Phylogeography within the Peromyscus maniculatus species group: Understanding past distribution of genetic diversity and areas of refugia in western North America.

The effects of anthropogenic climate change on biodiversity have been recognized on every continent, ocean, and across different taxonomic groups. Here, we study the range dynamics and demography of a cosmopolitan species: the deer mouse, Peromyscus maniculatus. We generated a multilocus SNP dataset using the ddRADseq protocol for 218 individuals across the geographic range within three western North American lineages of this species group. We evaluated population structure using several methods and explored the correlation between geographic and genetic distances. We modeled the demographic history using a site frequency spectrum approach and used a machine learning algorithm to infer current and past (Last Glacial Maximum; LGM) environmental suitability. Lastly, we explored the origin of population expansion for the identified lineages. The genome-wide SNP dataset was able to identify-three regionally distinct groups- 1) P. m. gambelii (southern California); 2) P. keeni (Pacific Northwest); 3) P. m. sonoriensis (a broad population spanning the Pacific Northwest through central California and across the Rocky Mountains into the Great Plains). Demographic analysis indicated the splits between the three populations occurred within the last 500 thousand years, with one very recent (late Holocene) split. Ecological niche models for each of these lineages predicted suitable environment present throughout their known ranges for current conditions, and a severe reduction of northern habitat in the past. The deer mouse has responded to past climate changes by expanding its range during interglacial periods and contracting its range during glacial periods leading to strong population differentiation. But lower magnitude climate change or other processes within the Holocene interglacial period led to population differentiation as well, which is likely still ongoing today given the substantial anthropogenic climate change and other landscape transformations caused by humans during the Anthropocene. By understanding the historical processes that led to the contemporary geographic distribution of biodiversity, we can determine the relative importance of different factors that shape biodiversity, now and into the future.

Genome-wide genetic variation coupled with demographic and ecological niche modeling of the dusky-footed woodrat (Neotoma fuscipes) reveal patterns of deep divergence and widespread Holocene expansion across northern California.

Understanding how species have responded to past climate change may help refine projections of how species and biotic communities will respond to future change. Here, we integrate estimates of genome-wide genetic variation with demographic and niche modeling to investigate the historical biogeography of an important ecological engineer: the dusky-footed woodrat, Neotoma fuscipes. We use RADseq to generate a genome-wide dataset for 71 individuals from across the geographic distribution of the species in California. We estimate population structure using several model-based methods and infer the demographic history of regional populations using a site frequency spectrum-based approach. Additionally, we use ecological niche modeling to infer current and past (Last Glacial Maximum) environmental suitability across the species' distribution. Finally, we estimate the directionality and possible spatial origins of regional population expansions. Our analyses indicate this species is subdivided into three regionally distinct populations, with the deepest divergence occurring ~1.7 million years ago across the modern-day San Francisco-Bay Delta region; a common biogeographic barrier for the flora and fauna of California. Our models of environmental suitability through time coincide with our estimates of population expansion, with relative long-term stability in the southern portion of the range, and more recent expansion into the northern end of the range. Our study illustrates how the integration of genome-wide data with spatial and demographic modeling can reveal the timing and spatial extent of historic events that determine patterns of biotic diversity and may help predict biotic response to future change.

Are geometric morphometric analyses replicable? Evaluating landmark measurement error and its impact on extant and fossil Microtus classification.

Geometric morphometric analyses are frequently employed to quantify biological shape and shape variation. Despite the popularity of this technique, quantification of measurement error in geometric morphometric datasets and its impact on statistical results is seldom assessed in the literature. Here, we evaluate error on 2D landmark coordinate configurations of the lower first molar of five North American Microtus (vole) species. We acquired data from the same specimens several times to quantify error from four data acquisition sources: specimen presentation, imaging devices, interobserver variation, and intraobserver variation. We then evaluated the impact of those errors on linear discriminant analysis-based classifications of the five species using recent specimens of known species affinity and fossil specimens of unknown species affinity. Results indicate that data acquisition error can be substantial, sometimes explaining >30% of the total variation among datasets. Comparisons of datasets digitized by different individuals exhibit the greatest discrepancies in landmark precision, and comparison of datasets photographed from different presentation angles yields the greatest discrepancies in species classification results. All error sources impact statistical classification to some extent. For example, no two landmark dataset replicates exhibit the same predicted group memberships of recent or fossil specimens. Our findings emphasize the need to mitigate error as much as possible during geometric morphometric data collection. Though the impact of measurement error on statistical fidelity is likely analysis-specific, we recommend that all geometric morphometric studies standardize specimen imaging equipment, specimen presentations (if analyses are 2D), and landmark digitizers to reduce error and subsequent analytical misinterpretations.

Community Assembly and Climate Mismatch in Late Quaternary Eastern North American Pollen Assemblages.

Plant community response to climate change ranges from synchronous tracking to strong mismatch. Explaining this variation in climate change response is critical for accurate global change modeling. Here we quantify how closely assemblages track changes in climate (match/mismatch) and how broadly climate niches are spread within assemblages (narrow/broad ecological tolerance, or "filtering") using data for the past 21,000 years for 531 eastern North American fossil pollen assemblages. Although climate matching has been strong over the last 21 millennia, mismatch increased in 30% of assemblages during the rapid climate shifts between 14.5 and 10 ka. Assemblage matching rebounded toward the present day in 10%-20% of assemblages. Climate-assemblage mismatch was greater in tree-dominated and high-latitude assemblages, consistent with persisting populations, slower dispersal rates, and glacial retreat. In contrast, climate matching was greater for assemblages comprising taxa with higher median seed mass. More than half of the assemblages were climatically filtered at any given time, with peak filtering occurring at 8.5 ka for nearly 80% of assemblages. Thus, vegetation assemblages have highly variable rates of climate mismatch and filtering over millennial scales. These climate responses can be partially predicted by species' traits and life histories. These findings help constrain predictions for plant community response to contemporary climate change.

Reorganization of surviving mammal communities after the end-Pleistocene megafaunal extinction.

Large mammals are at high risk of extinction globally. To understand the consequences of their demise for community assembly, we tracked community structure through the end-Pleistocene megafaunal extinction in North America. We decomposed the effects of biotic and abiotic factors by analyzing co-occurrence within the mutual ranges of species pairs. Although shifting climate drove an increase in niche overlap, co-occurrence decreased, signaling shifts in biotic interactions. Furthermore, the effect of abiotic factors on co-occurrence remained constant over time while the effect of biotic factors decreased. Biotic factors apparently played a key role in continental-scale community assembly before the extinctions. Specifically, large mammals likely promoted co-occurrence in the Pleistocene, and their loss contributed to the modern assembly pattern in which co-occurrence frequently falls below random expectations.

How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.

Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

Controlled comparison of species- and community-level models across novel climates and communities.

Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa.

The complete mitochondrial genome of the dusky-footed woodrat(Neotoma fuscipes) (Rodentia, Cricetidae).

The dusky-footed woodrat (Neotoma fuscipes) is an endemic North American rodent belonging to the family Cricetidae. We present here the first complete mitogenome within the Neotoma genus. The mitogenome is 16,199 bp in length, and has a structure and gene organization similar to other rodent species (e.g. Mus musculus, Peromyscus maniculatus and Microtus fortis calamorum). The overall base composition is A (35.2%), C (25.5%), G (12.3%), T (27.0%), with a GC content of 37.8%, similar to other rodents. This mitogenome serves as a foundation for future phylogenetic, phylogeographic and population genetic studies.

Holocene shifts in the assembly of plant and animal communities implicate human impacts.

Understanding how ecological communities are organized and how they change through time is critical to predicting the effects of climate change. Recent work documenting the co-occurrence structure of modern communities found that most significant species pairs co-occur less frequently than would be expected by chance. However, little is known about how co-occurrence structure changes through time. Here we evaluate changes in plant and animal community organization over geological time by quantifying the co-occurrence structure of 359,896 unique taxon pairs in 80 assemblages spanning the past 300 million years. Co-occurrences of most taxon pairs were statistically random, but a significant fraction were spatially aggregated or segregated. Aggregated pairs dominated from the Carboniferous period (307 million years ago) to the early Holocene epoch (11,700 years before present), when there was a pronounced shift to more segregated pairs, a trend that continues in modern assemblages. The shift began during the Holocene and coincided with increasing human population size and the spread of agriculture in North America. Before the shift, an average of 64% of significant pairs were aggregated; after the shift, the average dropped to 37%. The organization of modern and late Holocene plant and animal assemblages differs fundamentally from that of assemblages over the past 300 million years that predate the large-scale impacts of humans. Our results suggest that the rules governing the assembly of communities have recently been changed by human activity.

A 2.5-million-year perspective on coarse-filter strategies for conserving nature's stage.

Climate change will require novel conservation strategies. One such tactic is a coarse-filter approach that focuses on conserving nature's stage (CNS) rather than the actors (individual species). However, there is a temporal mismatch between the long-term goals of conservation and the short-term nature of most ecological studies, which leaves many assumptions untested. Paleoecology provides a valuable perspective on coarse-filter strategies by marshaling the natural experiments of the past to contextualize extinction risk due to the emerging impacts of climate change and anthropogenic threats. We reviewed examples from the paleoecological record that highlight the strengths, opportunities, and caveats of a CNS approach. We focused on the near-time geological past of the Quaternary, during which species were subjected to widespread changes in climate and concomitant changes in the physical environment in general. Species experienced a range of individualistic responses to these changes, including community turnover and novel associations, extinction and speciation, range shifts, changes in local richness and evenness, and both equilibrium and disequilibrium responses. Due to the dynamic nature of species responses to Quaternary climate change, a coarse-filter strategy may be appropriate for many taxa because it can accommodate dynamic processes. However, conservationists should also consider that the persistence of landforms varies across space and time, which could have potential long-term consequences for geodiversity and thus biodiversity.

Community ecology in a changing environment: Perspectives from the Quaternary.

Community ecology and paleoecology are both concerned with the composition and structure of biotic assemblages but are largely disconnected. Community ecology focuses on existing species assemblages and recently has begun to integrate history (phylogeny and continental or intercontinental dispersal) to constrain community processes. This division has left a "missing middle": Ecological and environmental processes occurring on timescales from decades to millennia are not yet fully incorporated into community ecology. Quaternary paleoecology has a wealth of data documenting ecological dynamics at these timescales, and both fields can benefit from greater interaction and articulation. We discuss ecological insights revealed by Quaternary terrestrial records, suggest foundations for bridging between the disciplines, and identify topics where the disciplines can engage to mutual benefit.

Climate refugia: joint inference from fossil records, species distribution models and phylogeography.

Climate refugia, locations where taxa survive periods of regionally adverse climate, are thought to be critical for maintaining biodiversity through the glacial-interglacial climate changes of the Quaternary. A critical research need is to better integrate and reconcile the three major lines of evidence used to infer the existence of past refugia - fossil records, species distribution models and phylogeographic surveys - in order to characterize the complex spatiotemporal trajectories of species and populations in and out of refugia. Here we review the complementary strengths, limitations and new advances for these three approaches. We provide case studies to illustrate their combined application, and point the way towards new opportunities for synthesizing these disparate lines of evidence. Case studies with European beech, Qinghai spruce and Douglas-fir illustrate how the combination of these three approaches successfully resolves complex species histories not attainable from any one approach. Promising new statistical techniques can capitalize on the strengths of each method and provide a robust quantitative reconstruction of species history. Studying past refugia can help identify contemporary refugia and clarify their conservation significance, in particular by elucidating the fine-scale processes and the particular geographic locations that buffer species against rapidly changing climate.

Climate change and the past, present, and future of biotic interactions.

Biotic interactions drive key ecological and evolutionary processes and mediate ecosystem responses to climate change. The direction, frequency, and intensity of biotic interactions can in turn be altered by climate change. Understanding the complex interplay between climate and biotic interactions is thus essential for fully anticipating how ecosystems will respond to the fast rates of current warming, which are unprecedented since the end of the last glacial period. We highlight episodes of climate change that have disrupted ecosystems and trophic interactions over time scales ranging from years to millennia by changing species' relative abundances and geographic ranges, causing extinctions, and creating transient and novel communities dominated by generalist species and interactions. These patterns emerge repeatedly across disparate temporal and spatial scales, suggesting the possibility of similar underlying processes. Based on these findings, we identify knowledge gaps and fruitful areas for research that will further our understanding of the effects of climate change on ecosystems.

Model systems for a no-analog future: species associations and climates during the last deglaciation.

As the earth system moves to a novel state, model systems (experimental, observational, paleoecological) are needed to assess and improve the predictive accuracy of ecological models under environments with no contemporary analog. In recent years, we have intensively studied the no-analog plant associations and climates in eastern North America during the last deglaciation to better constrain their spatiotemporal distribution, test hypotheses about climatic and megaherbivory controls, and assess the accuracy of species- and community-level models. The formation of no-analog plant associations was asynchronous, beginning first in the south-central United States; at sites in the north-central United States, it is linked to declining megafaunal abundances. Insolation and temperature were more seasonal than present, creating climates currently nonexistent in North America, and shifting species-climate relationships for some taxa. These shifts pose a common challenge to empirical paleoclimatic reconstructions, species distribution models (SDMs), and conservation-optimization models based on SDMs. Steps forward include combining recent and paleoecological data to more fully describe species' fundamental niches, employing community-level models to model shifts in species interactions under no-analog climates, and assimilating paleoecological data with mechanistic ecosystem models. Accurately modeling species interactions under novel environments remains a fundamental challenge for all forms of ecological models.

Space can substitute for time in predicting climate-change effects on biodiversity.

"Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.