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Increasing the availability of shrubland habitat is a major conservation priority in the Northeastern United States because many wildlife species require this habitat and its extent has been decreasing in recent decades. Conservation agencies often monitor the number of hectares of shrubland habitat created, but rarely monitor the density of the resulting vegetation because the process is tedious and time-consuming. The current study tested a new approach to assess vegetation density: Digital Imagery Vegetation Analysis (DIVA). We compared the density estimates of DIVA with four other methods (Cover Board, Robel Pole, Height of Obstruction, and Line Intercept), and assessed the advantages and disadvantages of using these five methods in shrubland studies. We concluded that DIVA offers two main advantages over the other methods: (a) it directly measures the vertical structure of the vegetation and thus better captures the complex wildlife habitat characteristics required by many wildlife, and (b) it does not rely on ocular estimates and thus avoids much of the bias associated with the other methods that estimate vertical structure. Furthermore, DIVA provides a rich documentation that permits quality control and other analyses to be conducted after the fieldwork is completed. However, DIVA is more time consuming than the other methods, thus we recommend either Robel Pole or Cover Board for routine monitoring.

Assessing the Density of Vegetation for Wildlife Cover in Regenerating Clearcuts via Analysis of Digital Imagery