Why have land use change models for the Amazon failed to capture the amount of deforestation over the last decade?

Land cover change in the Neotropics represents one of the major drivers of global environmental change. Several models have been proposed to explore future trajectories of land use and cover change, particularly in the Amazon. Despite the remarkable development of these tools, model results are still surrounded by uncertainties. None of the model projections available in the literature plausibly captured the overall trajectory of land use and cover change that has been observed in the Amazon over the last decade. In this context, this study aims to review and analyze the general structure of the land use models that have most recently been used to explore land use change in the Amazon, seeking to investigate methodological factors that could explain the divergence between the observed and projected rates, paying special attention to the land demand calculations. Based on this review, the primary limitations inherent to this type of model and the extent to which these limitations can affect the consistency of the projections will also be analyzed. Finally, we discuss potential drivers that could have influenced the recent dynamic of the land use system in the Amazon and produced the unforeseen land cover change trajectory observed in this period. In a complementary way, the primary challenges of the new generation of land use models for the Amazon are synthesized. (c) 2014 Elsevier Ltd. All rights reserved.

Design, implementation and application of a generic framework for integrated regional land-use modeling

Land use is a crucial link between human activities and the natural environment and one of the main driving forces of global environmental change. Large parts of the terrestrial land surface are used for agriculture, forestry, settlements and infrastructure. Given the importance of land use, it is essential to understand the multitude of influential factors and resulting land use patterns. An essential methodology to study and quantify such interactions is provided by the adoption of land-use models. By the application of land-use models, it is possible to analyze the complex structure of linkages and feedbacks and to also determine the relevance of driving forces. Modeling land use and land use changes has a long-term tradition. In particular on the regional scale, a variety of models for different regions and research questions has been created. Modeling capabilities grow with steady advances in computer technology, which on the one hand are driven by increasing computing power on the other hand by new methods in software development, e.g. object- and component-oriented architectures. In this thesis, SITE (Simulation of Terrestrial Environments), a novel framework for integrated regional sland-use modeling, will be introduced and discussed. Particular features of SITE are the notably extended capability to integrate models and the strict separation of application and implementation. These features enable efficient development, test and usage of integrated land-use models. On its system side, SITE provides generic data structures (grid, grid cells, attributes etc.) and takes over the responsibility for their administration. By means of a scripting language (Python) that has been extended by language features specific for land-use modeling, these data structures can be utilized and manipulated by modeling applications. The scripting language interpreter is embedded in SITE. The integration of sub models can be achieved via the scripting language or by usage of a generic interface provided by SITE. Furthermore, functionalities important for land-use modeling like model calibration, model tests and analysis support of simulation results have been integrated into the generic framework. During the implementation of SITE, specific emphasis was laid on expandability, maintainability and usability. Along with the modeling framework a land use model for the analysis of the stability of tropical rainforest margins was developed in the context of the collaborative research project STORMA (SFB 552). In a research area in Central Sulawesi, Indonesia, socio-environmental impacts of land-use changes were examined. SITE was used to simulate land-use dynamics in the historical period of 1981 to 2002. Analogous to that, a scenario that did not consider migration in the population dynamics, was analyzed. For the calculation of crop yields and trace gas emissions, the DAYCENT agro-ecosystem model was integrated. In this case study, it could be shown that land-use changes in the Indonesian research area could mainly be characterized by the expansion of agricultural areas at the expense of natural forest. For this reason, the situation had to be interpreted as unsustainable even though increased agricultural use implied economic improvements and higher farmers' incomes. Due to the importance of model calibration, it was explicitly addressed in the SITE architecture through the introduction of a specific component. The calibration functionality can be used by all SITE applications and enables largely automated model calibration. Calibration in SITE is understood as a process that finds an optimal or at least adequate solution for a set of arbitrarily selectable model parameters with respect to an objective function. In SITE, an objective function typically is a map comparison algorithm capable of comparing a simulation result to a reference map. Several map optimization and map comparison methodologies are available and can be combined. The STORMA land-use model was calibrated using a genetic algorithm for optimization and the figure of merit map comparison measure as objective function. The time period for the calibration ranged from 1981 to 2002. For this period, respective reference land-use maps were compiled. It could be shown, that an efficient automated model calibration with SITE is possible. Nevertheless, the selection of the calibration parameters required detailed knowledge about the underlying land-use model and cannot be automated. In another case study decreases in crop yields and resulting losses in income from coffee cultivation were analyzed and quantified under the assumption of four different deforestation scenarios. For this task, an empirical model, describing the dependence of bee pollination and resulting coffee fruit set from the distance to the closest natural forest, was integrated. Land-use simulations showed, that depending on the magnitude and location of ongoing forest conversion, pollination services are expected to decline continuously. This results in a reduction of coffee yields of up to 18% and a loss of net revenues per hectare of up to 14%. However, the study also showed that ecological and economic values can be preserved if patches of natural vegetation are conservated in the agricultural landscape. -----------------------------------------------------------------------

Contrasting models of land use regulation: Community, government and tourism development

This paper assesses the capacity of local communities and sub-national governments to influence patterns of tourism development, within the context of a globalizing economy. Through a comparison of the contrasting examples of Hawaii and Queensland, the paper indicates the consequences of different approaches to land use regulation. It points to the importance of planning and policy processes that integrate community interests, in order to achieve long-term, sustainable tourism development. Effective regulation of development can minimize the social and environmental impacts of tourism. The paper illustrates how community organizations and sub-national governments can articulate local interests, despite the global demands of investors for more deregulated markets in land.

Simulating SOC changes in 11 land use change chronosequences from the Brazilian Amazon with RothC and Century models

Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.

Modeling plant transpiration under limited soil water: comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models

Accurate estimates of how soil water stress affects plant transpiration are crucial for reliable land surface model (LSM) predictions. Current LSMs generally use a water stress factor, β, dependent on soil moisture content, θ, that ranges linearly between β = 1 for unstressed vegetation and β = 0 when wilting point is reached. This paper explores the feasibility of replacing the current approach with equations that use soil water potential as their independent variable, or with a set of equations that involve hydraulic and chemical signaling, thereby ensuring feedbacks between the entire soil–root–xylem–leaf system. A comparison with the original linear θ-based water stress parameterization, and with its improved curvi-linear version, was conducted. Assessment of model suitability was focused on their ability to simulate the correct (as derived from experimental data) curve shape of relative transpiration versus fraction of transpirable soil water. We used model sensitivity analyses under progressive soil drying conditions, employing two commonly used approaches to calculate water retention and hydraulic conductivity curves. Furthermore, for each of these hydraulic parameterizations we used two different parameter sets, for 3 soil texture types; a total of 12 soil hydraulic permutations. Results showed that the resulting transpiration reduction functions (TRFs) varied considerably among the models. The fact that soil hydraulic conductivity played a major role in the model that involved hydraulic and chemical signaling led to unrealistic values of β, and hence TRF, for many soil hydraulic parameter sets. However, this model is much better equipped to simulate the behavior of different plant species. Based on these findings, we only recommend implementation of this approach into LSMs if great care with choice of soil hydraulic parameters is taken

Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Assessing the impacts of land use and land cover change on hydrology of watershed: a case study on Gigel-Abbay Watershed, Lake Tana Basin, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Climate and land-use changes effects on the distribution of a regional endemism: Melanophryniscus sanmartini (Amphibia, Bufonidae)

ABSTRACT Amphibians are the most threatened vertebrate group according to the IUCN. Land-use and land cover change (LULCC) and climate change (CC) are two of the main factors related to declining amphibian populations. Given the vulnerability of threatened and rare species, the study of their response to these impacts is a conservation priority. The aim of this work was to analyze the combined impact of LULCC and CC on the regionally endemic species Melanophryniscus sanmartini Klappenbach, 1968. This species is currently categorized as near threatened by the IUCN, and previous studies suggest negative effects of projected changes in climate. Using maximum entropy methods we modeled the effects of CC on the current and mid-century distribution of M. sanmartini under two IPCC scenarios - A2 (severe) and B2 (moderate). The effects of LULCC were studied by superimposing the potential distribution with current land use, while future distribution models were evaluated under the scenario of maximum expansion of soybean and afforestation in Uruguay. The results suggest that M. sanmartini is distributed in eastern Uruguay and the south of Brazil, mainly related to hilly and grasslands systems. Currently more than 10% of this species' distribution is superimposed by agricultural crops and exotic forest plantations. Contrasting with a recent modelling study our models suggest an expansion of the distribution of M. sanmartini by mid-century under both climate scenarios. However, despite the rise in climatically suitable areas for the species in the future, LULCC projections indicate that the proportion of modified habitats will occupy up to 25% of the distribution of M. sanmartini. Future change in climate conditions could represent an opportunity for M. sanmartini, but management measures are needed to mitigate the effects of habitat modification in order to ensure its survival and allow the eventual expansion of its distribution.

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

Knowing the past to predict the future: land-use change and the distribution of invasive bullfrogs

Biological invasions and land-use changes are two major causes of the global modifications of biodiversity. Habitat suitability models are the tools of choice to predict potential distributions of invasive species. Although land-use is a key driver of alien species invasions, it is often assumed that land-use is constant in time. Here we combine historical and present day information, to evaluate whether land-use changes could explain the dynamic of invasion of the American bullfrog Rana catesbeiana (=Lithobathes catesbeianus) in Northern Italy, from the 1950s to present-day. We used maxent to build habitat suitability models, on the basis of past (1960s, 1980s) and present-day data on land-uses and species distribution. For example, we used models built using the 1960s data to predict distribution in the 1980s, and so on. Furthermore, we used land-use scenarios to project suitability in the future. Habitat suitability models predicted well the spread of bullfrogs in the subsequent temporal step. Models considering land-use changes predicted invasion dynamics better than models assuming constant land-use over the last 50 years. Scenarios of future land-use suggest that suitability will remain similar in the next years. Habitat suitability models can help to understand and predict the dynamics of invasions; however, land-use is not constant in time: land-use modifications can strongly affect invasions; furthermore, both land management and the suitability of a given land-use class may vary in time. An integration of land-use changes in studies of biological invasions can help to improve management strategies.

Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach

Protecting native biodiversity against alien invasive species requires powerful methods to anticipate these invasions and to protect native species assumed to be at risk. Here, we describe how species distribution models (SDMs) can be used to identify areas predicted as suitable for rare native species and also predicted as highly susceptible to invasion by alien species, at present and under future climate and land-use scenarios. To assess the condition and dynamics of such conflicts, we developed a combined predictive modelling (CPM) approach, which predicts species distributions by combining two SDMs fitted using subsets of predictors classified as acting at either regional or local scales. We illustrate the CPM approach for an alien invader and a rare species associated to similar habitats in northwest Portugal. Combined models predict a wider variety of potential species responses, providing more informative projections of species distributions and future dynamics than traditional, non-combined models. They also provide more informative insight regarding current and future rare-invasive conflict areas. For our studied species, conflict areas of highest conservation relevance are predicted to decrease over the next decade, supporting previous reports that some invasive species may contract their geographic range and impact due to climate change. More generally, our results highlight the more informative character of the combined approach to address practical issues in conservation and management programs, especially those aimed at mitigating the impact of invasive plants, land-use and climate changes in sensitive regions

Risk-based modelling of diffuse land use impacts from rural landscapes upon salmonid fry abundance

Research has demonstrated that landscape or watershed scale processes can influence instream aquatic ecosystems, in terms of the impacts of delivery of fine sediment, solutes and organic matter. Testing such impacts upon populations of organisms (i.e. at the catchment scale) has not proven straightforward and differences have emerged in the conclusions reached. This is: (1) partly because different studies have focused upon different scales of enquiry; but also (2) because the emphasis upon upstream land cover has rarely addressed the extent to which such land covers are hydrologically connected, and hence able to deliver diffuse pollution, to the drainage network However, there is a third issue. In order to develop suitable hydrological models, we need to conceptualise the process cascade. To do this, we need to know what matters to the organism being impacted by the hydrological system, such that we can identify which processes need to be modelled. Acquiring such knowledge is not easy, especially for organisms like fish that might occupy very different locations in the river over relatively short periods of time. However, and inevitably, hydrological modellers have started by building up piecemeal the aspects of the problem that we think matter to fish. Herein, we report two developments: (a) for the case of sediment associated diffuse pollution from agriculture, a risk-based modelling framework, SCIMAP, has been developed, which is distinct because it has an explicit focus upon hydrological connectivity; and (b) we use spatially distributed ecological data to infer the processes and the associated process parameters that matter to salmonid fry. We apply the model to spatially distributed salmon and fry data from the River Eden, Cumbria, England. The analysis shows, quite surprisingly, that arable land covers are relatively unimportant as drivers of fry abundance. What matters most is intensive pasture, a land cover that could be associated with a number of stressors on salmonid fry (e.g. pesticides, fine sediment) and which allows us to identify a series of risky field locations, where this land cover is readily connected to the river system by overland flow. (C) 2010 Elsevier B.V. All rights reserved.

Land use improves spatial predictions of mountain plant abundance but not presence-absence

Question Does a land-use variable improve spatial predictions of plant species presence-absence and abundance models at the regional scale in a mountain landscape? Location Western Swiss Alps. Methods Presence-absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo-climatic and/or land-use variables available at a 25-m resolution. The additional contribution of land use when added to topo-climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo-climatic variables and the land-use variable through variation partitioning, and (5) comparing spatial projections. Results Land use significantly improved the fit of presence-absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence-absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence-absence. The importance of adding land-use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence-absence and abundance models.

Modelling tree population dynamics at the alpine and boreal tree-line ecotones in response to climate and land-use change

Summary Ecotones are sensitive to change because they contain high numbers of species living at the margin of their environmental tolerance. This is equally true of tree-lines, which are determined by attitudinal or latitudinal temperature gradients. In the current context of climate change, they are expected to undergo modifications in position, tree biomass and possibly species composition. Attitudinal and latitudinal tree-lines differ mainly in the steepness of the underlying temperature gradient: distances are larger at latitudinal tree-lines, which could have an impact on the ability of tree species to migrate in response to climate change. Aside from temperature, tree-lines are also affected on a more local level by pressure from human activities. These are also changing as a consequence of modifications in our societies and may interact with the effects of climate change. Forest dynamics models are often used for climate change simulations because of their mechanistic processes. The spatially-explicit model TreeMig was used as a base to develop a model specifically tuned for the northern European and Alpine tree-line ecotones. For the latter, a module for land-use change processes was also added. The temperature response parameters for the species in the model were first calibrated by means of tree-ring data from various species and sites at both tree-lines. This improved the growth response function in the model, but also lead to the conclusion that regeneration is probably more important than growth for controlling tree-line position and species' distributions. The second step was to implement the module for abandonment of agricultural land in the Alps, based on an existing spatial statistical model. The sensitivity of its most important variables was tested and the model's performance compared to other modelling approaches. The probability that agricultural land would be abandoned was strongly influenced by the distance from the nearest forest and the slope, bath of which are proxies for cultivation costs. When applied to a case study area, the resulting model, named TreeMig-LAb, gave the most realistic results. These were consistent with observed consequences of land-abandonment such as the expansion of the existing forest and closing up of gaps. This new model was then applied in two case study areas, one in the Swiss Alps and one in Finnish Lapland, under a variety of climate change scenarios. These were based on forecasts of temperature change over the next century by the IPCC and the HadCM3 climate model (ΔT: +1.3, +3.5 and +5.6 °C) and included a post-change stabilisation period of 300 years. The results showed radical disruptions at both tree-lines. With the most conservative climate change scenario, species' distributions simply shifted, but it took several centuries reach a new equilibrium. With the more extreme scenarios, some species disappeared from our study areas (e.g. Pinus cembra in the Alps) or dwindled to very low numbers, as they ran out of land into which they could migrate. The most striking result was the lag in the response of most species, independently from the climate change scenario or tree-line type considered. Finally, a statistical model of the effect of reindeer (Rangifer tarandus) browsing on the growth of Pinus sylvestris was developed, as a first step towards implementing human impacts at the boreal tree-line. The expected effect was an indirect one, as reindeer deplete the ground lichen cover, thought to protect the trees against adverse climate conditions. The model showed a small but significant effect of browsing, but as the link with the underlying climate variables was unclear and the model was not spatial, it was not usable as such. Developing the TreeMig-LAb model allowed to: a) establish a method for deriving species' parameters for the growth equation from tree-rings, b) highlight the importance of regeneration in determining tree-line position and species' distributions and c) improve the integration of social sciences into landscape modelling. Applying the model at the Alpine and northern European tree-lines under different climate change scenarios showed that with most forecasted levels of temperature increase, tree-lines would suffer major disruptions, with shifts in distributions and potential extinction of some tree-line species. However, these responses showed strong lags, so these effects would not become apparent before decades and could take centuries to stabilise. Résumé Les écotones son sensibles au changement en raison du nombre élevé d'espèces qui y vivent à la limite de leur tolérance environnementale. Ceci s'applique également aux limites des arbres définies par les gradients de température altitudinaux et latitudinaux. Dans le contexte actuel de changement climatique, on s'attend à ce qu'elles subissent des modifications de leur position, de la biomasse des arbres et éventuellement des essences qui les composent. Les limites altitudinales et latitudinales diffèrent essentiellement au niveau de la pente des gradients de température qui les sous-tendent les distance sont plus grandes pour les limites latitudinales, ce qui pourrait avoir un impact sur la capacité des espèces à migrer en réponse au changement climatique. En sus de la température, la limite des arbres est aussi influencée à un niveau plus local par les pressions dues aux activités humaines. Celles-ci sont aussi en mutation suite aux changements dans nos sociétés et peuvent interagir avec les effets du changement climatique. Les modèles de dynamique forestière sont souvent utilisés pour simuler les effets du changement climatique, car ils sont basés sur la modélisation de processus. Le modèle spatialement explicite TreeMig a été utilisé comme base pour développer un modèle spécialement adapté pour la limite des arbres en Europe du Nord et dans les Alpes. Pour cette dernière, un module servant à simuler des changements d'utilisation du sol a également été ajouté. Tout d'abord, les paramètres de la courbe de réponse à la température pour les espèces inclues dans le modèle ont été calibrées au moyen de données dendrochronologiques pour diverses espèces et divers sites des deux écotones. Ceci a permis d'améliorer la courbe de croissance du modèle, mais a également permis de conclure que la régénération est probablement plus déterminante que la croissance en ce qui concerne la position de la limite des arbres et la distribution des espèces. La seconde étape consistait à implémenter le module d'abandon du terrain agricole dans les Alpes, basé sur un modèle statistique spatial existant. La sensibilité des variables les plus importantes du modèle a été testée et la performance de ce dernier comparée à d'autres approches de modélisation. La probabilité qu'un terrain soit abandonné était fortement influencée par la distance à la forêt la plus proche et par la pente, qui sont tous deux des substituts pour les coûts liés à la mise en culture. Lors de l'application en situation réelle, le nouveau modèle, baptisé TreeMig-LAb, a donné les résultats les plus réalistes. Ceux-ci étaient comparables aux conséquences déjà observées de l'abandon de terrains agricoles, telles que l'expansion des forêts existantes et la fermeture des clairières. Ce nouveau modèle a ensuite été mis en application dans deux zones d'étude, l'une dans les Alpes suisses et l'autre en Laponie finlandaise, avec divers scénarios de changement climatique. Ces derniers étaient basés sur les prévisions de changement de température pour le siècle prochain établies par l'IPCC et le modèle climatique HadCM3 (ΔT: +1.3, +3.5 et +5.6 °C) et comprenaient une période de stabilisation post-changement climatique de 300 ans. Les résultats ont montré des perturbations majeures dans les deux types de limites de arbres. Avec le scénario de changement climatique le moins extrême, les distributions respectives des espèces ont subi un simple glissement, mais il a fallu plusieurs siècles pour qu'elles atteignent un nouvel équilibre. Avec les autres scénarios, certaines espèces ont disparu de la zone d'étude (p. ex. Pinus cembra dans les Alpes) ou ont vu leur population diminuer parce qu'il n'y avait plus assez de terrains disponibles dans lesquels elles puissent migrer. Le résultat le plus frappant a été le temps de latence dans la réponse de la plupart des espèces, indépendamment du scénario de changement climatique utilisé ou du type de limite des arbres. Finalement, un modèle statistique de l'effet de l'abroutissement par les rennes (Rangifer tarandus) sur la croissance de Pinus sylvestris a été développé, comme première étape en vue de l'implémentation des impacts humains sur la limite boréale des arbres. L'effet attendu était indirect, puisque les rennes réduisent la couverture de lichen sur le sol, dont on attend un effet protecteur contre les rigueurs climatiques. Le modèle a mis en évidence un effet modeste mais significatif, mais étant donné que le lien avec les variables climatiques sous jacentes était peu clair et que le modèle n'était pas appliqué dans l'espace, il n'était pas utilisable tel quel. Le développement du modèle TreeMig-LAb a permis : a) d'établir une méthode pour déduire les paramètres spécifiques de l'équation de croissance ä partir de données dendrochronologiques, b) de mettre en évidence l'importance de la régénération dans la position de la limite des arbres et la distribution des espèces et c) d'améliorer l'intégration des sciences sociales dans les modèles de paysage. L'application du modèle aux limites alpines et nord-européennes des arbres sous différents scénarios de changement climatique a montré qu'avec la plupart des niveaux d'augmentation de température prévus, la limite des arbres subirait des perturbations majeures, avec des glissements d'aires de répartition et l'extinction potentielle de certaines espèces. Cependant, ces réponses ont montré des temps de latence importants, si bien que ces effets ne seraient pas visibles avant des décennies et pourraient mettre plusieurs siècles à se stabiliser.

Structural sustainability of cambisol under different land use system

Incongruous management techniques have been associated with some significant loss of agricultural land to degradation in many parts of the world. Land degradation results in the alteration of physical, chemical and biological properties of the soil, thereby posing a serious threat to sustainable agricultural development. In this study, our objective is to evaluate the changes in a Cambisol structure under six land use systems using the load bearing capacity model. Sampling was conducted in Amazonas Region, Brazil, in the following land use: a) young secondary forest; b) old secondary forest; c) forest; d) pasture; e) cropping, and f) agroforestry. To obtain the load bearing capacity models the undisturbed soil samples were collected in those land use systems and subjected to the uniaxial compression test. These models were used to evaluate which land use system preserved or degraded the Cambisol structure. The results of the bulk density and total porosity of the soil samples were not adequate to quantify structural degradation in Cambisol. Using the forest topsoil level (0-0.03 m) as a reference, it was observed that pasture land use system was most severe in the degradation of the soil structure while the structure were most preserved under old secondary forest, cropping system and forest. At the subsoil level (0.10-0.13 m depth), the soil structure was most degraded in the cropping land use system while it was most preserved in young secondary forest and pasture. At the 0.20-0.23 m depth, soil structure degradation was most severe in the old secondary forest system and well preserved in young secondary forest, cropping and agroforestry.