A novel modeling approach to evaluate the ecological effects of timing and location of grassland conservation measures

Johst, Karin; Drechsler, Martín; Mewes, Melanie; Sturm, Astrid; Wätzold, Frank

doi:10.1016/j.biocon.2014.11.033

Cited by 27 publications

(23 citation statements)

References 31 publications

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“…These measures benefit 2 species protected by the German Federal Nature Conservation Act: the butterfly Chestnut Heath ( Coenonympha glycerion ) and the bird Meadow Pipit ( Anthus pratensis ) (Johst et al. ). The bird's dispersal range is greater than the area we considered.…”

Section: Methodsmentioning

confidence: 99%

Cost‐effectiveness of conservation payment schemes for species with different range sizes

Drechsler

Smith

Sturm

et al. 2016

Conservation Biology

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Payments to compensate landowners for carrying out costly land-use measures that benefit endangered biodiversity have become an important policy instrument. When designing such payments, it is important to take into account that spatially connected habitats are more valuable for many species than isolated ones. One way to incentivize provision of connected habitats is to offer landowners an agglomeration bonus, that is, a bonus on top of payments they are receiving to conserve land if the land is spatially connected. Researchers have compared the cost-effectiveness of the agglomeration bonus with 2 alternatives: an all-or-nothing, agglomeration payment, where landowners receive a payment only if the conserved land parcels have a certain level of spatial connectivity, and a spatially homogeneous payment, where landowners receive a payment for conserved land parcels irrespective of their location. Their results show the agglomeration bonus is rarely the most cost-effective option, and when it is, it is only slightly better than one of the alternatives. This suggests that the agglomeration bonus should not be given priority as a policy design option. However, this finding is based on consideration of only 1 species. We examined whether the same applied to 2 species, one for which the homogeneous payment is best and the other for which the agglomeration payment is most cost-effective. We modified a published conceptual model so that we were able to assess the cost-effectiveness of payment schemes for 2 species and applied it to a grassland bird and a grassland butterfly in Germany that require the same habitat but have different spatial-connectivity needs. When conserving both species, the agglomeration bonus was more cost-effective than the agglomeration and the homogeneous payment; thus, we showed that as a policy the agglomeration bonus is a useful conservation-payment option.

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Section: Methodsmentioning

confidence: 99%

Cost‐effectiveness of conservation payment schemes for species with different range sizes

Drechsler

Smith

Sturm

et al. 2016

Conservation Biology

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“…Decision Support System (DSS) models seek to predict the impacts of policies (and related changes in management practices) that target biodiversity conservation as an objective in itself. Recently, these have included approaches which bridge the gap between detailed models of specific sites and regional models that may overlook many important aspects of biodiversity (Johst et al, 2015;Mouysset et al, 2014). In such models, management information and knowledge of the ecological niches of different species or species groups are combined to predict the biodiversity impacts of different strategies, and the economic costs associated with achieving more favourable environmental outcomes (Johst et al, 2015;Mewes et al, 2015).…”

Section: Modeling Grassland Biodiversity and Interactions With Producmentioning

confidence: 99%

“…Recently, these have included approaches which bridge the gap between detailed models of specific sites and regional models that may overlook many important aspects of biodiversity (Johst et al, 2015;Mouysset et al, 2014). In such models, management information and knowledge of the ecological niches of different species or species groups are combined to predict the biodiversity impacts of different strategies, and the economic costs associated with achieving more favourable environmental outcomes (Johst et al, 2015;Mewes et al, 2015). Designed to characterise different management strategies and conditions, they could potentially be adapted to include the impacts of climate change on biodiversity (Johst et al, 2015;Mewes et al, 2015).…”

Section: Modeling Grassland Biodiversity and Interactions With Producmentioning

confidence: 99%

Modeling European ruminant production systems: Facing the challenges of climate change

Kipling

Bannink

Bellocchi³

et al. 2016

Agricultural Systems

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This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.agsy.2016.05.007Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensification of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a priority. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are applied to develop ?smart? empirical modeling, may overcome the trade-off between complexity and usability. Developing the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems related to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks.authorsversionPeer reviewe

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“…[], Johst et al. []) but also by water authorities to enhance the quality of ground water or surface water due to less nitrogen input (Marconi et al. []).…”

Section: Introductionmentioning

confidence: 99%

“…The selection of agricultural land use measures aimed at conserving biodiversity and enhancing ecosystem services is a case in point (Jordan and Halpin [2006], Prager et al [2012], Ekroos et al [2014]). Consider the example of grassland extensification: this measure is sometimes implemented by nature conservation authorities in an effort to preserve endangered bird and butterfly species (Mouysset et al [2014], Johst et al [2015]) but also by water authorities to enhance the quality of ground water or surface water due to less nitrogen input (Marconi et al [2015]). Flower strips are another example: these are sometimes promoted by agricultural authorities to enhance the ecosystem services of pollination and pest control with the aim of improving agricultural output (Bommarco et al [2013]), whereas authorities responsible for tourism may implement them to enhance the recreational benefits of the landscape (Wratten et al [2012]).…”

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confidence: 99%

Costs of Uncoordinated Site Selection With Multiple Ecosystem Services

Drechsler¹,

Wätzold

2016

Natural Resource Modeling

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Models to spatially optimize land use measures for achieving multiple ecosystem service and biodiversity goals typically assume that a single actor optimizes land use measures to achieve the different goals. However, in reality public administrations are frequently divided into different units, each of which has its own budget and is responsible for one specific ecosystem service or biodiversity conservation target. Frequently these administrative units do not cooperate, even if they are implementing similar land use measures to achieve their respective goal. This lack of coordination may lead to cost‐effectiveness losses in comparison to a coordinated optimization strategy where the weighted conservation and ecosystem service goals are maximized for the total budget available to all administrative units. Considering the problem of selecting land patches for ecosystem service preservation, this paper analyzes with a conceptual model how cost‐effectiveness losses of the uncoordinated strategy in comparison to the coordinated strategy depend on changes in selected parameters (budget, mean and standard deviation of ecosystem services, correlation of ecosystem services on patches and weighting of different ecosystem services) that determine the ecological and socio‐economic context of the decision situation.

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A novel modeling approach to evaluate the ecological effects of timing and location of grassland conservation measures

Cited by 27 publications

References 31 publications

Cost‐effectiveness of conservation payment schemes for species with different range sizes

Cost‐effectiveness of conservation payment schemes for species with different range sizes

Modeling European ruminant production systems: Facing the challenges of climate change

Costs of Uncoordinated Site Selection With Multiple Ecosystem Services

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