{"title":"关于从空间数据推断生态相互作用的挑战的一些思考。","authors":"R. Holt","doi":"10.17161/bi.v15i1.13302","DOIUrl":null,"url":null,"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.","PeriodicalId":269455,"journal":{"name":"Biodiversity Informatics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Some thoughts about the challenge of inferring ecological interactions from spatial data.\",\"authors\":\"R. Holt\",\"doi\":\"10.17161/bi.v15i1.13302\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":269455,\"journal\":{\"name\":\"Biodiversity Informatics\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biodiversity Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17161/bi.v15i1.13302\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biodiversity Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17161/bi.v15i1.13302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
摘要
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。
Some thoughts about the challenge of inferring ecological interactions from spatial data.
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.