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

Time to better integrate paleoecological research infrastructures with neoecology to improve understanding of biodiversity long-term dynamics and to inform future conservation

Anthropogenic pressures are causing a global decline in biodiversity. Successful attempts at biodiversity conservation requires an understanding of biodiversity patterns as well as the drivers and processes that determine those patterns. To deepen this knowledge, neoecologists have focused on studying present-day or recent historical data, while paleoecologists usually study long-term data through the composition of various biological proxies and environmental indicators. By establishing standard protocols or gathering databases, research infrastructures (RIs) have been instrumental to foster exchange and collaboration among scientists within neoecology (e.g. Global Information Biodiversity Facility or National Ecological Observatory Network) and paleoecology (e.g. Paleobiology Database, Neotoma Paleoecology Database or European Pollen Database). However, these two subdisciplines (and their RIs) have traditionally remained segregated although both provide valuable information that combined can improve our understanding of biodiversity drivers and underlying processes, as well as our predictions of biodiversity responses in the future. For instance, integrative studies between paleo- and neoecology have addressed the global challenge of biodiversity loss by validating climate and ecological models, estimating species fundamental niches, understanding ecological changes and trajectories, or establishing baseline conditions for restoration. Supporting and contributing to research infrastructures from both paleo- and neoecology, as well as their further integration, could boost the amount and improve the quality of such integrative studies. We argue this will enable improved capabilities to anticipate the impacts of global change and biodiversity losses. To boost such integration and illustrate our arguments, we (1) review studies integrating paleo- and neoecology to advance in the light of global changes challenge, (2) describe RIs developed in paleoecology, and (3) discuss opportunities for further integration of RIs from both disciplines (i.e. paleo- and neoecology).publishedVersio

A framework for evaluating the influence of climate, dispersal limitation, and biotic interactions using fossil pollen associations across the late Quaternary

Environmental conditions, dispersal lags, and interactions among species are major factors structuring communities through time and across space. Ecologists have emphasized the importance of biotic interactions in determining local patterns of species association. In contrast, abiotic limits, dispersal limitation, and historical factors have commonly been invoked to explain community structure patterns at larger spatiotemporal scales, such as the appearance of late Pleistocene no-analog communities or latitudinal gradients of species richness in both modern and fossil assemblages. Quantifying the relative influence of these processes on species co-occurrence patterns is not straightforward. We provide a framework for assessing causes of species associations by combining a null-model analysis of co-occurrence with additional analyses of climatic differences and spatial pattern for pairs of pollen taxa that are significantly associated across geographic space. We tested this framework with data on associations among 106 fossil pollen taxa and paleoclimate simulations from eastern North America across the late Quaternary. The number and proportion of significantly associated taxon pairs increased over time, but only 449 of 56 194 taxon pairs were significantly different from random. Within this significant subset of pollen taxa, biotic interactions were rarely the exclusive cause of associations. Instead, climatic or spatial differences among sites were most frequently associated with significant patterns of taxon association. Most taxon pairs that exhibited co-occurrence patterns indicative of biotic interactions at one time did not exhibit significant associations at other times. Evidence for environmental filtering and dispersal limitation was weakest for aggregated pairs between 16 and 11 kyr BP, suggesting enhanced importance of positive species interactions during this interval. The framework can thus be used to identify species associations that may reflect biotic interactions because these associations are not tied to environmental or spatial differences. Furthermore, temporally repeated analyses of spatial associations can reveal whether such associations persist through time

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 cooccurrence 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. Includes supplementary materials

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.Peer reviewe

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. Integrating emerging information from conservation biology, paleobiology, and the Earth sciences is an important step forward on the path to success. Maintaining nature in all its aspects will also entail immediately addressing the overarching threats of growing human population, overconsumption, pollution, and climate change.Peer reviewe

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. Moreover, aeDNA data are complex and heterogeneous, generated by dispersed researcher networks, with methods advancing rapidly. Hence, expert community governance and curation are essential to building high-value data resources. Immediate recommendations include uploading metabarcoding-based taxonomic inventories into paleoecoinformatic resources, building linkages among open bioinformatic and paleoecoinformatic data resources, harmonizing aeDNA processing workflows, and expanding community data governance. These advances will enable transformative insights into global-scale biodiversity dynamics during large environmental and anthropogenic changes

Global climate evolution during the last deglaciation

Deciphering the evolution of global climate from the end of the Last Glacial Maximum approximately 19 ka to the early Holocene 11 ka presents an outstanding opportunity for understanding the transient response of Earth's climate system to external and internal forcings. During this interval of global warming, the decay of ice sheets caused global mean sea level to rise by approximately 80 m; terrestrial and marine ecosystems experienced large disturbances and range shifts; perturbations to the carbon cycle resulted in a net release of the greenhouse gases CO₂ and CH₄ to the atmosphere; and changes in atmosphere and ocean circulation affected the global distribution and fluxes of water and heat. Here we summarize a major effort by the paleoclimate research community to characterize these changes through the development of well-dated, high-resolution records of the deep and intermediate ocean as well as surface climate. Our synthesis indicates that the super-position of two modes explains much of the variability in regional and global climate during the last deglaciation, with a strong association between the first mode and variations in greenhouse gases, and between the second mode and variations in the Atlantic meridional overturning circulation