An Expanded Modern Coexistence Theory for Empirical Applications

Understanding long‐term coexistence of numerous competing species is a longstanding challenge in ecology. Progress requires determining which processes and species differences are most important for coexistence when multiple processes operate and species differ in many ways. Modern coexistence theory (MCT), formalized by Chesson, holds out the promise of doing that, but empirical applications remain scarce. We argue that MCT\u27s mathematical complexity and subtlety have obscured the simplicity and power of its underlying ideas and hindered applications. We present a general computational approach that extends our previous solution for the storage effect to all of standard MCT\u27s spatial and temporal coexistence mechanisms, and also process‐defined mechanisms amenable to direct study such as resource partitioning, indirect competition, and life history trade‐offs. The main components are a method to partition population growth rates into contributions from different mechanisms and their interactions, and numerical calculations in which some mechanisms are removed and others retained. We illustrate how our approach handles features that have not been analyzed in the standard framework through several case studies: competing diatom species under fluctuating temperature, plant–soil feedbacks in grasslands, facilitation in a beach grass community, and niche differences with independent effects on recruitment, survival and growth in sagebrush steppe

Inequitable walking conditions among older people: examining the interrelationship of neighbourhood socio-economic status and urban form using a comparative case study

<p>Abstract</p> <p>Background</p> <p>Supportive neighbourhood walking conditions are particularly important for older people as they age and who, as a group, prefer walking as a form of physical activity. Urban form and socio-economic status (SES) can influence neighbourhood walking behaviour. The objectives of this study were: a) to examine how urban form and neighbourhood SES inter-relate to affect the experiences of older people who walk in their neighbourhoods; b) to examine differences among neighbourhood stakeholder key informant perspectives on socio-political processes that shape the walkability of neighbourhood environments.</p> <p>Methods</p> <p>An embedded comparative case study examined differences among four Ottawa neighbourhoods that were purposefully selected to provide contrasts on urban form (inner-urban versus suburban) and SES (higher versus lower). Qualitative data collected from 75 older walkers and 19 neighbourhood key informants, as well as quantitative indicators were compared on the two axes of urban form and SES among the four neighbourhoods.</p> <p>Results and discussion</p> <p>Examining the inter-relationship of neighbourhood SES and urban form characteristics on older people's walking experiences indicated that urban form differences were accentuated positively in higher SES neighbourhoods and negatively in lower SES neighbourhoods. Older people in lower SES neighbourhoods were more affected by traffic hazards and more reliant on public transit compared to their higher SES counterparts. In higher SES neighbourhoods the disadvantages of traffic in the inner-urban neighbourhood and lack of commercial destinations in the suburban neighbourhood were partially offset by other factors including neighbourhood aesthetics. Key informant descriptions of the socio-political process highlighted how lower SES neighbourhoods may face greater challenges in creating walkable places. These differences pertained to the size of neighbourhood associations, relationships with political representatives, accessing information and salient neighbourhood association issues. Findings provide evidence of inequitable walking environments.</p> <p>Conclusion</p> <p>Future research on walking must consider urban form-SES inter-relationships and further examine the equitable distribution of walking conditions as well as the socio-political processes driving these conditions. There is a need for municipal governments to monitor differences in walking conditions among higher and lower SES neighbourhoods, to be receptive to the needs of lower SES neighbourhood and to ensure that policy decisions are taken to address inequitable walking conditions.</p

Parameterizing state–space models for infectious disease dynamics by generalized profiling: measles in Ontario

Parameter estimation for infectious disease models is important for basic understanding (e.g. to identify major transmission pathways), for forecasting emerging epidemics, and for designing control measures. Differential equation models are often used, but statistical inference for differential equations suffers from numerical challenges and poor agreement between observational data and deterministic models. Accounting for these departures via stochastic model terms requires full specification of the probabilistic dynamics, and computationally demanding estimation methods. Here, we demonstrate the utility of an alternative approach, generalized profiling, which provides robustness to violations of a deterministic model without needing to specify a complete probabilistic model. We introduce novel means for estimating the robustness parameters and for statistical inference in this framework. The methods are applied to a model for pre-vaccination measles incidence in Ontario, and we demonstrate the statistical validity of our inference through extensive simulation. The results confirm that school term versus summer drives seasonality of transmission, but we find no effects of short school breaks and the estimated basic reproductive ratio ℛ0 greatly exceeds previous estimates. The approach applies naturally to any system for which candidate differential equations are available, and avoids many challenges that have limited Monte Carlo inference for state–space models

Weak Interspecific Interactions in a Sagebrush Steppe? Conflicting Evidence from Observations and Experiments

Stable coexistence requires intraspecific limitations to be stronger than interspecific limitations. The greater the difference between intra‐ and interspecific limitations, the more stable the coexistence, and the weaker the competitive release any species should experience following removal of competitors. We conducted a removal experiment to test whether a previously estimated model, showing surprisingly weak interspecific competition for four dominant species in a sagebrush steppe, accurately predicts competitive release. Our treatments were (1) removal of all perennial grasses and (2) removal of the dominant shrub, Artemisia tripartita. We regressed survival, growth, and recruitment on the locations, sizes, and species identities of neighboring plants, along with an indicator variable for removal treatment. If our “baseline” regression model, which accounts for local plant–plant interactions, accurately explains the observed responses to removals, then the removal coefficient should be non‐significant. For survival, the removal coefficients were never significantly different from zero, and only A. tripartita showed a (negative) response to removals at the recruitment stage. For growth, the removal treatment effect was significant and positive for two species, Poa secunda and Pseudoroegneria spicata, indicating that the baseline model underestimated interspecific competition. For all three grass species, population models based on the vital rate regressions that included removal effects projected 1.4‐ to 3‐fold increases in equilibrium population size relative to the baseline model (no removal effects). However, we found no evidence of higher response to removal in quadrats with higher pretreatment cover of A. tripartita, or by plants experiencing higher pre‐treatment crowding by A. tripartita, raising questions about the mechanisms driving the positive response to removal. While our results show the value of combining observations with a simple removal experiment, more tightly controlled experiments focused on underlying mechanisms may be required to conclusively validate or reject predictions from phenomenological models

Data and R code

The zip archive contains the data and R code used to conduct the analyses reported in the publication. Readme files in the subdirectories contain metadata and instructions for running the code. Note that changing the directory structure will cause the R scripts to fail