Pseudo-biodiversity effects across scales

TL;DR

This paper discusses the challenges in accurately measuring biodiversity effects across different scales, highlighting pseudo-effects that can mislead interpretations and emphasizing the need for proper controls.

Contribution

It identifies and explains three types of pseudo-biodiversity effects that can distort scale-dependent biodiversity studies and proposes methods to control for these artifacts.

Findings

Identification of Population-level, Independence, and Arithmetic effects

Demonstration of how these effects can confound biodiversity measurements

Emphasis on controlling artifacts for accurate scale-dependent biodiversity analysis

Abstract

Over the last decade several attempts have been made to extend biodiversity studies in ways that would allow researchers to explore how biodiversity-ecosystem functioning relationships may change across different spatial and temporal scales. Unfortunately, the studies based on these attempts often overlooked the serious issues that can arise when quantifying biodiversity effects at larger scales, specifically the fact that biodiversity effects measured across space and time can contain trivial effects that are unrelated to the role of biodiversity per se -- or even effects that are non-biological in nature due to being simple artefacts of how properties and entities are counted and quantified. Here we outline and describe three such pseudo-biodiversity effects: Population-level effects, Independence effects, and Arithmetic effects. Population-level effects are those related to temporal changes due to individual species population growth or development, and are thus independent of biodiversity. Independence and Arithmetic effects (which we explore here primarily in a spatial context) arise either as a simple consequence of the fact that not all species are present everywhere -- i.e., species turnover is inevitable at greater spatial scales (Independence effects); or they arise when the purported biodiversity effects measured are a simple byproduct of how mathematical functions behave (Arithmetic effects). Our study demonstrates the necessity of controlling for these trivial artefactual effects if one wishes to meaningfully measure how true biodiversity effects change across spatial and temporal scales.