scholarly journals Effect of sunlight condition determined by terrain on tree health of Japanese mountain cherry (Cerasus jamasakura (Siebold ex Koidz.) H. Ohba var. jamasakura) in Yoshinoyama, Nara Prefecture, Japan

2012 ◽  
Vol 38 (1) ◽  
pp. 15-20
Author(s):  
Junichi IMANISHI ◽  
Hyunjun KIM ◽  
Yoshihiko IIDA ◽  
Hiroko OKUGAWA ◽  
Yukihiro MORIMOTO ◽  
...  
Keyword(s):  
Tree Health ◽  
Cerasus Jamasakura ◽  
Nara Prefecture

Estimation of Individual Tree Health Condition for Japanese Mountain Cherry (Cerasus jamasakura) Using Airborne LiDAR

2019 ◽  
Vol 45 (2) ◽  
Author(s):  
Takeshi Sasaki ◽  
Junichi Imanishi ◽  
Yoshihiko Iida ◽  
Youngkeun Song ◽  
Yukihiro Morimoto ◽  
...  
Keyword(s):  
Linear Models ◽  
Health Indicators ◽  
Health Condition ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Estimation Errors ◽  
Individual Tree ◽  
Tree Health ◽  
Crown Density ◽  
Cerasus Jamasakura

This study examined the usefulness of airborne light detection and ranging (LiDAR) data for estimating the individual tree health condition in Japanese mountain cherry (Cerasus jamasakura) in Yoshinoyama, Nara Prefecture, Japan. LiDAR variables that represented the ratio of lasers hitting tree components were calculated and their effectiveness was examined by relating them to the results of conventional field-based visual tree health assessments based on ordination, correlation analyses, and generalized linear models. The results showed that many of the LiDAR variables had significant correlations with the variables derived from visually evaluated tree health condition. In particular, the proportion of “only” returns, which represents the ratio of the lasers reflected from the crown surfaces, was the most effective for estimating total health condition in relation to the crown density, one of the key health indicators for representing physical properties. The individuals with large estimation errors had smaller crowns than the individuals with small errors, suggesting that sufficiently large crown sizes are important for more accurate estimations of the tree health condition using airborne LiDAR data.

scholarly journals Relationship between initial peritoneal dialysis modality and risk of peritonitis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Maiko Kokubu ◽  
Masaru Matsui ◽  
Takayuki Uemura ◽  
Katsuhiko Morimoto ◽  
Masahiro Eriguchi ◽  
...  
Keyword(s):  
Peritoneal Dialysis ◽  
Lower Risk ◽  
Observational Studies ◽  
Primary Outcome ◽  
Propensity Scores ◽  
First Episode ◽  
Connection Type ◽  
Adjusted Model ◽  
The Relationship ◽  
Nara Prefecture

Abstract Peritonitis is a critical complication of peritoneal dialysis (PD). Investigators have reported the risk of peritonitis in patients on continuous ambulatory peritoneal dialysis (CAPD) versus automated peritoneal dialysis (APD), but the available evidence is predominantly based on observational studies which failed to report on the connection type. Our understanding of the relationship between peritonitis risk and PD modality thus remained insufficient. We studied 285 participants who began PD treatment between 1997 and 2014 at three hospitals in Nara Prefecture in Japan. We matched 106 APD patients with 106 CAPD patients based on their propensity scores. The primary outcome was time to first episode of peritonitis within 3 years after PD commencement. In total, PD peritonitis occurred in 64 patients during the study period. Patients initiated on APD had a lower risk of peritonitis than did those initiated on CAPD in both the unadjusted and adjusted models. The hazard ratio (HR) and 95% confidence interval (CI) for the primary endpoint were 0.30 (0.17–0.53) in the fully adjusted model including connection type. In the matched cohort, APD patients had a significantly lower risk of peritonitis than did CAPD patients (log-rank: p < 0.001, HR 0.32, 95% CI 0.16–0.59). The weighting-adjusted analysis of the inverse probability of treatment yielded a similar result (HR 0.35, 95% CI 0.18–0.67). In conclusion, patients initiated on APD at PD commencement had a reduced risk of peritonitis compared with those initiated on CAPD, suggesting APD may be preferable for prevention of peritonitis among PD patients.

The influence of local elevation on soil properties and tree health in remnant eucalypt woodlands affected by secondary salinity

2004 ◽  
Vol 265 (1-2) ◽  
pp. 175-188 ◽  
Author(s):  
Viki A. Cramer ◽  
Richard J. Hobbs ◽  
Lyn Atkins ◽  
Geoff Hodgson
Keyword(s):  
Soil Properties ◽  
Tree Health ◽  
Eucalypt Woodlands ◽  
Secondary Salinity

Public acceptance of tree health management: Results of a national survey in the UK

2016 ◽  
Vol 59 ◽  
pp. 18-25 ◽  
Author(s):  
Lauren Fuller ◽  
Mariella Marzano ◽  
Andrew Peace ◽  
Christopher P. Quine ◽  
Norman Dandy
Keyword(s):  
National Survey ◽  
Health Management ◽  
Public Acceptance ◽  
Tree Health ◽  
The Uk

scholarly journals Development and Assessment of Ash Mortality Models in Relation to Emerald Ash Borer Infestation

2015 ◽  
Vol 41 (5) ◽  
Author(s):  
Rachel Clark ◽  
Kayla Boyes ◽  
Lori Morgan ◽  
Andrew Storer ◽  
Jordan Marshall
Keyword(s):  
Tree Mortality ◽  
Management Strategies ◽  
Health Assessment ◽  
Emerald Ash Borer ◽  
Decision Models ◽  
Correct Prediction ◽  
Tree Health ◽  
Prediction Of Mortality ◽  
Introduced Range ◽  
Wide Range

Emerald ash borer is a pest of North American ash that has caused significant mortality within its introduced range. The timeline for tree mortality, once infested by emerald ash borer, is variable for individual trees, with a small proportion surviving infestation. Using tree health assessments and signs of emerald ash borer infestation, researchers developed decision models to predict the probability of mortality. Two resulting models performed well at correctly predicting mortality (>83% correct) and significantly separating probability of mortality for those trees. Both models used diameter at breast height (DBH) and presence of bark splits, with one including percent crown dieback and the other including vigor rating (overall tree health assessment). A third model had reduced correct prediction of mortality, but was still potentially an effective model. Other tested models had shortcomings in prediction of mortality or in separation of probabilities of mortality. Using variables from three potential decision models, the year of mortality was modeled. However, specific year prediction was not as effective. Because of a wide range of external factors, prediction of a specific year of mortality may not be appropriate. Using DBH and rapid health and infestation assessment data, the authors were able to correctly predict ash mortality within a three-year period for the majority of trees within this study. Management strategies that use these models for developing hierarchical removal programs for infested ash may distribute financial and environmental costs over multiple years as opposed to mass removal of street and park trees.

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