Land use impacts on biodiversity from kiwifruit production in New Zealand assessed with global and national datasets

Coelho, Carla R. V.; Michelsen, Ottar

doi:10.1007/s11367-013-0628-7

Cited by 31 publications

(40 citation statements)

References 31 publications

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“…The methods proposed by de Baan et al [91,92] and Coelho and Michelsen [90] all use global datasets. Furthermore, de Baan et al's work [95] is based on a global dataset, even though only data for East Africa is given in the paper.…”

Section: Geographic Validitymentioning

confidence: 99%

“…However, de Baan et al [91] intend to develop characterization factors for seven land use classes for 14 biomes, and even if this gives very broad classes with high internal variation, the lack of data is still a severe problem; from a theoretical maximum of 98 combinations of land use classes and biomes, characterization factors for only 38 are given, while a substantial number of potential characterization factors potentially provided by de Baan et al [92] is either not available or found not to be significantly different from zero. Coelho and Michelsen [90] provide a method that can be used to generate characterization factors for all areas, but this is based on hemeroby values that are criticized for a weak empirical basis. Other methods based on species richness are based on data from a restricted part of the world, and it is questionable whether these are applicable outside this area (cf.…”

Section: Geographic Validitymentioning

confidence: 99%

“…Brentrup et al [71] only provide relevant data for Europe, while Michelsen [84] has a case-specific intactness indicator that hampers global application of the method. This is suggested by Coelho and Michelsen [90] to be overcome by actually combining the two methods using the generic values from Brentrup et al [71] on intactness and the geographic valuation from Michelsen [84]. de Baan et al [92] and Verones et al [125] use changes in species diversity to assess impact, but also, they include a geographic weighting factor for calculating characterization factors, making the methods similar in structure as the method proposed by Coelho and Michelsen [90].…”

Section: Geographic Validitymentioning

confidence: 99%

“…The latter is done by Coelho and Michelsen [90], who calculated values for ecosystem vulnerability based on present levels of native vegetation in the areas in focus. To some degree, this solves the problem of cumulative effects, but at the same time requires data that often will be hardly accessible.…”

Section: Assumptions On Linear Cause-effect Relationsmentioning

confidence: 99%

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Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

Michelsen

Lindner

2015

Sustainability

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Abstract:Loss of biodiversity is one of the most severe threats to sustainability, and land use and land use changes are still the single most important factor. Still, there is no sign of any consensus on how to include impacts on biodiversity from land use and land use changes in LCIA. In this paper, different characteristics of biodiversity are discussed and related to proposals on how to include land use and land use changes in LCIA. We identify the question of why we should care about biodiversity as a key question, since different motivations will result in different choices for the indicators, and we call for more openness in the motivation for indicator selection. We find a promising trend in combining pressure indicators with geographic weighting and regard this as a promising way ahead. More knowledge on the consequences of different choices, such as the selection of a reference state, is still needed.

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Section: Geographic Validitymentioning

confidence: 99%

Section: Geographic Validitymentioning

confidence: 99%

Section: Geographic Validitymentioning

confidence: 99%

Section: Assumptions On Linear Cause-effect Relationsmentioning

confidence: 99%

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Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

Michelsen

Lindner

2015

Sustainability

Self Cite

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“…Several recently published studies assess land use impacts, using a variety of different methods (see, e.g., Taelman et al 2016;Saikku et al 2015;Allacker et al 2014;Coelho and Michelsen 2014;Elshout et al 2014;Mueller et al 2014;Michelsen et al 2014;Helin et al 2014;Milà i Canals et al 2013;and Mattila et al 2012). Three case studies use (at least partially) the proposed biome-level CFs: margarine production , biomass production for energy (Helin et al 2014), and forestry plantations .…”

mentioning

confidence: 99%

Challenges in developing regionalized characterization factors in land use impact assessment: impacts on ecosystem services in case studies of animal protein production in Sweden

Nordborg

Sasu-Boakye

Cederberg

et al. 2016

Int J Life Cycle Assess

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Purpose The UNEP-SETAC Life Cycle Initiative has recently developed a guideline framework for land use impact assessment. This article evaluates the feasibility and highlights the challenges of applying a set of methods that adhere to this framework, and identifies the strengths and weaknesses of the indicators used in these methods, for the purpose of supporting further methodological development. Methods The methods were tested in two case studies of animal protein production in Sweden: dairy milk and pork. The reference situations were defined as the potential natural vegetation. County-level characterization factors (CFs) were calculated and occupation impacts were assessed for five ecosystem services, using six ecosystem service indicators: carbon flow change, groundwater recharge, mechanical filtration capacity, physicochemical filtration capacity, soil loss, and soil organic carbon, at two geographic scales: county and biome. Strengths and weaknesses of the ecosystem service indicators were identified using an evaluation framework for selected quality characteristics: representativeness, reliability, feasibility, and transparency. Results and discussion Occupation impacts at the two geographic scales, and for the two production cases, differ both in absolute numbers, and-for mechanical and physicochemical filtration capacity-in the ranking of cases. Results at both geographic scales indicate positive effects-or lower negative impacts-in protein production from dairy milk compared to pork, due to grass production on dairy farms, and lower use of land per unit protein. However, some of the observed benefits may be exaggerated due to challenges in adequately representing the reference situations. Most indicators were assigned medium or high degrees of representativeness, feasibility, and transparency, but several were assigned low degrees of reliability, due to the weak scientific basis upon which they were selected, low degrees of accuracy, and insufficient information on how they should be assessed. Conclusions Occupation impact results should be interpreted with caution due to challenges in applying the methods and use of indicators with identified weaknesses. The most challenging part of developing regionalized CFs was finding suitable land areas from which to derive representative data to parameterize the reference situations. More research is needed to provide adequate support to life cycle assessment practitioners who wish to calculate regionalized CFs and to address the identified weaknesses.

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Biodiversity impact assessment (BIA+) – methodological framework for screening biodiversity

Winter

Pflugmacher

Berger

et al. 2017

Integr Envir Assess & Manag

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For the past 20 years, the life cycle assessment (LCA) community has sought to integrate impacts on biodiversity into the LCA framework. However, existing impact assessment methods still fail to do so comprehensively because they quantify only a few impacts related to specific species and regions. This paper proposes a methodological framework that will allow LCA practitioners to assess currently missing impacts on biodiversity on a global scale. Building on existing models that seek to quantify the impacts of human activities on biodiversity, the herein proposed methodological framework consists of 2 components: a habitat factor for 14 major habitat types and the impact on the biodiversity status in those major habitat types. The habitat factor is calculated by means of indicators that characterize each habitat. The biodiversity status depends on parameters from impact categories. The impact functions, relating these different parameters to a given response in the biodiversity status, rely on expert judgments. To ensure the applicability for LCA practitioners, the components of the framework can be regionalized on a country scale for which LCA inventory data is more readily available. The weighting factors for the 14 major habitat types range from 0.63 to 1.82. By means of area weighting of the major habitat types in a country, country-specific weighting factors are calculated. In order to demonstrate the main part of the framework, examples of impact functions are given for the categories "freshwater eutrophication" and "freshwater ecotoxicity" in 1 major habitat type. The results confirm suitability of the methodological framework. The major advantages are the framework's user-friendliness, given that data can be used from LCA databases directly, and the complete inclusion of all levels of biodiversity (genetic, species, and ecosystem). It is applicable for the whole world and a wide range of impact categories. Integr Environ Assess Manag 2018;14:282-297. © 2017 SETAC.

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Land use impacts on biodiversity from kiwifruit production in New Zealand assessed with global and national datasets

Cited by 31 publications

References 31 publications

Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

Challenges in developing regionalized characterization factors in land use impact assessment: impacts on ecosystem services in case studies of animal protein production in Sweden

Biodiversity impact assessment (BIA+) – methodological framework for screening biodiversity

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