scholarly journals Estimating aboveground net biomass change for tropical and subtropical forests: Refinement of IPCC default rates using forest plot data

2019 ◽  
Vol 25 (11) ◽  
pp. 3609-3624 ◽  
Author(s):  
Daniela Requena Suarez ◽  
Danaë M. A. Rozendaal ◽  
Veronique De Sy ◽  
Oliver L. Phillips ◽  
Esteban Alvarez‐Dávila ◽  
...  
Keyword(s):  
Forest Plot ◽  
Subtropical Forests ◽  
Default Rates ◽  
Ipcc Default

The Orchard Plot: Cultivating a Forest Plot for Use in Ecology, Evolution and Beyond

2019 ◽  
Author(s):  
Shinichi Nakagawa ◽  
Malgorzata Lagisz ◽  
Rose E O'Dea ◽  
Joanna Rutkowska ◽  
Yefeng Yang ◽  
...  
Keyword(s):  
Meta Analysis ◽  
R Package ◽  
Effect Sizes ◽  
Forest Plot ◽  
Point Estimates ◽  
Aggregate Effect ◽  
The Individual ◽  
Meta Analyses ◽  
Heterogeneous Effect ◽  
Intuitive Interpretation

‘Classic’ forest plots show the effect sizes from individual studies and the aggregate effect from a meta-analysis. However, in ecology and evolution meta-analyses routinely contain over 100 effect sizes, making the classic forest plot of limited use. We surveyed 102 meta-analyses in ecology and evolution, finding that only 11% use the classic forest plot. Instead, most used a ‘forest-like plot’, showing point estimates (with 95% confidence intervals; CIs) from a series of subgroups or categories in a meta-regression. We propose a modification of the forest-like plot, which we name the ‘orchard plot’. Orchard plots, in addition to showing overall mean effects and CIs from meta-analyses/regressions, also includes 95% prediction intervals (PIs), and the individual effect sizes scaled by their precision. The PI allows the user and reader to see the range in which an effect size from a future study may be expected to fall. The PI, therefore, provides an intuitive interpretation of any heterogeneity in the data. Supplementing the PI, the inclusion of underlying effect sizes also allows the user to see any influential or outlying effect sizes. We showcase the orchard plot with example datasets from ecology and evolution, using the R package, orchard, including several functions for visualizing meta-analytic data using forest-plot derivatives. We consider the orchard plot as a variant on the classic forest plot, cultivated to the needs of meta-analysts in ecology and evolution. Hopefully, the orchard plot will prove fruitful for visualizing large collections of heterogeneous effect sizes regardless of the field of study.

Adjusting corporate default rates for rating withdrawals

2007 ◽  
Vol 3 (2) ◽  
pp. 3-25 ◽  
Author(s):  
Richard Cantor ◽  
David Hamilton
Keyword(s):  
Corporate Default ◽  
Default Rates

Questions to the Article of the Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China: a Combined Analysis of Population Samples (Preprint)

2020 ◽  
Author(s):  
CHIEN WEI
Keyword(s):  
Confidence Intervals ◽  
Infection Rate ◽  
Standard Error ◽  
Recent Article ◽  
Forest Plot ◽  
Combined Analysis ◽  
Infected People ◽  
Heterogeneity Test

UNSTRUCTURED The recent article published on July 22 in 2020 remains several questionable issues that are required to clarifications further, particularly for readers who hope to replicate Figure 1 from the data in Table 1. Although I reproduced a similar forest plot based on the effect ratios and their 95% confidence intervals(Cis) similar to Figure 1 in that article, no detailed information about the source of standard error(SE) for each country was seen and addressed. Others like the positive 95% Cis reflecting the negative Z values in the forest plot and the Q statistics used for examining the heterogeneity test are requied to interpretations and classifications. Most importantly, authors did not explain how to estimate the number of infected people in Wuhan, China, to be 143,000 ,significantly higher than the number of confirmed cases(=75,815 in Wuhan, China) that is required to provide the equations or methodologies in an article.

scholarly journals Developing Growth Models of Stand Volume for Subtropical Forests in Karst Areas: A Case Study in the Guizhou Plateau

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 83
Author(s):  
Yuzhi Tang ◽  
Quanqin Shao ◽  
Tiezhu Shi ◽  
Guofeng Wu
Keyword(s):  
Growth Models ◽  
Volume Growth ◽  
Site Quality ◽  
Rocky Desertification ◽  
Stand Volume ◽  
Subtropical Forests ◽  
Karst Areas ◽  
Growth Equations ◽  
Global Carbon ◽  
Guizhou Plateau

Forest stand volume is one of the key forest structural attributes in estimating and forecasting ecosystem productivity and carbon stock. However, studies on growth modeling and environmental influences on stand volume are still rare to date, especially in subtropical forests in karst areas, which are characterized by a complex species composition and are important in the global carbon budget. In this paper, we developed growth models of stand volume for all the dominant tree species (groups) (DTSG) in a subtropical karst area, the Guizhou Plateau based on an investigation of the effects of various environmental factors on stand volume. The Richards growth function, space-for-time substitution and zonal-hierarchical modeling method were applied in the model fitting, and multiple indices were used in the model evaluation. The results showed that the climatic factors of annual temperature and precipitation, as well as the site factors of stand origin, elevation, slope gradient, topsoil thickness, site quality degree, rocky desertification type and rocky desertification degree, have significant influences on stand volume, and the topsoil thickness and site quality degree have the strongest positive effect. A total of 959 growth equations of stand volume were fitted with a five-level stand classifier (DTSG–climatic zone–site quality degree–stand origin–rocky desertification type). All the growth equations were qualified, because all passed the TRE test (≤30%), and the majority of the R2 ≥ 0.50, above 70% of the RMSE were between 5.0 and 20.0, and above 80% of the P ≥ 75%. These findings provide updated knowledge about the environmental effect on the stand volume growth of subtropical forests in karst areas, and the developed stand volume growth models are convenient for forest management and planning, further contributing to the study of forest carbon storage assessments and global carbon cycling.

scholarly journals AB0576 BONE EROSION IN PSORIATIC ARTHRITIS ASSOCIATED WITH PSORIASIS DURATION, SKIN, NAIL AND JOINT DISEASE SEVERITY

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1325.2-1326
Author(s):  
M. Chamurlieva ◽  
E. Loginova ◽  
T. Korotaeva ◽  
Y. Korsakova ◽  
E. Gubar ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Psoriatic Arthritis ◽  
Disease Severity ◽  
Bone Erosion ◽  
Joint Disease ◽  
Practice Research ◽  
Forest Plot ◽  
Clinical Practice Research Datalink ◽  
Increased Risk ◽  
Nail Disease

Background:Psoriatic arthritis (PsA) is heterogeneous in its clinical presentation and disease course, but many patients (pts) develop a destructive form of arthritis. Psoriasis (PsO) precedes arthritis by an average of 7 years. [1]. Theory of transition from PsO to PsA has been proposed recently [2]. But association between skin disease severity and joint disease are still unclear.Objectives:to evaluate association between bone erosion, PsO duration, skin and nail disease severity in PsA pts based on data from clinical practice (RU-PsART cohort).Methods:737 (M/F=350/387) PsA pts fulfilling the CASPAR criteria were included. Mean age 47.4±12.7 years (yrs), PsA duration 55[17;120] mos., PsO duration 165[74.5;292] mos., mean DAPSA 23.3[14;36.9] mos., HAQ-DI - 0.98 [0.5;1.38], CRP - 7.4 [2.1;18] mg/l. All pts underwent standard clinical examination (tender joins count (TJC)/68, swelling joints count (SJC)/66, CRP (mg/l), DAPSA, dactylitis, enthesitis by LEI + Plantar Facia (PF), HAQ-DI. Mild disease was defined as body surface area (BSA)≤10%, moderate to severe as BSA>10%. The presence/absent of nail PsO was evaluated. X-ray of feet and hand were done in 622 out of 737 pts. The one-factor model of logistic regression was used to identify a group of features that are associated with achievement MDA. M±SD, Me [Q25; Q75], Min-Max, %, t-test, Pierson-χ2, Manna-Whitney tests, ORs with 95% CI were performed. All p<0.05 were considered to indicate statistical significance.Results:PsO precedes of PsA by an average of 9.2 years. BSA≤10% was found in 615 out of 672 pts (91.5%), BSA>10% - in 57 out of 672 pts (8.5%). Nail PsO were seen in 230 out of 737 (31.2%). Bone erosion was found in 237 out of 622 of pts (38.1%). Among these pts nail PsO were seen in 67 out of 237 pts (28.3%). Enthesitis found in 236 out of 737 pts (42.1%), dactylitis – in 197 out 731 pts (27%), axial PsA – in 315 out of 731 pts (43.1%). Bone erosion significantly associated with PsO duration more than 5 yrs., skin and nail PsO severity, high PsA activity by DAPSA, axial manifestation and duration of PsA > 36 mos. (Figure 1).Figure 1Forest plot of factors associated with bone erosion in PsA pts.Conclusion:In our cohort the majority of PsA pts had mild PsO preceded PsA on average of 9.2 yrs. Bone erosion was found in 30% of PsA pts which associated with PsO duration, skin and nail disease severity as well as with PsA activity. Early diagnosis and therapeutic intervention within a “window of opportunity” are very important for improving outcomes and prevent structural damage in PsA.References:[1]Tillett W, et al. Interval between onset of psoriasis and psoriatic arthritis comparing the UK Clinical Practice Research Datalink with a hospital-based cohort. Rheumatol. 2017; 56, 2109–2113[2]Scher JU, et al. Preventing psoriatic arthritis: focusing on patients with psoriasis at increased risk of transition. Nat Rev Rheumatol. 2019;15(3):153-166. doi: 10.1038/s41584-019-0175-0. PMID: 30742092.Disclosure of Interests:None declared.

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