Eco-Evolutionary Community Dynamics: Covariation between Diversity and Invasibility across Temperature Gradients

Abstract

Understanding biodiversity gradients is a long-standing challenge, and progress requires theory unifying ecology and evolution. Here, we unify concepts related to the speed of evolution, the influence of species richness on diversification, and niche-based coexistence. We focus on the dynamics, through evolutionary time, of community invasibility and species richness across a broad thermal gradient. In our framework, the evolution of body size influences the ecological structure and dynamics of a trophic network, and organismal metabolism ties temperature to eco-evolutionary processes. The framework distinguishes ecological invasibility (governed by ecological interactions) from evolutionary invasibility (governed by local ecology and constraints imposed by small phenotypic effects of mutation). The model yields four primary predictions: (1) ecological invasibility declines through time and with increasing temperature; (2) average evolutionary invasibility across communities increases and then decreases through time as the richness-temperature gradient flattens; (3) in the early stages of diversification, richness and evolutionary invasibility both increase with increasing temperature; and (4) at equilibrium, richness does not vary with temperature, yet evolutionary invasibility decreases with increasing temperature. These predictions emerge from the "evolutionary-speed" hypothesis, which attempts to account for latitudinal species richness gradients by invoking faster biological rates in warmer, tropical regions. The model contrasts with predictions from other richness-gradient hypotheses, such as "niche conservatism" and "species energy." Empirically testing our model's predictions should help distinguish among these hypotheses.

The Biogeography of Adaptive Radiations and the Geographic Overlap of Sister Species

“…For example, several studies have investigated the drivers of richness patterns between regions (Goldberg et al 2005;Roy and Goldberg 2007;Yoder and Nuismer 2010). Others have studied community assembly along environmental gradients (McPeek 2008;Stegen et al 2009Stegen et al , 2012aStegen et al , 2012b, and Birand et al (2012) examined speciation, extinction, and range sizes. Similar to these studies, we simulate assembly processes such as competition and coevolution of multiple species (see also Nuismer et al 2010) and analyze the emergent biogeographical patterns.…”

From Metabolic Constraints on Individuals to the Dynamics of Ecosystems

“…We propose Eqn (17) as a general model because different specifications of its parameters yield particular models, including LotkaeVolterra (for g($) ¼ r max x i and f($) ¼ 1) (May 1974;Pawar, 2009;Tang et al, 2014), RosenzweigeMacArthur (g($) ¼ r max x i , a ii ¼ 0 and f($) ¼ Type II functional response) (Yodzis and Innes, 1992;Weitz and Levin, 2006;Pawar et al, 2012), the recent family of "bio-energetic" models (f($) ¼ multispecies functional response) (Brose et al, 2006b;Otto et al, 2007) or Monod-like (g($) ¼ dilution rate-dependent substrate flux, a ii ¼ 0 and f($) ¼ saturating uptake function) (Tilman, 1977). We propose Eqn (17) as a general model because different specifications of its parameters yield particular models, including LotkaeVolterra (for g($) ¼ r max x i and f($) ¼ 1) (May 1974;Pawar, 2009;Tang et al, 2014), RosenzweigeMacArthur (g($) ¼ r max x i , a ii ¼ 0 and f($) ¼ Type II functional response) (Yodzis and Innes, 1992;Weitz and Levin, 2006;Pawar et al, 2012), the recent family of "bio-energetic" models (f($) ¼ multispecies functional response) (Brose et al, 2006b;Otto et al, 2007) or Monod-like (g($) ¼ dilution rate-dependent substrate flux, a ii ¼ 0 and f($) ¼ saturating uptake function) (Tilman, 1977).…”

“…For example, recent simulations using such models have posited that observed body sizes in communities allow stable coexistence of consumers and resources within local communities without any necessary optimization of consumption rates (Jonsson and Ebenman, 1998;Emmerson et al, 2005;Brose et al, 2006b;Otto et al, 2007;Tang et al, 2014). For example, recent simulations using such models have posited that observed body sizes in communities allow stable coexistence of consumers and resources within local communities without any necessary optimization of consumption rates (Jonsson and Ebenman, 1998;Emmerson et al, 2005;Brose et al, 2006b;Otto et al, 2007;Tang et al, 2014).…”

“…This new surge of research has led to the publication of key conceptual syntheses that on one front have advanced thermal biology and adaptation (Huey and Berrigan, 2001;Angilletta, 2009;Kingsolver, 2009;Dell et al, 2011;Schulte et al, 2011;Pörtner et al, 2012), and on another have The study of coupled ecological and evolutionary dynamics is inherently hierarchical, each level (individuals, interactions, and interaction networks) comprising a system with distinct measurable dynamics. This paper was ahead of its time, and little subsequent work was done until about 10 years ago, when a rapidly growing number of studies focused on the metabolic and biomechanical basis of consumereresource interactions (Vasseur and McCann, 2005;McGill and Mittelbach, 2006;Weitz and Levin, 2006;Vucic-Pestic et al, 2010;O'Connor et al, 2011;DeLong and Vasseur, 2012;Pawar et al, 2012;Rall et al, 2012;Kalinkat et al, 2013;Dell et al, 2014) as well as community-level (food-web) dynamics (Jonsson and Ebenman, 1998;Emmerson and Raffaelli, 2004;Loeuille and Loreau, 2005;Brose et al, 2006b;Otto et al, 2007;Cohen, 2008;O'Connor et al, 2009;Petchey et al, 2010;Stegen et al, 2012a;Tang et al, 2014). The bidirectional arrows connecting levels indicate that ecological (e.g., changes in abundance) and evolutionary (e.g., changes in trait distributions) feedback from one level can influence the system structure and dynamics in another.…”

Estimating partial regulation in spatiotemporal models of community dynamics

“…Inferring pairwise interactions remains one of the primary research goals in theoretical and applied ecology. However, species interactions are difficult to measure because the strength and sign of pairwise interactions depend on many circumstances, including (but not limited to) the presence of additional species (Hixon and Carr 1997), environmental conditions (Morris 2003), and recent evolutionary history (Stegen et al 2012). Manipulative experiments in micro-and mesocosms remain the goldstandard for inferring species interactions, but an increase in the number of species results in a factorial increase in the number of experimental treatments that must be conducted (Wootton and Emmerson 2005).…”