Pub Date : 2021-09-01DOI: 10.1016/J.ECOINF.2021.101334
Shrikrishna Kolhar, Jayant Jagtap
{"title":"Spatio-temporal deep neural networks for accession classification of Arabidopsis plants using image sequences","authors":"Shrikrishna Kolhar, Jayant Jagtap","doi":"10.1016/J.ECOINF.2021.101334","DOIUrl":"https://doi.org/10.1016/J.ECOINF.2021.101334","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"118619645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-02DOI: 10.1016/J.ECOINF.2021.101335
S. Sutradhar, Prolay Mondal
{"title":"Groundwater suitability assessment based on water quality index and hydrochemical characterization of Suri Sadar Sub-division, West Bengal","authors":"S. Sutradhar, Prolay Mondal","doi":"10.1016/J.ECOINF.2021.101335","DOIUrl":"https://doi.org/10.1016/J.ECOINF.2021.101335","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"119257149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1016/j.ecoinf.2020.101118
B. Guterres, A. Guerreiro, J. Sandrini, S. Botelho
{"title":"Feasibility of visual signals on the construction of biosensors based on behavioral analysis of Perna perna mussels","authors":"B. Guterres, A. Guerreiro, J. Sandrini, S. Botelho","doi":"10.1016/j.ecoinf.2020.101118","DOIUrl":"https://doi.org/10.1016/j.ecoinf.2020.101118","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117692774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-20DOI: 10.22541/au.159526101.18047353
Hongye Cao, Ling Han, Zhiheng Liu, Liangzhi Li
Hongjiannao lake is the largest desert fresh water lake in China and the largest breeding and habitat of relict gulls in the world. On the basis of remote sensing images, a high-precision long-time series lake area continuous monitoring data set was constructed from 1973 to 2019. On this basis, the temporal and spatial evolution law of lake area and the coupling relationship with natural factors and human activities were studied. At the same time, the effectiveness monitoring of protection measures implemented since 2012 was realized. The results show that: (1) from 1973 to 2019, the area of Hongjiannao lake experienced three stages (relatively stable period (1973-1997) - shrinking period (1997-2015) - expanding period (2015-2019)). (2) The shrinkage of Hongjiannao lake is mainly caused by human factors, followed by natural factors. Among them, human factors are mainly composed of the upstream river construction reservoir, industrial development water and the increase of water demand for vegetation growth. (3) For the first time, the preliminary results of the protection measures implemented since 2012 are analyzed. It is mainly reflected in the first positive growth of Hongjiannao Lake area since the long-term shrinkage in 2016. This phenomenon is mainly caused by measures such as artificial precipitation increase and ecological water replenishment on the surface of upstream reservoir. Climate change (high evaporation and low precipitation) and human activities (upstream water conservancy project construction, coal mining, highway construction around the lake, irrigation water consumption, etc.) are the key factors leading to the change of lake water area in the shrinking period. It is suggested that artificial precipitation increase and surface ecological water supplement normalization should be carried out in the study area, as well as scientific and reasonable utilization of water resources in the basin to effectively restrain the shrinking of Hongjiannao lake area, so as to achieve long-term sustainable restoration of wetland ecology.
{"title":"Monitoring and driving force analysis of spatial and temporal change of water area of Hongjiannao Lake from 1973 to 2019","authors":"Hongye Cao, Ling Han, Zhiheng Liu, Liangzhi Li","doi":"10.22541/au.159526101.18047353","DOIUrl":"https://doi.org/10.22541/au.159526101.18047353","url":null,"abstract":"Hongjiannao lake is the largest desert fresh water lake in China and the largest breeding and habitat of relict gulls in the world. On the basis of remote sensing images, a high-precision long-time series lake area continuous monitoring data set was constructed from 1973 to 2019. On this basis, the temporal and spatial evolution law of lake area and the coupling relationship with natural factors and human activities were studied. At the same time, the effectiveness monitoring of protection measures implemented since 2012 was realized. The results show that: (1) from 1973 to 2019, the area of Hongjiannao lake experienced three stages (relatively stable period (1973-1997) - shrinking period (1997-2015) - expanding period (2015-2019)). (2) The shrinkage of Hongjiannao lake is mainly caused by human factors, followed by natural factors. Among them, human factors are mainly composed of the upstream river construction reservoir, industrial development water and the increase of water demand for vegetation growth. (3) For the first time, the preliminary results of the protection measures implemented since 2012 are analyzed. It is mainly reflected in the first positive growth of Hongjiannao Lake area since the long-term shrinkage in 2016. This phenomenon is mainly caused by measures such as artificial precipitation increase and ecological water replenishment on the surface of upstream reservoir. Climate change (high evaporation and low precipitation) and human activities (upstream water conservancy project construction, coal mining, highway construction around the lake, irrigation water consumption, etc.) are the key factors leading to the change of lake water area in the shrinking period. It is suggested that artificial precipitation increase and surface ecological water supplement normalization should be carried out in the study area, as well as scientific and reasonable utilization of water resources in the basin to effectively restrain the shrinking of Hongjiannao lake area, so as to achieve long-term sustainable restoration of wetland ecology.","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132360898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
No systematic approach has yet been adopted to reliably reference and provide access to digital biodiversity datasets. Based on accumulated evidence, we argue that location-based identifiers such as URLs are not sufficient to ensure long-term data access. We introduce a method that uses dedicated data observatories to evaluate long-term URL reliability.From March 2019 through May 2020, we took periodic inventories of the data provided to major biodiversity aggregators, including GBIF, iDigBio, DataONE, and BHL by accessing the URL-based dataset references from which the aggregators retrieve data. Over the period of observation, we found that, for the URL-based dataset references available in each of the aggregators' data provider registries, 5% to 70% of URLs were intermittently or consistently unresponsive, 0% to 66% produced unstable content, and 20% to 75% became either unresponsive or unstable.We propose the use of cryptographic hashing to generate content-based identifiers that can reliably reference datasets. We show that content-based identifiers facilitate decentralized archival and reliable distribution of biodiversity datasets to enable long-term accessibility of the referenced datasets.
{"title":"Toward reliable biodiversity dataset references","authors":"Michael Elliott, J. Poelen, J. Fortes","doi":"10.32942/osf.io/mysfp","DOIUrl":"https://doi.org/10.32942/osf.io/mysfp","url":null,"abstract":"No systematic approach has yet been adopted to reliably reference and provide access to digital biodiversity datasets. Based on accumulated evidence, we argue that location-based identifiers such as URLs are not sufficient to ensure long-term data access. We introduce a method that uses dedicated data observatories to evaluate long-term URL reliability.From March 2019 through May 2020, we took periodic inventories of the data provided to major biodiversity aggregators, including GBIF, iDigBio, DataONE, and BHL by accessing the URL-based dataset references from which the aggregators retrieve data. Over the period of observation, we found that, for the URL-based dataset references available in each of the aggregators' data provider registries, 5% to 70% of URLs were intermittently or consistently unresponsive, 0% to 66% produced unstable content, and 20% to 75% became either unresponsive or unstable.We propose the use of cryptographic hashing to generate content-based identifiers that can reliably reference datasets. We show that content-based identifiers facilitate decentralized archival and reliable distribution of biodiversity datasets to enable long-term accessibility of the referenced datasets.","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116633676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1016/J.ECOINF.2018.12.008
A. Reinhold, G. Poole, C. Izurieta, A. Helton, E. Bernhardt
{"title":"Constraint-based simulation of multiple interactive elemental cycles in biogeochemical systems","authors":"A. Reinhold, G. Poole, C. Izurieta, A. Helton, E. Bernhardt","doi":"10.1016/J.ECOINF.2018.12.008","DOIUrl":"https://doi.org/10.1016/J.ECOINF.2018.12.008","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"906 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"119840694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1016/j.ecoinf.2019.01.013
S. Xiao, Han Y. H. Chen
{"title":"Unimodal diversity-productivity relationship emerged under stressful environment through sampling effect","authors":"S. Xiao, Han Y. H. Chen","doi":"10.1016/j.ecoinf.2019.01.013","DOIUrl":"https://doi.org/10.1016/j.ecoinf.2019.01.013","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"118480152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-01DOI: 10.1016/j.ecoinf.2019.01.011
L. Clarke, R. Hill, A. Ford, R. Herbert, L. Esteves, R. Stillman
{"title":"Using remote sensing to quantify fishing effort and predict shorebird conflicts in an intertidal fishery","authors":"L. Clarke, R. Hill, A. Ford, R. Herbert, L. Esteves, R. Stillman","doi":"10.1016/j.ecoinf.2019.01.011","DOIUrl":"https://doi.org/10.1016/j.ecoinf.2019.01.011","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"118549465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.1016/j.ecoinf.2018.11.005
Claire Kermorvant, N. Caill-Milly, N. Bru, F. D’Amico
{"title":"Optimizing cost-efficiency of long term monitoring programs by using spatially balanced sampling designs: The case of manila clams in Arcachon bay","authors":"Claire Kermorvant, N. Caill-Milly, N. Bru, F. D’Amico","doi":"10.1016/j.ecoinf.2018.11.005","DOIUrl":"https://doi.org/10.1016/j.ecoinf.2018.11.005","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"420 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120133753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.1016/j.ecoinf.2018.11.001
G. Jácome, Paulina Vilela, C. Yoo
{"title":"Social-ecological modelling of the spatial distribution of dengue fever and its temporal dynamics in Guayaquil, Ecuador for climate change adaption","authors":"G. Jácome, Paulina Vilela, C. Yoo","doi":"10.1016/j.ecoinf.2018.11.001","DOIUrl":"https://doi.org/10.1016/j.ecoinf.2018.11.001","url":null,"abstract":"","PeriodicalId":178797,"journal":{"name":"Ecol. Informatics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120601563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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