Birds - their importance to visitors to an Australian rainforest

Lamington National Park in Queensland, Australia is noted for its rainforest and is part of Australia’s fourteen World Heritage listed properties but no systematic study has been done of the importance of birds to its visitors. This study rectifies this situation. It is based on data from survey forms handed to visitors at an important site in this park and completed by visitors following their visit. This yielded 622 useable replies. These enabled us to establish the comparative importance of birds as an attraction to this site. Furthermore, logit regression is used to analyze and to identify factors that increase the likelihood of a visitor saying that birds are an important attraction. In addition, the relative importance to visitors of various attributes of birds at this site is established. These attributes include hearing birds, diversity of birds, seeing lots of birds, presence of rare birds, presence of brightly colored birds and physical contact with birds. Logit regression analysis is used to isolate independent variables that increase or decrease the likelihood that visitors find diversity of birds, brightly colored birds or physical contact with birds at this site to be important. For example, factors such as the level of education of visitors, their gender, knowledge of birds and conservation attitudes are statistically significant influences.

Birds in an Australian rainforest: Their attraction for visitors and visitors' ecological impacts

Lamington National Park in Queensland, Australia is noted for its rainforest and is part of the World Heritage listed property but prior to this work, no systematic study has been done of the importance of birds to its visitors. This study is based on data from survey forms handed to visitors at an important site in the park and completed by visitors following their visit. It yielded 622 useable responses. These enabled us to establish the comparative importance of birds as an attraction to this site for this sample of visitors. Furthermore, logit regression is used to target analysis and to identify factors that increase the likelihood of a visitor saying that birds are an important attraction. In addition, the relative importance to visitors of various attributes of birds at this site is established. These attributes include hearing birds, diversity of birds, seeing lots of birds, presence of rare birds, presence of brightly coloured birds and physical contact with birds. Logit regression analysis is used to isolate independent variables that increase or decrease the likelihood that visitors find diversity of birds, brightly coloured birds or physical contact with birds at this site to be important. For example, factors such as the level of education of visitors, their gender, knowledge of birds and conservation attitudes and statistically significant influences. As a result of the analysis potential conflicts between different types of park visitors in relation to human interaction with birds are identified. Some potential ecological implications of human interactions with birds are modelled and discussed, and their economic conservation and biodiversity consequences are considered

A comparison of observed versus estimated baseline creatinine for determination of RIFLE class in patients with acute kidney injury

Methods. Data from the Beginning and Ending Supportive Therapy for the Kidney (BEST Kidney) study, a prospective observational study from 54 ICUs in 23 countries of critically ill patients with severe AKI, were analysed. The RIFLE class was determined by using observed (o) pre-morbid and estimated (e) baseline SCr values. Agreement was evaluated by correlation coefficients and Bland-Altman plots. Sensitivity analysis by chronic kidney disease (CKD) status was performed. Results. Seventy-six percent of patients (n = 1327) had a pre-morbid baseline SCr, and 1314 had complete data for evaluation. Forty-six percent had CKD. The median (IQR) values were 97 mu mol/L (79-150) for oSCr and 88 mu mol/L (71-97) for eSCr. The oSCr and eSCr determined at ICU admission and at study enrolment showed only a modest correlation (r = 0.49, r = 0.39). At ICU admission and study enrolment, eSCr misclassified 18.8% and 11.7% of patients as having AKI compared with oSCr. Exclusion of CKD patients improved the correlation between oSCr and eSCr at ICU admission and study enrolment (r = 0.90, r = 0.84) resulting in 6.6% and 4.0% being misclassified, respectively. Conclusions. While limited, estimating baseline SCr by the MDRD equation when pre-morbid SCr is unavailable would appear to perform reasonably well for determining the RIFLE categories only if and when pre-morbid GFR was near normal. However, in patients with suspected CKD, the use of MDRD to estimate baseline SCr overestimates the incidence of AKI and should not likely be used. Improved methods to estimate baseline SCr are needed.