Identifying Conservation‐Priority Areas in a Fragmented Minnesota Landscape Based on the Umbrella Species Concept and Selection of Large Patches of Natural Vegetation
Identifying Conservation‐Priority Areas in a Fragmented Minnesota Landscape Based on the Umbrella Species Concept and Selection of Large Patches of Natural Vegetation
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基于伞物种概念和大片自然植被选择确定明尼苏达破碎景观中的保护优先区域
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发表时间：
2001
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通讯作者：
K. Chapman
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作者：
K. A. Poiani;M. Merrill;K. Chapman
摘要：确定保护区的优先次序有两种常见但相对未经检验的方法，包括确定伞状物种的栖息地和选择大片剩余的自然植被。我们根据大草原鸡( Tympanuchus cuido pinnatus)的栖息地需求，测试了一种伞种方法来确定明尼苏达州阿加西海滩脊景观的保护区。所有落在草原鸡繁殖地1.6公里以内的自然植被斑块被选为保护优先事项，并与随机选择的植被斑块进行比较。通过伞状物种方法选择的斑块包含的生物重要土地(59%)比选择最大的斑块(56%)略多，这两组斑块都比随机选择的斑块(47%)包含更多的生物重要土地。最大的一组自然植被斑块包含了最多数量的自然群落类型(16种可能中的12种)。与其他两种方法相比，伞状物种方法选择的斑块包含了更多的物种和群落的出现(个别位置)。利用草原鸡的栖息地要求来确定保护区，充分处理了其他草原物种和群落，但并不少见的森林栖息地。在许多情况下，大斑块方法在保护各种生物多样性成分方面做得同样好或更好，这表明伞状物种和大斑块方法在这一景观中是互补的。因为我们有关于伞状物种的长期信息，所以我们能够使用不同级别和类型的数据来探索保护优先事项的设置。正如预期的那样，通过结合多年数据(n=25到n=337)增加繁荣区的数量通常会增加选定植被斑块的数量和面积，以及出现的次数和其中包含的具有生物重要性的土地的数量。我们还发现，具有最少繁荣场地的数据集通常产生最有效的结果，例如所选单位面积上最具生物重要性的土地。我们观察到，稳定的繁荣区比临时繁荣区在单位面积的选定栖息地中更有效地吸收了生物多样性的其他组成部分。这些结果表明，雨伞树种数据的数量和质量将对规划结果产生很大影响。
Abstract: Two common but relatively untested approaches to prioritizing conservation areas involve identification of umbrella‐species habitat and selection of large blocks of remaining natural vegetation. We tested an umbrella‐species approach to identification of conservation areas in the Agassiz Beach Ridges landscape of Minnesota based on the habitat needs of the Greater Prairie Chicken ( Tympanuchus cupido pinnatus). All natural vegetation patches that fell within 1.6 km of prairie chicken booming grounds were selected as conservation priorities and were compared with randomly selected vegetation patches. Patches selected by the umbrella‐species approach encompassed slightly more biologically important land (59%) than selection of the largest patches (56%), and both these sets contained more biologically important land than randomly selected patches (47%). The set of largest natural vegetation patches encompassed the greatest number of natural community types (12 of 16 possible). Patches selected by the umbrella‐species approach encompassed more occurrences (individual locations) of species and communities than both other approaches. Using the habitat requirements of prairie chicken to identify conservation areas adequately addressed other grassland species and communities but not uncommon forested habitats. In many cases, the large‐patch approach did equally well or better at protecting various biodiversity components, indicating that the umbrella‐species and large‐patch approaches are complementary in this landscape. Because we had long‐term information on our umbrella species, we were able to explore the setting of conservation priorities using different levels and types of data. As expected, increasing the number of booming grounds by combining years of data (n = 25 to n = 337) generally increased the number and area of selected vegetation patches and the number of occurrences and amount of biologically important land contained within them. We also found that data sets with the fewest booming grounds often produced the most efficient results, such as most biologically important land per unit area selected. We observed that stable booming grounds were more efficient in incorporating other components of biodiversity per unit area of selected habitat than were temporary booming grounds. These results demonstrate that the quantity and quality of data on umbrella species will greatly affect planning results.