Some thoughts about the challenge of inferring ecological interactions from spatial data.

R. Holt
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引用次数: 10

Abstract

Dr. Luis Escobar asked me to provide a joint review of the submissions by Stephens et al. (2019, this issue) and Peterson et al. (2019, this issue).  I pulled thoughts together, but by the time I sent them along, he had received other reviews and made an editorial decision. He felt my perspective might nevertheless warrant publishing as a commentary alongside these two pieces.  My review was of the original submissions, which are now appearing with minor, mainly cosmetic changes.  I have only lightly edited the text of my review, and added a few additional thoughts and pertinent references. Neither group of authors has seen my commentary, and so I am responsible for any omissions or lapses in interpretation.  The protocol developed by Stephens seems to me a potentially valuable exploratory tool in describing patterns of co-occurrence, but I note several potential problems in identifying interactions usingsolely  this protocol.  I also gently disagree with Peterson et al., who state flatly that co-occurrence data can shed no light at all on interspecific interactions.  I suggest there are a number of counter-examples to this claim in the literature.  I argue that spatiotemporal data, when available, iprovide a much more powerful tool for discerning interactions, than do staticspatial data.  Finally, I use a simple thought experiment to point out that biotic drivers could be playing a key  causal role in limitnig distributions, even in equisitlvely accurate SDMs that use only abiotic (scenopoetic) data as input data.
关于从空间数据推断生态相互作用的挑战的一些思考。
Luis Escobar博士要求我对Stephens等人(2019年,本期)和Peterson等人(2019年,本期)提交的论文进行联合审查。我整理了一些想法,但当我把它们发给他时,他已经收到了其他评论,并做出了编辑决定。他觉得我的观点可能值得作为评论与这两篇文章一起发表。我的评论是原始的提交,现在出现了一些小的,主要是外观上的改变。我只是稍微编辑了一下我的评论,并添加了一些额外的想法和相关的参考文献。两组作者都没有看到我的评论,所以我要对任何解释上的遗漏或失误负责。Stephens开发的协议在我看来是描述共现模式的潜在有价值的探索性工具,但我注意到在单独使用该协议识别交互时存在几个潜在问题。我也稍微不同意Peterson等人的观点,他们直截了当地说,共现数据根本不能说明种间的相互作用。我认为在文献中有许多反例来反驳这一说法。我认为,与静态空间数据相比,时空数据在可用的情况下为识别交互提供了更强大的工具。最后,我用一个简单的思想实验来指出,生物驱动因素可能在限制分布中起着关键的因果作用,即使在只使用非生物(场景)数据作为输入数据的相当精确的sdm中也是如此。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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