The classical answer to the question of how competing species coexist in nature is that species coexist "stably" (i.e. each can invade an equilibrium population of the other from low abundance) by differing from each other in some way that lessens lessens their competitive influence on each other compared to their influence on themselves . The classical "niche theory" arising from these ideas also suggests that, among a set of coexisting competing species, not only must there be differences between species, but these differences must be large enough if stable coexistence is to occur--i.e. there are "limits to similarity”.
However, there is an important additional consideration that is essential to the concept of niche differences--robustness. Most competition models can actually produce stable coexistence of arbitrarily similar species if parameters are tuned. When we consider that environments may vary, or that parameters may not be tuned, we again see the need for species differences.
In past work, the Ostling lab further developed tools for calculating robustness or conversely “sensitivity” of coexistence, to generalize this idea and show the importance of differences in interaction with regulating factors for stable and robust coexistence.
We have also shown that "tight-packing" solutions to competition models, where arbitrarily similar species coexist, are not robust so long as the models are formulated so they are absent of unrealistic discontinuities.
Figure 3 from Ostling (2012) Plant Ecology (pdf) showing that large-scale spatial synchrony in taxa abundances observed over the Holocene in S. Ontario can result from fat-tailed dispersal in a neutral model, where prior work (Clark and MacLachlan 2003) had suggested this pattern allowed one to reject neutral theory.
In the past decades, ecologists have put renewed focus into an alternative to the classical "niche theory" answer to how species coexist: species similarities equalizing fitness in a given environment. The "neutral" theory of ecology is aimed at describing the structure of such non-stable, purely fitness-equalized, communities, in which community structure is shaped by stochastic events--birth, death, and immigration or dispersal.
Neutral theory has the potential to serve as a quantitative process-based null model for the detection of niche differentiation and other deterministic forces, similar to the role of a similar neutral theory in evolutionary biology as a null model for detecting selection.
However, it has not yet lived up to this potential. When the neutral model fails, it may be only because it simplifies demographic complexity unrelated to niches, such as the existence of long-distance dispersal, size structured demographic rates, or variation among species along tradeoffs that only equalize fitness in the environment (rather than allowing mutual invasion).
In the Ostling lab, we are carrying out theory development to figure out how to construct more informative tests of neutral theory, and beginning to carry out those tests. This includes: a) identifying what aspects of the complexity influencing dispersal and demographic stochasticity matter for neutral model predictions, and b) ground-truthing approaches to testing neutral theory in which additional complexities that must be incorporated are informed by data. We also employ these approached on data to better uncover the signature of niche differences.
Figure 2 of D'Andrea et al. 2020 (DOI: 10.1002/ecy.3019) showing a pattern of multiple clusters in the pattern of tree species abundances on functional trait axes for the 50-ha plot on Barro Colorado Island in Panama. This pattern arises in stochastic niche models.
The focus on neutral theory in recent decades has highlighted the potential role of stochastic forces that classical competition theory ignores: immigration and demographic stochasticity. Models studied in classical competition theory are of deterministic “closed” communities, i.e. communities where no individuals come from outside. What influence might niche differentiation have on community structure when acting in combination with these ever-present forces? Also, when chance events are factored in, will niche differentiation generally increase the number of species in a community relative to assembly through chance alone? How does it affect the distribution persistence times across species?
In work funded by the NSF Advancing Theory in Biology program, the Ostling lab has been working to consider the combined effects of stochastic events and niche differentiation, in “stochastic niche models”. We use high-throughput computation to analyze these models across a range of parameter values. Our focus has been on the influence of niche differentiation on trait-abundance patterns and species abundance distributions (SADs), and on the degree to which niche differences maintain more biodiversity than in neutral communities. We have found empirical support (see Figure) for the trait-abundance patterns involving multiple species clusters produced in stochastic niche models
We are currently learning approaches from Data Science/Machine Learning to create improved methodology to detect such clustering, as well as the associated patterning that may occur in phylogenetic data. This work is funded by a current NSF Mid-Career Advancement Grant from the NSF.
Much of the theory developed in the Ostling lab is broadly applicable across communities of many different types of organisms. However, broad theory can only take us so far in determining what the dynamics of coexistence in nature really are. Fully convincing evidence of niche differences requires developing and testing system-specific niche theory.
Plant species coexistence has always been a fascinating puzzle in ecology because coexisting plant species seem to all require the same limiting resources—light, water, nutrients. Tree species coexistence is particular important given the role of forests in the global carbon cycle. Forests are also a data-rich system due to the Forest GEO global network of forest census sites all using the same sampling protocol.
Particularly dominant hypotheses of coexistence of tropical tree species are: 1) successional niche differentiation, i.e. variation across species in strategy ranging from gap-specialization to shade-tolerance; and 2) differences in enemies and the tendency for more abundant species to be easier for enemies to find, i.e. the Janzen-Connell mechanism. Though there is evidence pointing to each, it is far from clear how big of a role they play. How much does each increase diversity compared with a neutral model? Or could these mechanisms actually lessen expected richness, as work from my lab on stochastic niche models mentioned above suggests can happen? To answer these questions, we need a deeper understanding of these mechanisms, and better tools to quantify their role using forest census data.
The Ostling lab is currently studying partial-differential equation models capturing the size-structured and patch-age structured nature of competition among tree species, to gain a more fundamental understanding of successional niche differentiation. We are also studying Janzen-Connell mechanisms and the patterns they produce, and collaborating with Brian Sedio's lab at UT Austin to use new chemical defense data they are amassing for the Forest GEO plots to quantify the role that differences in enemies and other mechamisms may play in the latitudinal diversity gradient in forests. That work is funded by a current NSF grant from the Division of Environmental Biology.
Another recent interest of the lab is the potential for coexistence through intransitive loop interactions, e.g. where pairwise interactions alone would involve species A outcompeting B, B outcompeting C, and C outcompeting A, but where when all species are together they can coexist. We have been obtaining a deeper understanding of the conditions for this coexistence to arise.
The lab is broadly interested in theoretical ecology, and has also been working with collaborators to study topics such as the impact of intraspecific variation on coexistence, the role of large scale diversity ecosystem function using metacommunity models, food web structure, and bleaching on coral reefs.