New uses for ancient middens: bridging ecological and evolutionary perspectives.

Rodent middens provide a fine-scale spatiotemporal record of plant and animal communities over the late Quaternary. In the Americas, middens have offered insight into biotic responses to past environmental changes and historical factors influencing the distribution and diversity of species. However, few studies have used middens to investigate genetic or ecosystem level responses. Integrating midden studies with neoecology and experimental evolution can help address these gaps and test mechanisms underlying eco-evolutionary patterns across biological and spatiotemporal scales. Fully realizing the potential of middens to answer cross-cutting ecological and evolutionary questions and inform conservation goals in the Anthropocene will require a collaborative research community to exploit existing midden archives and mount new campaigns to leverage midden records globally.

Spatial modeling could not differentiate early SARS-CoV-2 cases from the distribution of humans on the basis of climate in the United States.

The SARS-CoV-2 coronavirus is wreaking havoc globally, yet, as a novel pathogen, knowledge of its biology is still emerging. Climate and seasonality influence the distributions of many diseases, and studies suggest at least some link between SARS-CoV-2 and weather. One such study, building species distribution models (SDMs), predicted SARS-CoV-2 risk may remain concentrated in the Northern Hemisphere, shifting northward in summer months. Others have highlighted issues with SARS-CoV-2 SDMs, notably: the primary niche of the virus is the host it infects, climate may be a weak distributional predictor, global prevalence data have issues, and the virus is not in population equilibrium. While these issues should be considered, we believe climate's relationship with SARS-CoV-2 is still worth exploring, as it may have some impact on the distribution of cases. To further examine if there is a link to climate, we build model projections with raw SARS-CoV-2 case data and population-scaled case data in the USA. The case data were from across March 2020, before large travel restrictions and public health policies were impacting cases across the country. We show that SDMs built from population-scaled case data cannot be distinguished from control models (built from raw human population data), while SDMs built on raw case data fail to predict the known distribution of cases in the U.S. from March. The population-scaled analyses indicate that climate did not play a central role in early U.S. viral distribution and that human population density was likely the primary driver. We do find slightly more population-scaled viral cases in cooler areas. Ultimately, the temporal and geographic constraints on this study mean that we cannot rule out climate as a partial driver of the SARS-CoV-2 distribution. Climate's role on SARS-CoV-2 should continue to be cautiously examined, but at this time we should assume that SARS-CoV-2 will continue to spread anywhere in the U.S. where governmental policy does not prevent spread.

Paleo-metagenomics of North American fossil packrat middens: Past biodiversity revealed by ancient DNA.

Fossil rodent middens are powerful tools in paleoecology. In arid parts of western North America, packrat (Neotoma spp.) middens preserve plant and animal remains for tens of thousands of years. Midden contents are so well preserved that fragments of endogenous ancient DNA (aDNA) can be extracted and analyzed across millennia. Here, we explore the use of shotgun metagenomics to study the aDNA obtained from packrat middens up to 32,000 C14 years old. Eleven Illumina HiSeq 2500 libraries were successfully sequenced, and between 0.11% and 6.7% of reads were classified using Centrifuge against the NCBI "nt" database. Eukaryotic taxa identified belonged primarily to vascular plants with smaller proportions mapping to ascomycete fungi, arthropods, chordates, and nematodes. Plant taxonomic diversity in the middens is shown to change through time and tracks changes in assemblages determined by morphological examination of the plant remains. Amplicon sequencing of ITS2 and rbcL provided minimal data for some middens, but failed at amplifying the highly fragmented DNA present in others. With repeated sampling and deep sequencing, analysis of packrat midden aDNA from well-preserved midden material can provide highly detailed characterizations of past communities of plants, animals, bacteria, and fungi present as trace DNA fossils. The prospects for gaining more paleoecological insights from aDNA for rodent middens will continue to improve with optimization of laboratory methods, decreasing sequencing costs, and increasing computational power.

cRacle: R tools for estimating climate from vegetation.

PREMISE: The Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE) method utilizes a robust set of modeling tools for estimating climate and paleoclimate from vegetation using large repositories of biodiversity data and open access R software. METHODS: Here, we implement a new R package for the estimation of climate from extant and fossil vegetation. The 'cRacle' package implements functions for data access, aggregation, and modeling to estimate climate from plant community compositions. 'cRacle' is modular and includes many best-practice features. RESULTS: Performance tests using modern vegetation survey data from North and South America shows that CRACLE outperforms alternative methods. CRACLE estimates of mean annual temperature are usually within 1°C of the actual values when optimal model parameters are used. Generalized boosted regression (GBR) model correction improves CRACLE estimates by reducing bias. DISCUSSION: CRACLE provides accurate estimates of climate based on the composition of modern plant communities. Non-parametric CRACLE modeling coupled with GBR model correction produces the most accurate results to date. The 'cRacle' R package streamlines the estimation of climate from plant community data, which will make this modeling more accessible to a wider range of users.

Algorithms and strategies in short-read shotgun metagenomic reconstruction of plant communities.

PREMISE OF THE STUDY: DNA may be preserved for thousands of years in very cold or dry environments, and plant tissue fragments and pollen trapped in soils and shallow aquatic sediments are well suited for the molecular characterization of past floras. However, one obstacle in this area of study is the limiting bias in the bioinformatic classification of short fragments of degraded DNA from the large, complex genomes of plants. METHODS: To establish one possible baseline protocol for the rapid classification of short-read shotgun metagenomic data for reconstructing plant communities, the read classification programs Kraken, Centrifuge, and MegaBLAST were tested on simulated and ancient data with classification against a reference database targeting plants. RESULTS: Performance tests on simulated data suggest that Kraken and Centrifuge outperform MegaBLAST. Kraken tends to be the most conservative approach with high precision, whereas Centrifuge has higher sensitivity. Reanalysis of 13,000 years of ancient sedimentary DNA from North America characterizes potential post-glacial vegetation succession. DISCUSSION: Classification method choice has an impact on performance and any downstream interpretation of results. The reanalysis of ancient DNA from glacial lake sediments yielded vegetation histories that varied depending on method, potentially changing paleoecological conclusions drawn from molecular evidence.

Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): a method for the estimation of climate using vegetation.

UNLABELLED: • PREMISE OF THE STUDY: Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate.• METHODS: Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate.• KEY RESULTS: Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ∼250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods.• CONCLUSIONS: CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies.

Climate niche modeling in the perennial Glycine (Leguminosae) allopolyploid complex.

PREMISE OF STUDY: Polyploid plants, when compared with diploids, show similar molecular, morphological, physiological, and ecological tendencies across unrelated groups, but the degree to which these form "rules" of polyploid evolution are unclear. The Glycine (Leguminosae) allopolyploid complex affords the opportunity to test whether polyploidy in similar genetic backgrounds produces similar effects on geographical range or climatic space. METHODS: We used information on locality presence of four closely related Glycine allopolyploid species and their diploid progenitors to build models of the potentially available Australian ranges based on climate using Maxent3.3.3k. Principal coordinate analysis was used to characterize the multidimensional climate space occupied by each species. KEY RESULTS: Each of the four Glycine allopolyploids showed intermediacy in potential geographical space and in ecological space, relative to its diploid progenitors. The four allopolyploids did not have consistently larger ranges than their progenitors, though all four occupied a portion of climate niche space not available to its progenitors. The polyploids also differed in their exploitation of potentially available geographical range. Australian ranges and environmental space did not correlate with greater colonizing ability in these polyploids. CONCLUSIONS: The four Glycine allopolyploids do not show many common range- or climate-related features, other than intermediacy. Thus, despite their similar genetic and evolutionary backgrounds, polyploidy has not produced convergent ecological effects.

Four alleles of AtCESA3 form an allelic series with respect to root phenotype in Arabidopsis thaliana.

Plant cell shape is determined by the orientation of cellulose microfibrils in the primary cell wall. Consequently, mutations that affect genes encoding the enzymes responsible for the synthesis of cellulose, namely, the cellulose synthase catalytic subunits, can alter cell shape substantially, particularly in the roots of affected plants. The multiple response expansion1 (mre1) mutant of Arabidopsis thaliana results from a point mutation in the AtCESA3 gene, which encodes one of the three isoforms of the cellulose synthase catalytic subunit required for synthesis of cellulose in the primary cell wall. Phenotypic comparison of the mre1 mutant with three other alleles (ectopic lignification1-1, ectopic lignification1-2 and constitutive expression of vsp1) showed that these four alleles form an allelic series with respect to their root phenotypes, with mre1 being the weakest allele identified to date. These analyses demonstrated that sucrose affects a significant alteration of cell shape in the roots of these mutants and likely suppresses root cell division in them as well, and that the chemical aminoisobutyric acid can suppress these effects of sucrose. Interestingly, the cell walls in the roots of these four AtCESA3 alleles contain different percentages of cellulose, and these percentages correlate with the lengths of the roots and cortex cells in these roots when grown on media containing high levels of sucrose.