First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness model, the greenness and radiation model and a light use efficiency model. The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3 to 65 percent). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation, root-mean-square error, and Bayesian information criterion. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models. The results of this study show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.Comment: Accepted manuscript; 12 pages, 4 tables, 9 figure

Compulsory admissions of patients with mental disorders : State of the art on ethical and legislative aspects in 40 European countries

Copyright: This record is sourced from MEDLINE/PubMed, a database of the U.S. National Library of MedicineBACKGROUND.: Compulsory admission procedures of patients with mental disorders vary between countries in Europe. The Ethics Committee of the European Psychiatric Association (EPA) launched a survey on involuntary admission procedures of patients with mental disorders in 40 countries to gather information from all National Psychiatric Associations that are members of the EPA to develop recommendations for improving involuntary admission processes and promote voluntary care. METHODS.: The survey focused on legislation of involuntary admissions and key actors involved in the admission procedure as well as most common reasons for involuntary admissions. RESULTS.: We analyzed the survey categorical data in themes, which highlight that both medical and legal actors are involved in involuntary admission procedures. CONCLUSIONS.: We conclude that legal reasons for compulsory admission should be reworded in order to remove stigmatization of the patient, that raising awareness about involuntary admission procedures and patient rights with both patients and family advocacy groups is paramount, that communication about procedures should be widely available in lay-language for the general population, and that training sessions and guidance should be available for legal and medical practitioners. Finally, people working in the field need to be constantly aware about the ethical challenges surrounding compulsory admissions.Peer reviewe

Compulsory admissions of patients with mental disorders : State of the art on ethical and legislative aspects in 40 European countries

Background. Compulsory admission procedures of patients with mental disorders vary between countries in Europe. The Ethics Committee of the European Psychiatric Association (EPA) launched a survey on involuntary admission procedures of patients with mental disorders in 40 countries to gather information from all National Psychiatric Associations that are members of the EPA to develop recommendations for improving involuntary admission processes and promote voluntary care. Methods. The survey focused on legislation of involuntary admissions and key actors involved in the admission procedure as well as most common reasons for involuntary admissions. Results. We analyzed the survey categorical data in themes, which highlight that both medical and legal actors are involved in involuntary admission procedures. Conclusions. We conclude that legal reasons for compulsory admission should be reworded in order to remove stigmatization of the patient, that raising awareness about involuntary admission procedures and patient rights with both patients and family advocacy groups is paramount, that communication about procedures should be widely available in lay-language for the general population, and that training sessions and guidance should be available for legal and medical practitioners. Finally, people working in the field need to be constantly aware about the ethical challenges surrounding compulsory admissions.Peer reviewe

Phytochemical analysis of the essential oils of 10 endemic Cephalaria species from Turkey

WOS: 000318292300009PubMed ID: 22757667The volatile composition of 10 endemic Cephalaria (Dipsacaceae) species (Cephalaria gazipashensis, Cephalaria lycica, Cephalaria paphlagonica, Cephalaria elmaliensis, Cephalaria stellipilis, Cephalaria scoparia, Cephalaria isaurica, Cephalaria cilicica, Cephalaria elazigensis var. purpurea and Cephalaria davisiana) was investigated. The essential oil mixtures were obtained by steam distillation in a Clevenger-type apparatus. Twenty-eight components were identified by GC-FID and GC-MS techniques. While total volatile percentages ranged from 68.99% to 84.57%, the total essential oil yields ranged between 38.15% and 64.05%. Geraniol, -cedrene and p-cymene were determined as the main components. Geraniol was detected as a major component in C. cilicica (14.64%), and -cedrene was detected as a major component with 26.03% for C. lycica, 16.93% for C. scoparia, 13.01% for C. davisiana and 10.94% for C. paphlagonica. Cephalaria scoparia, C. davisiana and C. gazipashensis have considerable amount of p-cymene as 12.86%, 12.70% and 11.16%, respectively. This was the first essential oil report concerning the Cephalaria genus.TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [107T028]; EBILTEMEge University [2008BIL003]; Research Grant Office of Ege UniversityEge University [2009FEN080]We are grateful to ARGE-FAR (Ege University) for running GC/GC-MS analysis, and TUBITAK (107T028), EBILTEM (2008BIL003) and Research Grant Office of Ege University (2009FEN080) for their financial support. We also thank to Assist. Prof. Dr H. Ertas for his valuable discussions

First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO 2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO 2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness (T-G) model, the greenness and radiation (GöR) model and a light use efficiency model (MOD17). The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3–65%). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation (R 2 ), root-mean-square error (RMSE), and Bayesian information criterion (BIC). The GöR model produced R 2 = 0.73, RMSE = 1.45 g C m −2 d −1 , and BIC = 678; the T-G model produced R 2 = 0.68, RMSE = 1.57 g C m −2 d −1 , and BIC = 707; the MOD17 model produced R 2 = 0.49, RMSE = 1.98 g C m −2 d −1 , and BIC = 800. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models (R 2 = 0.77, RMSE = 1.32 g C m −2 d −1 , and BIC = 631). These results show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa