Increased concentrations of dissolved organic carbon (DOC), often labelled “browning”, is a current trend in northern, particularly boreal, freshwaters. The browning has been attributed to the recent reduction in sulphate (S) deposition during the last 2 to 3 decades. Over the last century, climate and land use change have also caused an increasing trend in vegetation cover (“greening”), and this terrestrially fixed carbon represents another potential source for export of organic carbon to lakes and rivers. The impact of this greening on the observed browning of lakes and rivers on decadal time scales remains poorly investigated, however. Here, we explore time-series both on water chemistry and catchment vegetation cover (using NDVI as proxy) from 70 Norwegian lakes and catchments over a 30-year period. We show that the increase in terrestrial vegetation as well as temperature and runoff significantly adds to the reduced SO4-deposition as a driver of freshwater DOC concentration. Over extended periods (centuries), climate mediated changes in vegetation cover may cause major browning of northern surface waters, with severe impact on ecosystem productivity and functioning.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: superindividual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Boreal lakes are impacted by climate change, reduced acid deposition, and changing loads of dissolved organic carbon (DOC) from catchments. We explored, using the process-based lake model MyLake, how changes in these pressures modulate ice phenology and the dissolved oxygen concentrations (DO) of a small boreal humic lake. The model was parametrized against year-round time series of water temperature and DO from a lake buoy. Observed trends in air temperature (+0.045°C yr À1 ) and DOC concentration (0.11 mg C L À1 yr À1 , +1% annually) over the past 40 years were used as model forcings. A backcast of ice freezing and breakup dates revealed that ice breakup occurred on average 8 days earlier in 2014 than in 1974. The earlier ice breakup enhanced water column ventilation resulting in higher DO in the spring. Warmer water in late summer led to longer anoxic periods, as microbial DOC turnover increased. A long-term increase in DOC concentrations caused a decline in lake DO, leading to 15% more hypoxic days (<3 mg L À1 ) and 10% more anoxic days (<15 μg L À1 ) in 2014 than in 1974. We conclude that climate warming and increasing DOC loads are antagonistic with respect to their effect on DO availability. The model suggests that DOC is a stronger driver of DO consumption than temperature. The browning of lakes may thus cause reductions in the oxythermal habitat of fish and aquatic biota in boreal lakes.
Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv) increase the transparency of model structure, assumptions and techniques, (v) achieve a greater Handling editor: Boping Han understanding of aquatic ecosystem functioning, (vi) increase the reliability of predictions by aquatic ecosystem models, (vii) stimulate model inter-comparisons including differing model approaches, and (viii) avoid 're-inventing the wheel', thus accelerating improvements to aquatic ecosystem models. We intend to achieve this as a community that fosters interactions amongst ecologists and model developers. Further, we outline scientific topics recently articulated by the scientific community, which lend themselves well to being addressed by integrative modelling approaches and serve to motivate the progress and implementation of an open source model framework.
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