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DDC: 690 × Subject: Modelling ×

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    Inconsistent recognition of uncertainty in studies of climate change impacts on forests
    (Bristol : IOP Publ., 2019) Petr, M.; Vacchiano, G.; Thom, D.; Mairota, P.; Kautz, M.; Goncalves, L.M.S.; Yousefpour, R.; Kaloudis, S.; Reyer, C.P.O.
    Background. Uncertainty about climate change impacts on forests can hinder mitigation and adaptation actions. Scientific enquiry typically involves assessments of uncertainties, yet different uncertainty components emerge in different studies. Consequently, inconsistent understanding of uncertainty among different climate impact studies (from the impact analysis to implementing solutions) can be an additional reason for delaying action. In this review we (a) expanded existing uncertainty assessment frameworks into one harmonised framework for characterizing uncertainty, (b) used this framework to identify and classify uncertainties in climate change impacts studies on forests, and (c) summarised the uncertainty assessment methods applied in those studies. Methods. We systematically reviewed climate change impact studies published between 1994 and 2016. We separated these studies into those generating information about climate change impacts on forests using models –'modelling studies', and those that used this information to design management actions—'decision-making studies'. We classified uncertainty across three dimensions: nature, level, and location, which can be further categorised into specific uncertainty types. Results. We found that different uncertainties prevail in modelling versus decision-making studies. Epistemic uncertainty is the most common nature of uncertainty covered by both types of studies, whereas ambiguity plays a pronounced role only in decision-making studies. Modelling studies equally investigate all levels of uncertainty, whereas decision-making studies mainly address scenario uncertainty and recognised ignorance. Finally, the main location of uncertainty for both modelling and decision-making studies is within the driving forces—representing, e.g. socioeconomic or policy changes. The most frequently used methods to assess uncertainty are expert elicitation, sensitivity and scenario analysis, but a full suite of methods exists that seems currently underutilized. Discussion & Synthesis. The misalignment of uncertainty types addressed by modelling and decision-making studies may complicate adaptation actions early in the implementation pathway. Furthermore, these differences can be a potential barrier for communicating research findings to decision-makers.
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    Modelling Climate Change’s Impact on the Hydrology of Natura 2000 Wetland Habitats in the Vistula and Odra River Basins in Poland
    (Basel : MDPI, 2019) O’Keeffe, Joanna; Marcinkowski, Paweł; Utratna, Marta; Piniewski, Mikołaj; Kardel, Ignacy; Kundzewicz, Zbigniew; Okruszko, Tomasz
    Climate change is expected to affect the water cycle through changes in precipitation, river streamflow, and soil moisture dynamics, and therefore, present a threat to groundwater and surface water-fed wetland habitats and their biodiversity. This article examines the past trends and future impacts of climate change on riparian, water-dependent habitats within the special areas of conservation (SAC) of the Natura 2000 network located within Odra and Vistula River basins in Poland. Hydrological modelling using the Soil and Water Assessment Tool (SWAT) was driven by a set of nine EURO-CORDEX regional climate models under two greenhouse gas concentration trajectories. Changes in the duration of flooding and inundation events were used to assess climate change’s impact on surface water-fed wetland habitats. The groundwater-fed wetlands were evaluated on the basis of changes in soil water content. Information about the current conservation status, threats, and pressures that affect the habitats suggest that the wetlands might dry out. Increased precipitation projected for the future causing increased water supply to both surface water and groundwater-fed wetlands would lead to beneficial outcomes for habitats with good, average, or reduced conservation status. However, habitats with an excellent conservation status that are already in optimum condition could be negatively affected by climate change as increased soil water or duration of overbank flow would exceed their tolerance.