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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Sven Teurlincx</dc:contributor>
  <dc:contributor>Donald L. DeAngelis</dc:contributor>
  <dc:contributor>Jan H. Janse</dc:contributor>
  <dc:contributor>Tineke A. Troost</dc:contributor>
  <dc:contributor>Dianneke van Wijk</dc:contributor>
  <dc:contributor>Wolf M. Mooij</dc:contributor>
  <dc:contributor>Annette B. G. Janssen</dc:contributor>
  <dc:creator>Manqi Chang</dc:creator>
  <dc:date>2019</dc:date>
  <dc:description>&lt;p&gt;&lt;span&gt;Worldwide, eutrophication is threatening lake ecosystems. To support lake management numerous eutrophication models have been developed. Diverse research questions in a wide range of lake ecosystems are addressed by these models. The established models are based on three key approaches: the empirical approach that employs field surveys, the theoretical approach in which models based on first principles are tested against lab experiments, and the process-based approach that uses parameters and functions representing detailed biogeochemical processes. These approaches have led to an accumulation of field-, lab- and model-based knowledge, respectively. Linking these sources of knowledge would benefit lake management by exploiting complementary information; however, the development of a simple tool that links these approaches was hampered by their large differences in scale and complexity. Here we propose a Generically Parameterized Lake eutrophication model (GPLake) that links field-, lab- and model-based knowledge and can be used to make a first diagnosis of lake water quality. We derived GPLake from consumer-resource theory by the principle that lacustrine phytoplankton is typically limited by two resources: nutrients and light. These limitations are captured in two generic parameters that shape the nutrient to chlorophyll-&lt;/span&gt;&lt;i&gt;a&lt;/i&gt;&lt;span&gt;&amp;nbsp;relations. Next, we parameterized GPLake, using knowledge from empirical, theoretical, and process-based approaches. GPLake generic parameters were found to scale in a comparable manner across data sources. Finally, we show that GPLake can be applied as a simple tool that provides lake managers with a first diagnosis of the limiting factor and lake water quality, using only the parameters for lake depth, residence time and current nutrient loading. With this first-order assessment, lake managers can easily assess measures such as reducing nutrient load, decreasing residence time or changing depth before spending money on field-, lab- or model- experiments to support lake management.&lt;/span&gt;&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1016/j.scitotenv.2019.133887</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Elsevier</dc:publisher>
  <dc:title>A generically parameterized model of lake eutrophication (GPLake) that links field-, lab- and model-based knowledge</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>