Search claims · PlantClaims

Associationauthor interpretationoriginal resultmeasured

Claim · model-written summary

Fire was inferred as the main tree mortality factor.

Taxon: treet0
Outcome: tree mortalitye0
Setting: firee0

Not reportedDirection

Verbatim

e0
“thereby pointing to fire as the main factor of tree mortality”
✓ located verbatim in the source · abstract, characters 955–1016

t0
“tree mortality”
✓ located verbatim in the source · title, characters 42–56

Title

Spatial structure and factors determining tree mortality in Beninese forest formations

Gilbert Atindogbe; Gabin Finangnon Laly; Hospice Afouda Akpo; et al. International Journal of Biological and Chemical Sciences 2021. doi:10.4314/ijbcs.v14i9.8

Other claims from this paper (7)

Observation Dead wood density was 32 stems/hectare.
Observation Mean quadratic diameter was 17.2 cm.
Observation Basal area was 0.88 m2.ha-1.
Observation Dead trees showed random and regular spatial distributions.
Association Dead and living trees lacked positive spatial interaction.
Association Senescence also influenced tree mortality.
Recommendation Authors suggest including dead trees in management plans.

Intervention effectobservedoriginal resultnegativemeasured

Claim · model-written summary

Delayed tree mortality was twice as high as instantaneous tree mortality after the storm.

Taxon: Palm Forestt0
Treatment: Hurricane Hugot1
Outcome: Delayed tree mortalitye0
Direction: twice as highe0
Comparator: instantaneous tree mortalitye0

Verbatim

e0
“Delayed tree mortality was twice as high as instantaneous tree mortality after the storm”
✓ located verbatim in the source · abstract, characters 1224–1312

t0
“Palm Forest”
✓ located verbatim in the source · title, characters 14–25

t1
“Hurricane Hugo”
✓ located verbatim in the source · title, characters 84–98

Title

A Flood Plain Palm Forest in the Luquillo Mountains of Puerto Rico Five Years After Hurricane Hugo¹

Jorge L. Frangi; Ariel E. Lugo Biotropica 1998. doi:10.1111/j.1744-7429.1998.tb00069.x

Other claims from this paper (17)

Intervention effect The hurricane caused the dominant species to become more dominant.
Intervention effect The hurricane created low instantaneous tree mortality, 1% of stems.
Intervention effect The hurricane reduced tree biomass at about -16 Mg/ha/yr.
Intervention effect The hurricane reduced tree density.
Intervention effect The hurricane did not reduce basal area.
Intervention effect Five years after the hurricane, the forest had exceeded its prehurricane aboveground tree biomass, tree density and basal area.
Observation Aboveground tree biomass accumulated at a rate of 9.2 Mg/ha/yr after the hurricane.
Observation Palms accounted for 76 percent of the aboveground tree biomass accumulation.
Observation Before the hurricane the aboveground biomass accumulation rate was on the order of 3 Mg/ha/yr.
Intervention effect Forest floor litter decreased to prehurricane levels (6.7 Mg/ha) within 5 yr, mostly due to disappearance of woody litter.
Observation Thirteen tree species not represented in the canopy entered the forest by regeneration.
Observation Two species suffered almost 20 percent/yr mortality over a 5-yr period after the storm.
Association Delayed mortality affected dicotyledonous trees more than palms.
Association Regeneration of dicotyledonous trees, palms and tree ferns was influenced by hydroperiod, light and space.
Observation Redundancy Data Analysis showed the area near the river channel was the most favorable for plant regeneration.
Association Palm regeneration was higher in locations with longer hydroperiods.
Association Regeneration of dicotyledonous trees was higher in areas with low risk of flooding.

Observationobservedreview summarymeasured

Claim · model-written summary

Normal mangrove tree mortality is density dependent.

Taxon: Mangrovet0
Outcome: mortality is density dependente0

Verbatim

e0
“This mortality is density dependent”
✓ located verbatim in the source · abstract, characters 359–394

t0
“Mangrove Forests”
✓ located verbatim in the source · title, characters 18–34

Title

Tree Mortality in Mangrove Forests

Jorge A. Jimenez; Ariel E. Lugo; Gilberto Cintron Biotropica 1985. doi:10.2307/2388214

Other claims from this paper (6)

Observationobservedoriginal resultmeasured

Claim · model-written summary

Many regions have limited ground-based information on tree mortality.

Taxon: treee0
Outcome: information on tree mortalitye2
Qualifier: many regions with limitede2

Verbatim

e0
“Rates of tree mortality are increasing globally”
✓ located verbatim in the source · abstract, characters 8–55

e2
“we also identify many regions with limited ground‐based information on tree mortality”
✓ located verbatim in the source · abstract, characters 633–718

Title

Towards a global understanding of tree mortality

International Tree Mortality Network New Phytologist 2025. doi:10.1111/nph.20407

Other claims from this paper (3)

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

A logistic function accurately estimated tree mortality following selective logging.

Taxon: treee0
Outcome: tree mortalitye0
Comparator: selective logginge0

Verbatim

e0
“Logistic function accurately estimates tree mortality after selective logging.”
✓ located verbatim in the source · abstract, characters 2158–2236

Title

Individual tree mortality: Risks of climate change in the eastern Brazilian Amazon region

Erica Karolina Barros de Oliveira; Alba Valéria Rezende; Leonidas Soares Murta Júnior; et al. Ecological Informatics 2024. doi:10.1016/j.ecoinf.2024.102880

Other claims from this paper (5)

Method / resource Mortality models produced similar estimates with R² above 0.90.
Observation The mortality models showed both underestimation and overestimation trends.
Method / resource NNAR satisfactorily represented species mortality over simulated years.
Observation The 25 cm DBH class had its highest mortality in 2012–2014 during neutral and weak El Niño conditions.
Association Maximum air temperature had the strongest positive correlation with tree mortality.

Associationobservedoriginal resultmeasured

Claim · model-written summary

Senescence also influenced tree mortality.

Taxon: treee0
Organ / stage: senescencee0
Outcome: tree mortalitye0

Not reportedDirection

Verbatim

e0
“Other factors influencing tree mortality included attacks by saproxylic animal species and other wood pests, and senescence”
✓ located verbatim in the source · abstract, characters 1018–1141

Title

Spatial structure and factors determining tree mortality in Beninese forest formations

Gilbert Atindogbe; Gabin Finangnon Laly; Hospice Afouda Akpo; et al. International Journal of Biological and Chemical Sciences 2021. doi:10.4314/ijbcs.v14i9.8

Other claims from this paper (7)

Observation Dead wood density was 32 stems/hectare.
Observation Mean quadratic diameter was 17.2 cm.
Observation Basal area was 0.88 m2.ha-1.
Observation Dead trees showed random and regular spatial distributions.
Association Dead and living trees lacked positive spatial interaction.
Association Fire was inferred as the main tree mortality factor.
Recommendation Authors suggest including dead trees in management plans.

Observationobservedreview summarynegativebasis n/a

Claim · model-written summary

Rising background tree mortality rates are evidence suggesting greater vulnerability.

Taxon: treet0
Outcome: background mortality ratese0
Direction: risinge0

Verbatim

e0
“rising background mortality rates”
✓ located verbatim in the source · abstract, characters 1313–1346

t0
“tree mortality”
✓ located verbatim in the source · title, characters 46–60

Title

On underestimation of global vulnerability to tree mortality and forest die‐off from hotter drought in the Anthropocene

Craig D. Allen; David D. Breshears; Nate G. McDowell Ecosphere 2015. doi:10.1890/es15-00203.1

Other claims from this paper (6)

Observationobservedoriginal resultmeasured

Claim · model-written summary

Border-tree mortality averaged 0.60%/yr.

Taxon: Border-treee0
Outcome: mortalitye0
Value: 0.60%/yre0

Verbatim

e0
“Border-tree mortality averaged 0.60%/yr”
✓ located verbatim in the source · abstract, characters 1055–1094

Title

CHANGES IN SOUTHERN APPALACHIAN CANOPY TREE GAPS SAMPLED THRICE

James R. Runkle Ecology 1998. doi:10.1890/0012-9658(1998)079[1768:cisact]2.0.co;2

Other claims from this paper (16)

Observationobservedoriginal resultnegativemeasured

Claim · model-written summary

Tree mortality increased with mulch depth.

Taxon: Peach TreePrunus persicat0
Treatment: pecan mulch depthe0
Outcome: Tree mortalitye0
Direction: increasede0

Verbatim

t0
“Peach Tree”
✓ located verbatim in the source · title, characters 37–47

e0
“Tree mortality increased with pecan mulch depth”
✓ located verbatim in the source · abstract, characters 1562–1609

Title

Pecan Shell Mulch Impact on ‘Loring’ Peach Tree Establishment and First Harvest

Eric T. Stafne; Charles T. Rohla; Becky L. Carroll HortTechnology 2009. doi:10.21273/horttech.19.4.775

Other claims from this paper (13)

Observation MOW had the poorest 2008 yield at 13.2 kg/tree.
Observation MOW had 93 fruit/tree in 2008.
Observation Other treatments did not differ in yield.
Observation Soluble solids concentration was unaffected by treatment.
Observation Fruit weight was unaffected by treatment.
Observation MOW had lower tree height, pruning weights and trunk cross-sectional area from 2007.
Observation Pecan mulch appeared to reduce soil pH.
Observation Foliar N, K and Zn showed treatment differences in 2006.
Observation K and Zn showed no treatment differences in 2007 and 2008.
Observation FOUR had greater foliar N than MOW in 2008.
Observation MOW, SPRAY and TWO had 0%–5% tree loss.
Observation FOUR had 15% mortality.
Observation SIX had 35% mortality.

Observationobservedoriginal resultmeasured

Claim · model-written summary

No tree mortality occurred.

Taxon: peach treesPrunus persicat0
Outcome: no tree mortalitye0

Not reportedDirection

Verbatim

e0
“no tree mortality occurred”
✓ located verbatim in the source · abstract, characters 1077–1103

t0
“peach trees”
✓ located after whitespace/quote normalisation · title, characters 52–63

Title

EFFECTS OF FALL APPLICATIONS OF ETHEPHON AND GA3 ON PEACH TREES

D.E. Deyton; D.W. Lockwood; S. Ventataraman HortScience 1992. doi:10.21273/hortsci.27.6.690c

Other claims from this paper (10)

Intervention effect GA3 delayed flower bud development after endodormancy.
Intervention effect Ethephon delayed flower bud development after endodormancy.
Intervention effect GA3 significantly delayed 50% bloom by about one day.
Intervention effect Ethephon at 150 mg per liter delayed bloom by 4.7 days.
Association Higher concentration of each chemical caused greater bloom delay.
Observation The two chemicals showed no interaction for bloom date.
Intervention effect The combined GA3 and ethephon treatment caused the greatest bloom delay of 6.5 days.
Intervention effect The two highest ethephon rates produced scaffold gummosis in fall and spring.
Observation Little gummosis was evident during summer and following fall.
Observation By September 1991 gummosis evidence was insignificant.

“tree mortality”

Claim types

Direction of the findings

Over time

Claim type

Research area

Polarity

Statistics