Alexander Peringer

Modeling Social-Ecological Feedback Effects in the Implementation of Payments for Environmental Services in Pasture-Woodlands

An effective implementation of payment for environmental services (PES) must allow for complex interactions of coupled social-ecological systems. We present an integrative study of the pasture-woodland landscape of the Swiss Jura Mountains combining methods from natural and social sciences to explore feedback between vegetation dynamics on paddock level, farm-based decision making, and policy decisions on the national political level. Our modeling results show that concomitant climatic and socioeconomic changes advance the loss of open grassland in silvopastoral landscapes. This would, in the longer term, deteriorate the historical wooded pastures in the region, which fulfill important functions for biodiversity and are widely considered as landscapes that deserve protection. Payment for environmental services could counteract this development while respecting historical land-use and ecological boundary conditions. The assessed policy feedback process reveals that current policy processes may hinder the implementation of PES, even though a payment for the upkeep of wooded pasture would generally enjoy the backing of the relevant policy network. To effectively support the upkeep of the wooded pastures in the Jura, concomitant policy changes, such as market deregulation, must also be taken into account.

Past and future landscape dynamics in pasture-woodlands of the Swiss Jura Mountains under climate change

Silvopastoral systems are traditional components of the landscape in the Swiss Jura Mountains, and are promising approaches for the sustainable management of mountain areas worldwide. Due to complex vegetation dynamics, pasture-woodlands are very vulnerable to the currently occurring land use and climate changes. Therefore, management requires integrative long-term predictions of successional trends. We present a refined version of the spatially explicit, dynamic simulation model WoodPaM with improved climate sensitivity of simulated vegetation. We investigate pasture-woodland dynamics by applying an innovative combination of retrospective simulations starting in the Middle Ages with prospective simulations following two climate change scenarios. The retrospective simulations demonstrate the strong dependency of the landscape mosaic on both climate and management. In high elevation mountain pastures, climate cooling during the Little Ice Age hindered simulated tree regeneration and reduced forage production of grasslands. Both led to an increase in open grassland and to a structural simplification of the landscape. In turn, climate warming afterwards showed the opposite effect. At lower elevations, high cattle stocking rates generally dominate simulated succession, leading to a slow development of quite homogenous landscapes whose structures are hardly affected by historical climate variability. Aerial photographs suggest that logging and windstorms critically shaped the current landscape, both homogenizing mosaic structures that emerge from selective grazing. Simulations of climate change scenarios suggest delayed but inevitable structural changes in the landscape mosaic and a temporary breakdown of the ecosystem service wood production. The population of currently dominating Norway spruce collapses due to simulated drought. Spruce is only slowly replaced either by beech under moderate warming or by Scots pine under extreme warming. In general, the shift in tree species dominance results in landscapes of less structural richness than today. In order to maintain the mosaic structure of pasture-woodlands, we recommend a future increase in cattle stocking on mountain pastures. The (re-) introduction of mixed herds (cattle with horses, sheep, and goats) could mitigate the simulated trend towards structural homogenization of the forest-grassland mosaic because diverse browsing effects selectively control tree regeneration and would counteract simulated forest encroachment. This could prevent the loss of species-rich open grasslands and forest-grassland ecotones. Forest management should respect forest-grassland mosaics and ecotones by following the traditional selective felling of single trees instead of large clear-cutting. Additionally, beech regeneration should be promoted from now on in order to smoothen tree species replacement with warming and to ensure the continuous provision of forest ecosystem services.

Dynamics of Forage Production in Pasture-woodlands of the Swiss Jura Mountains under Projected Climate Change Scenarios

Silvopastoral systems of the Swiss Jura Mountains serve as a traditional source of forage and timber in the subalpine vegetation belt, but their vulnerability to land use and climate change puts their future sustainability at stake. We coupled experimental and modeling approaches to assess the impact of climate change on the pasture-woodland landscape. We drew conclusions on the resistance potential of wooded pastures with different management intensities by sampling along a canopy cover gradient. This gradient spanned from unwooded pastures associated with intensive farming to densely wooded pastures associated with extensive farming. Transplanted mesocosms of these ecosystems placed at warmer and drier conditions provided experimental evidence that climate change reduced herbaceous biomass production in unwooded pastures but had no effect in sparsely wooded pastures, and even stimulated productivity in densely wooded pastures. Through modeling these results with a spatially explicit model of wooded pastures (WoodPaM) modified for the current application, results were extrapolated to the local landscape under two regionalized Intergovernmental Panel on Climate Change scenarios for climate change. This led to the suggestion that within the Jura pasture-woodlands, forage production in the near future (2000-2050 AD) would be affected disproportionately throughout the landscape. A stable forage supply in hot, dry years would be provided only by extensive and moderate farming, which allows the development of an insulating tree cover within grazed pastures. We conclude that such structural landscape diversity would grant wood-pastures with a buffering potential in the face of climate change in the forthcoming decades.

Multi-scale feedbacks between tree regeneration traits and herbivore behavior explain the structure of pasture-woodland mosaics

ContextThe pasture-woodlands of Central Europe are low-intensity grazing systems in which the structural richness of dynamic forest-grassland mosaics is causal for their high biodiversity. Distinct mosaic patterns in Picea abies- and Fagus sylvatica-dominated pasture-woodlands in the Swiss Jura Mountains suggest a strong influence of tree species regeneration ecology on landscape structural properties. At the landscape scale, however, cause-effect relationships are complicated by habitat selectivity of livestock.ObjectivesWe asked which tree species regeneration traits and what kind of feedbacks among local-scale vegetation dynamics and landscape-scale herbivore behavior are causal for the contrasted landscape structural characteristics of Picea- and Fagus-dominated pasture-woodlands.MethodsWe performed simulation experiments of mosaic pattern formation in both pasture-woodland types. The regeneration traits, namely dispersal distance, resistance to browsing and tolerance to shade, and the rules for habitat selection of cattle were modified and the corresponding shifts in landscape structure were analyzed.ResultsDispersal distance showed a significant, but only local, effect promoting forest fringe formation. Saplings’ resistance to browsing mainly determined overall tree cover, but did not influence landscape structure. At the landscape scale, both shade tolerance of saplings and selective habitat use by cattle were responsible for forest-grassland segregation: high shade tolerance triggered segregation, whereas non-selective habitat use hindered it.ConclusionsExisting local-scale theory on pasture-woodland dynamics is complemented by an herbivore-vegetation feedback among spatial scales. In low-intensity pastures, where large herbivores are preferentially “grazers” and trees form dense canopies, an intrinsic trend towards forest-grassland segregation at the expense of forest-grassland ecotones is predicted.

Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain

Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions.

Heuristic-driven graph wavelet modeling of complex terrain

We present a novel method for building a multi-resolution representation of large digital surface models. The surface points coincide with the nodes of a planar graph which can be processed using a critically sampled, invertible lifting scheme. To drive the lazy wavelet node partitioning, we employ an attribute aware cost function based on the generalized quadric error metric. The resulting algorithm can be applied to multivariate data by storing additional attributes at the graph’s nodes. We discuss how the cost computation mechanism can be coupled with the lifting scheme and examine the results by evaluating the root mean square error. The algorithm is experimentally tested using two multivariate LiDAR sets representing terrain surface and vegetation structure with different sampling densities.