The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource

Williams, John W.; Grimm, Eric C.; Blois, Jessica L.; Charles, Donald F.; Davis, Edward B.; Goring, Simon; Graham, Russell W.; Smith, Alison J.; Anderson, Michael T.; Arroyo-Cabrales, Joaquı́n; Ashworth, Allan; Betancourt, Julio L.; Bills, Brian; Booth, Robert K.; Buckland, Philip I.; Curry, B. Brandon; Giesecke, Thomas; Jackson, Stephen T.; Latorre, Claudio; Nichols, Jonathan M.; Purdum, Timshel; Roth, Robert E.; Stryker, Michael; Takahara, Hikaru

doi:10.1017/qua.2017.105

Cited by 236 publications

(194 citation statements)

References 117 publications

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“…Many of the tree and shrub taxa in our study are wind‐pollinated (Appendix ) and thus the two richness measures largely overlap. Similar to the pollen data in large databases such as the European Pollen Database (Davis et al, ; Giesecke et al, ) or the Neotoma Paleoecology Database (Williams et al, ), our pollen dataset combines the work of multiple analysts and the dataset loses taxonomic precision due to the merging of certain morphologically difficult pollen taxa. The lack of correlation between pollen and plant richness among insect‐pollinated taxa or among herbs and grasses may be related to this “analyst effect” but is likely to be additionally influenced by landscape configuration (c.f.…”

Section: Discussionmentioning

confidence: 99%

Patterns of modern pollen and plant richness across northern Europe

et al. 2019

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Sedimentary pollen offers excellent opportunities to reconstruct vegetation changes over past millennia. Number of different pollen taxa or pollen richness is used to characterise past plant richness. To improve the interpretation of sedimentary pollen richness, it is essential to understand the relationship between pollen and plant richness in contemporary landscapes. This study presents a regional‐scale comparison of pollen and plant richness from northern Europe and evaluates the importance of environmental variables on pollen and plant richness. We use a pollen dataset of 511 lake‐surface pollen samples ranging through temperate, boreal and tundra biomes. To characterise plant diversity, we use a dataset formulated from the two largest plant atlases available in Europe. We compare pollen and plant richness estimates in different groups of taxa (wind‐pollinated vs. non‐wind‐pollinated, trees and shrubs vs. herbs and grasses) and test their relationships with climate and landscape variables. Pollen richness is significantly positively correlated with plant richness (r = 0.53). The pollen plant richness correlation improves (r = 0.63) when high pollen producers are downweighted prior to estimating richness minimising the influence of pollen production on the pollen richness estimate. This suggests that methods accommodating pollen‐production differences in richness estimates deserve further attention and should become more widely used in Quaternary pollen diversity studies. The highest correlations are found between pollen and plant richness of trees and shrubs (r = 0.83) and of wind‐pollinated taxa (r = 0.75) suggesting that these are the best measures of broad‐scale plant richness over several thousands of square kilometres. Mean annual temperature is the strongest predictor of both pollen and plant richness. Landscape openness is positively associated with pollen richness but not with plant richness. Pollen richness values from extremely open and/or cold areas where pollen production is low should be interpreted with caution because low local pollen production increases the proportion of extra‐regional pollen. Synthesis. Our results confirm that pollen data can provide insights into past plant richness changes in northern Europe, and with careful consideration of pollen‐production differences and spatial scale represented, pollen data make it possible to investigate vegetation diversity trends over long time‐scales and under changing climatic and habitat conditions.

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Section: Discussionmentioning

confidence: 99%

Patterns of modern pollen and plant richness across northern Europe

et al. 2019

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“…Neotoma Paleoecology Database; Williams et al 2018). Samples that are taken from a sequence of sediment depths (with depth as a proxy for age as sediment is laid down over time) provide information, with varying degrees of certainty, about past vegetation communities.…”

Section: Paleoecological Datamentioning

confidence: 99%

“…Neotoma; Williams et al 2018;PBDB; pbdb.org) and contemporary occurrence (e.g. Extension of the integrative models to species with less representation in the fossil record will pose a significant challenge.…”

Section: Section 4 Continued Challenges and Frontiersmentioning

confidence: 99%

Inference of biogeographic history by formally integrating distinct lines of evidence: genetic, environmental niche and fossil

Hoban

Dawson

Robinson³

et al. 2019

Ecography

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A primary focus of historical biogeography is to understand changes in species ranges, abundance and genetic connectivity, and changes in community composition. Traditionally, biogeographic inference has relied on distinct lines of evidence, including DNA sequences, fossils and hindcasted ecological niche models. In this review we propose that the development of integrative modeling approaches that leverage multiple distinct data types from diverse disciplines has the potential to revolutionize the field of biogeography. Although each data type contains information on a distinct aspect of species' biogeographic histories, few studies formally integrate multiple types in analysis. For example, post hoc congruence among analyses based on different data types (e.g. fossils and genetics) is commonly assumed to indicate likely biogeographic histories. Unfortunately, analyses of different data often reach discordant conclusions. Thus, fundamental and unresolved debates continue regarding speed and timing of postglacial migration, location and size of glacial refugia, and degree of long distance dispersal. Formal statistical integration can help address these issues. More specifically, formal integration can leverage all available evidence, account for inherent biases associated with different data types, and quantify data and process uncertainty. Novel, quantitative integration of data and models across fields is now possible due to recent advances in cyberinfrastructure, spatial modeling, online and aggregated ecological databases, data processing and quantitative methods. Our purpose is to make the case for and give examples of rigorous integration of genetic, fossil and environmental/ occurrence data for inferring biogeographic history. In particular, we 1) review the need for such a framework; 2) explain common data types and approaches used to infer biogeographic history (and the challenges with each); 3) review state-of-the-art examples of data integration in biogeography; 4) lay out a series of novel, suggested improvements on current methods; and 5) provide an outlook on technical feasibility and future opportunities. Ecography E4 awardGlossary ABC (approximate Bayesian computation; also see Box 1) -a simulation-based statistical method that approximates the likelihood of a model through comparisons of summary statistics calculated from simulated and observed data. Biogeographic history -the study of processes and patterns related to: geographic range shifts, contractions and expansions; demographic fluctuations; locations of refugia; and migration patterns. Bottleneck -a drastic reduction in population size that often also results in a loss of genetic diversity; colonization at a continental scale often involves serial bottlenecks. Coalescent theory -a body of theory that uses probabilistic models to reconstruct the genealogy of a sample backward in time from the sampled lineages (present) to the most recent common ancestor (past). DRM (dynamic range model) -a hierarchical Bayesian approach to estimate paramet...

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“…Due to the large number of records available for this species (> 50 000), we restricted our search to preserved specimens with geographic coordinates and that were collected after 1950. We also downloaded fossil records for O. princeps from the Neotoma Paleoecology Database to calibrate niche models according to the experimental design (see below, Williams et al 2018). We only included five records spanning an interval between 25 and 14 kbp that includes the maxima ice-sheet extent until the onset of deglaciation of the Western Hemisphere (<https://apps.neotomadb.org/explorer>, downloaded on 28 April 2018).…”

Section: Input Datamentioning

confidence: 99%

How to survive a glaciation: the challenge of estimating biologically realistic potential distributions under freezing conditions

Guevara

León‐Paniagua

2019

Ecography

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Correlative ecological niche models are increasingly used to estimate potential distributions during the Last Glacial Maximum (LGM) for biogeographical research. In the case of presence‐background/pseudoabsences techniques, cold environments that are poorly represented in existing geography can complicate the process of model calibration and transfer into more extreme cold environments that were very common during the LGM (non‐analog conditions). This may lead to biologically unrealistic estimations. Using one cold‐adapted North American mammal, we explore a real scenario to better understand the effect of restricting the range of environmental conditions over which niche models are calibrated and then transferred to LGM conditions. We performed two sets of experiments in Maxent: 1) we calibrated models in the context of only present‐day climate conditions, which is the most common practice, and compared predictions under LGM conditions based on two extrapolation methods (clamping versus unconstrained); 2) we calibrated single models using both present‐day and LGM conditions as part of the same background in order to include more extreme environments in the model calibration. Our experiments led to dramatically different estimates of species’ potential distributions, showing notable differences with respect to latitudinal and elevational shifts during the LGM. Models calibrated using present‐day climates yielded biologically unrealistic estimations, suggesting that species survived in the glaciers during the LGM. Even more unrealistic estimations were achieved when clamping was enforced as the method to extrapolate. Models calibrated in the context of both modern and past climates reduced the required degree of extrapolation and allowed more realistic potential distributions, suggesting that the species avoided extremely cold conditions during the LGM. This study alerts to the possibility of obtaining implausible potential distributions during the LGM due to restricted background datasets and offers recommendations that should promote better strategies to estimate distributional changes during glaciations.

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The Neotoma Paleoecology Database, a multiproxy, international, community-curated data resource

Cited by 236 publications

References 117 publications

Patterns of modern pollen and plant richness across northern Europe

Patterns of modern pollen and plant richness across northern Europe

Inference of biogeographic history by formally integrating distinct lines of evidence: genetic, environmental niche and fossil

How to survive a glaciation: the challenge of estimating biologically realistic potential distributions under freezing conditions

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