Quantifying the Impact of Gene Flow on Phenotype-Environment Mismatch: A Demonstration with the Scarlet Monkeyflower Mimulus cardinalis

Geographic range margins offer testing grounds for limits to adaptation. If range limits are concordant with niche limits, range expansions require the evolution of new phenotypes that can maintain populations beyond current range margins. However, many species\u27 range margins appear static over time, suggesting limits on the ability of marginal populations to evolve appropriate phenotypes. A potential explanation is the swamping gene flow hypothesis, which posits that asymmetrical gene flow from large, well-adapted central populations prevents marginal populations from locally adapting. We present an empirical framework for combining gene flow, environment, and fitness-related phenotypes to infer the potential for maladaptation, and we demonstrate its application using the scarlet monkeyflower Mimulus cardinalis. We grew individuals sampled from populations on a latitudinal transect under varied temperatures and determined the phenotypic deviation (PD), the mismatch between phenotype and local environment. We inferred gene flow among populations and predicted that populations receiving the most temperature- or latitude-weighted immigration would show the greatest PD and that these populations were likely marginal. We found asymmetrical gene flow from central to marginal populations. Populations with more latitude-weighted immigration had significantly greater PD but were not necessarily marginal. Gene flow may limit local adaptation in this species, but swamping gene flow is unlikely to explain its northern range limit

The case for the continued use of the genus name Mimulus for all monkeyflowers

The genus Mimulus is a well-studied group of plant species, which has for decades allowed researchers to address a wide array of fundamental questions in biology (Wu & al. 2008; Twyford & al. 2015). Linnaeus named the type species of Mimulus (ringens L.), while Darwin (1876) used Mimulus (luteus L.) to answer key research questions. The incredible phenotypic diversity of this group has made it the focus of ecological and evolutionary study since the mid-20th century, initiated by the influential work of Clausen, Keck, and Hiesey as well as their students and collaborators (Clausen & Hiesey 1958; Hiesey & al. 1971, Vickery 1952, 1978). Research has continued on this group of diverse taxa throughout the 20th and into the 21st century (Bradshaw & al. 1995; Schemske & Bradshaw 1999; Wu & al. 2008; Twyford & al. 2015; Yuan 2019), and Mimulus guttatus was one of the first non-model plants to be selected for full genome sequencing (Hellsten & al. 2013). Mimulus has played a key role in advancing our general understanding of the evolution of pollinator shifts (Bradshaw & Schemske 2003; Cooley & al. 2011; Byers & al. 2014), adaptation (Lowry & Willis 2010; Kooyers & al. 2015; Peterson & al. 2016; Ferris & Willis 2018; Troth & al. 2018), speciation (Ramsey & al. 2003; Wright & al. 2013; Sobel & Streisfeld 2015; Zuellig & Sweigart 2018), meiotic drive (Fishman & Saunders 2008), polyploidy (Vallejo-Marín 2012; Vallejo-Marín & al. 2015), range limits (Angert 2009; Sexton et al. 2011; Grossenbacher & al. 2014; Sheth & Angert 2014), circadian rhythms (Greenham & al. 2017), genetic recombination (Hellsten & al. 2013), mating systems (Fenster & Ritland 1994; Dudash & Carr 1998; Brandvain & al. 2014) and developmental biology (Moody & al. 1999; Baker & al. 2011, 2012; Yuan 2019). This combination of a rich history of study coupled with sustained modern research activity is unparalleled among angiosperms. Across many interested parties, the name Mimulus therefore takes on tremendous biological significance and is recognizable not only by botanists, but also by zoologists, horticulturalists, naturalists, and members of the biomedical community. Names associated with a taxonomic group of this prominence should have substantial inertia, and disruptive name changes should be avoided. As members of the Mimulus community, we advocate retaining the genus name Mimulus to describe all monkeyflowers. This is despite recent nomenclature changes that have led to a renaming of most monkeyflower species to other genera.Additional co-authors: Jannice Friedman, Dena L Grossenbacher, Liza M Holeski, Christopher T Ivey, Kathleen M Kay, Vanessa A Koelling, Nicholas J Kooyers, Courtney J Murren, Christopher D Muir, Thomas C Nelson, Megan L Peterson, Joshua R Puzey, Michael C Rotter, Jeffrey R Seemann, Jason P Sexton, Seema N Sheth, Matthew A Streisfeld, Andrea L Sweigart, Alex D Twyford, John H Willis, Kevin M Wright, Carrie A Wu, Yao-Wu Yua

Data from: Testing range-limit hypotheses using range-wide habitat suitability and occupancy for the scarlet monkeyflower (Erythranthe cardinalis)

Determining the causes of geographic range limits is a fundamental problem in ecology, evolution, and conservation biology. Range limits arise due to fitness and dispersal limitation, which yield contrasting predictions about habitat suitability and occupancy of suitable habitat across geographic ranges. If a range edge is limited primarily by fitness, occupancy of suitable habitat should be high, habitat suitability should decline towards the edge, and no suitable habitat should exist beyond it. In contrast, a range edge limited primarily by dispersal should have unoccupied but suitable habitat at and beyond the edge. We built ecological niche models relating occurrence records for the scarlet monkeyflower (Erythranthe cardinalis) to climatic variables, and applied these models to independent data from systematic, range-wide surveys of presence and absence to estimate the availability and occupancy of climatically suitable habitat. We found that fitness limitation predominated over dispersal limitation, but dispersal limitation also played a role at the poleward edge. These results are consistent with the hypothesis that dispersal limitation is more important along shallow environmental gradients and also suggest that synergy between dispersal and fitness limitation can contribute to colonization failure. The framework used here is validated by independent data and could be readily applied to inferring causes of range limits in many other species

Understanding bias in geographic range size estimates

Aim Estimates of geographic range size derived from natural history museum specimens are probably biased for many species. We aim to determine how bias in these estimates relates to range size. Location We conducted computer simulations based on herbarium specimen records from localities ranging from the southern United States to northern Argentina. Methods We used theory on the sampling distribution of the mean and variance to develop working hypotheses about how range size, defined as area of occupancy (AOO), was related to the inter-specific distribution of: (1) mean collection effort per area across the range of a species (MC); (2) variance in collection effort per area across the range of a species (VC); and (3) proportional bias in AOO estimates (PBias: the difference between the expected value of the estimate of AOO and true AOO, divided by true AOO). We tested predictions from these hypotheses using computer simulations based on a dataset of more than 29,000 herbarium specimen records documenting occurrences of 377 plant species in the tribe Bignonieae (Bignoniaceae). Results The working hypotheses predicted that the mean of the inter-specific distribution of MC, VC and PBias were independent of AOO, but that the respective variance and skewness decreased with increasing AOO. Computer simulations supported all but one prediction: the variance of the inter-specific distribution of VC did not decrease with increasing AOO. Main conclusions Our results suggest that, despite an invariant mean, the dispersion and symmetry of the inter-specific distribution of PBias decreases as AOO increases. As AOO increased, range size was less severely underestimated for a large proportion of simulated species. However, as AOO increased, range size estimates having extremely low bias were less common.Conservation InternationalConservation Internationa

Best practices for reporting climate data in ecology

A large number of published ecological studies fail to include basic information about the climate data used. In the interest of reproducibility and transparency, we offer recommendations for best practices that we urge Editors, authors, and reviewers to adopt in future publications

Best practices for reporting climate data in ecology

A large number of published ecological studies fail to include basic information about the climate data used. In the interest of reproducibility and transparency, we offer recommendations for best practices that we urge Editors, authors, and reviewers to adopt in future publications