Strengthening global-change science by integrating aeDNA with paleoecoinformatics.

Ancient environmental DNA (aeDNA) data are close to enabling insights into past global-scale biodiversity dynamics at unprecedented taxonomic extent and resolution. However, achieving this potential requires solutions that bridge bioinformatics and paleoecoinformatics. Essential needs include support for dynamic taxonomic inferences, dynamic age inferences, and precise stratigraphic depth.

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.

A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data.

Understanding variation of traits within and among species through time and across space is central to many questions in biology. Many resources assemble species-level trait data, but the data and metadata underlying those trait measurements are often not reported. Here, we introduce FuTRES (Functional Trait Resource for Environmental Studies; pronounced few-tress), an online datastore and community resource for individual-level trait reporting that utilizes a semantic framework.

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.

Are geometric morphometric analyses replicable? Evaluating landmark measurement error and its impact on extant and fossil 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 (vole) species.

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.

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.

Merging paleobiology with conservation biology to guide the future of terrestrial ecosystems.

Conservation of species and ecosystems is increasingly difficult because anthropogenic impacts are pervasive and accelerating. Under this rapid global change, maximizing conservation success requires a paradigm shift from maintaining ecosystems in idealized past states toward facilitating their adaptive and functional capacities, even as species ebb and flow individually. Developing effective strategies under this new paradigm will require deeper understanding of the long-term dynamics that govern ecosystem persistence and reconciliation of conflicts among approaches to conserving historical versus novel ecosystems.

Predictability in community dynamics.

The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no-lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay.

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

The dusky-footed woodrat () is an endemic North American rodent belonging to the family Cricetidae. We present here the first complete mitogenome within the genus. The mitogenome is 16,199 bp in length, and has a structure and gene organization similar to other rodent species (e.

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.

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.

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.

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.

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.

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.

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.

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.