Samenvatting
Summary Revision Notes from Tutorials and Classes
- Instelling
- Maastricht University (UM)
A detailed compilation of what is needed to prepare for the final exam of this course, including in-class discussions.
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Exam Revisionhttps://referencelist.library.maastrichtuniversity.nl/E/04bfec8619d1441c80690bf8cd08f26a
Task 1 - the basics of sustainability science
Wicked problem (uncertainties and decision-stakes) see task 2
Social-environmental system => Europe?
o An integrated understanding of social- environ systems is
important as a one-sided fucus often results in unintended
and negative consequences – Matson et al. 2016 (maybe
link to transdisc.)
o They are Complex adaptive systems that have multiple
interconnected components interacting in diverse ways –
boundaries of the system need to be described –
characterised by self-organisation and emergent behavior so
more complex than would be predicted by the behavior of
individual parts
o For intergenerational concerns of sustainability analysis –
what time frame should be taken into consideration?
o Pursuit of sustainability in complex s-e- s needs to be an
adaptive process in which the best possible interventions are
tried, results carefully monitored, course corrected as seen fit
Stocks/flows and the 5 capital assets (natural, manufactured,
social, human, knowledge)
o Stocks are the resource pools in a system and an example of a stock is
natural capital
o flows are the relations between the stocks and an example of a flow is
the presence of a policy
o Spatial and temporal changes in systems can be understood
and tracked by measuring the changes in stocks of capital
assets whose size is controlled by inflows and outflows
o Sust dev can be seen as a challenge of maintaining assets
well managing the inflows and outflows
o Ex: policy is allowing manufactured Gl to go into
natural/human capital and possibly corrupting it ?
Systems boundary
o System boundaries refer to a bounded area with a set of
elements that are connected and interact with each other
(Matson, Clark and Andersson, 2016).
o The glyphosate case concerns the environmental, social
(political) and economic spheres of European society. The
internal elements are multiple.
Time scale
o 1970 – first intro of Gl in the product Roundup by Monsanto
o 15 years of debate
o 2015: IARC rules Glyphosate as probably carcinogenic
, o 2017-2022: last license renewal period
o Issues of crop yield (immediate in time) <> environmental
harm/loss and health risks (long term) knowledge needs to
become available on those different timescales too!
o Current state – see articles below
Geographical scale
o The Glyphosate case study focuses on the territory of the 27
member states of the European Union. The spatial scales
concerned range from the field and farm scale to the national
and European scale.
o Glocal scale
Social learning
mutual learning process between all those involved in solving a
sustainability problem. Kates refer it to the need of nre methodological
approaches that encompass science and other forms of knowledge and
experience
Kates et Al 2001 – linked to Sust. Science as social learning is needed
in the transition
Features that pose a challenge in social-environmental systems
o Feedback interactions/loops
o Invisibilities in space and time => Gl
o Invisibilities (local choices affecting communities and
generations in a way that decision makers cannot see) are
referred to as externalities
First dimension is ignorance: science not yet developed
(CFCs)
effects are not visible in geographical proximity (Nepal)
effects are on a later to come generation
essential to make them visible!
o Complexity
o Tipping points, regime shifts, surprises
o Systems can cross thresholds or tipping points at each small
perturbation (on the environment affected by Gl use?)
(more on this on notes), leading to regime shifts which are
persistent and abrupt changes in the dynamics of a system
o Poverty traps in the system is where poverty persists over
time – efforts to help people cross tipping points into more
dynamic systems
o Vulnerability and resilience (about a system’s resistance to stress)
o What determines the capacity of SESs to cope depends on:
Resilience: ability to continue to perform when faced
with perturbation at the current level if not even
benefitting from it – thanks to: diversity, redundancy
(insurance against loss) and connectivity
, Vulnerability: likelihood of suffering harm, which also
depends on differential access to capital assets
Sustainability science
o Strives to integrate study and practice through use-inspired
research
o Use-inspired
o Links knowledge to action
o Role of science in sustainability transition is to help ensure
informed agitation (Amartya Sen)
o Sustainability science is a field emerged that focussed on
creating and harnessing many different kinds of
knowledge to help address social problems, integrates
science and practice through use-inspired research –
goal is increasing our knowledge of and ability to maintain
interactions between environmental and social systems
o Kates et al 2001 - Sustainability science needs to move
forward along three pathways. First, there should be wide
discussion within the scientific community—North and South—
regarding key questions, appropriate methodologies, and
institutional needs. Second, science must be connected to the
political agenda for sustainable development. Third (and most
important), research itself must be focused on the character
of nature-society interactions, on our ability to guide those
interactions along sustainable trajectories, and on ways of
promoting the social learning that will be necessary to
navigate the transition to sustainability + Social Learning
needed see above
Mode 1/normal/traditional/basic science
o Tackles curiosity-led problems solved within the interests of
specific academic communities
o normal science in the Gl case would lead to a lot of different
answers and would thus lead to a lack of consensus from the
scientific side – this is normal and related to issue of excess of
objectivity (Sarewitz 2000)
these separate answers are needed to ensure an informed
decision can be made, but not sufficient ensure that other
types of knowledge are also taken into account and that an
extended peer community can be involved to check quality of
product, process, person and purpose.
o normal science is on its own unsuitable to help solve the
question
o exclusive scientific peer-community present
o reductionism (any issue can be broken down into constituents
and described significantly – nothing is unknownable) and
Newtonian science
Mode 2/post-normal science
, - (Funtowicz and Ravetz, 1993) - Emerged in response to
challenges of policy issues of risk and environment
- policy cannot proceed on factual predictions but only on
forecasts
o Issue-driven
o Needed in complex sustainability issues
o Facts and values are both central and cannot be separated
o Democratisation of science thanks to peer community thus
enlargement of legitimacy of stakeholders included in debates
– this implies toleration of diversity and inclusion of those who
do not belong to academia
o Embraces and manages uncertainty as impossible to
eradicate it from dec-mak be as informed as possible
o Values are explicit and not presupposed
o Provides the means to combine knowledge from different
sources and backgrounds to answer application-driven
solutions (Gibbons, 2013).
o Extended peer review community
o a problem-solving strategy when systems uncertainties and
decision stakes are high
o occurs when facts are uncertain, values in dispute,
stakes high and decisions urgent
a systems view of the world
quality assurance of more than only the scientific product, but also
process, people and purpose
an integrated approach
inter- and transdisciplinary approaches
Quality of science
o Good quality of info depends on good management of
uncertainties which was before kept at the margins of science
and methodology
Dealing with uncertainties
Values/facts – see mode 2 science above
Extended peer community
Traditional or basic research
o Curiosity-driven
Issue-driven
Linear model of science/policy interactions (comes back in task 3)
From R. Pielke Jr 2006: Why is the linear model of science not necessary
nor enough for decision making (according to Pielke)?
> Right science is not always enough for taking action and making decisions.
> Consensus on actions can occur without consensus on science and scientific
information
> If science would have a heavily privileged position, political battles would be a
matter of science and scientists.
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