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opencc-by-4.0Jan 2021View details →

Molecular Simulations of Lipid Membrane Partitioning and Translocation by Bacterial Quorum Sensing Modulators

All simulation data and analysis tools for regenerating results from the journal paper: T. Jin, S. J. Patel, and R. C. Van Lehn. “Molecular simulations of lipid membrane partitioning and translocation by bacterial quorum sensing modulators.” PLOS ONE, accepted.

opencc-zeroDec 2013View details →

Data from: Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes

Navigational ability is a critical component of an animal's spatial ecology and may influence the invasive potential of species. Burmese pythons (Python molurus bivittatus) are apex predators invasive to South Florida. We tracked the movements of 12 adult Burmese pythons in Everglades National Park, six of which were translocated 21–36 km from their capture locations. Translocated snakes oriented movement homeward relative to the capture location, and five of six snakes returned to within 5 km of the original capture location. Translocated snakes moved straighter and faster than control snakes and displayed movement path structure indicative of oriented movement. This study provides evidence that Burmese pythons have navigational map and compass senses and has implications for predictions of spatial spread and impacts as well as our understanding of reptile cognitive abilities.

opencc-zeroDec 2014View details →

Data from: Ecological relevance of energy metabolism: transcriptional responses in energy sensing and expenditure to thermal and osmotic stresses in an intertidal limpet

For rocky intertidal species that experience changes in a number of potential stressors seasonally and during the tidal cycle, sensing cellular energy status and modulating it adaptively may be crucial for responding to stressor effects. However, the responses of energy metabolism of intertidal species to multiple sublethal stressors are still unclear. Here, we examined gene expression profiles of biomarkers related to sensing of cellular energy status and regulation of catabolism and energy expenditure in a mid-intertidal limpet Cellana toreuma for elucidating the species' cellular energy responses stresses from high temperature, desiccation and rainfall. Expression levels of genes encoding metabolic regulators [two subunits of AMP-activated protein kinase, ampkα, ampkβ; Fu gene inhibition axis formation, axin; two sirtuins, NAD-dependent deacetylase sirtuin-1 (sirt1); NAD-dependent deacetylase sirtuin-5 (sirt5)], metabolic enzymes (hexokinase, hk; pyruvate kinase, pk; isocitrate dehydrogenase, idh) and heat shock protein 70 (hsp70) were quantified in specimens exposed to different temperatures and aerial/freshwater spray conditions. Based on the gene expression patterns, all individuals could be divided into three groups with divergent cellular energy status, indicating that the selected target genes are appropriate indicators of cellular metabolism. The divergent gene expression patterns indicated a sequence in which individuals from group 1, group 2 and group 3 were faced with increasing energy stress. The frequency distributions of individuals in the three groups were different among different time points and treatments, indicating that high temperature, desiccation, and rainfall, singly or in combination, could cause energy stress. Compared to the high percentage (100%) of individuals placed in the highest-stress group (group 3), after 2 h of freshwater spray at 18 °C, the lower percentage (77·8%) of individuals in group 3 after 2 h of freshwater spray at 30 °C indicated the existence of interactive effects of high temperature and rain; high temperature resulted in a lower response of cellular energy metabolism to rainfall. Sublethal environmental stresses from single stressors such as temperature or osmotic challenges can lead to cellular energy stress. Interactions among stressors may lead to a complex overall effect on cellular energy status in intertidal species.

opencc-by-4.0Jun 2021View details →

Data from: Decentralizing cell-free RNA sensing with the use of low-cost cell extracts

Data and DNA sequences for the publication "Decentralizing cell-free RNA sensing with the use of low-cost cell extracts" (https://www.biorxiv.org/content/10.1101/2021.05.29.446205v1)

opencc-zeroDec 2018View details →

Data from: Remotely-sensed primary productivity shows that domestic and native herbivores combined are overgrazing Patagonia

1. Carrying capacity is the maximum density of animals an area can sustain without a deterioration of its resources. Overgrazing degraded Patagonia grasslands in the past, but sheep stocks decreased in the last three decades and gave way to a mixed system with cattle, goats and guanacos (native wild camelids). 2. The objective of this paper was to develop a method to estimate carrying capacity based on remotely sensed data, and to assess wild and domestic herbivore numbers to establish if combined grazing stocks have evolved to a balance with carrying capacity. 3. Net Primary Productivity (NPP) MOD17/A3 images and Aerial Net Primary Productivity (ANPP) data of 66 sites were linearly regressed (R2= 0.83, P<0.01), and the slope 0.236 was used to convert MOD17/A3 NPP to ANPP. The proportion of ANPP that can be sustainably consumed (Harvest index) was HI=-5.71+0.72 ANPP0.5. Consumable forage was CF =ANPP.HI and carrying capacity CC =CF.EAC-1, where EAC is an estimate of annual consumption: 500, 3200 and 750 kg DM.head-1.year-1 for sheep or goats, cattle and guanacos, respectively. 4. Regional ANPP±SD (2000-2015) was 758±52 kg DM ha-1.yr-1; HI= 13.7±0.6% and CF= 104±12 kg DM ha-1yr-1 resulting in regional carrying capacity of 14.8±1.6 M sheep or goats, 2.3±0.3 M cattle or 9.9±1.2 M guanacos. 5. Domestic stock was high from 1920 to 1980, but declined thereafter and remained mostly within ±1SD of carrying capacity in this century. Annual mean provincial stocks and carrying capacity (2000-2015) correlated well (R²= 0.94, p<0.01) with a slope close to 1. 6. Guanacos increased from 0.5 M to 2 M between 2000 and 2015, driving linearly combined grazing pressures 36 and 62% above carrying capacity in southern Patagonia provinces in 2015. 7. Synthesis and applications: Herbivore de-stocking is necessary to restore grazing balance in south Patagonia. Guanacos are capable of grazing low-quality food and maintain production during dry periods, and their meat and fibre may be incorporated and combined with sheep production. Management of population of guanacos in mixed grazing systems with adjusted stocks may prevent further rangeland degradation, farm abandonment, and loss of ecosystem services of these rangelands.05-Apr-2019

opencc-zeroDec 2016View details →

Data from: Remote sensing of plant trait responses to field-based plant–soil feedback using UAV-based optical sensors

Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant–soil feedback (PSF). PSF is an important mechanism to explain plant community dynamics and plant performance in natural and agricultural systems. However, most PSF studies are short-term and small-scale due to practical constraints for field-scale quantification of PSF effects, yet field experiments are warranted to assess actual PSF effects under less controlled conditions. Here we used unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely. We established a randomized agro-ecological field experiment in which six different cover crop species and species combinations from three different plant families (Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on plant traits were tested in oat (Avena sativa) by quantifying the cover crop legacy effects on key plant traits: height, fresh biomass, nitrogen content, and leaf chlorophyll content. Prior to destructive sampling, hyperspectral data were acquired and used for calibration and independent validation of regression models to retrieve plant traits from optical data. Subsequently, for each trait the model with highest precision and accuracy was selected. We used the hyperspectral analyses to predict the directly measured plant height (RMSE  =  5.12 cm, R2  =  0.79), chlorophyll content (RMSE  =  0.11 g m−2, R2  =  0.80), N-content (RMSE  =  1.94 g m−2, R2  =  0.68), and fresh biomass (RMSE  =  0.72 kg m−2, R2  =  0.56). Overall the PSF effects of the different cover crop treatments based on the remote sensing data matched the results based on in situ measurements. The average oat canopy was tallest and its leaf chlorophyll content highest in response to legacy of Vicia sativa monocultures (100 cm, 0.95 g m−2, respectively) and in mixture with Raphanus sativus (100 cm, 1.09 g m−2, respectively), while the lowest values (76 cm, 0.41 g m−2, respectively) were found in response to legacy of Lolium perenne monoculture, and intermediate responses to the legacy of the other treatments. We show that PSF effects in the field occur and alter several important plant traits that can be sensed remotely and quantified in a non-destructive way using UAV-based optical sensors; these can be repeated over the growing season to increase temporal resolution. Remote sensing thereby offers great potential for studying PSF effects at field scale and relevant spatial-temporal resolutions which will facilitate the elucidation of the underlying mechanisms.

opencc-zeroJan 2020View details →

Data from: Use of a pressure-sensing walkway system for biometric assessment of gait characteristics in goats

The purpose of this study was to quantitatively assess gait characteristics and weight-bearing forces during ambulation in healthy goats using a pressure-sensing walkway as a biometric tool for stride, gait, and force analysis. Forty-six healthy adult goats ranging in age from 5 to 6 years, mixed-breeds, and with a mean body weight of 52 ± 7.1 kgs were used. Goats were trained to walk over a pressure-sensing walkway. Data for analysis was collected on 2 different days, 3 days apart. On each day, 2 to 5 walking passes, in the same direction, were captured for each goat. Data from 2 valid passes meeting the criteria for consistent walking gait on each day were averaged then used for analysis. Analysis was performed, including the day-effect, for stride, gait, and force characteristics. Of the 46 goats enrolled in the study, complete data sets were achieved in 33 (72%) goats. Gait biometrics were similar among the assessment days; therefore, all data was pooled for the purpose of characterizing data for individual limb and biometric parameter comparisons at the individual goat level. Statistical analysis revealed that no difference within the paired limbs and that there were significant differences between the front limbs and hind limbs. Maximum force and maximum peak pressure were significantly greater for the front limbs as compared with the hind limbs (p < 0.001). Based on the results, gait and force characteristics can be consistently measured in goats using a pressure-sensing walkway during a consistent walking gait. Goats apply greater force to the forelimbs during the weight-bearing phase of stride as compared with the hind limbs. The use of objective assessment tools is expected to improve the ability of researchers and clinicians to monitor changes in weight bearing and gait and will contribute to improved animal welfare.

opencc-zeroDec 2015View details →

Data from: Remotely sensed data informs red list evaluations and conservation priorities in southeast Asia

The IUCN Red List has assessed the global distributions of the majority of the world's amphibians, birds and mammals. Yet these assessments lack explicit reference to widely available, remotely-sensed data that can sensibly inform a species' risk of extinction. Our first goal is to add additional quantitative data to the existing standardised process that IUCN employs. Secondly, we ask: do our results suggest species of concern—those at considerably greater risk than hitherto appreciated? Thirdly, these assessments are not only important on a species-by-species basis. By combining distributions of species of concern, we map conservation priorities. We ask to what degree these areas are currently protected and how might knowledge from remote sensing modify the priorities? Finally, we develop a quick and simple method to identify and modify the priority setting in a landscape where natural habitats are disappearing rapidly and so where conventional species' assessments might be too slow to respond. Tropical, mainland Southeast Asia is under exceptional threat, yet relatively poorly known. Here, additional quantitative measures may be particularly helpful. This region contains over 122, 183, and 214 endemic mammals, birds, and amphibians, respectively, of which the IUCN considers 37, 21, and 37 threatened. When corrected for the amount of remaining natural habitats within the known elevation preferences of species, the average sizes of species ranges shrink to <40% of their published ranges. Some 79 mammal, 49 bird, and 184 amphibian ranges are <20,000km2—an area at which IUCN considers most other species to be threatened. Moreover, these species are not better protected by the existing network of protected areas than are species that IUCN accepts as threatened. Simply, there appear to be considerably more species at risk than hitherto appreciated. Furthermore, incorporating remote sensing data showing where habitat loss is prevalent changes the locations of conservation priorities.

opencc-zeroDec 2016View details →

Data from: MERRAclim, a high-resolution global dataset of remotely sensed bioclimatic variables for ecological modelling

Species Distribution Models (SDMs) combine information on the geographic occurrence of species with environmental layers to estimate distributional ranges and have been extensively implemented to answer a wide array of applied ecological questions. Unfortunately, most global datasets available to parameterize SDMs consist of spatially interpolated climate surfaces obtained from ground weather station data and have omitted the Antarctic continent, a landmass covering c. 20% of the Southern Hemisphere and increasingly showing biological effects of global change. Here we introduce MERRAclim, a global set of satellite-based bioclimatic variables including Antarctica for the first time. MERRAclim consists of three datasets of 19 bioclimatic variables that have been built for each of the last three decades (1980s, 1990s and 2000s) using hourly data of 2 m temperature and specific humidity. We provide MERRAclim at three spatial resolutions (10 arc-minutes, 5 arc-minutes and 2.5 arc-minutes). These reanalysed data are comparable to widely used datasets based on ground station interpolations, but allow extending their geographical reach and SDM building in previously uncovered regions of the globe.

opencc-byAug 2022View details →

Spider Sense NES

Spider-Man: Return of the Sinister Six Source: Objaverse 1.0 / Sketchfab

FIGURES 91–97. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 91–97. P. (M.) proceroides sp. nov. 91–92—pronotum: 91—♂, Faz. Jerusalem, HT (SDEI); 92—♀, Faz. Jerusalem, AT (SDEI); 93–97—elytron: 93—♂, Faz. Jerusalem, HT (SDEI); 94–95—♂, Villa de Alegre PT (SDEI); 96—♂, Palmital PT (SDEI); 97—♀, Faz. Jerusalem, AT (SDEI). Bars = 1 mm.

FIGURES 76–79 in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 76–79. Habitus of P. (M.) proceroides sp. nov. 76—♂, 10.3 mm, Faz. Jerusalem, HT (SDEI); 77—♂, 11.6 mm, Villa de Alegre, PT (SDEI); 78—♂, 11.2 mm, Palmital, PT (SDEI); 79—♀, 12.8 mm, Faz. Jerusalem, AT (SDEI).

FIGURES 80–90. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 80–90. P. (M.) proceroides sp. nov. 80–83—head: 80—♂, Faz. Jerusalem, HT (SDEI); 81—♂, Palmital PT (SDEI); 82—♂, Faz. Jerusalem, PT (SDEI); ♂, Villa de Alegre PT (SDEI); 84–89—labrum: 84–85—Villa de Alegre PT (SDEI); 86— ♂, Faz. Jerusalem, HT (SDEI); 87—♂, ibid., PT (SDEI); 88—♂, Palmital PT (SDEI); 89—♀, Faz. Jerusalem, AT (SDEI); 90—ditto, with buccal appendages. Bars = 1 mm.

FIGURES 63–75. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 63–75. P. (M.) procera (Chaudoir). 63–64—elytron: 63—♀, ex Chaudoir, PLT (MNHN); 64—♀, HT of synonymous Odontochila chaudoiri Dokhtouroff (SDEI); 65–66 –aberrant ♂, Sao Paulo (SDEI): 65—head; 66—labrum; 67– 73—aedeagus or its apex: 67—"1521", Petrópolis, LT (MNHN); 68—Rio de Janeiro (BMNH); 69—"Brésil" (MNHN); 70— Rio de Janeiro (MNHN); 71—ditto, ventral view; 72—Sao Paulo (SDEI); 73—Rio de Janeiro (SDEI); 74–75—ditto, internal sac in left and right lateral view. Bars = 1 mm.

FIGURES 55–62. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 55–62. P. (M.) procera (Chaudoir). 55–57—pronotum: 55 - ♂, "Brésil" (MNHN); 56—♀, Petrópolis (BMNH); 57—♀, HT of synonymous Odontochila chaudoiri Dokhtouroff (SDEI); 58–62—elytron: 58—♂, Petrópolis, LT (MNHN); 59—♂, ex Chaudoir (MNHN); 60—♂, "Brésil" (MNHN); 61—aberrant ♂, Sao Paulo (SDEI); 62—♂, Rio de Janeiro (BMNH). Bars = 1 mm.

FIGURES 98–110. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 98–110. P. (M.) proceroides sp. nov. 99–104—aedeagus: 98—Faz. Jerusalem, HT (SDEI); 99—ibid. PT (SDEI); 100—Villa de Alegre PT (SDEI); 101—ibid., PT (SDEI); 102—ditto, apex in ventral view; 103—Palmital PT (SDEI); 104— anomalous, Faz. Jerusalem, PT (SDEI); 105–110—internal sac: 105–106—left and right lateral view, Palmital PT (SDEI); 107—Faz. Jerusalem, HT (SDEI): 108—ditto, dorsal view; 109—ditto, ventral view; 110 ditto, right lateral view. Bars = 1 mm.

FIGURES 37–42 in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 37–42. Habitus of P. (M.) procera (Chaudoir). 37—♂, 11.7 mm, Petrópolis, LT (MNHN); 38—♂, 11.8 mm, ex Chaudoir (MNHN); 39—♂, 11.5 mm, Rio de Janeiro (BMNH); 40—aberrant ♂, 10.2 mm, Sao Paulo (MNHN); 41—♀, 13.3 mm, ex Chaudoir, PLT (MNHN); 42—♀, 13.7 mm, HT of synonymous Odontochila chaudoiri Dokhtouroff (SDEI).

FIGURES 25–36. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 25–36. P. (M.) conformis (Dejean). 25–30—aedeagus or its apex: 25—"1524, Brésil" (MNHN); 26—"Brasilia" (MFBB); 27—Rio de Janeiro (MNHN); 28—ditto, apex in ventral view; 29—Rio de Janeiro (SDEI); 30—ditto, apex in ventral view; 31–36—internal sac: 31—"Brasilia" (MFBB); 32—ditto, dorsal wiew, 33—ditto, ventral voew; 34—ditto, right lateral view; 35—Rio de Janeiro (SDEI); 36—ditto, right lateral view. Bars = 1 mm.

FIGURES 17–24. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 17–24. P. (M.) conformis (Dejean). 17–19—pronotum: 17—♂, Rio de Janeiro (SDEI); 18—♀, "Brasilia" (MFNB); 19—♀, Rio de Janeiro, HT (MNHN); 20–24—elytron: 20—♂, "Brasilia" (MFNB); 21—♂, "Brésil" (MNHN); 22—Rio de Janeiro (SDEI); 23—♀, Rio de Janeiro, HT (MNHN); 24—♀, "Brasilia" (MFNB). Bars = 1 mm.

FIGURES 43–54. P in Taxonomic and nomenclatorial revision within the Neotropical genera of the subtribe Odontocheilina W. Horn in a new sense— 16. Pentacomia (Mesochila) procera (Chaudoir), P. (M.) conformis (Dejean), and P. (M.) proceroides sp. nov. (Coleoptera: Cicindelidae)

FIGURES 43–54. P. (M.) procera (Chaudoir). 43—head, ♂, Rio de Janeiro (BMNH); 44–51—labrum, or with buccal appendages: 44—♂, Rio de Janeiro (BMNH); 45—♂, Petrópolis, LT (MNHN); 46—♂, Rio de Janeiro (MNHN); 47—♂, ex Chaudoir (MNHN); 48—♂, "Brésil" (MNHN); 49—♀, ex Chaudoir, PLT (MNHN); 50—♀, Petrópolis (BMNH); 51—♀, HT of synonymous Odontochila chaudoiri Dokhtouroff (SDEI); 52–54—pronotum: 52—♂, Petrópolis, LT (MNHN); 53—♂, Rio de Janeiro (MNHN); 54—♂, ex Chaudoir (MNHN). Bars = 1 mm.