- Chris A.M. Swaay van (1)
- Amina Abdu (1)
- Takele Beyene Tufa (1)
- Amanuel Eshetu (1)
- Michiel F. WallisDeVries (1)
- Sascha Fassler (1)
- Ashenafi Feyisa Beyi (1)
- Sven Gastauer (1)
- Sami Ibrahim (1)
- Arco J. Strien van (1)
- Martin J.M. Poot (1)
- Tariku Jibat Beyene (1)
- Daniel P.L.D. Benden (1)
- Miles Parsons (1)
- Ben Scoulding (1)
- Willy T.F.H. Strien-van Liempt van (1)
- Etenesh Wondimu (1)
Over a century of data reveal more than 80% decline in butterflies in the Netherlands
Strien, Arco J. van; Swaay, Chris A.M. van; Strien-van Liempt, Willy T.F.H. van; Poot, Martin J.M. ; WallisDeVries, Michiel F. - \ 2019
Biological Conservation 234 (2019). - ISSN 0006-3207 - p. 116 - 122.
Bayesian inference - Distribution - JAGS - List length analysis - Living Planet Index - Monitoring
Opportunistic butterfly records from 1890 to 2017 were analysed to quantitatively estimate the overall long-term change in occurrence of butterfly species in the Netherlands. For 71 species, we assessed trends in the number of occupied 5 km × 5 km sites by applying a modified List Length method, which takes into account changes in observation effort. We summarised the species trends in a Multi-Species Indicator (MSI) by taking the geometric mean of the species indices. Between 1890–1930 and 1981–1990, the MSI decreased by 67%; downward trends were detected for 42 species, many of which have disappeared completely from the Netherlands. Monitoring count data available from 1992 showed a further 50% decline in MSI. Combined, this yields an estimated decline of 84% in 1890–2017. We argue that in reality the loss is likely even higher. We also assessed separate MSIs for three major butterfly habitat types in the Netherlands: grassland, woodland and heathland. Butterflies strongly declined in all three habitats alike. The trend has stabilised over recent decades in grassland and woodland, but the decline continues in heathland.
Assisting differential clinical diagnosis of cattle diseases using smartphone-based technology in low resource settings : A pilot study
Beyene, Tariku Jibat ; Eshetu, Amanuel ; Abdu, Amina ; Wondimu, Etenesh ; Beyi, Ashenafi Feyisa ; Tufa, Takele Beyene ; Ibrahim, Sami - \ 2017
BMC Veterinary Research 13 (2017)1. - ISSN 1746-6148
Bayesian inference - Cattle disease - Differential diagnosis - Ethiopia - Smartphone-based application
Background: The recent rise in mobile phone use and increased signal coverage has created opportunities for growth of the mobile Health sector in many low resource settings. This pilot study explores the use of a smartphone-based application, VetAfrica-Ethiopia, in assisting diagnosis of cattle diseases. We used a modified Delphi protocol to select important diseases and Bayesian algorithms to estimate the related disease probabilities based on various clinical signs being present in Ethiopian cattle. Results: A total of 928 cases were diagnosed during the study period across three regions of Ethiopia, around 70% of which were covered by diseases included in VetAfrica-Ethiopia. Parasitic Gastroenteritis (26%), Blackleg (8.5%), Fasciolosis (8.4%), Pasteurellosis (7.4%), Colibacillosis (6.4%), Lumpy skin disease (5.5%) and CBPP (5.0%) were the most commonly occurring diseases. The highest (84%) and lowest (30%) levels of matching between diagnoses made by student practitioners and VetAfrica-Ethiopia were for Babesiosis and Pasteurellosis, respectively. Multiple-variable logistic regression analysis indicated that the putative disease indicated, the practitioner involved, and the level of confidence associated with the prediction made by VetAfrica-Ethiopia were major determinants of the likelihood that a diagnostic match would be obtained. Conclusions: This pilot study demonstrated that the use of such applications can be a valuable means of assisting less experienced animal health professionals in carrying out disease diagnosis which may lead to increased animal productivity through appropriate treatment.
Target strength estimates of red emperor (Lutjanus sebae) with Bayesian parameter calibration
Gastauer, Sven ; Scoulding, Ben ; Fassler, Sascha ; Benden, Daniel P.L.D. ; Parsons, Miles - \ 2016
Aquatic Living Resources 29 (2016)3. - ISSN 0990-7440
Bayesian inference - Fisheries acoustics - KRM - Lutjanus sebae - Target Strength - Vessel of opportunity
Red emperor (Lutjanus sebae) is a long-lived tropical demersal snapper which is widely distributed in the Western Pacific and Indian Ocean. Despite the commercial and recreational importance of the species for the Northern Demersal Scalefish Fishery off the Northwest coast of Western Australia, we still lack a thorough understanding of its distribution and abundance in the area. To better understand the acoustic scattering properties of red emperor its acoustic backscattering characteristics were modelled based on swimbladder and body morphology, determined using computed tomography scans. A Kirchhoff-ray mode approximation was coupled with empirical (ex situ) measurements of target strength (TS) obtained from a 38 and 120 kHz split-beam echosounder on board a fishing vessel. Bayesian methods were used for model parameter calibration, which provided uncertainty estimates for some of the TS-model parameters. The derived TS-length relationships were 19.7log 10(L)-75.5 (C.I. 5.9 dB) at 120 kHz and 14.6 log10(L)-64.9 (C.I. 5.8 dB) at 38 kHz. The study demonstrated that small commercial fishing vessels can be used to conduct ex situ experiments and target strength modelling can be effectively based on computer tomography scans. This relatively low cost approach could be applied to other species.