Towards an integrated ecological-economic land-use change model

Land-use changes have transformed tropical landscapes throughout the past decades dramatically. We describe here an ecologicaleconomicland-use change model to provide an integrated, exploratory tool to analyze how tropical land use and land-use change affect ecological and socio-conomic functions. The guiding question of the model is what kind of landscape mosaic can improve the ensemble of ecosystem functioning, biodiversity and economic benefit based on the synergies and trade-offs that we have to account for. The economic submodel simulates smallholder land-use management decisions based on a profit maximization assumption and a Leontief production function. Each household determines factor inputs for all household fields and decides about land-use change based on available wealth. The ecological submodel includes a simple account of carbon sequestration in above- and belowground vegetation. Initialized with realistic or artificial land use maps, the ecological-economic model will advance our understanding of the mechanisms underlying the trade-offs and synergies of ecological and economic functions in tropical landscapes

Drivers for global agricultural land use change: The nexus of diet, population, yield and bioenergy

The nexus of population growth and changing diets has increased the demands placed on agriculture to supply food for human consumption, animal feed and fuel. Rising incomes lead to dietary changes, from staple crops, towards commodities with greater land requirements, e.g. meat and dairy products. Despite yield improvements partially offsetting increases in demand, agricultural land has still been expanding, causing potential harm to ecosystems, e.g. through deforestation. We use country-level panel data (1961-2011) to allocate the land areas used to produce food for human consumption, waste and biofuels, and to attribute the food production area changes to diet, population and yields drivers. The results show that the production of animal products dominates agricultural land use and land use change over the 50-year period, accounting for 65% of land use change. The rate of extensification of animal production was found to have reduced more recently, principally due to the smaller effect of population growth. The area used for bioenergy was shown to be relatively small, but formed a substantial contribution (36%) to net agricultural expansion in the most recent period. Nevertheless, in comparison to dietary shifts in animal products, bioenergy accounted for less than a tenth of the increase in demand for agricultural land. Population expansion has been the largest driver for agricultural land use change, but dietary changes are a significant and growing driver. China was a notable exception, where dietary transitions dominate food consumption changes, due to rapidly rising incomes. This suggests that future dietary changes will become the principal driver for land use change, pointing to the potential need for demand-side measures to regulate agricultural expansion. (C) 2015 Elsevier Ltd. All rights reserved

Breaking Functional Connectivity into Components: A Novel Approach Using an Individual-Based Model, and First Outcomes

Landscape connectivity is a key factor determining the viability of populations in fragmented landscapes. Predicting ‘functional connectivity’, namely whether a patch or a landscape functions as connected from the perspective of a focal species, poses various challenges. First, empirical data on the movement behaviour of species is often scarce. Second, animal-landscape interactions are bound to yield complex patterns. Lastly, functional connectivity involves various components that are rarely assessed separately. We introduce the spatially explicit, individual-based model FunCon as means to distinguish between components of functional connectivity and to assess how each of them affects the sensitivity of species and communities to landscape structures. We then present the results of exploratory simulations over six landscapes of different fragmentation levels and across a range of hypothetical bird species that differ in their response to habitat edges. i) Our results demonstrate that estimations of functional connectivity depend not only on the response of species to edges (avoidance versus penetration into the matrix), the movement mode investigated (home range movements versus dispersal), and the way in which the matrix is being crossed (random walk versus gap crossing), but also on the choice of connectivity measure (in this case, the model output examined). ii) We further show a strong effect of the mortality scenario applied, indicating that movement decisions that do not fully match the mortality risks are likely to reduce connectivity and enhance sensitivity to fragmentation. iii) Despite these complexities, some consistent patterns emerged. For instance, the ranking order of landscapes in terms of functional connectivity was mostly consistent across the entire range of hypothetical species, indicating that simple landscape indices can potentially serve as valuable surrogates for functional connectivity. Yet such simplifications must be carefully evaluated in terms of the components of functional connectivity they actually predict

The carbon fluxes in different successional stages: modelling the dynamics of tropical montane forests in South Ecuador

Abstract Background Tropical forests play an important role in the global carbon (C) cycle. However, tropical montane forests have been studied less than tropical lowland forests, and their role in carbon storage is not well understood. Montane forests are highly endangered due to logging, land-use and climate change. Our objective was to analyse how the carbon balance changes during forest succession. Methods In this study, we used a method to estimate local carbon balances that combined forest inventory data with process-based forest models. We utilised such a forest model to study the carbon balance of a tropical montane forest in South Ecuador, comparing two topographical slope positions (ravines and lower slopes vs upper slopes and ridges). Results The simulation results showed that the forest acts as a carbon sink with a maximum net ecosystem exchange (NEE) of 9.3 Mg C∙(ha∙yr)−1 during its early successional stage (0–100 years). In the late successional stage, the simulated NEE fluctuated around zero and had a variation of 0.77 Mg C∙(ha∙yr) –1. The simulated variability of the NEE was within the range of the field data. We discovered several forest attributes (e.g., basal area or the relative amount of pioneer trees) that can serve as predictors for NEE for young forest stands (0–100 years) but not for those in the late successional stage (500–1,000 years). In case of young forest stands these correlations are high, especially between stand basal area and NEE. Conclusion In this study, we used an Ecuadorian study site as an example of how to successfully link a forest model with forest inventory data, for estimating stem-diameter distributions, biomass and aboveground net primary productivity. To conclude, this study shows that process-based forest models can be used to investigate the carbon balance of tropical montane forests. With this model it is possible to find hidden relationships between forest attributes and forest carbon fluxes. These relationships promote a better understanding of the role of tropical montane forests in the context of global carbon cycle, which in future will become more relevant to a society under global change

EFForTS-LGraf: A landscape generator for creating smallholder-driven land-use mosaics.

Spatially-explicit simulation models are commonly used to study complex ecological and socio-economic research questions. Often these models depend on detailed input data, such as initial land-cover maps to set up model simulations. Here we present the landscape generator EFFortS-LGraf that provides artificially-generated land-use maps of agricultural landscapes shaped by small-scale farms. EFForTS-LGraf is a process-based landscape generator that explicitly incorporates the human dimension of land-use change. The model generates roads and villages that consist of smallholder farming households. These smallholders use different establishment strategies to create fields in their close vicinity. Crop types are distributed to these fields based on crop fractions and specialization levels. EFForTS-LGraf model parameters such as household area or field size frequency distributions can be derived from household surveys or geospatial data. This can be an advantage over the abstract parameters of neutral landscape generators. We tested the model using oil palm and rubber farming in Indonesia as a case study and validated the artificially-generated maps against classified satellite images. Our results show that EFForTS-LGraf is able to generate realistic land-cover maps with properties that lie within the boundaries of landscapes from classified satellite images. An applied simulation experiment on landscape-level effects of increasing household area and crop specialization revealed that larger households with higher specialization levels led to spatially more homogeneous and less scattered crop type distributions and reduced edge area proportion. Thus, EFForTS-LGraf can be applied both to generate maps as inputs for simulation modelling and as a stand-alone tool for specific landscape-scale analyses in the context of ecological-economic studies of smallholder farming systems

Additional file 1: of The carbon fluxes in different successional stages: modelling the dynamics of tropical montane forests in South Ecuador

Field data and model calibration. (PDF 716 kb