Abstract:The management of non-point source pollution from agricultural land use is a complex issue for the management of freshwater worldwide. This paper presents a case study from New Zealand to examine how predictive modelling and land use rules are being used to regulate diffuse pollution to manage water quality. Drawing on a science studies conceptual framework, the research evaluates the deployment of a numeric regime to enforce compliance with resource limits. It shows that in contrast to claims that a quantitative modelled 'outputsbased' approach would provide certainty and clarity and remove ambiguity in the implementation of resource limits at the farm scale, the opposite is unfolding. It is argued from the case study that in the development of land use policy greater recognition and understanding is needed of the social and political dimensions of numbers and predictive models. This research highlights epistemological, institutional and practical challenges for the workability and enforceability of policy regimes seeking to regulate diffuse pollution that tightly link numbers derived from predictive models to compliance and enforcement mechanisms.Keywords: New Zealand, non-point source pollution, resource limits, water quality, predictive modelling, science policy, knowledge governance Highlights  In contrast to assertions that numbers and models would provide clarity and remove ambiguity, the opposite is unfolding  Seeking to resolve 'upstream' effects presents a range of challenges that centre on credibility and accountability  While the need for credibility is shared, criteria to achieve it differ across the science policy interface  Regulating diffuse pollution is not just a scientific and technical endeavour -it is also a social-political one 2  Relying on numbers presents epistemological, institutional and practical challenges for implementing resource limits IntroductionWorldwide, non-point source pollution from agricultural production is contributing to the nutrient enrichment of freshwater and the diminishment of water quality. Management efforts are exacerbated by lag effects. In New Zealand, the erosion and nutrient leaching legacies of past and current land use change from sheep and beef to dairy farming are merging with challenging implications for science and policy (PCE, 2013). Even with extensive improvements in land use practices and expensive mitigation, authorities have to explain to communities that water quality is likely to get worse before it gets better. This is due to nutrient losses from past land practices still moving through the system into waterways and contributing to the growth of nuisance algae and eutrophication (Goolsby et al., 2001;Howden et al., 2013; PCE, 2012 PCE, , 2013Sanford and Pope, 2013;Sims and Volk, 2013;Skelton and Caygill, 2013 The starting point for this research are assertions that certainty and clarity and the removal of ambiguity would be achieved under a water quality management regime that creates enforceable quantitative limits and a regula...

It is well known in impact assessment that predictive model outputs will be as credible as their inputs and that model assumptions will drive outputs. What is less well known is how the practice of integrated impact assessment with its pervasive use of predictive computer models and multiple teams of consultants can influence evidence relied upon in deliberations over the impacts and benefits of major projects. This paper draws on an integrated impact assessment of a major energy infrastructure project in Australia known as Basslink to examine the epistemic implications of current practice. It will be argued that what has become standard procedure can serve to diminish the disclosure of prediction uncertainty.

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Calls for transformation, transformative research, and transformational impact are increasingly heard from governments, industry, and universities to recast a course towards sustainability. This paper retraces a social, qualitative, and interpretive research endeavor to contribute to broadening the conceptual base of transformation. Drawing on perspectives of practitioners involved in working with communities to bring about change in how land and water are managed, the objective of the research was to elicit a range of practice-based encounters of transformation to inform policy and theory. In identifying precursors and processes for change, the findings bring into view the often unseen internal and experiential dimensions of transformation. As such, the research provides insights on where transformation takes place, what the first step of transformation might look like, and what might be deemed transformational. The paper also builds on social practice theory to produce an explanatory model of transformational capacity that is enabled and constrained by structures, processes, understanding, and authority that impact on social practices of knowledge generation (including science) and land and water decision-making.

This paper examines farmers' ways of knowing water quality and their encounters with the science used in policy to address the cumulative effects of agriculture. Drawing on constructivist theories of knowledge and discussions with farmers in two locations of New Zealand's South Island region of Canterbury, the research identifies a significant divergence between farmers' conception of the water quality problem compared to the issue's policy framing. In theory, and increasingly in practice, ways of knowing are assumed merely outof-sync and their integration or coproduction possible and necessary. This paper poses the question: what if the ways of knowing of farmers and science have become incompatible? The presented research indicates incompatibility that derives from epistemic practices that mobilise different ontologies at different scales. It is shown how the predictive practices of science present what appear to be insurmountable obstacles to integration or coproduction. It is argued that collaborative governance needs to find ways to work with divergent ways of knowing -not for the purpose of integration or coproduction but co-existence.

The question posed in this paper is how shifts in governance ushered in by the sustainability paradigm are reshaping knowledge governance. Drawing on constructivist theories of knowledge, I examine the tension between the sustainability mandate to open up knowledgemaking to local knowledge, and conventional science policy practice that would see it excluded. I present a water management case study from New Zealand's South Island region of Canterbury, where communities are involved in establishing catchment nutrient limits to manage land use and water quality. It is concluded that although local knowledge was embraced within the knowledge-making process, the pursuit of epistemic authority led to its recalibration, aggregation and standardization. As such it was stripped of its complexity. This research highlights the role of politics in anchoring the linear knowledge governance model in place and the challenge for supplanting it.

In the context of an increasing reliance on predictive computer simulation models to calculate potential project impacts, it has become common practice in impact assessment (IA) to call on proponents to disclose uncertainties in assumptions and conclusions assembled in support of a development project. Understandably, it is assumed that such disclosures lead to greater scrutiny and better policy decisions. This paper questions this assumption. Drawing on constructivist theories of knowledge and an analysis of the role of narratives in managing uncertainty, I argue that the disclosure of uncertainty can obscure as much as it reveals about the impacts of a development project. It is proposed that the opening up of institutional spaces that can facilitate the negotiation and deliberation of foundational assumptions and parameters that feed into predictive models could engender greater legitimacy and credibility for IA outcomes.

Knowledge brokers are often portrayed as neutral intermediaries that act as a necessary conduit between the spheres of science and policy. Conceived largely as a task in packaging, brokers are expected to link knowledge producers and users and objectively translate science into policy-useable knowledge. The research presented in this paper shows how brokering can be far more active and precarious. We present findings from semistructured interviews with practitioners working with community-based groups involved in collaborative water planning in New Zealand's South Island region of Canterbury. Working in a highly conflicted situation, our brokers had to navigate different knowledges and epistemic practices, highly divergent values and grapple with uncertainties to deliver recommendations for regional authorities to set water quality and quantity limits. Conceiving science and policy as interlinked, mutually constitutive and co-produced at multiple levels, rather than as separate domains, shows how the brokers of this study were not only bridging or blurring science policy boundaries to integrate and translate knowledges. They were also building boundaries between science and policy to foster credibility and legitimacy for themselves as scientists and the knowledge they were brokering. This research identifies further underexplored aspects of brokering expertise, namely, the multiple dimensions of brokering, transdisciplinary skills and expertise, 'absorptive' uncertainty management and knowledge translation practices.