Landscape dynamics of floral resources affect the supply of a biodiversity-dependent cultural ecosystem service
Landscape dynamics of floral resources affect the supply of a biodiversity-dependent cultural ecosystem service
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DOI：
10.1007/s10980-016-0452-0
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发表时间：
2017-02-01
影响因子：
5.2
通讯作者：
Turner, Monica G.
中科院分区：
文献类型：
--
作者：
Graves, Rose A.;Pearson, Scott M.;Turner, Monica G.
文化生态系统服务，其中许多依赖于生物多样性，被认为是重要的，但很少量化的生物生态学景观。此外，许多生态系统服务模型是静态的，如果忽略生物群落的季节性变化，文化生态系统服务的供应可能会被歪曲。（野花物种丰富度，丰度，时间和魅力物种的存在）在生长季节发生变化，（2）预计的野花观赏热点如何随空间和时间变化，以及（3）花卉资源的空间变化如何影响潜在的公众对野花的观赏。广义线性模型被用来确定在两个时间尺度上影响植物资源的因素。利用覆盖分析法对景观中的花卉资源进行了预测，并对野花观赏热点进行了量化分析。花卉资源受地形、气候和周围建筑密度的影响，并随季节变化。季节性模型揭示了生态系统服务热点的位置变化，这改变了公众可访问的热点的比例，并确定了静态models.Relationships景观梯度，生物多样性和生态系统服务供应之间的关系随季节变化，我们的模型确定了文化生态系统服务热点，否则被简单的代理人掩盖。基于生物多样性的文化生态系统服务景观模型应包括生物群落的季节动态，以避免在生态系统服务评估中对特定地点的重要性强调不足或过分强调。
Cultural ecosystem services, many of which depend on biodiversity, are recognized as important but seldom quantified biophysically across landscapes. Furthermore, many ecosystem service models are static, and the supply of cultural ecosystem services may be misrepresented if seasonal shifts in biotic communities are ignored.We modeled landscape dynamics of wildflower blooms in a temperate montane landscape to determine (1) how floral resources (wildflower species richness, abundance, timing, and presence of charismatic species) changed over the growing season, (2) how projected wildflower viewing hotspots varied over space and time, and (3) how spatial shifts in floral resources affected potential public access to wildflower viewing.Data were collected at 63 sites across a rural-to-urban gradient in the Southern Appalachian Mountains (USA). Generalized linear models were used to identify factors affecting floral resources at two temporal scales. Floral resources were projected across the landscape and hotspots of wildflower viewing were quantified using overlay analysis.Floral resources were affected by topoedaphic conditions, climate, and surrounding building density and changed seasonally. Seasonal models revealed locational shifts in ecosystem service hotspots, which changed the proportion of hotspots accessible to the public and identified wildflower-viewing opportunities unnoticed by static models.Relationships between landscape gradients, biodiversity, and ecosystem service supply varied seasonally, and our models identified cultural ecosystem service hotspots otherwise obscured by simple proxies. Landscape models of biodiversity-based cultural ecosystem services should include seasonal dynamics of biotic communities to avoid under- or over-emphasizing the importance of particular locations in ecosystem service assessments.