Refine
Year of publication
- 2020 (22) (remove)
Document Type
- Article (22)
Has Fulltext
- yes (22)
Is part of the Bibliography
- no (22) (remove)
Keywords
- climate change (3)
- Phylogeny (2)
- Animal personality (1)
- Aquilegia (1)
- Behavioral reaction norms (1)
- Behavioral specialization (1)
- Behavioral syndromes (1)
- Behavioral type (1)
- Biodiversity (1)
- Biogeography (1)
Institute
- Biodiversität und Klima Forschungszentrum (BiK-F) (22) (remove)
Vegetation responds to drought through a complex interplay of plant hydraulic mechanisms, posing challenges for model development and parameterization. We present a mathematical model that describes the dynamics of leaf water-potential over time while considering different strategies by which plant species regulate their water-potentials. The model has two parameters: the parameter λ describing the adjustment of the leaf water potential to changes in soil water potential, and the parameter Δψww describing the typical ‘well-watered’ leaf water potentials at non-stressed (near-zero) levels of soil water potential. Our model was tested and calibrated on 110 time-series datasets containing the leaf- and soil water potentials of 66 species under drought and non-drought conditions. Our model successfully reproduces the measured leaf water potentials over time based on three different regulation strategies under drought. We found that three parameter sets derived from the measurement data reproduced the dynamics of 53% of an drought dataset, and 52% of a control dataset [root mean square error (RMSE) < 0.5 MPa)]. We conclude that, instead of quantifying water-potential-regulation of different plant species by complex modeling approaches, a small set of parameters may be sufficient to describe the water potential regulation behavior for large-scale modeling. Thus, our approach paves the way for a parsimonious representation of the full spectrum of plant hydraulic responses to drought in dynamic vegetation models.
The turnover time of terrestrial ecosystem carbon is an emergent ecosystem property that quantifies the strength of land surface on the global carbon cycle–climate feedback. However, observation- and modeling-based estimates of carbon turnover and its response to climate are still characterized by large uncertainties. In this study, by assessing the apparent whole ecosystem carbon turnover times (τ) as the ratio between carbon stocks and fluxes, we provide an update of this ecosystem level diagnostic and its associated uncertainties in high spatial resolution (0.083∘) using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble of data, we estimated the global median τ to be 43+7−7 yr (median+difference to percentile 75−difference to percentile 25) when the full soil is considered, in contrast to limiting it to 1 m depth. Only considering the top 1 m of soil carbon in circumpolar regions (assuming maximum active layer depth is up to 1 m) yields a global median τ of 37+3−6 yr, which is longer than the previous estimates of 23+7−4 yr (Carvalhais et al., 2014). We show that the difference is mostly attributed to changes in global Csoil estimates. Csoil accounts for approximately 84 % of the total uncertainty in global τ estimates; GPP also contributes significantly (15 %), whereas Cveg contributes only marginally (less than 1 %) to the total uncertainty. The high uncertainty in Csoil is reflected in the large range across state-of-the-art data products, in which full-depth Csoil spans between 3362 and 4792 PgC. The uncertainty is especially high in circumpolar regions with an uncertainty of 50 % and a low spatial correlation between the different datasets (0.2<r<0.5) when compared to other regions (0.6<r<0.8). These uncertainties cast a shadow on current global estimates of τ in circumpolar regions, for which further geographical representativeness and clarification on variations in Csoil with soil depth are needed. Different GPP estimates contribute significantly to the uncertainties of τ mainly in semiarid and arid regions, whereas Cveg causes the uncertainties of τ in the subtropics and tropics. In spite of the large uncertainties, our findings reveal that the latitudinal gradients of τ are consistent across different datasets and soil depths. The current results show a strong ensemble agreement on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30–60∘ N) than in the subtropical and tropical zones (30∘ S–30∘ N). Additionally, while the strength of the τ–precipitation correlation was dependent on the Csoil data source, the latitudinal gradients also agree among different ensemble members. Overall, and despite the large variation in τ, we identified robust features in the spatial patterns of τ that emerge beyond the differences stemming from the data-driven estimates of Csoil, Cveg and GPP. These robust patterns, and associated uncertainties, can be used to infer τ–climate relationships and for constraining contemporaneous behavior of Earth system models (ESMs), which could contribute to uncertainty reductions in future projections of the carbon cycle–climate feedback. The dataset of τ is openly available at https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
The turnover time of terrestrial carbon (τ) controls the global carbon cycle – climate feedback and, yet, is poorly simulated by the current Earth System Models (ESMs). In this study, by assessing apparent carbon turnover time as the ratio between carbon stocks and fluxes, we provide a new, updated ensemble of diagnostic terrestrial carbon turnover times and associated uncertainties on a global scale using multiple, state-of-the-art, observation-based datasets of soil organic carbon stock (Csoil), vegetation biomass (Cveg) and gross primary productivity (GPP). Using this new ensemble, we estimated the global average τ to be 42$% &' years when the full soil depth is considered, longer than the previous estimates of 23$) &* years. Only considering the top 1 m (assuming maximum active layer depth is up to 1 meter) of soil carbon in circumpolar regions yields a global τ of 35$) &' years. Csoil in circumpolar regions account for two thirds of the total uncertainty in global τ estimates, whereas Csoil in non-circumpolar contributes merely 9.38%. GPP (2.25%) and Cveg (0.05%) contribute even less to the total uncertainty. Therefore, the high uncertainty in Csoil is the main factor behind the uncertainty in global τ, as reflected in the larger range of full-depth Csoil (3152-4372 PgC). The uncertainty is especially high in circumpolar regions with a behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI: 10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019) uncertainty of 50% and the spatial correlations among different datasets are also low compared to other regions. Overall, we argue that current global datasets do not support robust estimates of τ globally, for which we need clarification on variations of Csoil with soil depth and stronger estimates of Csoil in circumpolar regions. Despite the large variation in both magnitude and spatial patterns of τ, we identified robust features in the spatial patterns of τ that emerge regardless of soil depth and differences in data sources of Csoil, Cveg and GPP. Our findings show that the latitudinal gradients of τ are consistent across different datasets and soil depth. Furthermore, there is a strong consensus on the negative correlation between τ and temperature along latitude that is stronger in temperate zones (30ºN-60ºN) than in subtropical and tropical zones (30ºS30ºN). The identified robust patterns can be used to infer the response of τ to climate and for constraining contemporaneous behaviour of ESMs which could contribute to uncertainty reductions in future projections of the carbon cycle - climate feedback. The dataset of the terrestrial turnover time ensemble (DOI:10.17871/bgitau.201911) is openly available from the data portal: https://doi.org/10.17871/bgitau.201911 (Fan et al., 2019).
To support future research based on natural sciences collection data, DiSSCo (Distributed System of Scientific Collections) – the European Research Infrastructure for Natural Science Collections – adopts Digital Object Architecture as the basis for its planned data infrastructure. Using the outputs of one Research Data Alliance (RDA) interest group (IG) and five working groups (WGs) we show how RDA recommendations and supporting documents have been applied to the various stages of the DiSSCo data lifecycle.
Abstract
Divergence is mostly viewed as a progressive process often initiated by selection targeting individual loci, ultimately resulting in ever increasing genomic isolation due to linkage. However, recent studies show that this process may stall at intermediate stable equilibrium states without achieving complete genomic isolation. We tested the extent of genomic isolation between two recurrently hybridizing nonbiting midge sister taxa, Chironomus riparius and Chironomus piger, by analyzing the divergence landscape. Using a principal component‐based method, we estimated that only about 28.44% of the genomes were mutually isolated, whereas the rest was still exchanged. The divergence landscape was fragmented into isolated regions of on average 30 kb, distributed throughout the genome. Selection and divergence time strongly influenced lengths of isolated regions, whereas local recombination rate only had minor impact. Comparison of divergence time distributions obtained from several coalescence‐simulated divergence scenarios with the observed divergence time estimates in an approximate Bayesian computation framework favored a short and concluded divergence event in the past. Most divergence happened during a short time span about 4.5 million generations ago, followed by a stable equilibrium between mutual gene flow through ongoing hybridization for the larger part of the genome and isolation in some regions due to rapid purifying selection of introgression, supported by high effective population sizes and recombination rates.
Impact Summary
The process of speciation has fascinated biologists from early on. Prevailing theory suggested that gene flow among populations is the main obstacle for their divergence. Recently, it became clear that speciation with gene flow is possible under certain circumstances. However, it remains unclear how the divergence process proceeds in time, how widespread the phenomenon is, and whether it always and inevitably leads to complete isolation. Comparing the genomes of individuals of two regularly hybridizing sister taxa of nonbiting midges, we could show that they diverged during a short period millions of generations ago. Their divergence process apparently ceased before the entire genome was mutually isolated. The taxa remain distinct since, even though they share most of their genome. Our findings thus extend our view of the nature of species and the temporal dynamics of their divergence and describe novel approaches to analyze both current and past divergence processes.
In search for practical silvicultural management tools to identify alternative tree species for predicted Central European climate conditions, a cross-species survey with five evergreen, semi-evergreen, and deciduous Quercus taxa with contrasting morphological leaf traits was performed. Fast chlorophyll fluorescence induction of PSII and relative leaf chlorophyll contents were performed to assess the overall plant vitality at any point in time during two complete vegetation periods in consecutive years (2012 and 2013). Maximum photochemical efficiency of PSII and the performance index on absorption base showed a very conservative relationship to each other and a similar intra-annual progress in all deciduous species, but with a different speed of increase and decrease during leaf development and senescence and thus a different length of vegetation period. The intra-annual variability of OJIP and chlorophyll content parameters is considered with respect to the practicability of measurements in the field for management purposes.
Social insects dominate arthropod communities worldwide due to cooperation and division of labor in their societies. This, however, makes them vulnerable to exploitation by social parasites, such as slave‐making ants. Slave‐making ant workers pillage brood from neighboring nests of related host ant species. After emergence, host workers take over all nonreproductive colony tasks, whereas slavemakers have lost the ability to care for themselves and their offspring. Here, we compared transcriptomes of different developmental stages (larvae, pupae, and adults), castes (queens and workers), and sexes of two related ant species, the slavemaker Temnothorax americanus and its host Temnothorax longispinosus. Our aim was to investigate commonalities and differences in group‐specific transcriptomes, whereupon across‐species differences possibly can be explained by their divergent lifestyles. Larvae and pupae showed the highest similarity between the two species and upregulated genes with enriched functions of translation and chitin metabolism, respectively. Workers commonly upregulated oxidation‐reduction genes, possibly indicative of their active lifestyle. Host workers, but not workers of the slavemaker, upregulated a “social behavior” gene. In slavemaker queens and workers, genes associated with the regulation of transposable elements were upregulated. Queens of both species showed transcriptomic signals of anti‐aging mechanisms, with hosts upregulating various DNA repair pathways and slavemaker queens investing in trehalose metabolism. The transcriptomes of males showed enriched functions for quite general terms realized in different genes and pathways in each species. In summary, the strong interspecific commonalities in larvae, pupae, and workers were reflected in the same enriched Gene Ontology (GO) terms. Less commonalities occurred in the transcriptomes of queens and males, which apparently utilize different pathways to achieve a long life and sperm production, respectively. We found that all analyzed groups in this study show characteristic GO terms, with similar patterns in both species.
Microthlaspi erraticum is widely distributed in temperate Eurasia, but restricted to Ca2+-rich habitats, predominantly on white Jurassic limestone, which is made up by calcium carbonate, with little other minerals. Thus, naturally occurring Microthlaspi erraticum individuals are confronted with a high concentration of Ca2+ ions while Mg2+ ion concentration is relatively low. As there is a competitive uptake between these two ions, adaptation to the soil condition can be expected. In this study, it was the aim to explore the genomic consequences of this adaptation by sequencing and analysing the genome of Microthlaspi erraticum. Its genome size is comparable with other diploid Brassicaceae, while more genes were predicted. Two Mg2+ transporters known to be expressed in roots were duplicated and one showed a significant degree of positive selection. It is speculated that this evolved due to the pressure to take up Mg2+ ions efficiently in the presence of an overwhelming amount of Ca2+ ions. Future studies on plants specialized on similar soils and affinity tests of the transporters are needed to provide unequivocal evidence for this hypothesis. If verified, the transporters found in this study might be useful for breeding Brassicaceae crops for higher yield on Ca2+-rich and Mg2+ -poor soils.
Animal tracking and biologging devices record large amounts of data on individual movement behaviors in natural environments. In these data, movement ecologists often view unexplained variation around the mean as “noise” when studying patterns at the population level. In the field of behavioral ecology, however, focus has shifted from population means to the biological underpinnings of variation around means. Specifically, behavioral ecologists use repeated measures of individual behavior to partition behavioral variability into intrinsic among-individual variation and reversible behavioral plasticity and to quantify: a) individual variation in behavioral types (i.e. different average behavioral expression), b) individual variation in behavioral plasticity (i.e. different responsiveness of individuals to environmental gradients), c) individual variation in behavioral predictability (i.e. different residual within-individual variability of behavior around the mean), and d) correlations among these components and correlations in suites of behaviors, called ‘behavioral syndromes’. We here suggest that partitioning behavioral variability in animal movements will further the integration of movement ecology with other fields of behavioral ecology. We provide a literature review illustrating that individual differences in movement behaviors are insightful for wildlife and conservation studies and give recommendations regarding the data required for addressing such questions. In the accompanying R tutorial we provide a guide to the statistical approaches quantifying the different aspects of among-individual variation. We use movement data from 35 African elephants and show that elephants differ in a) their average behavior for three common movement behaviors, b) the rate at which they adjusted movement over a temporal gradient, and c) their behavioral predictability (ranging from more to less predictable individuals). Finally, two of the three movement behaviors were correlated into a behavioral syndrome (d), with farther moving individuals having shorter mean residence times. Though not explicitly tested here, individual differences in movement and predictability can affect an individual’s risk to be hunted or poached and could therefore open new avenues for conservation biologists to assess population viability. We hope that this review, tutorial, and worked example will encourage movement ecologists to examine the biology of individual variation in animal movements hidden behind the population mean.