Niche models do not predict experimental demography but both suggest dispersal limitation across the northern range limit of the scarlet monkeyflower (Erythranthe cardinalis)

Abstract

Aim Geographical ranges largely reflect the projection of species’ environmental niches onto the landscape, but dispersal limitation can cause ranges to fall short of niche limits. Understanding the prevalence of niche and dispersal limitation is a fundamental problem in ecology and biogeography, and it is relevant in predicting climate‐driven range shifts. Dispersal limitation could also cause widely used ecological niche models (ENM), which relate records of occurrence to environmental predictors, to underestimate properties of the ecological niche. Using a combination of experimental transplants and ENM, we tested for (a) dispersal and niche limitation across a species’ range boundary and (b) associations between ENM predictions and population performance. Location Oregon, USA. Taxon Scarlet monkeyflower (Erythranthe cardinalis). Methods We created experimental populations within and beyond the northern range edge and used integral projection models (IPM) to infer potential population growth trajectories. We also built two classes of ecological niche models (ENM), one using climatic predictors and the other using fine‐scale stream habitat variables, to estimate habitat suitability across the northern range edge. Finally, we tested whether higher ENM suitability scores predict greater demographic performance. Results Consistent with dispersal limitation, experimental populations beyond the range were projected to persist or spread in three of four sites (compared to two of four sites within the range) and stream habitat ENM projected abundant suitable stream microhabitat within the species’ thermal envelope beyond the range edge. In contrast, climatic ENM suggested decreasing habitat suitability and availability at the northern range edge. Unexpectedly, higher climatic ENM scores were associated with negative population growth rates, while higher stream habitat ENM scores were unrelated to population growth. Main conclusions The northern range edge falls short of the species niche limit and is instead limited by dispersal into suitable habitat. Dispersal limitation caused correlative niche models to underestimate the climatic niche and to poorly predict demographic performance in a short‐term field study. These results highlight key challenges to applying predictions from correlative ENM to understanding range and niche limits.

A resurrection study reveals limited evolution of phenology in response to recent climate change across the geographic range of the scarlet monkeyflower

“…Mimulus cardinalis (Phrymaceae), which typically flowers between May and September, is an herbaceous perennial that occurs below 2,400 m in wet habitats alongside streams from Baja California to Oregon in western North America (Figure 1a; Fraga, 2018; Lowry et al., 2019). Mimulus cardinalis has become a model system for studying local adaptation, geographic range limits, and responses to climate change (Angert, 2009; Angert & Schemske, 2005; Angert et al., 2011; Bayly & Angert, 2019; Paul et al., 2011; Wooliver et al., 2020). We chose M. cardinalis as the study system for this experiment due to the availability of seeds from phenotypically differentiated populations across the species' geographic range (Muir & Angert, 2017; Sheth & Angert, 2016).…”

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

“…Previous studies that have examined both suitability-abundance and suitability-demography relationships typically find that the former are significant while the latter are not (Bean et al, 2014;Oliver et al, 2012;Pironon et al, 2015;Thuiller et al, 2014). Similarly, studies of solely suitability-demography relationships commonly find that suitability is not correlated with overall demographic performance in any consistent manner (Bacon et al, 2017;Bayly & Angert, 2019;Csergő et al, 2017;Pironon et al, 2018). As with explanations for a lack of a suitability-abundance relationship, the lack of a suitability-demography relationship is generally attributed to the influence of local conditions that yield habitat suitability which differs from climatic suitability.…”

“…These may include heterogeneity in a site's local physiography, the availability of necessary resources unrelated to climate, or the distribution of facilitative partners, competitors, or predators, all of which may be obscured by single-species SDMs built using solely large-scale climatic predictors (e.g. Bean et al, 2014;Bayly & Angert, 2019). In addition, suitability based upon a model built for the entire distribution may not reflect the climatic optimum for all populations and may poorly predict demographic responses to climate variation across the distribution (Chardon et al, 2020;Peterson et al, 2019).…”

“…On the other hand, a recent analysis of the relationship between ENM-predicted suitability and abundance of 396 mammal and tree species found no such relationship (Dallas & Hastings, 2018). The smaller number of studies that have evaluated the relationship between demographic performance and projected suitability yield similarly equivocal results: positive suitability-demography relationships have been observed in some cases (Brambilla & Ficetola, 2012;McLane & Aitken, 2012;Monnet, Hardouin, Robert, Hingrat, & Jiguet, 2015;Searcy & Shaffer, 2016;Sheppard, Burns, & Stanley, 2014), but appear to be the exception rather than the rule (Bacon et al, 2017;Bayly & Angert, 2019;Chardon, Pironon, Peterson, & Doak, 2020;Csergő et al, 2017;Oliver et al, 2012). The lack of consensus regarding the ubiquity of suitability-abundance and suitability-demography relationships may be due to local-scale constraints not captured in the large-scale predictors often used in ENMs (Davis, Jenkinson, Lawton, Shorrocks, & Wood, 1998;Guisan & Thuiller, 2005;Lembrechts, Nijs, & Lenoir, 2019;Pearson & Dawson, 2003;Varner & Dearing, 2014;Wisz et al, 2013), such that suitability predicts a maximum abundance or performance at a site that is then altered by attributes of the local environment (VanDerWal, Shoo, Johnson, & Williams, 2009).…”

Integrated empirical approaches to better understand species’ range limits

“…If so, the range may be dispersal‐limited; if not, niche limitation is likely. However, ENMs will overestimate the potential range if they do not account for important biotic interactions or if edge populations are sinks, requiring integration with demographic studies (Eckhart et al., ) or transplant experiments (Bayly and Angert, ).…”