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Spatial conservation prioritization on different scales : What was the question?
- 1. Spatial conservation prioritization on different scales What was the question? iDiv seminar, Leipzig 2015-11-11
- 2. Hi! Joona Lehtomäki University of Helsinki Metapopulation Research Centre Conservation Biology Informatics Group @jlehtoma jlehtoma
- 5. • Identify spatial allocation of conservation resources (actions) • Protection • Management • Restoration • Offsetting • Why + what where, when and how? Spatial conservation prioritization
- 6. Land-use planning Natural resource management Conservation planning Spatial conservation prioritization Ferrier & Wintle (2009) Spatial conservation planning
- 9. Priorities: What was the question?
- 10. Global scale
- 11. Pouzols et al. (2014): 1. What is the potential performance of PA network (species ranges and ecoregions) in the context of Aichi Target 11? 2. How will land-use change by 2040 impact this performance and the spatial pattern of priorities? 3. What is the difference between globally coordinated and nationally devolved PAs? Objectives
- 12. ~25 000 Red-listed species 827 ecoregions Land use - present - future (2040) Country borders Current PAs The approach
- 13. ~25 000 Red-listed species 827 ecoregions Land use - present - future (2040) Country borders Current PAs The approach
- 14. ~25 000 Red-listed species 827 ecoregions Land use - present - future (2040) Country borders Current PAs The approach
- 15. Priorities 2040
- 17. Extending the global PA network Performance curves Pouzols et al. 2014
- 18. Global loss Pouzols et al. 2014 Performance curves
- 19. 19 % Pouzols et al. 2014 Performance curves
- 20. 61 % Pouzols et al. 2014 Performance curves
- 21. 56 % 12 % Pouzols et al. 2014 Performance curves
- 22. Pouzols et al. 2014 National or international?
- 23. Pouzols et al. 2014 Performance curves
- 24. 43 / 38 % Pouzols et al. 2014 Performance curves
- 25. Summary • Emphasis on the broad patterns and overall performance • Analysis resolution constrained by the available data • Stakeholders not (and probably can’t be) identified • What is the policy process to be informed?
- 26. Local scale
- 27. Private Reserves State Forestry Private State Lehtomäki et al. 2015 Objectives
- 31. © Metla Woodland key habitats Protected areas © Metsähallitus
- 32. Kainuu Pohjois-Pohjanmaa Etelä-Savo Keski-Suomi Pohjois-Savo Pirkanmaa Lapin METSO-alue Pohjois-Karjala Etelä- jaKeski-Pohjanmaaja Ra Lounais-Suomi ja Rannikko Häme-Uusimaa jaRannikko Kaakkois-Suomi
- 37. • Emphasis on the verification and validation of the results • Analysis resolution matched with the planning context • Stakeholders clearly identified • Questions are clear; however, only little to be generalized Summary
- 38. Priorities: What was the question?
- 39. ”Science for science” (curiosity-driven science) ”Science for action” (issue-driven science) Objective Scientific insight, novelty, and significance Knowledge relevant for forming and assessing policies Products Published scientific papers Reports and white papers, often unpublished Important knowledge production components Credibility Relevance, legitimacy Decision-making context Does not necessarily have one An existing context, can also aim at establishing a new process Accountability To scientific community and professional peers To political decision-makers, general public Jasanoff 1990; Van den Hove 2007 ”Science for science” vs ”science for action”
- 40. Data Scientists Policymakers Stakeholders and the public Knowledge Decisions Soranno et al. 2014; Young et al. 2014 The linear model of knowledge production
- 41. Credibility The scientific adequacy of the technical evidence and arguments. Salience (Relevance) The relevance of the assessment to the needs of decision makers. Legitimacy The perception that the production of information and technology has been respectful of stakeholders’ divergent values and beliefs, unbiased in its conduct, and fair in its treatment of opposing views and interests. Cash et al. 2003 Attributes of science-policy interface
- 42. • Data • Knowledge • Decisions Soranno et al. 2014; Lynman et al. 2007 The roundtable model of sci-pol interaction
- 43. The future for spatial conservation prioritization 1. Explicit framing of which policy process the prioritization is supposed to inform 2. Acknowledging that not all research into spatial conservation prioritization needs to be policy- relevant
- 45. References Cash, D.W. et al. (2003) Knowledge systems for sustainable development. Proceedings of the National Academy of Sciences of the United States of America 100, 8086–91 Dicks, L. V et al. (2014) Organising evidence for environmental management decisions: a “4S” hierarchy.Trends in Ecology & Evolution 29, 607–613 Ferrier S. & Wintle B.A. (2009) Quantitative approaches to spatial conservation prioritization: matching the solution to the need. Spatial conservation prioritization: quantitative methods & computational tools (ed. by A. Moilanen, K.A. Wilson, and H.P. Possingham), pp. 304. Oxford University Press, Oxford. Jasanoff S. (1990) The Fifth Branch: Scientific Advisors as Policymakers. Harvard University Press, Harvard. Lehtomäki, J. (2014) , Spatial conservation prioritization for Finnish forest conservation management. , University of Helsinki Lehtomäki J., Tuominen S., Toivonen T., & Leinonen A. (2015) What Data to Use for Forest Conservation Planning? A Comparison of Coarse Open and Detailed Proprietary Forest Inventory Data in Finland. PLoS ONE, 10, e0135926. Lynam, T. et al. (2007) A Review of Tools for Incorporating Community Knowledge , Preferences , and Values into Decision Making in Natural Resources Management. Ecology And Society 12, 5 Sarkki, S. et al. (2013) Balancing credibility, relevance and legitimacy: A critical assessment of trade-offs in science-policy interfaces. Science and Public Policy Soranno, P.A. et al. (2015) It’s good to share: Why environmental scientists' ethics are out of date. BioScience 65, 69–73 Pouzols F.M., Toivonen T., Di Minin E., Kukkala A.S., Kullberg P., Kuusterä J., Lehtomäki J., Tenkanen H., Verburg P.H., & Moilanen A. (2014) Global protected area expansion is compromised by projected land-use and parochialism. Nature, 516, 383–386. http://dx.doi.org/10.1038/nature14032 Young, J.C. et al. (2014) Improving the science-policy dialogue to meet the challenges of biodiversity conservation: Having conversations rather than talking at one-another. Biodiversity and Conservation 23, 387–404 van den Hove S. (2007) A Rationale for Science-Policy Interfaces. Futures, 39, 1–19.
- 46. References – conservation biology Cook, C.N. et al. (2013) Achieving conservation science that bridges the knowledge-action boundary. Conservation Biology 27, 669–678 Opdam, P. (2010) Learning science from practice. Landscape Ecology 25, 821–823 Reyers, B. et al. (2010) Conservation Planning as a Transdisciplinary Process. Conservation biology 24, 957–65
- 47. Computationally easier Higher ecological realism, more useful planning Arponenetal.2012 Extending the local PA network Scale matters
- 48. Informing policies and implementation Alternative/complementary models Dicks et al. 2014
Notes de l'éditeur
- Today I want to talk how I think framing your research questions has a big role in how we do conservation science and how it isn’t perhaps happening to the extent necessary I’m going to do this using to examples are two very different scales This is a bit of a ”perspective talk”
- Today I want to talk a little about the types of questions we typically try to answer in conservation science Background in quantitative ecology I work with developing quantitative conservation prioritization concepts and methods I’ve mostly worked with different ecosystems in the Boreal forests in Finland, but lately also with global protected area analysis I finisihed by PhD “Spatial conservation prioritization for Finnish forest conservation management” about a year ago..
- Something I work with a lot is combining very heterogeneous datasets on species and habitat distributions as well as ecosystem services and anthropogenic threats. Obviously there’s quite a lot of overlap to the type of work being done in iDiv and much of work you do here seems super interesting I was going through the iDiv website and was lookin at this image of broad mission statement. One particular part of this caught my eye, because lately I’ve been getting more and more intersted in the science-policy interface
- - Policy
- Paikallisen tason suunnittelun tarkoitus siis tuottaa käyttökelpoisia työkaluja viranomaisten käyttöön. Koska METSO perustuu vapaaehtoisuuteen, voidaan suojeluprioriteetteja käyttää eri kohteiden vertailussa (luonnontieteelliset valintakriteerit edelleen perustana) tai maanomistajien aktivoinnissa (jos löytyy mielenkiintoisen oloisia kohteita) Suunnittelutyön tuloksista voidaan tiedottaa esimerkiksi alueellisen yhteistoimintaverkoston kautta. tuskeino Tarkoituksenmukainen rajaus Hoitotyöt Hoito-ohje metsänomistajalle
- Several potentially useful data sources primarily collected for forestry can be used for conservation prioritization as well Again, primary biodiversity data would be desirable, but often these data are not available for large areas. Detailed forest planning data mostly on stand level is available for most of Finland (and Sweden?). These are further complemented by national forest inventory data based on remote sensing. Then the questions becomes how to derive biodiversity-relevant information from these data? Several options exist: Simple habitat-suitability indexes More complex and realistic statistical models for various species or communities Mechanistic/process models for whole communities Operational use of the whole toolset should not be dependent on the particular tool used (although details will vary).
- Spatial conservation prioritization analysis described only provide decision-support: The most important decision criteria should, of course, still be what is actually there (field inventories). By closely linking the result interpretation and field inventories, should work as validation and development benchmark for the methods used. This (validation) nothing new for any predictive analytical methods, but for operational conservation planning it is a crucial component of the whole workflow. Special care needs to be directed to opening up the decisions, methods and results for practitioners who may not have a scientific background.
- With these two questions, it’s clear that for much the spatial conservation prioritization and planning that we do, it’s really important to define already well-advance how the questions is framed
- “Many initiatives exist to improve communication, but these largely conform to a ‘linear’ or technocratic model of communication in which scientific ‘‘facts’’ are transmitted directly to policy advisers to ‘‘solve problems’’. While this model can help start a dialogue, it is, on its own, insufficient, as decision taking is complex, iterative and often selective in the information used.” - Young et al. 2014
- Three attributes of science-policy interface
- THEN we can back to sorting out important questions related to what constitutes conservation value, how do we account for complex ecological processes on multiple spatiotemporal scales and what are the most cost-effective ways of implementing conservation action (etc).