{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T03:45:41Z","timestamp":1788234341119,"version":"build-2803163510"},"reference-count":71,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2021,1,20]],"date-time":"2021-01-20T00:00:00Z","timestamp":1611100800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["esajournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Ecological Applications"],"published-print":{"date-parts":[[2021,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Coastal wetlands intercept significant amounts of nitrogen (N) from watersheds, especially when surrounding land cover is dominated by agriculture and urban development. Through plant uptake, soil immobilization, and denitrification, wetlands can remove excess N from flow\u2010through water sources and mitigate eutrophication of connected aquatic ecosystems. Excess N can also change plant community composition in wetlands, including communities threatened by invasive species. Understanding how variable hydrology and N loading impact wetland N removal and community composition can help attain desired management outcomes, including optimizing N removal and\/or preventing invasion by nonnatives. By using a dynamic, process\u2010based ecosystem simulation model, we are able to simulate various levels of hydrology and N loading that would otherwise be difficult to manipulate. We investigate in silico the effects of hydroperiod, hydrologic residence time, N loading, and the : ratio on both N removal and the invasion success of two nonnative species (<jats:italic>Typha<\/jats:italic>\u00a0\u00d7\u00a0<jats:italic>glauca<\/jats:italic> or <jats:italic>Phragmites australis<\/jats:italic>) in temperate freshwater coastal wetlands. We found that, when residence time increased, annual N removal increased up to 10\u2010fold while longer hydroperiods also increased N removal, but only when residence time was &gt;10\u00a0d and N loading was &gt;30\u00a0g\u00a0N\u00b7m<jats:sup>\u22122<\/jats:sup>\u00b7yr<jats:sup>\u22121<\/jats:sup>. N removal efficiency also increased with increasing residence time and hydroperiod, but was less affected by N loading. However, longer hydrologic residence time increased vulnerability of wetlands to invasion by both invasive plants at low to medium N loading rates where native communities are typically more resistant to invasion. This suggests a potential trade\u2010off between ecosystem services related to nitrogen removal and wetland invasibility. These results help elucidate complex interactions of community composition, N loading and hydrology on N removal, helping managers to prioritize N removal when N loading is high or controlling plant invasion in more vulnerable wetlands.<\/jats:p>","DOI":"10.1002\/eap.2233","type":"journal-article","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T19:04:51Z","timestamp":1602615891000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Hydrologic flushing rates drive nitrogen cycling and plant invasion in a freshwater coastal wetland model"],"prefix":"10.1002","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6724-0186","authenticated-orcid":false,"given":"Sean J.","family":"Sharp","sequence":"first","affiliation":[{"name":"School for Environment and Sustainability University of Michigan Ann Arbor Michigan 48109 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9012-8590","authenticated-orcid":false,"given":"Kenneth J.","family":"Elgersma","sequence":"additional","affiliation":[{"name":"Department of Biology University of Northern Iowa Cedar Falls Iowa 50614 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3912-4911","authenticated-orcid":false,"given":"Jason P.","family":"Martina","sequence":"additional","affiliation":[{"name":"Department of Biology Texas State University San Marcos Texas 78666 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1975-0808","authenticated-orcid":false,"given":"William S.","family":"Currie","sequence":"additional","affiliation":[{"name":"School for Environment and Sustainability University of Michigan Ann Arbor Michigan 48109 USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,1,20]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1890\/14-1525"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13157-019-01174-7"},{"key":"e_1_2_7_4_1","unstructured":"Barton K.2019.MuMIn: Multi\u2010Model Inference. 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