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Studies explaining the choice of model structure for population viability analysis (PVA) are rare and no such study exists for butterfly species, a focal group for conservation. Here, we describe in detail the development of a model to predict population viability of a glacial relict butterfly species, Boloria eunomia, under climate change. We compared four alternative formulations of an individual-based model, differing in the environmental factors acting on the survival of immature life stages: temperature (only temperature impact), weather (temperature, precipitation, and sunshine), temperature and parasitism, and weather and parasitism. Following pattern-oriented modeling, four observed patterns were used to contrast these models: one qualitative (response of population size to habitat parameters) and three quantitative ones describing population dynamics during eight years (mean and variability of population size, and magnitude of the temporal autocorrelation in yearly population growth rates). The four model formulations were not equally able to depict population dynamics under current environmental conditions; the model including only temperature was selected as the most parsimonious model sufficiently well reproducing the empirical patterns. We used all four model formulations to test a range of climate change scenarios that were characterized by changes in both mean and variability of the weather variables. All models predicted adverse effects of climate change and resulted in the same ranking of mean climate change scenarios. However, models differed in their absolute values of population viability measures, underlining the need to explicitly choose the most appropriate model formulation and avoid arbitrary usage of environmental drivers in a model. We conclude that further applications of pattern-oriented modeling to butterfly and other species are likely to help in identifying the key factors impacting the viability of certain taxa, which, ultimately, will aid and speed up informed management decisions for endangered species under climate change.
Ecological regime shifts and carbon cycling in aquatic systems have both been subject to increasing attention in recent years, yet the direct connection between these topics has remained poorly understood. A four-fold increase in sedimentation rates was observed within the past 50 years in a shallow eutrophic lake with no surface in-or outflows. This change coincided with an ecological regime shift involving the complete loss of submerged macrophytes, leading to a more turbid, phytoplankton-dominated state. To determine whether the increase in carbon (C) burial resulted from a comprehensive transformation of C cycling pathways in parallel to this regime shift, we compared the annual C balances (mass balance and ecosystem budget) of this turbid lake to a similar nearby lake with submerged macrophytes, a higher transparency, and similar nutrient concentrations. C balances indicated that roughly 80% of the C input was permanently buried in the turbid lake sediments, compared to 40% in the clearer macrophyte-dominated lake. This was due to a higher measured C burial efficiency in the turbid lake, which could be explained by lower benthic C mineralization rates. These lower mineralization rates were associated with a decrease in benthic oxygen availability coinciding with the loss of submerged macrophytes. In contrast to previous assumptions that a regime shift to phytoplankton dominance decreases lake heterotrophy by boosting whole-lake primary production, our results suggest that an equivalent net metabolic shift may also result from lower C mineralization rates in a shallow, turbid lake. The widespread occurrence of such shifts may thus fundamentally alter the role of shallow lakes in the global C cycle, away from channeling terrestrial C to the atmosphere and towards burying an increasing amount of C.