Quantifying suitable habitat of the threatened western prairie fringed orchid.

P.M. Wolken, C.H. Sieg, S.E. Williams

Abstract


Land managers need accurate and quick techniques to identify suitable habitat of species of interest. For species protected by federal or state laws, identification of suitable habitat is critical for developing a conservation strategy that includes reestablishing populations and altering management to address this need. In this research, we quantified vegetative and edaphic habitat of the western prairie fringed orchid (Platanthera praeclara Sheviak and Bowles), a federally listed threatened plant. Lowlands (swales) that supported orchids in our southeastern North Dakota study area were characterized as having a higher soil moisture content within the top 10 cm, when compared to swales devoid of orchids. The vegetative composition of orchid-supporting swales reflected this higher moisture content. These data were then used in developing a logistic regression model to differentiate suitable habitat. The model correctly classified 84% of 38 swales as either orchid-supporting or non-orchid-supporting using 4 variables: percent canopy cover of Baltic rush (Juncus balticus Willd.) and hedge-nettle (Stachys palustris L.), soluble soil magnesium and August surface soil moisture. Land managers can use this model to rapidly assess the suitability of a site in this ecoregion for the orchid. By collecting data on the cover of just Baltic rush, which would take about 45 minutes, and entering it in the equation, a land manager could correctly classify 66% of the orchid swales as either suitable or unsuitable as orchid habitat. This approach, because it incorporates quantitative data and allows managers to rapidly and accurately identify suitable habitats, shows promise for other plant species.

DOI:10.2458/azu_jrm_v54i5_wolken


Keywords


wetlands;Juncus;juncus balticus;wetland soils;endangered species;Platanthera;Platanthera praeclara;stachys palustris;sheyenne national grassland;swales;habitat selection;prediction;regression analysis;forbs;soil water content;plant communities;shrubs;plant litter;canopy;grasses

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