Avifaunal responses to fire in southwestern montane forests along a burn severity gradient.
Avifaunal responses to fire in southwestern montane forests along a burn severity gradient.
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西南山地森林中鸟类动物对火灾的反应沿着烧伤严重程度梯度。
DOI：
10.1890/06-0253
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
K. Ferree
中科院分区：
文献类型：
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作者：
N. B. Kotliar;P. Kennedy;K. Ferree
人们对烧伤严重程度对鸟类群落的影响知之甚少，但这些信息对于火灾管理计划至关重要。为了量化沿烧伤严重程度梯度的鸟类反应模式，我们在美国新墨西哥州 17351 公顷的 Cerro Grande 火灾（2000 年）中随机抽取了 49 个样地（2001-2002 年）。此外，火灾前鸟类调查（1986-1988、1990）创造了一个独特的机会来量化火灾前 13 个样带（2002 年重新采样）的鸟类动物变化，并比较两种分析意外干扰影响的设计：仅事后分析和前后比较。使用距离分析来计算密度。我们使用梯度分析分析了 21 个物种的事后密度，检测到对烧伤严重程度增加的广泛反应：(I) 大幅下降，(II) 微弱但显着下降，(III) 无显着密度变化，(IV) 低或中等严重程度斑块中的峰值密度，(V) 微弱但显着增加，(VI) 大幅显着增加。总体而言，仅事后梯度分析中包含的 71% 的物种在整个或部分严重梯度（响应 III-VI）中表现出对火灾效应的正密度响应或中性密度响应。我们通过前后比较，使用前后对分析来量化 15 个物种的密度变化；对于大多数物种来说，密度的时空变化很大并且混淆了火灾效应。只有四种物种表现出烧毁严重程度的显着影响，并且与未烧毁的森林相比，烧毁的森林的密度都较高。除严重程度较高的地区外，火灾前后的群落相似性很高。所有烧伤严重程度的火灾前后物种丰富度相似。因此，我们对火灾后鸟类群落的研究并不支持基于西南黄松林最近发生的严重火灾具有压倒性的负面生态影响这一假设的生态系统恢复计划。这项研究说明了在火灾影响研究中量化烧伤严重程度和控制时空变化的混杂来源的重要性。仅事后梯度分析可以成为量化火灾效应的有效工具。这种分析还可以增强历史数据集，这些数据集具有较小的样本量以及较高的非过程变化，这限制了前后比较的能力。
The effects of burn severity on avian communities are poorly understood, yet this information is crucial to fire management programs. To quantify avian response patterns along a burn severity gradient, we sampled 49 random plots (2001-2002) at the 17351-ha Cerro Grande Fire (2000) in New Mexico, USA. Additionally, pre-fire avian surveys (1986-1988, 1990) created a unique opportunity to quantify avifaunal changes in 13 pre-fire transects (resampled in 2002) and to compare two designs for analyzing the effects of unplanned disturbances: after-only analysis and before-after comparisons. Distance analysis was used to calculate densities. We analyzed after-only densities for 21 species using gradient analysis, which detected a broad range of responses to increasing burn severity: (I) large significant declines, (II) weak, but significant declines, (III) no significant density changes, (IV) peak densities in low- or moderate-severity patches, (V) weak, but significant increases, and (VI) large significant increases. Overall, 71% of the species included in the after-only gradient analysis exhibited either positive or neutral density responses to fire effects across all or portions of the severity gradient (responses III-VI). We used pre/post pairs analysis to quantify density changes for 15 species using before-after comparisons; spatiotemporal variation in densities was large and confounded fire effects for most species. Only four species demonstrated significant effects of burn severity, and their densities were all higher in burned compared to unburned forests. Pre- and post-fire community similarity was high except in high-severity areas. Species richness was similar pre- and post-fire across all burn severities. Thus, ecosystem restoration programs based on the assumption that recent severe fires in Southwestern ponderosa pine forests have overriding negative ecological effects are not supported by our study of post-fire avian communities. This study illustrates the importance of quantifying burn severity and controlling confounding sources of spatiotemporal variation in studies of fire effects. After-only gradient analysis can be an efficient tool for quantifying fire effects. This analysis can also augment historical data sets that have small samples sizes coupled with high non-process variation, which limits the power of before-after comparisons.