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Record W3119942214

The Financialization of Conservation: Myth and Reality

2019· article· en· W3119942214 on OpenAlexaff
Diane‐Laure Arjaliès, Delphine Gibassier

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSustainable Finance and Green Bonds
Canadian institutionsWestern University
Fundersnot available
KeywordsConvention on Biological DiversityBusinessIncentiveThrivingCorporate governanceClimate FinanceFinanceEconomicsBiodiversityEconomic growthDeveloping countryMarket economyEcology
DOInot available

Abstract

fetched live from OpenAlex

Under the Paris Agreement signed in 2016 within the United Nations Framework Convention on Climate Change, international community stands in a commitment to strengthen the global response to climate change, including by limiting global warming to well below 2°C. Such goal will not be achieved without the support of financial markets. When the rest of the world transitions away from carbon, corporations will be lassoed with a heavy load of stranded assets. “has a critical role to play in supporting the real economy through the transition. The emerging field of ‘sustainable finance’ is focused squarely on channeling financial sector expertise, ingenuity and influence towards the challenges and opportunities posed by climate change. ” Globally, innovative financial instruments offer exciting potential to help build thriving and healthy ecosystems and communities. When successful, such investment vehicles enable investors to generate profits; address social and environmental challenges; strengthen collective governance through multi-stakeholder partnerships; and ensure a more efficient use of both public and private money by sharing risks and implementing specific incentive and measurement systems. However, when poorly designed, the same financial instruments can have the opposite effect. Yet little research has been done on the mechanisms of success and failure of these devices. In particular, little is known about a fast-growing emerging field within sustainable finance, known as “conservation finance” (Huwyler et al. 2016, 2014). The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) released its most recent report in May 2019. Compiled by 555 worldwide experts from 50 countries, it paints a grim picture. One million of the 8 million species on Earth are threatened with extinction, most within decades. Such losses will compromise the resilience of other ecosystems, including those on which people depend. The recent loss of species is so dramatic and serious that it could propel the world to a state of mass extinction (Barnosky et al. 2011; Ceballos et al. 2015). Protecting biodiversity is important for several reasons. According to the Convention About Life on Earth, at least 40 per cent of the world’s economy and 80 per cent of the needs of the poorest people on the planet are derived from biological resources. Healthy ecosystems are more likely to survive disasters and greater species diversity tends to ensure natural sustainability for all life forms. When the diversity of life is richer, there is greater opportunity for discoveries that could help address global challenges, such as epidemics or climate change. In addition, communities cannot thrive if ecosystems die. Research abounds about the social and health benefits of restoring a relationship between human beings and nature, whether in rural or urban communities. But communities also bear their own difficulties and often fail to see the importance of investing in conservation efforts (Gray and Milne 2018). Conservation needs keep increasing yet capital available to address the current crisis is shrinking. It is estimated that USD 200 billion to 300 billion in additional capital is needed to finance the preservation of the world’s most precious ecosystems. Between 2004 and 2015, private investors have already invested USD 8.2 billion in projects that demonstrated the potential to yield measurable environmental benefits. Among other initiatives, the Zoological Society of London (ZSL) and the World Wildlife Fund (WWF) attempted to create a Rhino Impact Bond that links investors’ financial returns to the ability of conservationists to save the rhinoceros. By calling for private actors to take part of those conservation efforts, public authorities and conservationists have begun to import financial and accounting techniques in a field that was previously immune to this language and these calculative practices. The selection of projects to be funded, the way resources are being allocated and how success is judged will all be shaped by the types of financial instruments and impact assessment used to assign value to conservation (Atkins and Maroun 2017; Atkins et al. 2018). For instance, if an insurance company sees some financial benefits in restoring wetlands, then it might invest in such a project. If an Indigenous community fails to demonstrate the added value of preserving this land through an Indigenous lens, the insurance company might reward other success factors, such as the building of flood barriers. All these decisions will be dictated by the financial instruments and impact assessment metrics used to finance conservation efforts. The consequences of these decisions are significant as they have major effects on both ecosystems and communities. Yet no one has investigated those processes and devices, the visions of the world they carry and the impacts they have on environmental and social life. This paper is a first step towards this direction. The paper provides the first comprehensive account of the global field of conservation finance, through an in-depth review of the financial instruments that have been developed over the past 10 years in the field of conservation worldwide. It analyzes the types of financial instruments being used (e.g. bond, project financing), the stakeholders involved (e.g. conservation organizations, public authorities, financiers), the impact assessment measures in-use, and the ecosystems under care. Based on this comparative analysis, the paper offers a typology of conservation finance that helps understand the modalities through which conservation is being financialized, its specificities, its strengths but also its limitations. In doing so, this paper enriches previous research on the financialization of nature (Chiapello 2018; Cooper et al. 2016; Himick and Brivot 2018) and the use of (biodiversity) accounting (Feger et al. 2018; Cuckston 2018, 2013) for this matter.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.205
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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