Resolving the biodiversity paradox

Abstract

The paradox of biodiversity involves three elements, (i) mathematical models predict that species must differ in specific ways in order to coexist as stable ecological communities, (ii) such differences are difficult to identify, yet (iii) there is widespread evidence of stability in natural communities. Debate has centred on two views. The first explanation involves tradeoffs along a small number of axes, including 'colonization-competition', resource competition (light, water, nitrogen for plants, including the 'successional niche'), and life history (e.g. high-light growth vs. low-light survival and few large vs. many small seeds). The second view is neutrality, which assumes that species differences do not contribute to dynamics. Clark et al. (2004) presented a third explanation, that coexistence is inherently high dimensional, but still depends on species differences. We demonstrate that neither traditional low-dimensional tradeoffs nor neutrality can resolve the biodiversity paradox, in part by showing that they do not properly interpret stochasticity in statistical and in theoretical models. Unless sample sizes are small, traditional data modelling assures that species will appear different in a few dimensions, but those differences will rarely predict coexistence when parameter estimates are plugged into theoretical models. Contrary to standard interpretations, neutral models do not imply functional equivalence, but rather subsume species differences in stochastic terms. New hierarchical modelling techniques for inference reveal high-dimensional differences among species that can be quantified with random individual and temporal effects (RITES), i.e. process-level variation that results from many causes. We show that this variation is large, and that it stands in for species differences along unobserved dimensions that do contribute to diversity. High dimensional coexistence contrasts with the classical notions of tradeoffs along a few axes, which are often not found in data, and with 'neutral models', which mask, rather than eliminate, tradeoffs in stochastic terms. This mechanism can explain coexistence of species that would not occur with simple, low-dimensional tradeoff scenarios.

Successional dynamics in Neotropical forests are as uncertain as they are predictable

“…Such a dual perception of ecological processes hampers a synthetic understanding of community reassembly in regenerating forests (6). Indeed, in complex adaptive systems, erratic patterns can arise from either stochastic processes that emerge from seemingly random fluctuations, or from unexplained but causal variability emerging from "unknown unknowns" (33). Thus, despite the high levels of ecological noise observed here, what we typically view as stochasticity may ultimately be explained by deterministic factors that have not been measured or incorporated.…”

Combined niche and neutral effects in a microbial wastewater treatment community

“…The call for a reconciliation of niche and neutral models (25,26) of community assembly has, until now, been met by adapting what were deterministic niche-based models to include stochasticity and immigration (27)(28)(29). We have argued in the introduction to this paper that the emergent parameter-rich models defy calibration for very diverse microbial communities.…”

“…The initial polarization of "nichists" and "neutralists" caused by Hubbell's (9) monograph has waned and recognition that neutral models embody mechanisms (birth, death, immigration, and sometimes speciation) that are indisputable features of virtually all biological systems (24) has led to calls for, what some call, "reconciliation" (25,26). To this end, a variety of niche models have been extended to include some stochastic elements (27)(28)(29).…”

Plant functional traits and the multidimensional nature of species coexistence

“…For example, fitness and stabilizing niche differences could be correlated with distinct sets of traits (17). Moreover, it may be that niche and fitness differences are best described by multivariate suites of traits, supporting a hypothesis of high-dimensional coexistence between species in communities (18)(19)(20)(21).…”