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A visual technique used by citizen scientists shows higher herbivory in understory vs. canopy leaves of a tropical forest
Ecology ( IF 4.8 ) Pub Date : 2021-09-28 , DOI: 10.1002/ecy.3539 Christopher J Frost 1
Ecology ( IF 4.8 ) Pub Date : 2021-09-28 , DOI: 10.1002/ecy.3539 Christopher J Frost 1
Affiliation
Citizen science (CS) initiatives can transform how some ecological data are collected. Herbivory is a fundamental ecological interaction, but herbivory rates in many natural systems are unknown due in part to lack of personnel for monitoring efforts. This limits our ability to understand broad ecological patterns relevant to herbivory. Fortunately, accurate and reliable visual estimation techniques for assessing herbivory could be amenable to CS approaches. In 2008, I developed a CS training initiative (the Million Leaf Project, MLP) to measure herbivory based on a seven-category visual assessment of leaf area removed (LAR). From 2010 to 2018, 394 citizen scientists assessed damage on 175,421 leaves to test the hypothesis that herbivory varies between understory and canopy leaves in a Peruvian tropical forest. In support of this hypothesis, the longitudinal CS data reveal that understory leaves consistently experience more herbivory than do canopy leaves on average (18.3% vs. 12.3%, P < 0.001), a difference that was consistent regardless of CS observer age. Furthermore, data integrity was high, even though younger participants showed some leaf selection bias. The MLP is based on a simple technique, intended to broaden public participation in ecological science, and applicable to any ecological system in which herbivory or leaf damage occurs.
中文翻译:
公民科学家使用的一种视觉技术显示,在热带森林的林下与树冠叶相比,草食性更高
公民科学 (CS) 计划可以改变一些生态数据的收集方式。食草是一种基本的生态相互作用,但许多自然系统中的食草率是未知的,部分原因是缺乏监测工作的人员。这限制了我们理解与食草动物相关的广泛生态模式的能力。幸运的是,用于评估食草动物的准确可靠的视觉估计技术可能适用于 CS 方法。2008 年,我开发了一项 CS 培训计划(百万叶项目,MLP),以根据去除的叶面积 (LAR) 的七类视觉评估来测量食草动物。从 2010 年到 2018 年,394 名公民科学家评估了 175,421 片树叶的损坏情况,以检验秘鲁热带森林中草食性在林下和树冠叶之间存在差异的假设。为了支持这个假设,P < 0.001),无论 CS 观察者年龄如何,这种差异都是一致的。此外,即使年轻的参与者表现出一些叶子选择偏差,数据完整性也很高。MLP 基于一种简单的技术,旨在扩大公众对生态科学的参与,适用于任何发生食草或叶片损害的生态系统。
更新日期:2021-09-28
中文翻译:
公民科学家使用的一种视觉技术显示,在热带森林的林下与树冠叶相比,草食性更高
公民科学 (CS) 计划可以改变一些生态数据的收集方式。食草是一种基本的生态相互作用,但许多自然系统中的食草率是未知的,部分原因是缺乏监测工作的人员。这限制了我们理解与食草动物相关的广泛生态模式的能力。幸运的是,用于评估食草动物的准确可靠的视觉估计技术可能适用于 CS 方法。2008 年,我开发了一项 CS 培训计划(百万叶项目,MLP),以根据去除的叶面积 (LAR) 的七类视觉评估来测量食草动物。从 2010 年到 2018 年,394 名公民科学家评估了 175,421 片树叶的损坏情况,以检验秘鲁热带森林中草食性在林下和树冠叶之间存在差异的假设。为了支持这个假设,P < 0.001),无论 CS 观察者年龄如何,这种差异都是一致的。此外,即使年轻的参与者表现出一些叶子选择偏差,数据完整性也很高。MLP 基于一种简单的技术,旨在扩大公众对生态科学的参与,适用于任何发生食草或叶片损害的生态系统。