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1,542 results for “Degradation”
Hippocampal spectral degradation
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Removing climbers more than doubles tree growth and biomass in degraded tropical forests
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P-TEFb is degraded by Siah1/2 in quiescent cells-Huang etc
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Land degradation and development
<p>All figures of the manuscript which submitted to Land degradation and development.</p>
Satellite-Based Estimates Reveal Widespread Forest Degradation in the Amazon
<p>This is the initial release of the repository containing the data used in the Global Change Biology article "Satellite-Based Estimates Reveal Widespread Forest Degradation in the Amazon" By Eric L Bullock, Curtis E. Woodcock, Carlos Souza Jr., and Pontus Olofsson. The github repository address is https://github.com/bullocke/amazon. </p>
Figure 4 from: Drapak I, Zimenkovsky B, Ivanauskas L, Bezruk I, Perekhoda L, Muzychenko V, Logoyda L, Demchuk I (2020) HPLC method for simultaneous determination of impurities and degradation products in Cardiazol. Pharmacia 67(1): 29-37. https://doi.org/10.3897/pharmacia.67.e37004
Figure 4 Chromatogram of a resolution mixture (impurity B (12.04; 0.65); impurity B (18.5; 0.98); Cardiazol (18.87; 1.00).
The impacts of tropical forest degradation and fragmentation on ant-plant mutualisms, and consequences for plant community dynamics
<b>Description: </b><p>Myrmecophyte interactions in differing habitats</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/119"><b>The impacts of tropical forest degradation and fragmentation on ant-plant mutualisms, and consequences for plant community dynamics</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>GACR (National, 16-09427S, <a href="NA">NA</a>)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Council (Research licence NA)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3979296">here</a></p><p><b>Files: </b>This consists of 1 file: M.pearsonii_habitat_comparison_OP_Matrix_MH_August.xlsx</p><p><b>M.pearsonii_habitat_comparison_OP_Matrix_MH_August.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Branch data</b> (described in worksheet Branch_data)</p><p>Description: Branch data</p><p>Number of fields: 86</p><p>Number of data rows: 611</p><p>Fields: </p><ul><li><b>Tree_code</b>: Tree ID (Field type: location)</li><li><b>Branch_code</b>: Branch code (Field type: id)</li><li><b>Coccids</b>: Number of coccids on br0nches (Field type: numeric interaction)</li><li><b>Brood1</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants1</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates1</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen1</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood2</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants2</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates2</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen2</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood4</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants4</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates4</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen4</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood5</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants5</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates5</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen5</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood6</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants6</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates6</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen6</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood7</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants_7</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates7</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen7</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood8</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants8</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates8</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen8</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood9</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants9</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates9</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen9</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood10</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants10</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates10</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen10</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood11</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants11</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates11</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen11</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood12</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants12</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates12</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen12</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood13</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants13</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates13</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen13</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood14</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants14</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates14</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen14</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood15</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants15</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates15</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen15</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood16</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants16</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates16</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen16</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood17</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants17</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates17</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen17</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood18</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants18</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates18</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen18</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood19</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants19</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates19</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen19</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood20</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants20</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates20</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen20</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Brood21</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Ants21</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>Allates21</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>queen21</b>: Number of ants on branch (Field type: numeric interaction)</li><li><b>damaged_queens</b>: Number of damaged ants (Field type: numeric interaction)</li><li><b>wasp</b>: Number of wasps (Field type: numeric interaction)</li><li><b>Notes</b>: Comments (Field type: comments)</li></ul></li><li><p><b>Tree data</b> (described in worksheet Tree_data)</p><p>Description: Tree data, including soil nutrient profiles</p><p>Number of fields: 23</p><p>Number of data rows: 84</p><p>Fields: </p><ul><li><b>Date</b>: Date of sampling (Field type: date)</li><li><b>Tree</b>: Tree ID (Field type: id)</li><li><b>Tree_code</b>: Tree ID code (Field type: location)</li><li><b>Habitat</b>: Habitat type (Field type: categorical)</li><li><b>Number_ants_first_5_leaves</b>: Number of ants on first 5 leaves (Field type: numeric trait)</li><li><b>DBH</b>: Diametre at breast height (Field type: numeric trait)</li><li><b>Height</b>: Tree height (Field type: numeric trait)</li><li><b>N</b>: Canopy cover (Field type: numeric trait)</li><li><b>S</b>: Canopy cover (Field type: numeric trait)</li><li><b>E</b>: Canopy cover (Field type: numeric trait)</li><li><b>W</b>: Canopy cover (Field type: numeric trait)</li><li><b>Canopy_cover</b>: Canopy cover (Field type: numeric trait)</li><li><b>Leaf_biomass</b>: Leaf biomass (Field type: numeric trait)</li><li><b>Total_branches</b>: Total number of branches (Field type: numeric trait)</li><li><b>Phosphate</b>: Leaf phosphates (Field type: numeric trait)</li><li><b>Nitrate</b>: Leaf nitrates (Field type: numeric trait)</li><li><b>Total_wet_weight</b>: Total soil wet weight (Field type: numeric trait)</li><li><b>Wet_weight_sample</b>: Soil wet weight (sample) (Field type: numeric trait)</li><li><b>Dry_weight_sample</b>: Soil dry weight (sample) (Field type: numeric trait)</li><li><b>pH</b>: Leaf pH (Field type: numeric trait)</li><li><b>Dry_Wet_ratio</b>: Soil wet: dry weight ratio (Field type: numeric trait)</li><li><b>Total_dry_weight</b>: Total soildry weight (Field type: numeric trait)</li><li><b>Density</b>: Soil density (Field type: numeric trait)</li></ul></li><li><p><b>All M.Pearsonii-Herbivory data</b> (described in worksheet All_Pearsonii-Herbivory_data)</p><p>Description: Summarised version of data used for analysis</p><p>Number of fields: 17</p><p>Number of data rows: 86</p><p>Fields: </p><ul><li><b>Date</b>: Date the measurements were taken (Field type: date)</li><li><b>Tree</b>: Tree tag (Field type: id)</li><li><b>Tree_Code</b>: Tree code (Field type: id)</li><li><b>Habitat</b>: Habitat type (Field type: categorical)</li><li><b>Tree_Height_Rank</b>: Tree height rank (Field type: categorical)</li><li><b>Corrected_Leaf_Biomass</b>: Corrected leaf biomass (Field type: numeric trait)</li><li><b>Herbivory</b>: Leaf herbivory (Field type: numeric trait)</li><li><b>Coccids</b>: Coccid abundance (Field type: numeric interaction)</li><li><b>Ant_abundance</b>: Ant abundance (Field type: numeric interaction)</li><li><b>Ant_ranked_abundance</b>: Ant coverage ranked (Field type: categorical)</li><li><b>Brood</b>: Ant abundance (Field type: numeric interaction)</li><li><b>Biomass_height_ratio</b>: Tree biomass to height ratio (Field type: numeric trait)</li><li><b>Coccid_ant_ratio</b>: Coccid to ant ratio (Field type: numeric)</li><li><b>Brood_ant_ratio</b>: Brood to ant ratio (Field type: numeric trait)</li><li><b>Attendence_ratio</b>: Attendence ratio (Field type: numeric)</li><li><b>DomTaxa</b>: Taxa record for the dominant species (Field type: taxa)</li><li><b>Dominant_species</b>: Is there a dominant species? (Field type: categorical interaction)</li></ul></li></ol><p><b>Date range: </b>2016-11-19 to 2017-11-24</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Plantae <br> -  -  Tracheophyta <br> -  -  -  Magnoliopsida <br> -  -  -  -  Malpighiales <br> -  -  -  -  -  Euphorbiaceae <br> -  -  -  -  -  -  <i>Macaranga</i> <br> -  -  -  -  -  -  -  <i>Macaranga pearsonii</i> <br> -  Animalia <br> -  -  Arthropoda <br> -  -  -  Insecta <br> -  -  -  -  Hymenoptera <br> -  -  -  -  -  Formicidae <br> -  -  -  -  -  -  sp.1 <br> -  -  -  -  -  -  sp.2 <br> -  -  -  -  -  -  sp.4 <br> -  -  -  -  -  -  sp.5 <br> -  -  -  -  -  -  sp.6 <br> -  -  -  -  -  -  sp.7 <br> -  -  -  -  -  -  sp.8 <br> -  -  -  -  -  -  sp.9 <br> -  -  -  -  -  -  sp.10 <br> -  -  -  -  -  -  sp.11 <br> -  -  -  -  -  -  sp.12 <br> -  -  -  -  -  -  sp.13 <br> -  -  -  -  -  -  sp.14 <br> -  -  -  -  -  -  sp.15 <br> -  -  -  -  -  -  sp.16 <br> -  -  -  -  -  -  sp.17 <br> -  -  -  -  -  -  sp.18 <br> -  -  -  -  -  -  sp.19 <br> -  -  -  -  -  -  sp.20 <br> -  -  -  -  -  -  sp.21 <br> -  -  -  -  Hemiptera <br> -  -  -  -  -  Coccidae <br></div><p></p>
Replication Package for the paper: "How Does Modern Code Review Impact Software Design Degradation? An In-depth Empirical Study"
<p>This is the replication package for the paper: "How Does Modern Code Review Impact Software Design Degradation? An In-depth Empirical Study", published at the 36th International Conference on Software Maintenance and Evolution (ICSME' 20).</p> <p> </p> <p>It contains all the preliminary and final results of our empirical methodology. We highlight the manual classification of design-related and design-unrelated reviews, according to the developers’ intent of improving the structural design of the system. This might be used for further studies on the impact of design discussions on the structural quality of design.</p> <p> </p> <p>Feel free to use any part of this replication package in your study, please cite as:</p> <p>Anderson Uchôa, Caio Barbosa, Willian Oizumi, Publio Blenílio, Rafael Lima, Alessandro Garcia, and Carla Bezerra. How Does Modern Code Review Impact Software Design Degradation? An In-depth Empirical Study. Proceedings of the 36th International Conference on Software Maintenance and Evolution (ICSME), Adelaide, Australia, September 2020.</p>
Photocatalytic degradation of methylene blue under natural sunlight using Fe2TiO5 nanoparticles prepared by a modified sol-gel method
<p><span>Iron titanate (Fe<sub>2</sub>TiO<sub>5</sub>) nanoparticles with an orthorhombic structure were successfully synthesized using a modified sol-gel method and calcination at 750 </span><span>°</span><span>C. The as-prepared Fe<sub>2</sub>TiO<sub>5</sub> nanoparticles exhibited a moderate specific surface area. The mesoporous Fe<sub>2</sub>TiO<sub>5</sub> nanoparticles possessed strong absorption in the visible light region and the band gap was estimated to be around 2.16 eV. The photocatalytic activity was evaluated by the degradation of methylene blue under natural sunlight. The effect of parameters such as the amount of catalyst, initial concentration of the dye and pH of the dye solution were investigated on the removal efficiency of methylene blue. Fe<sub>2</sub>TiO<sub>5</sub> showed high degradation efficiency in a strong alkaline medium that can be the result of the facilitated formation of OH radicals due to an increased concentration of hydroxyl ions.</span></p>
Figure 1 from: Fatihah-Syafiq M, Badli-Sham BH, Fahmi-Ahmad M, Aqmal-Naser M, Rizal SA, Azmi MSA, Grismer LL, Ahmad AB (2020) Checklist of herpetofauna in the severely degraded ecosystem of Bidong Island, Peninsular Malaysia, South China Sea. ZooKeys 985: 143-162. https://doi.org/10.3897/zookeys.985.54737
Figure 1 Map of Peninsular Malaysia (left) showing the location of Bidong Island, off the Terengganu coast, indicated by the red square. Map of Bidong Island (right) with the study locations indicated by red circles.
FIGURE 3 in A new species of Sphaerotheca Günther, 1859 (Anura: Dicroglossidae) from the degraded urban ecosystems of Bengaluru, Deccan Plateau, India
FIGURE 3. (A) Sphaerotheca bengaluru sp. nov. and (B) S. breviceps in life from the type locality.
FIGURE 1 in A new species of Sphaerotheca Günther, 1859 (Anura: Dicroglossidae) from the degraded urban ecosystems of Bengaluru, Deccan Plateau, India
FIGURE 1. Map showing type localities of extant species of Sphaerotheca in South Asia.
Riparian forests can mitigate warming and ecological degradation of agricultural headwater streams
<p>1. Riparian forests are commonly advocated as a key management option to mitigate the effects of agriculture on headwater stream biodiversity and ecosystem functions. However, the benefits of riparian forests might be reduced by uninterrupted catchment-scale pollution.</p> <p>2.We studied the effects of riparian land use on multiple ecological endpoints in headwater streams in an agricultural landscape. We studied stream habitat characteristics, water temperature and algal accrual, and macrophyte, benthic macroinvertebrate and fish communities in 11 paired forested and open agricultural headwater stream reaches that differed in their extent of riparian forest cover but had similar water quality.</p> <p>3. Hydromorphological habitat quality was higher in forested reaches than in open reaches. Riparian forest had a strong effect on the summer water temperature regime, with maximum and mean water temperatures and temperature variation in forested reaches substantially lower than in open reaches.</p> <p>4. Macrophyte communities differed between forested and open reaches. The mean abundance of bryophytes was higher in forested reaches but the difference to open reaches was only marginally significant, whereas graminoids were significantly more abundant in open reaches. Within-stream dissimilarity of benthic macroinvertebrate community structure was significantly related to the difference in riparian land use between reach pairs. The relative DNA sequence abundance of pollution-sensitive EPT (Ephemeroptera, Plecoptera, Trichoptera) species tended to be higher in forested reaches than in open reaches. Finally, fish densities were not significantly different between forested and open reaches, although densities were higher in forested reaches.</p> <p>5. This unequivocal evidence for the ecological benefits of forested riparian reaches in agricultural headwater streams suggests that riparian forest can partly mitigate the adverse impacts of agricultural diffuse pollution on biota. The strong effect of forests on stream water temperature suggest that riparian forest could also mitigate harmful effects on headwater stream biodiversity and ecosystem functions of the predicted more frequent high summer temperatures. </p>
Data from: Accelerated degradation of polyetheretherketone and its composites in the deep sea
The performance of polymer composites in seawater under high hydrostatic pressure (typically few tens of MPa), for simulating exposures at great depths in seas and oceans, has been little studied. In this paper, PEEK and its composites reinforced by carbon fibers and glass fibers were prepared, respectively. And the seawater environments with different seawater hydrostatic pressure ranging from normal pressure to 40 MPa was simulated with special equipment, in which the seawater absorption and wear behaviors of PEEK and PEEK-based composites were examined in situ. The effects of seawater hydrostatic pressure on the mechanical properties, wear resistance and microstructure of PEEK and its composites were focused on. The results showed that seawater absorption of PEEK and its composites were greatly accelerated by increased hydrostatic pressure in the deep sea. And affected by seawater absorption, both for neat PEEK and composites, the degradation on mechanical properties, wear resistance and crystallinity were induced, the degree of which were increasingly serious with the hydrostatic pressure of seawater environment increasing. And there existed a good correlation in an identical form of exponential function between the wear rate and the seawater hydrostatic pressure. Moreover, the corresponding mechanisms of the effects of deep-sea hydrostatic pressure were also discussed.
Data from: Irradiation-catalyzed degradation of methyl orange using BaF2-TiO2 nanocomposite catalysts prepared by a sol–gel method
BaF2-TiO2 nanocomposite material (hereinafter called the composite) was prepared by a sol–gel method. And the composite surface area, morphology and structure were characterized by Brunauer-Emmett-Teller (BET) method, X-ray diffraction(XRD) and scanning electron microscopy (SEM). The results showed that BaF2 and TiO2 form a PN-like structure on the surface of the composite. Composites were used to catalyze the degradation of methyl orange by irradiation with ultraviolet light, γ-rays, and an electron beam(EB). It was demonstrated that the composite is found to be more efficient than prepared TiO2 and commercial P25 in the degradation of methyl orange under γ-irradiation. And increasing the composite catalyst concentration within a certain range can effectively improve the decolorization rate of the methyl orange solution. However, when the composite material is used to catalyze the degradation of organic matter in the presence of ultraviolet light or 10 MeV electron beam irradiation, the catalytic effect is poor or substantially ineffective. In addition, a hybrid mechanism is proposed; BaF2 absorbs γ-rays to generate radioluminescence(RL) and further excites TiO2 to generate photo-charges. And due to the heterojunction effect, the resulting photo-charge will produce more active particles. This seems to be a possible mechanism to explain γ-irradiation catalytic behavior.
Data from: Evidence of degradation of hair corticosterone in museum specimens
Researchers increasingly rely on non-invasive physiological indices, such as glucocorticoid (GC) levels, to interpret how vertebrates respond to changes in their environment. Recently, hair GCs have been of particular interest, because they are presumed stable over long periods of storage, which may facilitate the study of large-scale spatial and temporal patterns of stress in mammals. In the current study, we evaluated the stability of hair corticosterone levels in museum specimens, and the potential effects of different museum curation treatments. Using deer mouse (Peromyscus maniculatus) specimens collected from Vancouver Island (11 sites, 82 individuals) over 76 years, we found that specimens collected earlier in the 20th century had lower hair corticosterone than more recently collected specimens. These results suggest that hair hormone levels may not be stable over decades of storage time. We then subjected hair samples collected from white-footed mouse (Peromyscus leucopus, n = 36) to 3 different museum curation treatments, and found that borax lowered hair corticosterone levels relative to control samples, but air drying samples, or treating them with turpentine had no effect. Our results present a source of concern for the use of museum specimens for hair hormone analysis, and for studying long term trends in glucocorticoid levels.
Data from: Resilience of peatland ecosystem services over millennial timescales: evidence from a degraded British bog
1. Many peatland ecosystems in Europe have become degraded in the last century owing to the effects of drainage, burning, pollution, and climate change. There is a need to understand the drivers of peatland degradation because management and restoration interventions can affect the natural ecohydrological dynamics of such sensitive environments, and are expensive. However, if given enough time peatlands may have the ability to recover spontaneously without deliberate action. 2. We use a detailed multiproxy palaeoecological dataset from a degraded raised bog in Northern England to examine its ecosystem stability and long-term dynamics in response to anthropogenic disturbance over a variety of timescales. One feature of many degraded peatlands (including our study site) is the local dominance of Molinia caerulea (purple moor-grass), which has expanded at the expense of characteristic peatland plants, including sedges and Sphagnum mosses. 3. Our data show that there has been a long history of human impacts at the site which have culminated in its current unfavourable condition. Several distinct episodes of past peat cutting are evident as hiatuses in peat accumulation; however, peat accumulation and plant community structure have subsequently recovered spontaneously. The appearance of M. caerulea occurs coevally with an unprecedented variety of recent anthropogenic impacts, all of which have arguably contributed to providing a suitable environment for its rise to dominance. We have dated the appearance of M. caerulea to the latter half of the twentieth century which corresponds to a number of anthropogenic press disturbances, including: dust loading from post-war expansion of the adjacent quarry; burning; drainage; airborne pollution; and contamination from soil dust and agrochemicals. 4. Synthesis Our study demonstrates the importance of palaeoecology for understanding the trajectories of peatland development and ecosystem dynamics, including their resilience and resistance to pulse and press disturbances. We show that peatlands have the capability to recover spontaneously from severe disturbances such as peat cutting, albeit on timescales much longer than those applied to monitoring of restoration efforts. The implications are relevant for determining whether it is better to manage and restore peatlands, or to allow them to recover naturally without human intervention.
Data from: Coral reef degradation is not correlated with local human population density
The global decline of reef-building corals is understood to be due to a combination of local and global stressors. However, many reef scientists assume that local factors predominate and that isolated reefs, far from human activities, are generally healthier and more resilient. Here we show that coral reef degradation is not correlated with human population density. This suggests that local factors such as fishing and pollution are having minimal effects or that their impacts are masked by global drivers such as ocean warming. Our results also suggest that the effects of local and global stressors are antagonistic, rather than synergistic as widely assumed. These findings indicate that local management alone cannot restore coral populations or increase the resilience of reefs to large-scale impacts. They also highlight the truly global reach of anthropogenic warming and the immediate need for drastic and sustained cuts in carbon emissions.
Data from: Critical analysis of forest degradation in the southern Eastern Ghats of India: comparison of satellite imagery and soil quality index
India has one of the largest assemblages of tropical biodiversity, with its unique floristic composition of endemic species. However, current forest cover assessment is performed via satellite-based forest surveys, which have many limitations. The present study, which was performed in the Eastern Ghats, analysed the satellite-based inventory provided by forest surveys and inferred from the results that this process no longer provides adequate information for quantifying forest degradation in an empirical manner. The study analysed 21 soil properties and generated a forest soil quality index of the Eastern Ghats, using principal component analysis. Using matrix modules and geospatial technology, we compared the forest degradation status calculated from satellite-based forest surveys with the degradation status calculated from the forest soil quality index. The Forest Survey of India classified about 1.8% of the Eastern Ghats' total area as degraded forests and the remainder (98.2%) as open, dense, and very dense forests, whereas the soil quality index results found that about 42.4% of the total area is degraded, with the remainder (57.6%) being non-degraded. Our ground truth verification analyses indicate that the forest soil quality index along with the forest cover density data from the Forest Survey of India are ideal tools for evaluating forest degradation.
Data from: The interrelationship among economic activities, environmental degradation, material consumption, and population health in low-income countries: a longitudinal ecological study
Objectives: The theory of ecological unequal exchange explains how trade and various forms of economic activity create the problem of environmental degradation, and lead to the deterioration of population health. Based on this theory, our study examined the inter-relationship among economic characteristics, ecological footprints, CO2 emissions, infant mortality rates and under-5 mortality rates in low-income countries. Design: A longitudinal ecological study design. Setting: Sixty-six low-income countries from 1980 to 2010 were included in the analyses. Data for each country represented an average of 23 years (N=1497). Data sources: Data were from the World Development Indicators, UN Commodity Trade Statistics Database, Global Footprint Network and Polity IV Project. Analyses: Linear mixed models with a spatial power covariance structure and a correlation that decreased over time were constructed to accommodate the repeated measures. Statistical analyses were conducted separately by sub-Saharan Africa, Latin America and other regions. Results: After controlling for country-level sociodemographic characteristics, debt and manufacturing, economic activities were positively associated with infant mortality rates and under-5 mortality rates in sub-Saharan Africa. By contrast, export intensity and foreign investment were beneficial for reducing infant and under-5 mortality rates in Latin America and other regions. Although the ecological footprints and CO2 emissions did not mediate the relationship between economic characteristics and health outcomes, export intensity increased CO2 emissions, but reduced the ecological footprints in sub-Saharan Africa. By contrast, in Asia, the Middle East and North Africa, although export intensity was positively associated with the ecological footprints and also CO2 emissions, the percentage of exports to high-income countries was negatively associated with the ecological footprints. Conclusions: This study suggested that environmental protection and economic development are important for reducing infant and under-5 mortality rates in low-income countries.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.