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opencc-zeroNov 2021View details →

Relaxed feeding constraints facilitate the evolution of mouthbrooding in Neotropical cichlids

Multifunctionality is often framed as a core constraint of phenotypic evolution. Mouthbrooding, a form of parental care where offspring develop inside a parent's mouth, increases multifunctionality by adding a major function (reproduction) to a structure already serving other vital functions (feeding and respiration). Despite increasing multifunctionality, mouthbrooding has evolved repeatedly from other forms of parental care in at least 7 fish families. We hypothesized that mouthbrooding is more likely to evolve in lineages with feeding adaptations that are already advantageous for mouthbrooding. We tested this hypothesis in Neotropical cichlids, where mouthbrooding has evolved 4–5 times, largely within winnowing clades, providing several pairwise comparisons between substrate brooding and mouthbrooding sister taxa. We found that the mouthbrooding transition rate was 15 times higher in winnowing than in non-winnowing clades, and that mouthbrooders and winnowers overlapped substantially in their buccal cavity morphologies, which is where offspring are incubated. Species that exhibit one or both of these behaviors had larger, more curved buccal cavities, while species that exhibit neither behavior had narrow, cylindrical buccal cavities. Given the results we present here, we propose a new model for the evolution of mouthbrooding, integrating the roles of multifunctional morphology and the environment.

openother-openDec 2021View details →

Erratum: Constraints on dark matter-nucleon effective couplings in the presence of kinematically distinct halo substructures using the DEAP-3600 detector [Phys. Rev. D 102, 082001 (2020)]

Corrections to the results from O3 operator in <a href="https://journals.aps.org/prd/abstract/10.1103/PhysRevD.102.082001">Phys. Rev. D 102, 082001</a>. "Constraints on dark matter-nucleon effective couplings in the presence of kinematically distinct halo substructures using the DEAP-3600 detector".

opencc-by-4.0Feb 2022View details →

New constraints for slip rates along the Altyn Tagh fault, northwestern Tibet Plateau

High-resolution UAV data (DEM and DOM)

opencc-by-4.0Mar 2022View details →

Data of glaciological property constraints for fractures in FRIS

This dataset is applied to set the glaciological property-based constraints for fractures extracted in FRIS. The dataset includes: (1) Outer boundaries of ice rises and ice rumples in FRIS and the corresponding buffer zones, which is modified from Inventory of Antarctic ice rises and rumples (Matsuoka et al., 2015). (2) Ice velocity maps of FRIS, including x and y component of ice velocity, which is generated based on MEaSUREs InSAR-Based Antarctica Ice Velocity Map (Version 2) (Mouginot et al., 2017).

opencc-by-4.0Mar 2022View details →

Data: Physical constraints on thermoregulation and flight drive morphological evolution in bats

Body size and shape fundamentally determine organismal energy requirements by modulating heat and mass exchange with the environment and the costs of locomotion, thermoregulation, and maintenance. Ecologists have long used the physical linkage between morphology and energy balance to explain why the body size and shape of many organisms vary across climatic gradients, e.g., why larger endotherms are more common in colder regions. However, few modeling exercises have aimed at investigating this link from first principles. Body size evolution in bats contrasts with the patterns observed in other endotherms, probably because physical constraints on flight limit morphological adaptations. Here, we develop a biophysical model based on heat transfer and aerodynamic principles to investigate energy constraints on morphological evolution in bats. Our biophysical model predicts that the energy costs of thermoregulation and flight, respectively, impose upper and lower limits on the relationship of wing surface area to body mass (S-MR), giving rise to an optimal S-MR at which both energy costs are minimized. A comparative analysis of 278 species of bats supports the model’s prediction that S-MR evolves toward an optimal shape and that the strength of selection is higher among species experiencing greater energy demands for thermoregulation in cold climates. Our study suggests that energy costs modulate the mode of morphological evolution in bats—hence shedding light on a long-standing debate over bats’ conformity to ecogeographical patterns observed in other mammals—and offers a procedure for investigating complex macroecological patterns from first principles.

opencc-by-4.0Apr 2022View details →

RICE WHEAT CROPPING SYSTEMS-CONSTRAINTS AND STRATEGIES : A REVIEW

The rice-wheat cropping system (RWCS) in the Indo-Gangetic plains (IGP) of South Asia with the help of Green Revolution in the early 1970’s greatly contributed to India's food self-sufficiency and livelihood of millions of peoplethus, became the country's primary source of food-grain production. However, deterioration of soil health and quality, ground water depletion, water stress, labour shortage, introduction of new weeds and pests particularly Phalaris minor, Scirpophaga incertulas and climate change have all contributed to a major production standstill and deterioration in recent years by which the sustainability of rice wheat cropping system is now at jeopardy. Traditional agronomic practices had various negative implications on the sustainability of rice wheat cropping system with the introduction of HYVs. So, a paradigm shift is required to achieve long-term productivity, sustainability and allow farmers to minimise inputs, optimise yields, enhance profitability, maintain the natural resource base and reduce risk owing to both environmental and economic issues through resource-conserving technologies (RCTs) including zero/minimaltillage, PUSA decomposer, bed planting, crop residue management, mechanical rice transplanter (MRT) and crop diversification. This article focuses some of the issues that need to be addressed in the RWCS in order to achieve the goal of increasing regional productivity and assuring food security while maximising the effective use of natural resources, enhancing rural livelihoods and aiding in poverty alleviation.

opencc-zeroMay 2022View details →

Climatic history, constraints, and the plasticity of phytochemical traits under water stress

Environmental stress can induce changes in organismal traits and in resulting intraspecific variation. The nature of such effects will depend on the plasticity of trait expression and on any ecological constraints to such expression. Plants can mitigate abiotic stress, like drought, by changing their chemistry, but the ability to induce costly metabolites may be under strong local selection and ecologically constrained. Here we asked whether climate at the seed source predicts plant chemical plasticity in response to water stress and what the consequences are for intraspecific variation in phytochemical traits. To this end, we used common gardens of two widespread species of western milkweed (Asclepias fascicularis and Asclepias speciosa) that had been collected from sites across an aridity gradient. Both species produce high concentrations of leaf flavonols, which are hypothesized to mitigate water stress by functioning as antioxidants. These compounds were found in higher constitutive concentrations in plants sourced from drier sites, and both species responded to water stress in the common garden by increasing leaf flavonol concentrations. Interestingly, flavonol plasticity was higher in plants sourced from wetter sites in A. fascicularis, with similar, but weaker, patterns in A. speciosa. These opposing patterns in constitutive and induced flavonol expression reduced the variation between populations in leaf flavonol concentrations under water stress. These results suggest that local adaptation in plants can shape phytochemical strategies for water limitation but that the cost of metabolite production may ultimately limit the range of phytochemical variation.

opencc-zeroMay 2022View details →

Nest choice in arboreal ants is an emergent consequence of network creation under spatial constraints

Biological transportation networks must balance competing functional priorities. The self-organizing mechanisms used to generate such networks have inspired scalable algorithms to construct and maintain low-cost and efficient human-designed transport networks. The pheromone-based trail networks of ants have been especially valuable in this regard. Here, we use turtle ants as our focal system: In contrast to the ant species usually used as models for self-organized networks, these ants live in a spatially constrained arboreal environment where both nesting options and connecting pathways are limited. Thus, they must solve a distinct set of challenges which resemble those faced by human transport engineers constrained by existing infrastructure. Here, we ask how a turtle ant colony's choice of which nests to include in a network may be influenced by their potential to create connections to other nests. In laboratory experiments with Cephalotes varians and Cephalotes texanus, we show that nest choice is influenced by spatial constraints, but in unexpected ways. Under one spatial configuration, colonies preferentially occupied more connected nest sites; however, under another spatial configuration, this preference disappeared. Comparing the results of these experiments to an agent-based model, we demonstrate that this apparently idiosyncratic relationship between nest connectivity and nest choice can emerge without nest preferences via a combination of self-reinforcing random movement along constrained pathways and density-dependent aggregation at nests. While this mechanism does not consistently lead to the de-novo construction of low-cost, efficient transport networks, it may be an effective way to expand a network, when coupled with processes of pruning and restructuring.

opencc-by-4.0Jun 2022View details →

Convergence in phosphorus constraints to photosynthesis dataset - modelling results

The archive contains the extract of model results shown in the publication 'Convergence in phosphorus constraints to photosynthesis' by David Ellsworth et al. in Nature Communication. README: # Simulation results from ORCHIDEE LSM v1.2 (https://doi.org/10.14768/20200407002.1) # time period: 1992-2021 # author: Daniel Goll (dsgoll123@gmail.com) # the following variables are found in these files: # GPP [g/m2/yr]                                         -> gpp.nc # POTENTIAL GPP (assuming maximum P content) [g/m2/yr]  -> gpp_pot_max.nc # POTENTIAL GPP (assuming average P content) [g/m2/yr]  -> gpp_pot_avg.nc # LEAF N:P RATIO [g/g]                                  -> leafNP.nc

opencc-by-4.0May 2021View details →

Global input datasets for use in constraints on global seafloor biogenic methane production from deterministic and machine learning modeling

This dataset includes 9 grids used as model input for manuscript "Constraints on global seafloor biogenic methane production from deterministic and machine learning modeling". Additionally, there are four grids (heat flow, total organic carbon, porosity, and crust age) for which variable uncertainty was given. Grids here are available in xyz (longitude in decimal degrees, latitude in decimal degrees, and variable) ascii file format. Each reference is below is the grids native reference. For more information on the creation of these grids please visit the main manuscript. Below are respective file names and variable name/units: Dataset 1: Elevation in Meters (+ indicates above sea level, - below sea level) Tozer, B., Sandwell, D. T., Smith, W. H. F., Olson, C., Beale, J. R., & Wessel, P. (2019). Global bathymetry and topography at 15 arc sec: SRTM15+. Earth and Space Science, 6. https://doi.org/10.1029/ 2019EA000658 Dataset 2: Seawater Density in Kilograms per Cubic Meter Boyer, T. P., Antonov, J. I., Baranova, O. K., Garcia, H. E., Johnson, D. R., Mishonov, A. V., … Grodsky, A. (2013). World Ocean Database 2013. In S. Levitus, A. Mishonov (Ed.), Technical Ed.; NOAA Atlas NESDIS 72 (pp. 209). Dataset 3: Seawater Temperature in Degrees Celcius  Boyer, T. P., Antonov, J. I., Baranova, O. K., Garcia, H. E., Johnson, D. R., Mishonov, A. V., … Grodsky, A. (2013). World Ocean Database 2013. In S. Levitus, A. Mishonov (Ed.), Technical Ed.; NOAA Atlas NESDIS 72 (pp. 209). Dataset 4: Seawater Salinity in Percent Salinity Units Boyer, T. P., Antonov, J. I., Baranova, O. K., Garcia, H. E., Johnson, D. R., Mishonov, A. V., … Grodsky, A. (2013). World Ocean Database 2013. In S. Levitus, A. Mishonov (Ed.), Technical Ed.; NOAA Atlas NESDIS 72 (pp. 209). Dataset 5: Heat Flow in Milliwatts per Square Meter Global Heat Flow Compilation Group (2013). Component parts of the World Heat Flow Data Collection. PANGAEA, https://doi.org/10.1594/PANGAEA.810104 Hornbach, M. J., Harris, R. N. & Phrampus, B. J. (2020). Heat flow on the U.S. Beaufort Margin, Arctic Ocean: Implications for ocean warming, methane hydrate stability, and regional tectonics. Geochemistry, Geophysics, Geosystems, 21(5). e2020GC008933. https://doi.org/10.1029/2020GC008933 Dataset 6: Sediment Thickness in Meters Straume, E. O., Gaina, C., Medvedev, S., Hochmuth, K., Gohl, K., Whittaker, J. M., … Hopper, J. R. (2019). GlobSed: updated total sediment thickness in the world’s oceans. Geochemistry, Geophysics, Geosystems, 20(4), 1756–1772. Dataset 7: Seafloor Porosity in Fraction Martin, K. M., Wood, W. T., & Becker, J. J. (2015). A global prediction of seafloor sediment porosity using machine learning. Geophysical Research Letters, 42(24), 2015GL065279. https://doi.org/10.1002/2015GL065279 Dataset 8: Seafloor Total Organic Carbon in Percent Dry Weight Lee, T.R., Wood, W.T., & Phrampus, B.J. (2019). A machine learning (kNN) approach to predicting global seafloor total organic carbon. Global Biogeochemical Cycles. 33, 37–46, doi:10.1029/2018GB005992. Dataset 9: Crust Age in Million Years Müller, R. D., Sdrolias, M., Gaina, C., & Roest, W. R. (2008). Age, spreading rates, and spreading asymmetry of the world’s ocean crust. Geochemistry, Geophysics, Geosystems, 9, Q04006. https://doi.org/10.1029/2007GC001743 Dataset 10: Seafloor Porosity Uncertainty in Fraction Dataset 11: Seafloor Total Organic Carbon Uncertainty in Percent Dry Weight Lee, T.R., Wood, W.T., & Phrampus, B.J. (2019). A machine learning (kNN) approach to predicting global seafloor total organic carbon. Global Biogeochemical Cycles. 33, 37–46, doi:10.1029/2018GB005992. Dataset 12: Heat Flow Uncertainty in Milliwatts per Square Meter Dataset 13: Crust Age Uncertainty in Million Years Müller, R. D., Sdrolias, M., Gaina, C., & Roest, W. R. (2008). Age, spreading rates, and spreading asymmetry of the world’s ocean crust. Geochemistry, Geophysics, Geosystems, 9, Q04006. https://doi.org/10.1029/2007GC001743

opencc-zeroJun 2022View details →

Clumped-isotope constraint on upper-tropospheric cooling during the Last Glacial Maximum

Ice cores and other paleotemperature proxies, together with general circulation models, have provided information on past surface temperatures and the atmosphere's composition in different climates. Little is known, however, about past temperatures at high altitudes, which play a crucial role in Earth's radiative energy budget. Paleoclimate records at high-altitude sites are sparse, and the few that are available show poor agreement with climate model predictions. These disagreements could be due to insufficient spatial coverage, spatiotemporal biases, or model physics; new records that can mitigate or avoid these uncertainties are needed. Here, we constrain the change in upper-tropospheric temperature at the global scale during the Last Glacial Maximum (LGM) using the clumped-isotope composition of molecular oxygen trapped in polar ice cores. Aided by global three-dimensional chemical transport modeling, we exploit the intrinsic temperature sensitivity of the clumped-isotope composition of atmospheric oxygen to infer that the upper troposphere (effective mean altitude 10 – 11 km) was 6-9ºC cooler during the LGM than during the late preindustrial Holocene. A complementary energy balance approach supports a minor or negligible steepening of atmospheric lapse rates during the LGM, which is consistent with a range of climate model simulations. Proxy-model disagreements with other high-altitude records may stem from inaccuracies in regional hydroclimate simulation, possibly related to land-atmosphere feedbacks.

opencc-zeroJul 2022View details →

Data from: Convergence and constraint in the cranial evolution of mosasaurid reptiles and early cetaceans

The repeated return of tetrapods to aquatic life provides some of the best-known examples of convergent evolution. One comparison which has received relatively little focus is that of mosasaurids (a group of Late Cretaceous squamates) and archaic cetaceans (the ancestors of modern whales and dolphins), both of which show high levels of craniodental disparity, similar initial trends in locomotory evolution, and global distributions. Here we investigate convergence in skull ecomorphology during the initial aquatic radiations of these groups. A series of functionally informative ratios were calculated from 38 species, with ordination techniques used to reconstruct patterns of functional ecomorphospace occupation. The earliest fully aquatic members of each clade occupied different regions of ecomorphospace, with basilosaurids and early russellosaurines exhibiting marked differences in cranial functional morphology. Subsequent ecomorphological trajectories notably diverge: mosasaurids radiated across ecomorphospace with no clear pattern and numerous reversals, whereas cetaceans notably evolved towards shallower, more elongated snouts, perhaps as an adaptation for capturing smaller prey. Incomplete convergence between the two groups is present among megapredatory and longirostrine forms, suggesting stronger selection on cranial function in these two ecomorphologies. Our study highlights both the similarities and divergences in craniodental evolutionary trajectories between archaic cetaceans and mosasaurids, with convergences transcending their deeply divergent phylogenetic affinities.

opencc-by-nc-4.0Oct 2022View details →

Breaking the constraint on the number of cervical vertebrae in mammals: on homeotic transformations in lorises and pottos

Data-collection Specimens. We analysed 1090 skeletons of wild-born primates belonging to 60 species of ten families (Table 1). These skeletons are held in collections of ten European and American natural history museums (Naturalis Biodiversity Center, Leiden (Naturalis); The Natural History Museum, London (NHMUK); the Royal Museum for Central Africa, Tervuren (RMCA); the Royal Belgian Institute of Natural Sciences, Brussels (RBINS); the Natural History Museum of Denmark, Copenhagen (ZMUC); Naturhistorisches Museum Wien, Vienna (NHMW); the Swedish Museum of Natural History, Stockholm (NRM); Museum fur Naturkunde, Berlin (MfN); and the National Museum for Natural History, Paris (MNHN), Natural History Museum Oslo, American Museum of Natural History, New York, Field Museum of Natural History, Chicago (FMNH). Five families belonged to the Strepsirrhini (Lorisidae, Galagidae, Daubentoniidae, Lemuridae, Indriidae) and five to the Haplorrhini, of which two Platyrrhini (Cebidae, Atelidae) and three Catarrhini (Cercopithecidae, Hylobatidae, Hominidae). Cervical vertebrae and transitional cervicothoracic vertebrae. We determined the number of cervical vertebrae and transitional cervicothoracic vertebrae (vertebrae with both cervical and thoracic characteristics, i.e. a seventh vertebrae with a rudimentary rib or one full rib instead of two, or an eighth vertebrae with rudimentary ribs or without ribs on one side). The identification of transitional cervicothoracic vertebrae was based on the presence of cervical or rudimentary first ribs. In the case of a fusion of rudimentary cervical ribs with the transverse process (apophysomegaly), the vertebra was counted as a transitional cervicothoracic vertebra when the transverse process was at least 15% longer than that of the first thoracic vertebra, or when traces of the articulation were still visible. Explanatory variables. Per specimen where we determined the vertebral pattern, we recorded the species, life style ("fast" vs. "slow"), individual age class and sex and whether the animal was kept in a zoo later in life or not. This last indicator variable can accommodate effects of relaxed selection in captive environments on the probability of finding an abnormal pattern. Phylogeny. We used the consensus phylogeny of primates provided by the 10k Trees Project (Arnold & Nunn, 2010) to represent our data per species graphically and to calculate correlations between species effects Statistical analysis. The R script with our analysis is added.

opencc-by-4.0Apr 2024View details →

Key dataset used in the paper of "Emergent constraints reveal lower estimates of global river flow"

This dataset includes key data used in the emergent constraint approach for refined partitioning of global water cycle components.

opencc-zeroJun 2024View details →

Data from: Designing eco-evolutionary experiments for restoration projects: Opportunities and constraints revealed during Stickleback introductions

Eco-evolutionary experiments are typically conducted in semi-unnatural controlled settings, such as mesocosms; yet inferences about how evolution and ecology interact in the real world would surely benefit from experiments in natural uncontrolled settings. Opportunities for such experiments are rare but do arise in the context of restoration ecology – where different "types" of a given species can be introduced into different "replicate" locations. Designing such experiments requires wrestling with consequential questions. Q1. Which specific "types" of a focal species should be introduced to the restoration location? Q2. How many sources of each type should be used – and should they be mixed together? Q3. Which specific source populations should be used? Q4. Which type or population(s) should be introduced into which restoration sites? We recently grappled with these questions when designing an eco-evolutionary experiment with threespine stickleback (Gasterosteus aculeatus) introduced into nine small lakes and ponds on the Kenai Peninsula in Alaska that required restoration. After considering the options at length, we decided to use benthic versus limnetic ecotypes (Q1) from a mixture of four source populations of each ecotype (Q2) selected based on trophic morphology (Q3), and introduced into restoration lakes in a paired design (Q4). We hope that the present paper outlining the alternatives and resulting choices will provide the rationales clear for future studies leveraging our experiment, while also proving useful for investigators considering similar experiments in the future.

Fig. 9 in Constraints on Phylogenetic Interrelationships among Four Free-living Litostomatean Lineages Inferred from 18S rRNA gene-ITS Region sequences and Secondary Structure of the ITS2 molecule

Fig. 9. Evolutionary hypothesis of interrelationships among the four free-living litostomatean lineages studied. This scenario was suggested on the basis of morphology and the consensus secondary structure of the ITS2 molecules. CK – circumoral kinety, DB – dorsal brush, OB – oral bulge, OO – oral bulge opening, P – proboscis, PE – perioral kinety, PR – preoral kineties, SK – somatic kineties.

Fig. 5 in Constraints on Phylogenetic Interrelationships among Four Free-living Litostomatean Lineages Inferred from 18S rRNA gene-ITS Region sequences and Secondary Structure of the ITS2 molecule

Fig. 5. Quartet likelihood-mapping showing distribution of phylogenetic signal in the 18S-A and the CON-1 alignment for three possible relationships among the four main free-living litostomatean lineages studied. The corners of the triangles show the percentage of fully resolved trees, i.e., phylogenetically informative signal. The rectangular areas show the percentage of trees that are in conflict. The central triangle shows the percentage of unresolved star-like trees, i.e., phylogenetically uninformative signal. Coding of free-living litostomatean lineages: H – Haptorida, P – Pleurostomatida, R – Rhynchostomatia, S – Spathidiida.

Fig. 4 in Constraints on Phylogenetic Interrelationships among Four Free-living Litostomatean Lineages Inferred from 18S rRNA gene-ITS Region sequences and Secondary Structure of the ITS2 molecule

Fig. 4. Super-network of 66 free-living litostomatean taxa constructed from 80 randomly selected post-burn-in trees from the Bayesian inference of the 18S-A–D, ITSR-C and ITSR-D as well as the CON-1 and CON-2 alignments. The super-network was constructed in the program SplitsTree, using the Z-closure option, tree size weighted mean, ten runs, and the refined heuristic technique. For details on taxa and characteristics of the alignments analyzed, see Supplementary Table S1 and S2.

Fig. 3 in Constraints on Phylogenetic Interrelationships among Four Free-living Litostomatean Lineages Inferred from 18S rRNA gene-ITS Region sequences and Secondary Structure of the ITS2 molecule

Fig. 3. Phylogeny based on the 18S rRNA gene and the ITS1-5.8S-ITS2 region of 56 free-living litostomatean taxa (alignment CON-1). Posterior probabilities for the Bayesian inference and bootstrap values for maximum likelihood were mapped onto the 50% majority rule ML tree. Dashes indicate posterior probabilities below 0.50 and ML bootstrap values below 50%. The scale bar indicates five substitutions per ten nucleotide positions. For details on taxa, evolutionary model used, and characteristics of the CON-1 alignment, see Supplementary Table S1 and S2.

Fig. 1 in Constraints on Phylogenetic Interrelationships among Four Free-living Litostomatean Lineages Inferred from 18S rRNA gene-ITS Region sequences and Secondary Structure of the ITS2 molecule

Fig. 1. Phylogeny based on the 18S rRNA gene of 64 free-living litostomatean taxa (alignment 18S-A). Posterior probabilities for Bayesian inference and bootstrap values for maximum likelihood were mapped onto the 50% majority rule Bayesian consensus tree. Dashes indicate ML bootstrap values below 50%. Sequences in bold were obtained during this study. The scale bar indicates two substitutions per one hundred nucleotide positions. For details on taxa, evolutionary model used, and characteristics of the 18S-A alignment, see Supplementary Table S1 and S2.