Posts Tagged ‘Science’

Intelligent tinkering : a personal account of the science and practice of ecological restoration

Thursday, August 9th, 2012

You’re interested in the real world application of the knowledge and methods of ecological science, and especially restoration ecology? Maybe you’re interested in how the practice of ecological restoration can inform ecological theory? Whichever way, Robert J. Cabin has some interesting stories to tell on the complex and often awkward relationships between the practice of ecological restoration and the science of restoration ecology.

He tells his stories in Intelligent Tinkering, a book published by Island Press in 2011. The book starts off with a personal account of how, as an aspiring research ecologist, R.J. Cabin got drawn to the hands-in-the-mud nitty-gritty business of getting restoration plans off the ground, or rather, in the ground. He participated in planing countless native trees and shrubs in order to restore tropical dry forests in Hawaii.

Restoring these forests involved working with many different stakeholders, who often had diverging agendas. It also involved project management and hard physical labour. There was some science in there too, but it’s role didn’t follow the standard model of knowledge feeding into action… Trained as a research ecologist, maybe this model is what R.J. Cabin had initially expected to encounter when coming to Hawaii to work on restoration. The real world is just a lot more messy.

His account of how he confronted this is very interesting, and you get to learn a lot about the island’s ecology, and politics. Good writing makes it easy to follow. In a second part of the book, he tries to outline a few things he learned from that experience. This attempt to theorize the links between science and practice comes a bit short however, both in style (especially given the quality of the first part of the book), and in content.

Many authors have explored how science and practice interact but no grand theory has emerged. As R.J. Cabin explains, maybe that’s because no final, widely shared, definition has been given to either… Anyway, the key message from the book is probably that, in the end, getting things done is what matters.

Biodiversity indicators: 10 common mistakes

Wednesday, October 28th, 2009

In a paper published in 2003 in the Journal of Environmental Management, Lee Failing and Robin Gregory list 10 common mistakes made in designing biodiversity indicators for forest management. The paper is a worthy read for anyone dealing with issues of monitoring or decisions concerning land-use or ecosystem management.

According to the authors, indicators can have three uses: tracking performance (for results-based management), discriminating alternative hypotheses (for scientific exploration), discriminating alternative policies or management options.

In their paper, they focus on the latter. They list ten common mistakes made in developing and using biodiversity indicators aimed at providing guidance to policy makers or forest managers who must decide on landscape or forest management policies and plans. Deciding whether or not to allow a specific project to go forward requires a different suite of indicators than assessing whether or not the project was a success.

They provide a nice example to illustrate their point:

When we go to the doctors and ask “what is my risk of heart disease”, we do not expect the answer to be framed as a percentage of the target daily donut intake”. (…) Eating fewer donuts may be part of a sensible management strategy but it does not answer the question “am I healthy?” A report of two dozen indicators may be an important part of the the analysis process, but it is also not an acceptable answer to the question (…). Doctors it seems understand the need to take a complex thing, break it down into a relatively small number of indicators, and provide a summary judgement about the status of our health or the probability of recovery associated with alternative treatments.

The 10 mistakes:

  • 1. Failing to define end-points – Is the aim to preserve ecosystem services or scenic value, to prevent the loss of a particular set of species or the intrinsic values and rights of all species.
  • 2. Mixing means and ends – Appropriate performance indicators should focus on the desired goals, not on whether “actions” were taken. Guideline are no substitute to goals.
  • 3. Ignoring the management context – Outside a specific context, “biodiversity” has no meaning – The context must thus be specified.
  • 4. Making lists instead of indicators
  • 5. Avoiding importance weights for individual indicators – Unfortunately, stating that “everything is important” doesn’t work in practice.
  • 6. Avoiding summary indicators or indices because they are considered overly simple
  • 7. Failing to link indicators to decisions
  • 8. Confusing value judgements with technical judgements
  • 9. Substituting data collection for critical thinking – If no data is available, then the authors suggest using established methods for gathering and synthesizing qualitative expert judgements.
  • 10. Oversimplifying: Ignoring spatial and temporal trade-offs – In giving examples for mistake 10, Failing and Gregory mention the importance of taking into account spatial and temporal trade-offs in designing policies aimed at no-net-loss of biodiversity. Temporary and /or local losses could provide – or be made to – provide gains at a broader scale or on the longer term. The same point is made by Kerry ten Kate in an EM podcast on making biodiversity offsets work (mp3).
  • IPBS: It’s all about the “how”!

    Tuesday, October 20th, 2009

    The IPBS had its second ad-hoc meeting in Nairobi on 5-9 October. Participants in the meeting shared some of their thoughts on the event in last week’s Open Science Conference by DIVERSITAS in Cape Town.

    They said that everyone agreed an IPBES was needed and that hopefully the IPBES would be launched in September 2010, at the UN General Assembly. Note that 2010 is also the international year of biodiversity – can’t hurt!

    However, the concrete functioning of an IPBS platform wasn’t agreed upon. It seems that it would be intergovernmental and anchored to UNEP. Being intergovernmental, national governments will be the #1 entry point into the IPBES process and effective lobbying will be essential. Speakers at Diversitas mentionned that unfortunately, participants were not necessarily well informed of the issues at stake. Their point was that the scientific community could do a better job of providing input to their country representatives.

    Other questions on stand-by relate to the scientific advisory committee of the IPBS (i.e. will it have one?), its role beyond serving international conventions (can it actually provide information to national governments, civil society or the private sector?), how knowledge will be framed to make it relevant and more. These questions are all about “how”!

    How you craft the policy-science interface – the platform’s governance – is key. It will be negotiated at the third and final meeting (perhaps in April 2010).

    If all goes well, a clear separation will be set up between governments who request knowledge and information, and the scientific community who will have to collect and synthesize all the information, in a non-prescriptive format, for countries to decide upon. If the science gets politicized, the whole platform will be a waste of time.

    Research priorities according to Rubicode

    Wednesday, September 30th, 2009

    The RUBICODE project on “Rationalising biodiversity conservation in dynamic ecosystems” has published its latest and final newsletter.

    Among other products, the project has prepared an interesting report on research priorities for ecosystem services (pdf here). The report lists 11 priorities, which are commented briefly below.

  • Quantify the role of biodiversity, including uncharismatic and speciose groups of organisms such as invertebrates, lower plants and fungi, in ecosystem function and service provision.

    This is a major goal of ecosystem service science when it comes to informing decision-makers concerning the management of biodiversity. It is somewhat overarching.

  • Develop trait-based approaches to ecosystem service assessment which include: (i) improved knowledge of trait-based multi-trophic linkages within ecosystems; (ii) trait based thresholds for the provision of services; and (iii) trait-based indicators to assess and define quantitatively service provision at multiple scales.

    Trait-based approaches, also labelled functional diversity approaches, are now well developped for linking biodiversity, ecosystem properties and ecosystem services, in particular for plant diversity. As well as being grounded in theory, they offer useful indicators that are often require less expertise than the identification of species and the estimation of their abundance. Expanding these approaches to address multi-trophic linkages, thresholds and multiple scale is the next step.

  • Develop improved methods for the integrated assessment of ecosystem services at different spatial and temporal scales, including methods for: (i) investigating interactions between the demand and supply of multiple ecosystem services; (ii) upscaling and downscaling; and (iii) integrating valuation processes and results in impact assessments and models.

    This point relates particularly well with policy and management issues. As the incorporation of ecosystem services into the decision-making process of land management marches forward such questions will most likely gain in practicality and lose their esoteric touch – which is probably a good thing.

  • Identify thresholds in the relationships between biodiversity, ecosystem functioning, ecosystem services and human well-being to identify points beyond which the level of ecosystem service delivery changes dramatically and perhaps irreversibly. Thresholds again…
  • Identify and quantify the impact of direct and indirect socio-economic and environmental drivers on ecosystem services, and develop tools to design and evaluate policy options for ecosystem service management under uncertain futures.

    As well as uncertainty in the future changes in direct and indirect drivers, ecosystem service science should also assist decision makers in incorporating uncertainty in the scientific knowledge itself. Given the limitations and contextuality of what we know of the dynamics of biodiversity and ecosystems, dealing with uncertainty should be central to the design and evaluation of policy options as well as concrete – on the ground – actions.

  • Improve understanding of the role of the cultural, economic and policy contexts in ecosystem service assessment, particularly in the choice of: (i) metrics, valuation and appraisal methods; (ii) stakeholder involvement; (iii) required levels of precision; and (iv) policy instruments and decision support tools.

    As well as understanding who and what determines the choice of metrics and who is called upon to value ecosystem services, the conceptual bases for these choices should be made explicit (and possibly challenged).

  • Develop an improved classification for ecosystem services and values, which includes values of flows of ecosystem services and stocks of ecosystem assets and allows for the distinction between final and intermediate services.

    Double accounting in the definition of ecosystem service is a recurrent problem, in particular among ecologists. The issue will be discussed in a later post. Meanwhile, you can read the excellent paper by Boyd & Banzhaf (2006).

  • Enhance the usefulness of value, price and cost estimates for ecosystem services by: (i) improving database coverage, quality, depth and access; (ii) filling key gaps in valuation evidence; (iii) investigating replication, validity and transfer of functional assumptions and values estimates; and (iv) developing agreed protocols for comparing and transferring value estimates.

    These priorities are central to the incorporation of ecosystem services in mainstream decision making concerning land-use and natural resource management.

  • Develop tools, methods and decision-support systems to assist the multi-level governance of ecosystem services. What does that mean?
  • Quantify the role of multifunctional land management and landscape patterns on the provision of ecosystem services and develop options to conserve biodiversity and maintain ecosystem integrity outside protected areas.

    The goal of making land management more biodiversity- and ecosystem service-friendly is a very notable trend in public policies for agriculture and forestry (at least in the developed world). Providing quantitative data on ecosystem service provision by alternative policy options is necessary for designing precise incentives schemes that actually serve the goal of ecosystem service provision (rather than the goal of satisfying a particular political base…). Such incentive schemes are an essential component of the policy mix for biodiversity and ecosystem service enhancement.

  • Develop tools and methods to promote the uptake of business opportunities associated with the sustainable management of ecosystem service delivery.

    The development of biodiversity and ecosystem service offsets in recent years is a step in this direction. Hopefully, ecosystem service scientists will embrace this trend and strengthen its scientific basis.

  • Did you notice how long the list is?