21 research outputs found
Myrmecophilous Pselaphine beetles in tropical forests
No full text<b>Description: </b><p>This data set includes taxanomic and abunance data for Pselaphinae beetles and ants collected in the leaf litter across Primary and logged forests sites. Selected environemntal variables (soil temperature, soil moisture and canopy cover) were also recorded at each sample site. </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/46"><b>The Maliau Quantitative Inventory</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=180">here</a></p><p><b>Files: </b>This consists of 1 file: Psomas_Ant_Pselaphine_SAFE_dataset.xlsx</p><p><b>Psomas_Ant_Pselaphine_SAFE_dataset.xlsx</b></p><p>This file contains dataset metadata and 4 data tables:</p><ol><li><p><b>EnvironVariables</b> (described in worksheet EnvironVariables)</p><p>Description: Environmental variables</p><p>Number of fields: 4</p><p>Number of data rows: 20</p><p>Fields: </p><ul><li><b>Site</b>: Site of measurements (Field type: Location)</li><li><b>Temp</b>: Soil temperature (Field type: Numeric)</li><li><b>Moisture</b>: Soil moisture (Field type: Numeric)</li><li><b>Cover</b>: Canopy cover (Field type: Numeric)</li></ul></li><li><p><b>Ant-Psel</b> (described in worksheet Ant-Psel)</p><p>Description: Ant-Pselaphine data</p><p>Number of fields: 3</p><p>Number of data rows: 20</p><p>Fields: </p><ul><li><b>Site</b>: Site where sample was collected (Field type: Location)</li><li><b>ant species richness</b>: Number of ant species in sample (Field type: Numeric)</li><li><b>ant abundance</b>: Total number of ants in sample (Field type: Abundance)</li></ul></li><li><p><b>MorphAbundance</b> (described in worksheet MorphAbundance)</p><p>Description: Morphospeices abundance</p><p>Number of fields: 43</p><p>Number of data rows: 20</p><p>Fields: </p><ul><li><b>Site</b>: Site where specimens were collected (Field type: Location)</li><li><b>Psel1</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel2</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel3</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel4</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel5</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel6</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel7</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel8</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel9</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel10</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel11</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel12</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel13</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel14</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel15</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel16</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel17</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel18</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel19</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel20</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel21</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel22</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel23</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel24</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel25</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel26</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel27</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel28</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel29</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel30</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel31</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel32</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel33</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel34</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel35</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel36</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel37</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel38</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel39</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel40</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel41</b>: Number of individuals collected (Field type: Abundance)</li><li><b>Psel42</b>: Number of individuals collected (Field type: Abundance)</li></ul></li><li><p><b>MorphFunctTraits</b> (described in worksheet MorphFunctTraits)</p><p>Description: Morphospecies_Functional Traits</p><p>Number of fields: 17</p><p>Number of data rows: 42</p><p>Fields: </p><ul><li><b>Morphospecies</b>: Morphospecies identity (Field type: Taxa)</li><li><b>AL</b>: Antennae length (Field type: Numeric Trait)</li><li><b>TAL</b>: Termianl antennomere length (Field type: Numeric Trait)</li><li><b>TAW</b>: Termianl antennomere width (Field type: Numeric Trait)</li><li><b>AN</b>: Antennomere number (Field type: Numeric Trait)</li><li><b>HCA</b>: Hollow cavity absent in terminal antennomere (Field type: Categorical Trait)</li><li><b>HCP</b>: Hollow cavity present in terminal antennomere (Field type: Categorical Trait)</li><li><b>TA</b>: Trichomes absent (Field type: Categorical Trait)</li><li><b>TP</b>: Trichomes present (Field type: Categorical Trait)</li><li><b>FP</b>: Foveae present (Field type: Categorical Trait)</li><li><b>FA</b>: Foveae absent (Field type: Categorical Trait)</li><li><b>Bef2</b>: Basal elytral foveae, two set (Field type: Categorical Trait)</li><li><b>Bef3</b>: Basal elytral fovea, thee set (Field type: Categorical Trait)</li><li><b>Bef1</b>: Basal elytral foveae, one set (Field type: Categorical Trait)</li><li><b>Bef0</b>: Basal elytral foveae, no set (Field type: Categorical Trait)</li><li><b>Bef4</b>: Basal elyral fovea, four set (Field type: Categorical Trait)</li><li><b>Myrmycophile</b>: Myrmecophily status (Field type: Categorical Trait)</li></ul></li></ol><p><b>Date range: </b>2012-09-01 to 2012-10-31</p><p><b>Latitudinal extent: </b>4.6922 to 4.9702</p><p><b>Longitudinal extent: </b>116.9669 to 117.7981</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>Animalia<br> - Arthropoda<br> -  - Insecta<br> -  -  - Coleoptera<br> -  -  -  - Pselaphidae<br> -  -  -  -  - [Psel1]<br> -  -  -  -  - [Psel10]<br> -  -  -  -  - [Psel15]<br> -  -  -  -  - [Psel17]<br> -  -  -  -  - [Psel28]<br> -  -  -  -  - [Psel29]<br> -  -  -  -  - [Psel30]<br> -  -  -  -  - [Psel33]<br> -  -  -  -  - [Psel35]<br> -  -  -  -  - [Psel41]<br> -  -  -  -  - [Psel9]<br> -  -  -  - Staphylinidae<br> -  -  -  -  - <i>Apharinodes</i><br> -  -  -  -  -  - [Psel13]<br> -  -  -  -  -  - [Psel37]<br> -  -  -  -  - <i>Aphilia</i><br> -  -  -  -  -  - [Psel12]<br> -  -  -  -  -  - [Psel38]<br> -  -  -  -  - <i>Batraxis</i><br> -  -  -  -  -  - [Psel31]<br> -  -  -  -  -  - [Psel39]<br> -  -  -  -  - <i>Bibloporus</i><br> -  -  -  -  -  - [Psel2]<br> -  -  -  -  - <i>Cerylambus</i><br> -  -  -  -  -  - [Psel27]<br> -  -  -  -  - <i>Cratna</i><br> -  -  -  -  -  - [Psel16]<br> -  -  -  -  -  - [Psel19]<br> -  -  -  -  -  - [Psel32]<br> -  -  -  -  - <i>Curculionellus</i><br> -  -  -  -  -  - [Psel26]<br> -  -  -  -  - <i>Diaugis</i><br> -  -  -  -  -  - [Psel42]<br> -  -  -  -  - <i>Enantius</i><br> -  -  -  -  -  - [Psel36]<br> -  -  -  -  - <i>Harmophorus</i><br> -  -  -  -  -  - [Psel4]<br> -  -  -  -  - <i>Mechanicus</i><br> -  -  -  -  -  - [Psel14]<br> -  -  -  -  -  - [Psel34]<br> -  -  -  -  -  - [Psel40]<br> -  -  -  -  -  - [Psel7]<br> -  -  -  -  - <i>Mnia</i><br> -  -  -  -  -  - [Psel11]<br> -  -  -  -  -  - [Psel18]<br> -  -  -  -  - <i>Plagiophorus</i><br> -  -  -  -  -  - [Psel20]<br> -  -  -  -  -  - [Psel22]<br> -  -  -  -  -  - [Psel3]<br> -  -  -  -  -  - [Psel6]<br> -  -  -  -  -  - [Psel8]<br> -  -  -  -  - <i>Pselaphodes</i><br> -  -  -  -  -  - [Psel21]<br> -  -  -  -  -  - [Psel25]<br> -  -  -  -  - <i>Pseudacerus</i><br> -  -  -  -  -  - [Psel23]<br> -  -  -  -  - <i>Pseudophanias</i><br> -  -  -  -  -  - [Psel5]<br> -  -  -  -  - <i>Sathytes</i><br> -  -  -  -  -  - [Psel24]<br> -  -  - Hymenoptera<br> -  -  -  - Formicidae<br></div><p></p>
Ant diversity as a direct and indirect driver of Pselaphinae beetle functional diversity in tropical rainforests, Sabah, Borneo
No full textImperial Users onl
The impact of altered forest microclimate on the development rate of mosquito vectors
No full textImperial Users onl
Hydrologic modeling in the Diamond Bell Ranch area
No full textabstract: Purpose of this report is to provide a detailed analysis of the runoff characteristics of the Diamond Bell Ranch area.To this end, HEC-HMS models were generated to analyze the runoff under existing watershed conditions.Special study (Pima County Regional Flood Control District (Ariz.)) ; 4
Ant diversity as a direct and indirect driver of pselaphine rove beetle (Coleoptera: Staphylinidae) functional diversity in tropical rainforests, Sabah, Malaysian Borneo
No full textSustainable Agricultural Water Management in Pinios River Basin Using Remote Sensing and Hydrologic Modeling
No full textAbstractThe Pinios river basin is a major agricultural area in Greece, which faces environmental issues with water scarcity and nutrient pollution. Recent Earth Observation satellite data and ground truth information were combined to produce an updated land use map, focusing on irrigated crop areas. A process-based hydrological model (SWAT) was set up using the produced land use map. The model was calibrated and validated using observed streamflows and nutrient concentrations at selected gauging stations. Four irrigation and nutrient management practices related to resource efficiency (i.e. deficit irrigation, reduced fertilization, combination of deficit irrigation and fertilization, precision agriculture) were modelled and simulated. The sustainability of the management practices was assessed using indicators to quantify their impacts on the water-energy-land-food nexus of the river basin
Designing Water Efficiency Measures in a Catchment in Greece Using WEAP and SWAT Models
No full textAbstractThe Ali Efenti catchment is a rural upstream subcatchment of the Pinios river basin that suffers from seasonal water shortages due to the rapid increase of the total water abstraction in the summer months, which is mainly attributed to local crop irrigation. Catchment modelling is being implemented using two different modelling approaches: a conceptual model based on water balances, the Water Evaluation And Planning system (WEAP), and a physically-based model coupled with routines for irrigation and crop growth, the Soil and Water Assessment Tool (SWAT). Both models were set up, calibrated and validated using observed streamflows. The strengths of the two models were combined in order to design effective, efficient and comprehensive demand-side measures for the urban, tourism, industrial and agricultural sectors to achieve sustainable water management in the Ali Efenti catchment. The comparison of the two models and the results of modelling are being discussed
Microclimate and the development rate of mosquito vectors
No full text<b>Description: </b><p>This data sets includes microclimate data, mosquito development rate and mosquito wing size measurements collected from primary forest, logged forest and oil palm plantations. Microclimate data was recorded using Ibutton data loggers which measured soil temeprature at given sample sites. All mosquito eggs collected were reared under field conditions. Each mosquito sample was monitored daily in order to record the proportion emerging at each developemnt stage (larva, pupa and adult) along with the numebr of transition days between each development stage. Adult wing length (of each adult mosquito collected) was used as a simple proxy to measure adult vectorial capacity. </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/21"><b>The impact of altered forest microclimate on the development rate of mosquito vectors</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=110">here</a></p><p><b>Files: </b>This consists of 1 file: template_PsomosMosquitoes.xlsx</p><p><b>template_PsomosMosquitoes.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Soil temperature</b> (described in worksheet Soiltemp)</p><p>Description: Datalogger records of soil temperature time series as sample sites</p><p>Number of fields: 4</p><p>Number of data rows: 875</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project sample site (Field type: Location)</li><li><b>Day</b>: Day of measurement; each site had records collected over seven days (Field type: Numeric)</li><li><b>Time</b>: Time of measurement (Field type: Time)</li><li><b>Soil Temperature</b>: Soil temperature (Field type: Numeric)</li></ul></li><li><p><b>Mosquito size</b> (described in worksheet Mosquito_wing_length)</p><p>Description: Wing measurements on individual mosquitoes</p><p>Number of fields: 3</p><p>Number of data rows: 119</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project sample site (Field type: Location)</li><li><b>SampleNumber</b>: Each replicate within a site represents a different mosquito that was measured (Field type: Replicate)</li><li><b>WingSize</b>: Adult mosquito wing length (Field type: Numeric Trait)</li></ul></li><li><p><b>Mosquito life history stages</b> (described in worksheet Development_data)</p><p>Description: Abundance and time frame for mosquito development</p><p>Number of fields: 8</p><p>Number of data rows: 26</p><p>Fields: </p><ul><li><b>Site</b>: SAFE Project sample site (Field type: Location)</li><li><b>Eggs</b>: Number eggs (Field type: Abundance)</li><li><b>Larvae</b>: Number larvae (Field type: Abundance)</li><li><b>Pupae</b>: Number pupae (Field type: Abundance)</li><li><b>Adults</b>: Number adults (Field type: Abundance)</li><li><b>egg-larvae</b>: Number of days to develop from egg to larvae (Field type: Numeric Trait)</li><li><b>larvae-pupae</b>: Number of days to develop from larvae to pupae (Field type: Numeric Trait)</li><li><b>pupae-adult</b>: Number of days to develop from pupae to adult (Field type: Numeric Trait)</li></ul></li></ol><p><b>Date range: </b>2015-05-01 to 2015-07-13</p><p><b>Latitudinal extent: </b>4.6532 to 4.7520</p><p><b>Longitudinal extent: </b>116.9635 to 117.5932</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>Animalia<br> - Arthropoda<br> -  - Insecta<br> -  -  - Diptera<br> -  -  -  - Culicidae<br></div><p></p>
The development of quantitative methods for residues in foods of animal origin with validation according to commission decision 2002/657/EC
No full textResidue methods were developed for the determination o f the coccidiostat robenidine in egg, the benzimidazoles (13) in liver (albendazole 2-amino albendazole sulphone, albendazole sulphoxide, albendazole sulphone, thiabendazole, oxfendazole or fenbendazole sulphoxide, hydroxy mebendazole, amino flubendazole, fenbendazole sulphone, oxibendazole, mebendazole, flubendazole and albendazole) and the triphenylmethane dyes (4) in salmon (malachite green, crystal violet, leucomalachite green and leucocrystal violet). The methods were validated according to the criteria defined in Commission Decision 2002/657/EC. Robenidine was extracted from egg with acetonitrile and the sample extracts analysed by liquid chromatography (LC) with ultraviolet (UV) spectrophotometric detection at 317 nm. The decision limit (CCa) and the detection capability (CCP) were 10 |xg.kg_I and 17 ng.kg'1 respectively.
The benzimidazoles were extracted from liver samples with ethyl acetate, sample extracts were defatted with hexane and cleaned up by automated solid-phase extraction (SPE) on Ci8 cartridges. Aliquots o f the extracts were analysed by LC with UV detection at 298 nm. The CCa values ranged between maximum residue limit (MRL) + 12% and MRL + 25% and the CCP ranged between MRL + 25% and MRL + 45%. The triphenylmethane dyes were extracted from salmon with acetonitrile and pH 3 buffer, extracts were cleaned up using cation-exchange SPE on sulphonic acid (SCX) cartridges and the sample extracts were analysed by liquid chromatography tandem mass spectroscopy (LC-MS/MS). CCa for malachite green, leucomalachite green, crystal violet and leucocrystal violet were 0.17, 0.15, 0.40 and 0.17 iig-kg'1 respectively and CCP were 0.30, 0.35, 0.80 and 0.32 ng.kg 1 respectively.
All research undertaken in this thesis was published in peer reviewed journals. This work has made a significant contribution to residues science as more novel methods have become available for surveillance of these drugs at national and international level. The methods developed in this research also provide a legal basis for prosecuting individuals who use these veterinary products without adhering to EU legislation. Ultimately the work enhances food safety as methods developed help to eliminate the hazards associated with drug residues entering the food chain
Revisiting cost of poor quality in the digital era : evidence from global survey organisations
No full textPurpose: This study investigates contemporary practices in measuring and managing the Cost of Poor Quality (COPQ), the distribution of costs across the four classic Cost of Quality (COQ) categories, the influence of COPQ information on managerial decisions, and the continuing relevance of Mikel Harry's COPQ benchmarks in a digitalised context. Methodology: Data were collected via an online global survey (175 respondents) and analysed using descriptive statistics, chi-square tests, and Random Forest classification. Findings: The findings show that COPQ is often measured only in selected functions; many organisations struggled to analyse COPQ as a percentage of sales revenue; and internal and external failure costs frequently remain in double-digit ranges, while prevention costs spending is relatively low. COPQ information is most strongly used at the operational level and less in strategic and tactical decisions. Moreover, Mikel Harry's benchmark figures (COPQ is equal to 1% at Six Sigma quality level, 25% at Three Sigma quality level of the sales revenue) are viewed more as heuristics than as universal truths. Originality: The study offers new evidence on COPQ measurement, links COPQ to Operational Excellence (OpEx) and Quality 4.0 (Q4.0) initiatives and demonstrates the value of predictive analytics for understanding departmental drivers of quality costs.
