<p>Wetland indicator status values (WIVs) are ratings that reflect a plant species’ affinity for wetlands and are used as core tools for wetland delineation. In this study, we assessed the effectiveness of WIVs using 587 wetland and 646 non-wetland plots from an Illinois wetland delineation database. If WIVs captured meaningful information about plant assemblages and affinity for wetlands, we would expect that species’ WIVs would correlate to the mean weighted average WIVs of their co-occurring species across multiple sites (i.e., the mean prevalence index [PI] of co-occurring species, <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13157_2025_1947_Article_IEq1.gif" Format="GIF" Height="24" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">\(\:\stackrel{-}{\text{P}\text{I}}\)</EquationSource> </InlineEquation><sub><i>i</i></sub>). Similarly, when WIVs are used in the PI to classify vegetation as either non-hydrophytic or hydrophytic, these classifications should correspond to wetland designations that are more sensitive and specific than expected by chance. Using data from 1,233 plots in Illinois (USA), we tested these predictions by comparing observed PI and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13157_2025_1947_Article_IEq1.gif" Format="GIF" Height="24" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">\(\:\stackrel{-}{\text{P}\text{I}}\)</EquationSource> </InlineEquation><sub><i>i</i></sub> to those generated under a null model based on randomized WIVs. We also related species’ WIVs to their frequency of occurrence in wetlands and estimated whether certain types of species (life history, woodiness, prior WIV revision, and nativity) had less accurate WIVs based on the co-occurrence data. Species’ WIVs were much more strongly correlated to the <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="13157_2025_1947_Article_IEq1.gif" Format="GIF" Height="24" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">\(\:\stackrel{-}{\text{P}\text{I}}\)</EquationSource> </InlineEquation><sub><i>i</i></sub> than would be expected under the null model. However, some species, particularly short-lived plants, had less accurate WIVs based on their co-occurrence characteristics; no effect was detected for the other three species type comparisons. Using WIVs to determine hydrophytic status led to highly sensitive (99%) and somewhat specific (66%) correspondence to actual wetland status; sensitivity was far greater than null expectations, whereas specificity was only marginally greater. As expected, species’ frequency of occurrence in wetlands declined with increasing WIV. Obligate wetland and upland (non-wetland) species typically occurred in wetland and non-wetland plots, respectively; facultative wetland and facultative species had greater variability and inconsistent presence in wetlands. WIVs outperformed null expectations, validating their application. Although WIVs are expert-based, future efforts could apply vegetation data to test and improve species’ WIV assignments.</p>

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A Null Model Approach to Test the Validity and Efficacy of Wetland indicator Status Values

  • Jack Zinnen,
  • Laura Sass,
  • Paul B. Marcum,
  • Jeffrey W. Matthews

摘要

Wetland indicator status values (WIVs) are ratings that reflect a plant species’ affinity for wetlands and are used as core tools for wetland delineation. In this study, we assessed the effectiveness of WIVs using 587 wetland and 646 non-wetland plots from an Illinois wetland delineation database. If WIVs captured meaningful information about plant assemblages and affinity for wetlands, we would expect that species’ WIVs would correlate to the mean weighted average WIVs of their co-occurring species across multiple sites (i.e., the mean prevalence index [PI] of co-occurring species, \(\:\stackrel{-}{\text{P}\text{I}}\) i). Similarly, when WIVs are used in the PI to classify vegetation as either non-hydrophytic or hydrophytic, these classifications should correspond to wetland designations that are more sensitive and specific than expected by chance. Using data from 1,233 plots in Illinois (USA), we tested these predictions by comparing observed PI and \(\:\stackrel{-}{\text{P}\text{I}}\) i to those generated under a null model based on randomized WIVs. We also related species’ WIVs to their frequency of occurrence in wetlands and estimated whether certain types of species (life history, woodiness, prior WIV revision, and nativity) had less accurate WIVs based on the co-occurrence data. Species’ WIVs were much more strongly correlated to the \(\:\stackrel{-}{\text{P}\text{I}}\) i than would be expected under the null model. However, some species, particularly short-lived plants, had less accurate WIVs based on their co-occurrence characteristics; no effect was detected for the other three species type comparisons. Using WIVs to determine hydrophytic status led to highly sensitive (99%) and somewhat specific (66%) correspondence to actual wetland status; sensitivity was far greater than null expectations, whereas specificity was only marginally greater. As expected, species’ frequency of occurrence in wetlands declined with increasing WIV. Obligate wetland and upland (non-wetland) species typically occurred in wetland and non-wetland plots, respectively; facultative wetland and facultative species had greater variability and inconsistent presence in wetlands. WIVs outperformed null expectations, validating their application. Although WIVs are expert-based, future efforts could apply vegetation data to test and improve species’ WIV assignments.