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Using presence-only and presence–absence data to estimate the current and potential distributions of established invasive species

机译:使用仅存在和不存在的数据来估计已建立入侵物种的当前和潜在分布

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摘要

>1.Predicting the current and potential distributions of established invasive species is critical for evaluating management options, but methods for differentiating these distributions have received little attention. In particular, there is uncertainty among invasive species managers about the value of information from incidental sightings compared to data from designed field surveys. This study compares the two approaches, and develops a unifying framework, using the case of invasive sambar deer Cervus unicolor in Victoria, Australia.>2.We first used 391 incidental sightings of sambar deer and 12 biophysical variables to construct a presence-only habitat suitability model using Maxent. We then used that model to stratify field sampling, with proportionately greater sampling of cells with high predicted habitat suitability. Field sampling, consisting of faecal pellet surveys, sign surveys and camera trapping, was conducted in 80 4-km2 grid cells. A Bayesian state-space occupancy model was used to predict probability of suitable habitat from the field data.>3.The Maxent and occupancy models predicted similar spatial distributions of habitat suitability for sambar deer in Victoria and there was a strong positive correlation between the rankings of cells by the two approaches. The congruence of the two models suggests that any spatial and detection biases in the presence-only data were relatively unimportant in our study.>4.We predicted the extent of suitable habitat from the occupancy model using a threshold that gave a false negative error rate of 0·05. The current distribution was the suitable habitat within a kernel that had a 99·5% chance of including the presence locations pooled from incidental sightings and field surveys: the potential distribution was suitable habitat outside that kernel. Several discrete areas of potential distribution were identified as priorities for surveillance monitoring with the aim of detecting and managing incursions of sambar deer.>5.Synthesis and applications.Our framework enables managers to robustly estimate the current and potential distributions of established invasive species using either presence-only and/or presence–absence data. Managers can then focus control and/or containment actions within the current distribution and establish surveillance monitoring to detect incursions within the potential distribution.
机译:> 1。预测已建立的入侵物种的当前和潜在分布对于评估管理方案至关重要,但是区分这些分布的方法却鲜有关注。特别是,入侵物种管理人员对于偶然发现的信息与设计现场调查数据相比的价值不确定。本研究以澳大利亚维多利亚州的侵入性水鹿鹿为例,比较了这两种方法,并建立了一个统一的框架。> 2。我们首先使用了391只偶然观察到的水鹿和12个生物物理变量来观察使用Maxent构建仅存在的栖息地适宜性模型。然后,我们使用该模型对田间采样进行分层,对具有较高预测栖息地适应性的细胞进行更大比例的采样。在80个4 km 2 网格单元中进行了现场采样,包括粪便颗粒调查,体征调查和照相机诱集。 > 3。。Maxent模型和占用模型预测维多利亚州水鹿的栖息地适宜性空间分布相似,并且存在一个空间分布模型。两种方法在细胞等级之间具有很强的正相关性。这两个模型的一致性表明,仅存在数据中的任何空间和检测偏差在我们的研究中都相对不重要。> 4。我们使用一个阈值从占用模型中预测了合适的栖息地范围给出的假阴性错误率为0·05。当前的分布是内核中合适的栖息地,有99.5%的机会包括从偶然的目击和野外调查中收集的存在位置:潜在的分布是该内核之外的合适栖息地。 > 5。综合与应用。我们的框架使管理人员能够可靠地估计当前和潜在的分布,这是监视监测重点,以监测和管理水鹿的入侵。仅存在和/或不存在数据就可以确定已建立的入侵物种。然后,管理人员可以集中控制和/或控制当前分布内的行动,并建立监视监视以检测潜在分布内的入侵。

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