arXiv subjects

Pradeep Pillai

Publications and source records attributed to Pradeep Pillai.

8 recordsLinked to original sources

arXiv2025

Pseudo-biodiversity effects across scales

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.

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arXiv2025

Time-structured models of population growth in fluctuating environments

1. Although environmental variability is expected to play a more prominent role under climate change, current demographic models that ignore the differential environmental histories of cohorts across generations are unlikely to accurately predict population dynamics and growth. The use of these approaches, which we collectively refer to as non time-structured models or nTSMs, will instead yield error-prone estimates by giving rise to a form of ecological memory loss due to their inability to account for the historical effects of past environmental exposure on subsequent growth rates. 2. To address this important issue, we introduce a new class of time-structured models or TSMs that accurately depict growth under variable environments by splitting seemingly homogeneous populations into distinct demographic cohorts based on their past exposure to environmental fluctuations. By accounting for this cryptic population structure, TSMs accurately simulate the historical effects of environmental variability, even when individuals exhibit different degrees of phenotypic plasticity. 3. Here, we provide a conceptual framework, the mathematical tools needed to simulate any TSM, and a closed form solution for simple exponential growth. We then show that traditional nTSMs yield large errors compared to TSMs when estimating population dynamics under fluctuating temperatures. Overall, TSMs represent a critical tool for predicting population growth in a variable world.

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arXiv2019

Not even wrong: Reply to Loreau and Hector

The Loreau and Hector (2019) Comment on our paper (Pillai and Gouhier, 2019) failed to address the two core elements of our critique, both the circularity of the BEF research program, in general, and the mathematical flaws of the Loreau-Hector partitioning scheme, in particular. Loreau and Hector avoided dealing with the first part of our critique by arguing against a non-existent claim that all biodiversity effects could be reduced to coexistence, while the mathematical flaws in the Loreau-Hector partitioning method that we described in the second part of our critique were ignored altogether. Here, we address these misconceptions and demonstrate that all of the claims that were made in our original paper hold. We conclude that (i) BEF studies need to adopt baselines that account for coexistence in order to avoid overestimating the effects of biodiversity and (ii) the LH partitioning method should not be used unless the linearity of the abundance-ecosystem functioning relationship in monocultures can be verified for all species.

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arXiv2019

Not even wrong: Reply to Wagg et al

We demonstrate that the issues described in the Wagg et al. (2019) Comment on our paper (Pillai and Gouhier, 2019) are all due to misunderstandings about the implications of pairwise effects, the nature of the null baseline in both our framework and in the Loreau-Hector (LH) partitioning scheme (i.e., the midpoint of the monocultures), and the impact of nonlinearity on the LH partitioning results. Specifically, we show that (i) pairwise effects can be computed over any time horizon and thus do not imply stable coexistence, (ii) the midpoint of the monocultures corresponds to a neutral community so coexistence was always part of the LH baseline, and (iii) contrary to what Wagg et al. suggested, generalized diversity-interaction models do not account for (and may in fact exacerbate) the problem of nonlinearity in monocultures, which inflates the LH net biodiversity effect and generates incorrect estimates of selection and complementarity. Hence, all of our original claims about the triviality inherent in biodiversity-ecosystem functioning research and the issues with the LH partitioning scheme hold.

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arXiv2019

No evidence of fish biodiversity effects on coral reef ecosystem functioning across scales

We demonstrate that the conclusions drawn by Lefcheck et al. (2019) regarding the positive effects of fish diversity on coral reef ecosystem functioning across scales are flawed because of a series of conceptual and statistical issues that include spurious correlations, the conflation of population size and species diversity effects and a failure to recognize that observing a biodiversity effect at multiple sites is not equivalent to observing it at multiple scales.

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arXiv2019

Trivial pursuits

We demonstrate that the conclusions drawn by Bernhard et al. (2018) regarding the ability of nonlinear averaging to accurately predict organismal performance under fluctuating temperatures are flawed because of a series of experimental and statistical issues that include the presence of a hidden treatment effect, the use of a single low frequency temperature fluctuation that could easily be tracked by the fast growing organism, and the decision to quantify performance via population growth rate, a metric that can mask significant variation in population size.

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arXiv2018

On the use and abuse of Price equation concepts in ecology

In biodiversity and ecosystem functioning (BEF) research, the Loreau-Hector (LH) statistical scheme is widely-used to partition the effect of biodiversity on ecosystem properties into a "complementarity effect" and a "selection effect". This selection effect was originally considered analogous to the selection term in the Price equation from evolutionary biology. However, a key paper published over thirteen years ago challenged this interpretation by devising a new tripartite partitioning scheme that purportedly quantified the role of selection in biodiversity experiments more accurately. This tripartite method, as well as its recent spatiotemporal extension, were both developed as an attempt to apply the Price equation in a BEF context. Here, we demonstrate that the derivation of this tripartite method, as well as its spatiotemporal extension, involve a set of incoherent and nonsensical mathematical arguments driven largely by naïve visual analogies with the original Price equation, that result in neither partitioning scheme quantifying any real property in the natural world. Furthermore, we show that Loreau and Hector's original selection effect always represented a true analog of the original Price selection term, making the tripartite partitioning scheme a nonsensical solution to a non-existent problem [...]

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arXiv2018

Not even wrong: The spurious link between biodiversity and ecosystem functioning

Resolving the relationship between biodiversity and ecosystem functioning has been one of the central goals of modern ecology. Early debates about the relationship were finally resolved with the advent of a statistical partitioning scheme that decomposed the biodiversity effect into a "selection" effect and a "complementarity" effect. We prove that both the biodiversity effect and its statistical decomposition into selection and complementarity are fundamentally flawed because these methods use a naïve null expectation based on neutrality, likely leading to an overestimate of the net biodiversity effect, and they fail to account for the nonlinear abundance-ecosystem functioning relationships observed in nature. Furthermore, under such nonlinearity no statistical scheme can be devised to partition the biodiversity effects. We also present an alternative metric providing a more reasonable estimate of biodiversity effect. Our results suggest that all studies conducted since the early 1990s likely overestimated the positive effects of biodiversity on ecosystem functioning.

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