Biology subjects

Cavender-Bares, J.

Publications and source records attributed to Cavender-Bares, J..

18 recordsLinked to original sources

bioRxiv2024

Genetically based variation in fitness and carbon assimilation among bur oak populations

Ongoing climate change will negatively impact tree populations unless they are able to acclimate to the changes in their local environment. Effective planning for climate adaptation management requires an understanding of the current state of local adaptation and physiological performance to assess whether populations are at risk of local extinction, to determine if seed movement is appropriate, and to select appropriate seed sources if intervention is needed. We established a new reciprocal transplant experiment (ACE, Adaptation to Climate and Environment) across a latitudinal gradient in North America to examine the impacts of warming on three bur oak (Quercus macrocarpa) populations across much of the species range. We established common gardens in Minnesota, Illinois, and Oklahoma with seedlings grown from seeds collected within 50 km of each of those locations from a total of sixty maternal families. We aimed to 1) assess local adaptation in each of the populations using survival and size as fitness metrics, and 2) evaluate physiological responses to different environments along the latitudinal gradient. We found that northern populations are maladapted to hotter climates as evidenced by their low survival, growth, and photosynthetic rates in the warmest common garden. The southernmost population had the highest survival rate, growth rate, and fitness of the three populations in the southernmost garden, providing evidence for local adaptation to the warmest site. However, conditions in the middle garden resulted in the highest fitness and best physiological performance for all populations. Growth and survival were correlated in the middle garden but were decoupled in the northern and southern gardens. This decoupling is likely due to stress associated with more extreme climates at the ends of the gradient that led to greater resource allocation to survival than to growth. Our results suggest that southern seed sources may perform well in warmer conditions in the north brought on by climate change, which has important implications for managers assisting broadly ranged tree species in adapting to climate change.

ecology↗

bioRxiv2024

Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience

O_LIWe introduce a new "low-density" tree diversity experiment at the Cedar Creek Ecosystem Science Reserve in central Minnesota, USA aimed at testing long-term ecosystem consequences of tree diversity and composition. The experiment was designed to provide guidance on forest restoration efforts that will simultaneously advance carbon sequestration goals and contribute to biodiversity conservation and sustainability. C_LIO_LIThe new Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity to test the mechanisms and processes that contribute to forest stability and ecosystem productivity in the face of global change. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at high density (0.5 m spacing). In addition to lower density plantings (1 m spacing), FAB2 also has larger plots (100 m2 and 400 m2) appropriate for testing long-term ecosystem consequences of species composition and diversity. C_LIO_LIWithin the first six years, mortality in the 400 m2 monoculture plots was significantly higher than in the 100 m2 plots. The highest mortality among any treatments occurred in Tilia americana and Acer negundo monocultures, but mortality for both species decreased with increasing plot diversity. These results highlight the importance of forest diversity in reducing mortality in some species and point to potential mechanisms, including light and drought stress, that cause tree mortality in vulnerable monocultures. The experiment highlights challenges to maintaining monoculture and low-diversity treatments in tree mixture experiments of large extent. C_LIO_LIThe FAB2 experiment provides a long-term platform for discerning the importance of species and lineage effects and of multiple dimensions of diversity in restoring ecosystem functions and services provided by forests. It also provides a platform for improving remote sensing approaches, including Uncrewed Aerial Vehicles (UAVs) equipped with LiDAR, multispectral, and hyperspectral sensors, to complement ground-based monitoring of forest function and diversity. We aim for the experiment to contribute to international efforts to monitor and manage forests in the face of global change. C_LI

ecology↗

bioRxiv2024

Seasonal structural stability promoted by forest diversity and composition explains overyielding

The stability of forest productivity over time is a widely studied parameter often associated with benefits of forest diversity. Yet, the structural stability (SS) through the season of forest communities and its relationship to diversity, composition, and productivity remains poorly understood. Using a large-scale (10 ha) young tree diversity experiment, we evaluated how forest structure and multiple dimensions of diversity and composition affect remotely-sensed structural metrics and their stability through the growing season. We then studied the impact of SS across the season (April-October) on the net biodiversity effects of annual wood productivity (i.e., overyielding) of forest mixtures. We surveyed experimental tree communities eight times at regular intervals from before bud-break to after leaf senescence, using an UAV-LiDAR to derive metrics associated with canopy height heterogeneity, gap probability, and forest structural complexity (i.e., fractal geometry). The inverse coefficient of variation of these metrics through the season was used as descriptors SS. These metrics along with their SS were then coupled with annual tree inventories to evaluate their relationships. Our findings indicate that plot wood volume and, to some extent, multiple dimensions of diversity and composition (i.e., taxonomic, phylogenetic, and functional) influence remotely-sensed metrics of forest structure and stability over time. We found that increases in plot wood volume as well as functional and phylogenetic diversity and variability (a measure of diversity independent of species richness), are linked to higher structural stability of forest complexity over time. We further found that higher stability of forest structural complexity and tree cover (i.e., 1 - gap probability) increases net biodiversity effects in forest mixtures through species complementarity. Structural equation models indicate that structural stability explains more the variation among plots in net biodiversity effects than multiple dimensions of diversity or variability, highlighting it as a measure that integrates several contributors to net biodiversity effects. Our results provide evidence that diversity and composition promote temporal stability of remotely-sensed forest structure and, in turn, enhanced productivity. The study highlights the potential to integrate remote sensing and ecology to disentangle the role of forest structural stability into ecological processes.

ecology↗

bioRxiv2023

Rapid estimates of leaf litter chemistry using reflectance spectroscopy

Measuring the chemical traits of leaf litter is important for understanding plants roles in nutrient cycles, including through nutrient resorption and litter decomposition, but conventional leaf trait measurements are often destructive and labor-intensive. Here, we develop and evaluate the performance of partial least-squares regression (PLSR) models that use reflectance spectra of intact or ground leaves to estimate leaf litter traits, including carbon and nitrogen concentration, carbon fractions, and leaf mass per area (LMA). Our analyses included more than 300 samples of senesced foliage from 11 species of temperate trees, including needleleaf and broadleaf species. Across all samples, we could predict each trait with moderate-to-high accuracy from both intact-leaf litter spectra (validation R2 = 0.543-0.941; %RMSE = 7.49-18.5) and ground-leaf litter spectra (validation R2 = 0.491-0.946; %RMSE = 7.00-19.5). Notably intact-leaf spectra yielded better predictions of LMA. Our results support the feasibility of building models to estimate multiple chemical traits from leaf litter of a range of species. In particular, the success of intact-leaf spectral models allows non-destructive trait estimation in a matter of seconds, which could enable researchers to measure the same leaves over time in studies of nutrient resorption.

ecology↗

bioRxiv2023

Mapping oak wilt disease using phenological observations from space

Protecting the future of forests relies on our ability to observe changes in forest health. Thus, developing tools for sensing diseases in a timely fashion is critical for managing threats at broad scales. Oak wilt --a disease caused by a pathogenic fungus (Bretziella fagacearum)-- is threatening oaks, killing thousands yearly while negatively impacting the ecosystem services they provide. Here we propose a novel workflow for mapping oak wilt by targeting temporal disease progression through symptoms using land surface phenology (LSP) from spaceborne observations. By doing so, we hypothesize that phenological changes in pigments and photosynthetic activity of trees affected by oak wilt can be tracked using LSP metrics derived from the Chlorophyll/Carotenoid Index (CCI). We used dense time-series observations from Sentinel-2 to create Analysis Ready Data across Minnesota and Wisconsin and to derive three LSP metrics: the value of CCI at the start and end of the growing season, and the coefficient of variation of the CCI during the growing season. We integrate high-resolution airborne imagery in multiple locations to select pixels (n = 3,872) from the most common oak tree health conditions: healthy, symptomatic for oak wilt, and dead. These pixels were used to train an iterative Partial Least Square Discriminant (PLSD) model and derive the probability of an oak tree (i.e., pixel) in one of these conditions and the associated uncertainty. We assessed these models spatially and temporally on testing datasets revealing that it is feasible to discriminate among the three health conditions with overall accuracy between 80-82%. Within conditions, our models suggest that spatial variations among three CCI-derived LSP metrics can predict healthily (Area Under the Curve (AUC) = 0.98), symptomatic (AUC = 0.89), and dead (AUC = 0.94) oak trees with low false positive rates. The model performance was robust across different years as well. The predictive maps were used to guide local stakeholders in locating disease hotspots for ground verification and subsequent decision-making for treatment. Our results highlight the capabilities of LSP metrics from dense spaceborne observations to map diseases and their importance for monitoring changes in biodiversity at large scales.

ecology↗

bioRxiv2023

Drivers of plant diversity, community composition, functional traits and soil processes along an alpine gradient in the central Chilean Andes

High alpine regions are threatened but understudied ecosystems that harbor diverse endemic species, making them an important biome in which to test the role of environmental factors in driving functional trait-mediated community assembly processes. In a high mountain system in the central Chilean Andes, we tested hypotheses about the drivers of plant community diversity, functional composition and soil processes along an elevation gradient. We surveyed vegetation and spectroscopic reflectance (400-2400 nm) to quantify taxonomic, phylogenetic, functional, and spectral diversity at five sites from 2400 m to 3500 m elevation. We characterized soil attributes and processes by measuring water content, carbon and nitrogen, and net nitrogen mineralization rates. At high elevation, colder temperatures led to a reduction in available soil nitrogen, while at warmer, lower elevations, soil moisture was lower. Metrics of taxonomic, functional, and spectral alpha diversity peaked at mid-elevations, while phylogenetic species richness was highest at low elevation. Leaf nitrogen followed global patterns of increasing leaf nitrogen with colder temperatures, a pattern consistent at the community level as well as within individual species. The increase in leaf nitrogen, coupled with shifts in taxonomic and functional diversity associated with turnover in lineages, indicate that the ability to acquire and retain nitrogen in colder temperatures may be important in plant community assembly in this range. Such environmental filters have important implications for forecasting shifts in alpine plant communities under a warming climate.

ecology↗

bioRxiv2022

Disentangling leaf structural and material properties in relation to their anatomical and chemical compositional traits in oaks (Quercus L.)

The existence of sclerophyllous plants has been considered an adaptive strategy against different environmental stresses. As it literally means "hard-leaved", it is essential to quantify the leaf mechanical properties to understand sclerophylly. However, the relative importance of each leaf trait on mechanical properties is not yet well established. The genus Quercus is an excellent system to shed light on this since it minimizes phylogenetic variation while having a wide variation in sclerophylly. Thus, leaf anatomical traits and cell wall composition were measured, analyzing their relationship with LMA and leaf mechanical properties in a set of 25 oak species. Outer wall contributed strongly to leaf mechanical strength. Moreover, cellulose plays a critical role in increasing leaf strength and toughness. The PCA plot based on leaf trait values clearly separated Quercus species into two groups corresponding to evergreen and deciduous species. Sclerophyllous Quercus species are tougher and stronger due to their thicker epidermis outer wall and/or higher cellulose concentration. Furthermore, section Ilex species share common traits regardless of they occupy quite different climates. In addition, evergreen species living in Mediterranean-type climates share common leaf traits irrespective of their different phylogenetic origin.

plant biology↗

bioRxiv2022

No branch left behind: tracking terrestrial biodiversity from a phylogenetic completeness perspective

Biodiversity, as we see it today, ultimately is the outcome of millions of years of evolution; however, biodiversity in its multiple dimensions is changing rapidly due to increasing human domination of Earth. Here, we present the "phylogenetic completeness" (PC) a concept and methodology that intends to safeguard Earths evolutionary heritage by maintaining all branches of the tree of life. We performed a global evaluation of the PC approach using data from five major terrestrial clades and compared the results to an approach in which species are conserved or lost randomly. We demonstrate that under PC, for a given number of species extinctions, it is possible to maximize the protection of evolutionary innovations in every clade. The PC approach is flexible and can be used to conduct a phylogenetic audit of biodiversity under different conservation scenarios. The PC approach complements existing conservation efforts and is linked to the post-2020 Convention of Biodiversity targets.

ecology↗

bioRxiv2022

Tree species and genetic diversity increase productivity via functional diversity and trophic feedbacks

Addressing global biodiversity loss requires an expanded focus on multiple dimensions of biodiversity. While most studies have focused on the consequences of plant interspecific diversity, our mechanistic understanding of how the diversity within a given plant species (genetic diversity) affects plant productivity remains limited. Here, we use a tree species x genetic diversity experiment to disentangle the effects of species diversity and genetic diversity, and how they are related to tree functional diversity and trophic feedbacks. Tree species as well as genetic diversity increased tree productivity via increased tree functional diversity, reduced soil fungal diversity and marginally reduced herbivory. The effect of tree genetic diversity on productivity was partly different between tree species monocultures and mixtures: the functional diversity effect resulting from tree genetic diversity was only found in tree species monocultures, but the trophic feedbacks via herbivory were similar in species monocultures and mixtures. Given the complexity of interactions between tree species and genetic diversity, tree functional diversity and trophic feedbacks on productivity, we suggest that both tree species and genetic diversity should be considered in reforestation.

ecology↗

bioRxiv2021

Remotely detected plant function in two midwestern prairie grassland experiments reveals belowground processes

Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In grassland systems, aboveground and belowground vegetation quantity and quality are coupled, and both influence belowground microbial processes and nutrient cycling, providing a potential link between remote sensing and belowground processes. We hypothesized that ecosystem productivity, and the chemical, structural and phylogenetic-functional composition of plant communities would be detectable with remote sensing and could be used to characterize belowground plant and soil processes in two grassland biodiversity experiments--the BioDIV experiment at Cedar Creek Ecosystem Science Reserve in Minnesota and the Wood River Nature Conservancy experiment in Nebraska. Specifically, we tested whether aboveground vegetation chemistry and productivity, as detected from airborne sensors, predict soil properties microbial processes and community composition. Imaging spectroscopy data were used to map aboveground biomass and green vegetation cover, functional traits and phylogenetic-functional community composition of vegetation. We examined the relationships between the image-derived variables and soil carbon and nitrogen concentration, microbial community composition, biomass and extracellular enzyme activity, and soil processes, including net nitrogen mineralization. In the BioDIV experiment--which has low overall diversity and productivity despite high variation in each--belowground processes were driven mainly by variation in the amount of organic matter inputs to soils. As a consequence, soil respiration, microbial biomass and enzyme activity, and fungal and bacterial composition and diversity were significantly predicted by remotely sensed vegetation cover. In contrast, at Wood River, where plant diversity and productivity were consistently higher, remotely sensed functional, chemical and phylogenetic composition of vegetation predicted belowground extracellular enzyme activity, microbial biomass, and net nitrogen mineralization rates, while aboveground biomass did not. The strong, contrasting associations between the quantity and chemistry of aboveground inputs with belowground soil processes and properties provide a basis for using imaging spectroscopy to understand belowground processes across productivity gradients in grassland systems. However, a mechanistic understanding of how above and belowground components interact among different ecosystems remains critical to extending these results broadly.

ecology↗

bioRxiv2021

Reflectance spectroscopy allows rapid, accurate, and non-destructive estimates of functional traits from pressed leaves

O_LIMore than ever, ecologists seek to employ herbarium collections to estimate plant functional traits from the past and across biomes. However, many trait measurements are destructive, which may preclude their use on valuable specimens. Researchers increasingly use reflectance spectroscopy to estimate traits from fresh or ground leaves, and to delimit or identify taxa. Here, we extend this body of work to non-destructive measurements on pressed, intact leaves, like those in herbarium collections. C_LIO_LIUsing 618 samples from 68 species, we used partial least-squares regression to build models linking pressed-leaf reflectance spectra to a broad suite of traits, including leaf mass per area (LMA), leaf dry matter content (LDMC), equivalent water thickness, carbon fractions, pigments, and twelve elements. We compared these models to those trained on fresh- or ground-leaf spectra of the same samples. C_LIO_LIOur pressed-leaf models were best at estimating LMA (R2 = 0.932; %RMSE = 6.56), C (R2 = 0.855; %RMSE = 9.03), and cellulose (R2 = 0.803; %RMSE = 12.2), followed by water-related traits, certain nutrients (Ca, Mg, N, and P), other carbon fractions, and pigments (all R2 = 0.514-0.790; %RMSE = 12.8-19.6). Remaining elements were predicted poorly (R2 < 0.5, %RMSE > 20). For most chemical traits, pressed-leaf models performed better than fresh-leaf models, but worse than ground-leaf models. Pressed-leaf models were worse than fresh-leaf models for estimating LMA and LDMC, but better than ground-leaf models for LMA. Finally, in a subset of samples, we used partial least-squares discriminant analysis to classify specimens among 10 species with near-perfect accuracy (>97%) from pressed- and ground-leaf spectra, and slightly lower accuracy (>93%) from fresh-leaf spectra. C_LIO_LIThese results show that applying spectroscopy to pressed leaves is a promising way to estimate leaf functional traits and identify species without destructive analysis. Pressed-leaf spectra might combine advantages of fresh and ground leaves: like fresh leaves, they retain some of the spectral expression of leaf structure; but like ground leaves, they circumvent the masking effect of water absorption. Our study has far-reaching implications for capturing the wide range of functional and taxonomic information in the worlds preserved plant collections. C_LI

ecology↗

bioRxiv2021

Canopy spectral reflectance detects oak wilt at the landscape scale using phylogenetic discrimination

The oak wilt disease caused by the invasive fungal pathogen Bretziella fagacearum is one of the greatest threats to oak-dominated forests across the Eastern United States. Accurate detection and monitoring over large areas are necessary for management activities to effectively mitigate and prevent the spread of oak wilt. Canopy spectral reflectance contains both phylogenetic and physiological information across the visible near-infrared (VNIR) and short-wave infrared (SWIR) ranges that can be used to identify diseased red oaks. We develop partial least square discriminant analysis (PLS-DA) models using airborne hyperspectral reflectance to detect diseased canopies and assess the importance of VNIR, SWIR, phylogeny, and physiology for oak wilt detection. We achieve high accuracy through a three-step phylogenetic process in which we first distinguish oaks from other species (90% accuracy), then red oaks from white oaks (Quercus macrocarpa) (93% accuracy), and, lastly, infected from non-infected trees (80% accuracy). Including SWIR wavelengths increased model accuracy by ca. 20% relative to models based on VIS-NIR wavelengths alone; using a phylogenetic approach also increased model accuracy by ca. 20% over a single-step classification. SWIR wavelengths include spectral information important in differentiating red oaks from other species and in distinguishing diseased red oaks from healthy red oaks. We determined the most important wavelengths to identify oak species, red oaks, and diseased red oaks. We also demonstrated that several multispectral indices associated with physiological decline can detect differences between healthy and diseased trees. The wavelengths in these indices also tended to be among the most important wavelengths for disease detection within PLS-DA models, indicating a convergence of the methods. Indices were most significant for detecting oak wilt during late August, especially those associated with canopy photosynthetic activity and water status. Our study suggests that coupling phylogenetics, physiology, and canopy spectral reflectance provides an interdisciplinary and comprehensive approach that enables detection of forest diseases at large scales. These results have potential for direct application by forest managers for detection to initiate actions to mitigate the disease and prevent pathogen spread.

ecology↗

bioRxiv2020

Predicting species distributions and community composition using remote sensing products

Accurate predictions of species composition and diversity are critical to the development of conservation actions and management strategies. In this paper using oak assemblages distributed across the conterminous United States as study model, we assessed the performance of stacked species distribution models (S-SDMs) and remote sensing products in building the next-generation of biodiversity models. This study represents the first attempt to evaluate the integrated predictions of biodiversity models, including assemblage diversity and composition, obtained by stacking next-generation SDMs. We found three main results. First, environmental predictors derived entirely from remote sensing products represent adequate covariates for biodiversity modeling. Second, applying constraints to assemblage predictions, such as imposing the probability ranking rule, results in more accurate species diversity predictions. Third, independent of the stacking procedure (bS-SDM versus cS-SDM), biodiversity models do not recover the observed species composition with high spatial resolution, i.e., correct species identities at the scale of individual plots. However, they do return reasonable predictions at macroecological scales (1 km). Our results provide insights for the prediction of assemblage diversity and composition at different spatial scales. An important task for future studies is to evaluate the reliability of combining S-SDMs with direct detection of species using image spectroscopy to build a new generation of biodiversity models to accurately predict and monitor ecological assemblages through time and space.Competing Interest StatementThe authors have declared no competing interest.View Full Text

ecology↗

bioRxiv2020

Spectral niches reveal taxonomic identity and complementarity in plant communities

Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here we investigate the linkages between plant spectral variation, spectral and resource-use complementarity that contribute to ecosystem productivity. In both a prairie grassland and a forest diversity experiment, we delineated N-dimensional hypervolumes using either wavelength-bands of reflectance spectra or foliar traits. First, we compared the hypervolume fraction unique to each species in either spectral or trait space with increasing dimensionality. Then, we investigated the association between the spectral space occupied by individual plants and their growth, as well as the spectral space occupied by plant communities and ecosystem productivity. We show that species are better distinguished in spectral space than in trait space, providing a conceptual basis for identifying plant taxa spectrally. In addition, the spectral space occupied by individuals increased with plant growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.

ecology↗

bioRxiv2019

Testing Darwin's naturalization conundrum based on taxonomic, phylogenetic and functional dimensions of vascular plants

Charles Darwin posited two alternative hypotheses to explain the success of nonnative species based on their relatedness to incumbent natives: coexistence between them should be (i) more likely with greater relatedness (due to trait similarity that correlates with better matching to the environment), or (ii) less likely (due to biotic interference, such as competition). The paradox raised by the opposing predictions of these two hypotheses has been termed Darwins naturalization conundrum (DNC). Using plant communities measured repeatedly over a 31-year time span across an experimental fire gradient in an oak savanna (Minnesota, USA) we evaluated the DNC by explicitly incorporating taxonomic, functional and phylogenetic information. Our approach was based on focal-species such that the taxonomic, functional and phylogenetic structure of species co-occurring with a given nonnative species in local communities was quantified. We found three main results: first, nonnatives colonizers tended to co-occur most with closely related incumbent natives in recipient communities, except in the extreme ends of the fire gradient (i.e., communities with no fire and those subjected to high fire frequencies); second, with increasing fire frequency, nonnative species were functionally more similar to native species in recipient communities; third, functional similarity of co-occurring nonnatives and natives in recipient communities showed a consistent pattern over time, but the phylogenetic similarity shifted over time, suggesting that external forces (e.g., climate variability) are also relevant in driving the phylogenetic relatedness of nonnatives to natives in invaded communities. Our results provide insights for understanding the invasion dynamics across environmental gradients and highlight the importance of evaluating different dimensions of biodiversity in order to produce more powerful evaluations of species co-occurrence at different spatial and temporal scales.

ecology↗

bioRxiv2019

The results of biodiversity-ecosystem functioning experiments are realistic

A large body of research shows that biodiversity loss can reduce ecosystem functioning, thus providing support for the conservation of biological diversity1-4. Much of the evidence for this relationship is drawn from biodiversity-ecosystem functioning experiments (hereafter: biodiversity experiments), in which biodiversity loss is simulated by randomly assembling communities of varying species diversity, and ecosystem functions are measured5-9. This random assembly has led some ecologists to question the relevance of biodiversity experiments to real-world ecosystems, where community assembly may often be non-random and influenced by external drivers, such as climate or land-use intensification10-18. Despite these repeated criticisms, there has been no comprehensive, quantitative assessment of how experimental and real-world plant communities really differ, and whether these differences invalidate the experimental results. Here, we compare data from two of the largest and longest-running grassland biodiversity experiments globally (Jena Experiment, Germany; BioDIV, USA) to related real-world grassland plant communities in terms of their taxonomic, functional, and phylogenetic diversity and functional-trait composition. We found that plant communities of biodiversity experiments have greater variance in these compositional features than their real-world counterparts, covering almost all of the variation of the real-world communities (82-96%) while also containing community types that are not currently observed in the real world. We then re-analysed a subset of experimental data that included only ecologically-realistic communities, i.e. those comparable to real-world communities. For ten out of twelve biodiversity-ecosystem functioning relationships, biodiversity effects did not differ significantly between the full dataset of biodiversity experiments and the ecologically-realistic subset of experimental communities. This demonstrates that the results of biodiversity experiments are largely insensitive to the inclusion/exclusion of unrealistic communities. By bridging the gap between experimental and real-world studies, these results demonstrate the validity of inferences from biodiversity experiments, a key step in translating their results into specific recommendations for real-world biodiversity management.

ecology↗

bioRxiv2019

Conserved DNA polymorphisms distinguish species in the eastern North American white oak syngameon: Insights from an 80-SNP oak DNA genotyping toolkit

The eastern North American white oaks, a complex of approximately 16 potentially interbreeding species, have become a classic model for studying the genetic nature of species in a syngameon. Genetic work over the past two decades has demonstrated the reality of oak species, but gene flow between sympatric oaks raises the question of whether there are conserved regions of the genome that define oak species. Does gene flow homogenize the entire genome? Do the regions of the genome that distinguish a species in one part of its range differ from the regions that distinguish it in other parts of its range, where it grows in sympatry with different species? Or are there regions of the genome that are relatively conserved across species ranges? In this study, we revisit seven species of the eastern North American white oak syngameon using a set of 80 SNPs selected in a previous study because they show differences among, and consistency within, the species. We test the hypothesis that there exist segments of the genome that do not become homogenized by repeated introgression, but retain distinct alleles characteristic of each species. We undertake a rangewide sampling to investigate whether SNPs that appeared to be fixed based on a relatively small sample in our previous work are fixed or nearly fixed across the range of the species. Each of the seven species remains genetically distinct across its range, given our diagnostic set of markers, with relatively few individuals exhibiting admixture of multiple species. SNPs map back to all 12 Quercus linkage groups (chromosomes) and are separated from each other by an average of 7.47 million base pairs ({+/-} 8.74 million bp, s.d.), but are significantly clustered relative to a random null distribution, suggesting that our SNP toolkit reflects genome-wide patterns of divergence while potentially being concentrated in regions of the genome that reflect a higher-than-average history of among-species divergence. This application of a DNA toolkit designed for the simple problem of identifying species in the field has an important implication: the eastern North American white oak syngameon is composed of entities that most taxonomists would consider \"good species,\" and species in the syngameon retain their genetic cohesion because characteristic portions of the genome do not become homogenized despite a history of introgression.

evolutionary biology↗

bioRxiv2019

Genomic landscape of the global oak phylogeny

O_LIThe tree of life is highly reticulate, with the history of population divergence buried amongst phylogenies deriving from introgression and lineage sorting. In this study, we test the hypothesis that there are regions of the oak (Quercus, Fagaceae) genome that are broadly informative about phylogeny and investigate global patterns of oak diversity.\nC_LIO_LIWe utilize fossil data and restriction-site associated DNA sequencing (RAD-seq) for 632 individuals representing ca. 250 oak species to infer a time-calibrated phylogeny of the worlds oaks. We use reversible-jump MCMC to reconstruct shifts in lineage diversification rates, accounting for among-clade sampling biases. We then map the > 20,000 RAD-seq loci back to a recently published oak genome and investigate genomic distribution of introgression and phylogenetic support across the phylogeny.\nC_LIO_LIOak lineages have diversified among geographic regions, followed by ecological divergence within regions, in the Americas and Eurasia. Roughly 60% of oak diversity traces back to four clades that experienced increases in net diversification due to climatic transitions or ecological opportunity.\nC_LIO_LIThe support we find for the phylogeny contrasts with high genomic heterogeneity in phylogenetic signal and introgression. Oaks are phylogenomic mosaics, and their diversity may in fact depend on the gene flow that shapes the oak genome.\nC_LI

evolutionary biology↗