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94 results for “Biology Economics”
FIGURE 1 in Reproductive biology of Parona signata (Actinopterygii: Carangidae), a valuable economic resource, in the coastal area of Mar del Plata, Buenos Aires, Argentina
FIGURE 1 | Monthly variation of the gonadosomatic index (GSI) of females (black continuous line), standard deviation (dashed lines) and temperature (in Celsius degrees) (gray continuous line) based on an annual cycle.
FIGURE 3 in Reproductive biology of Parona signata (Actinopterygii: Carangidae), a valuable economic resource, in the coastal area of Mar del Plata, Buenos Aires, Argentina
FIGURE 3 | Photomicrographs of Parona signata. A: primary growth oocytes (P); B: cortical alveoli oocytes (CA); C: yolked oocytes (YO) and a post-ovulatory follicle (large arrow); D: details of a yolked oocyte (r: radiate zone; g: granulosa cells; t: theca cells); E: hydrated oocyte (arrow); F: details of a post-ovulatory follicle (arrow); G: primary growth oocytes in an adult ovary (notice the thick wall of the ovary – OW); H: atresic follicle (arrow).
FIGURE 2 in Reproductive biology of Parona signata (Actinopterygii: Carangidae), a valuable economic resource, in the coastal area of Mar del Plata, Buenos Aires, Argentina
FIGURE 2 | Monthly relative frequency of the different gonadal development stages observed in females of Parona signata on the annual cycle.
Where do Gyps fulvus (Griffon Vultures) feed? Combining biologging with socio-economic analysis can guide sustainable ecotourism development
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Supplementary material 4 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Extrapolated annual average costs for those invasive species known to be in Singapore with recorded costs in InvaCost
Supplementary material 1 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Description of the procedure used for collecting and describing cost data in the InvaCost database (adapted from Diagne et al. 2020)
Supplementary material 5 from: Haubrock PJ, Cuthbert RN, Yeo DCJ, Banerjee AK, Liu C, Diagne C, Courchamp F (2021) Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 131-152. https://doi.org/10.3897/neobiota.67.64560
Relationships between trade value and recorded cost entries per country in InvaCost, as well as land area and human population with total cost
Supplementary material 4 from: Cuthbert RN, Bartlett AC, Turbelin AJ, Haubrock PJ, Diagne C, Pattison Z, Courchamp F, Catford JA (2021) Economic costs of biological invasions in the United Kingdom. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 299-328. https://doi.org/10.3897/neobiota.67.59743
Total costs of species with individual cost entries, alongside first record years and introduction pathways
Supplementary material 8 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
List of the 68 invasive alien species in metropolitan France for which no economic cost was documented in our database
Supplementary material 6 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
Categorical representation of the cumulated costs caused by invasive alien species in metropolitan France and French overseas over the period 1993–2018
Supplementary material 7 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
For each French region, listing of the taxa for which we had cost information in the InvaCost database over the time range 1993–2018
Supplementary material 1 from: Haubrock PJ, Cuthbert RN, Sundermann A, Diagne C, Golivets M, Courchamp F (2021) Economic costs of invasive species in Germany. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 225-246. https://doi.org/10.3897/neobiota.67.59502
Description of the procedure used for collecting and describing cost data in the InvaCost database (adapted from Diagne et al. 2020)
Supplementary material 7 from: Diagne C, Turbelin AJ, Moodley D, Novoa A, Leroy B, Angulo E, Adamjy T, Dia CA.K.M, Taheri A, Tambo J, Dobigny G, Courchamp F (2021) The economic costs of biological invasions in Africa: a growing but neglected threat? In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 11-51. https://doi.org/10.3897/neobiota.67.59132
Relative weights of predictor categories in the linear robust regression between cost data and time period
Supplementary material 11 from: Diagne C, Turbelin AJ, Moodley D, Novoa A, Leroy B, Angulo E, Adamjy T, Dia CA.K.M, Taheri A, Tambo J, Dobigny G, Courchamp F (2021) The economic costs of biological invasions in Africa: a growing but neglected threat? In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 11-51. https://doi.org/10.3897/neobiota.67.59132
Summary of the outputs from the different models used for analyzing the temporal trend of invasion costs in Africa between 1970 and 2019
Supplementary material 3 from: Cuthbert RN, Bartlett AC, Turbelin AJ, Haubrock PJ, Diagne C, Pattison Z, Courchamp F, Catford JA (2021) Economic costs of biological invasions in the United Kingdom. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 299-328. https://doi.org/10.3897/neobiota.67.59743
Web of Science search terms for UK invasive species publication numbers, alongside resulting study numbers
Supplementary material 1 from: Renault D, Manfrini E, Leroy B, Diagne C, Ballesteros-Mejia L, Angulo E, Courchamp F (2021) Biological invasions in France: Alarming costs and even more alarming knowledge gaps. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 191-224. https://doi.org/10.3897/neobiota.67.59134
Datasets of the economic costs of invasive alien species in France and descriptive variables (from Diagne et al. 2020b)
Supplementary material 2 from: Cuthbert RN, Bartlett AC, Turbelin AJ, Haubrock PJ, Diagne C, Pattison Z, Courchamp F, Catford JA (2021) Economic costs of biological invasions in the United Kingdom. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 299-328. https://doi.org/10.3897/neobiota.67.59743
Summary of the content of the descriptive columns of the database used in this study (adapted from Diagne et al. 2020a)
Supplementary material 2 from: Adelino JRP, Heringer G, Diagne C, Courchamp F, Faria LDB, Zenni RD (2021) The economic costs of biological invasions in Brazil: a first assessment. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 349-374. https://doi.org/10.3897/neobiota.67.59185
Table S2. Observed costs for Brazil from the invacost database organized into the following group of intervention: damage, management, and mixed
Supplementary material 1 from: Adelino JRP, Heringer G, Diagne C, Courchamp F, Faria LDB, Zenni RD (2021) The economic costs of biological invasions in Brazil: a first assessment. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 349-374. https://doi.org/10.3897/neobiota.67.59185
Table S1. Observed costs for Brazil from the invacost database including the confidence attributed to the observed costs
Supplementary material 1 from: Cuthbert RN, Bartlett AC, Turbelin AJ, Haubrock PJ, Diagne C, Pattison Z, Courchamp F, Catford JA (2021) Economic costs of biological invasions in the United Kingdom. In: Zenni RD, McDermott S, García-Berthou E, Essl F (Eds) The economic costs of biological invasions around the world. NeoBiota 67: 299-328. https://doi.org/10.3897/neobiota.67.59743
Subset of InvaCost database used for analyses of UK invasion costs. Note that cost data are not annualised.
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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.