any modeling toolkit would, therefore, need to include tools for analyzing the process of forest loss and degradation, such as the statistical and rule-based approaches included here, as well as response options such as restoration and sustainable harvesting (Appendix 3).

The development of tools to support SFM in regions such as Latin America faces a number of significant challenges. The parameterization of dynamic forest models is hindered by the lack of information about the ecological characteristics of most of the tree species, an issue compounded by the high species richness and endemicity of the forests concerned. Unlike in North America, it is not the case that a large number of well-parameterized models are already available. There is an urgent need for collection of new field data for model parameterization, as existing forest inventory data are few. Further information is also required on the ecological impacts of different human activities. Our research has indicated that forests may be subjected to a variety of different activities simultaneously, which may have interactive effects on ecological processes. Exploration of such interactions remains a significant modeling challenge.

The issue of scale is recognized to be a central challenge in ecology (Levin 1992, Wiens 1989), and an ability to integrate information obtained at a range of different scales represents an important attribute of any modeling toolkit for SFM. As suggested by Sturtevant et al. (2007), meta-modeling offers a potential approach to assist in this process, for example by using the output of stand-based models (such as FORMIND and PINQUE considered here) to parameterize coarser-scaled models (such as LANDIS II). However, scaling up some ecological phenomena (such as edge effects and processes influencing genetic variation) is particularly challenging (Appendix 2). Land-management decisions should ideally be made at the landscape scale, but the scope for this within the study areas examined here is currently limited because of the lack of appropriate spatial planning processes relating to native forests. Forest loss and degradation, although creating patterns observable at the landscape scale, are largely being produced as a result of the actions of individual landowners at very local scales. Tools may, therefore, be required for scaling up the impacts of land-use decisions made by smallholders, such as agent-based modeling approaches (Berger and Schreinemachers 2006, Huigen 2004, Janssen and Ostrom 2006).

Another key challenge is the integration of different modeling activities in a way that supports decision making. According to Sturtevant et al. (2007), the toolkit approach involves the development of meta-models, created by linking existing models together through some form of loose coupling. In the research described here a degree of such linkage was achieved, for example, through the integration of statistical models of forest loss, fragmentation and species richness to provide forecasts of potential biodiversity loss under different management regimes. The potential exists for much greater integration between models (Appendix 3). For example, current research is focusing on linking statistical models of land-cover change with LANDIS-II and spatial MCA approaches (Newton 2008a). The current aim is for all modeling tools to share the same spatial data sets, which facilitates data transfer and enables strong links to be made with GIS and its associated analytical functionality. However, for some domains (such as genetic variation) this may be difficult to achieve, and some modeling tools will necessarily remain conceptual or qualitative in nature. There is also a need to integrate other forms of evidence besides models, including results from experimental investigations and field surveys, such as the restoration trials and analyses of edge effects described here. Our experience to date suggests that BBNs (Appendix 2) may be particularly valuable for integrating the output of different models, together with other forms of evidence, such as experimental results and expert knowledge, to provide decision-support tools (Newton 2008a, Miles et al. 2007). Scenario planning and spatial MCA approaches (Appendix 2) also have demonstrable value in supporting dialog with decision makers and exploring the potential impacts of different management decisions in domains characterized by high uncertainty (Miles et al. 2007), and are being applied in current research.

Sturtevant et al. (2007) also envisage the toolkit approach being implemented as a collaborative process involving the participation of a range of stakeholders. This is more difficult in areas without an established institutional or policy framework for forest management planning, and in areas where the technical capacity for SFM is very limited, as in the study areas examined here. Stakeholder dialog has, therefore, been limited to date. However, this is being addressed in the latest phase of the research, where a process of consultation with stakeholders has been initiated, involving representatives from local communities and private landowners as well as government and non-government organizations (Newton 2008a). Stakeholder involvement will inevitably require an increased emphasis on the role of forests in supporting livelihoods, as well as on forest biodiversity. An example of how this may be modeled is provided by the CEPFOR project, which examined the socioeconomic values of forests in Mexico and Bolivia, using a variety of participatory approaches (Marshall et al. 2006, Newton et al. 2006). A key current challenge is to develop methods for mapping the value of different ecosystem services on which livelihoods depend (Naidoo and Ricketts 2006) so that this information may be incorporated in spatial planning. Such analyses could potentially be integrated with spatially explicit models of forest dynamics, providing a tool for exploring provision of ecosystem services under different scenarios of environmental change, an approach we are now beginning to explore (Newton 2008a).


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Most of the research described here was undertaken in three projects supported by the European Commission (INCO programme), namely SUCRE (ERBIC18CT970146), BIOCORES (ICA4-CT-2001-10095), and ReForLan (INCO-DEV-3 N° 032132), and three Darwin Initiative (DEFRA, UK Government) grants to the senior author. Additional funding was provided by a variety of sources within the partner countries. All sources of financial support are gratefully acknowledged.


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Address of Correspondent:
Adrian C. Newton
Centre for Conservation Ecology and Environmental Change,
School of Conservation Sciences,
Bournemouth University,
Talbot Campus,
Poole, Dorset BH12 5BB,
United Kingdom

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