Forest canopy disturbance geospatial data for Lake Superior basin, USA, 1985-2008

We investigate the spread of an exotic herb, Hieracium lepidulum , into a New Zealand Nothofagus forest with the aim of understanding how stand-development of tree populations, propagule pressure and invader persistence, affect invasion across the landscape and within communities. Using data repeatedly collected over 35 years, from 250 locations, we parametrize continuous-time Markov chain models and use these models to examine future projections of the invasion under a range of hypothetical scenarios. We found that the probability of invasion into a stand was relatively high following canopy disturbance and that local abundance of Hieracium was promoted by minor disturbances. However, model predictions extrapolated 45 years into the future show that neither the rate of landscape-level invasion, nor local population growth of Hieracium , was affected much by changing the frequency of canopy disturbance events. Instead, invasion levels were strongly affected by the ability of Hieracium to persist in the understorey following forest canopy closure, and by propagule supply from streams, forest edges and plants already established within the stand. Our results show that disturbance frequency has surprisingly little influence on the long-term trajectory of invasion, while invader persistence strongly determines invasion patterns.

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Towards Operational Monitoring of Forest Canopy Disturbance in Evergreen Rain Forests: A Test Case in Continental Southeast Asia

Remote Sensing ◽

10.3390/rs10040544 ◽

2018 ◽

Vol 10 (4) ◽

pp. 544 ◽

Cited By ~ 20

Author(s):

Andreas Langner ◽

Jukka Miettinen ◽

Markus Kukkonen ◽

Christelle Vancutsem ◽

Dario Simonetti ◽

...

Keyword(s):

Southeast Asia ◽

Forest Canopy ◽

Test Case ◽

Rain Forests ◽

Operational Monitoring ◽

Canopy Disturbance

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Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot

Biogeosciences ◽

10.5194/bg-18-6517-2021 ◽

2021 ◽

Vol 18 (24) ◽

pp. 6517-6531

Author(s):

Raquel Fernandes Araujo ◽

Samuel Grubinger ◽

Carlos Henrique Souza Celes ◽

Robinson I. Negrón-Juárez ◽

Milton Garcia ◽

...

Keyword(s):

Tropical Forest ◽

Temporal Variation ◽

Forest Canopy ◽

Tree Mortality ◽

Extreme Rainfall ◽

Barro Colorado Island ◽

Weibull Function ◽

Wet Season ◽

Wind Speeds ◽

Canopy Disturbance

Abstract. A mechanistic understanding of how tropical-tree mortality responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure; temporal variation; and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or the collapse of standing dead trees. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though wind speeds were lower in the wet season. The strongest correlate of monthly variation in canopy disturbance rates was the frequency of extreme rainfall events. The size distribution of canopy disturbances was best fit by a Weibull function and was close to a power function for sizes above 25 m2. Treefalls accounted for 74 % of the total area and 52 % of the total number of canopy disturbances in treefalls and branchfalls combined. We hypothesize that extremely high rainfall is a good predictor because it is an indicator of storms having high wind speeds, as well as saturated soils that increase uprooting risk. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates at fine temporal and spatial resolutions over large areas, thereby enabling robust tests of how temporal variation in disturbance relates to climate drivers. Further insights could be gained by integrating these canopy observations with high-frequency measurements of wind speed and soil moisture in mechanistic models to better evaluate proximate drivers and with focal tree observations to quantify the links to tree mortality and woody turnover.

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Using Light-Use and Production Efficiency Models to Predict Photosynthesis and Net Carbon Exchange During Forest Canopy Disturbance

Ecosystems ◽

10.1007/s10021-007-9105-0 ◽

2007 ◽

Vol 11 (1) ◽

pp. 26-44 ◽

Cited By ~ 52

Author(s):

Bruce D. Cook ◽

Paul V. Bolstad ◽

Jonathan G. Martin ◽

Faith Ann Heinsch ◽

Kenneth J. Davis ◽

...

Keyword(s):

Production Efficiency ◽

Forest Canopy ◽

Carbon Exchange ◽

Canopy Disturbance ◽

Net Carbon Exchange

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Lessons Learned While Implementing a Time-Series Approach to Forest Canopy Disturbance Detection in Nepal

Remote Sensing ◽

10.3390/rs13142666 ◽

2021 ◽

Vol 13 (14) ◽

pp. 2666

Author(s):

Raja Ram Aryal ◽

Crystal Wespestad ◽

Robert Kennedy ◽

John Dilger ◽

Karen Dyson ◽

...

Keyword(s):

Time Series ◽

Iterative Process ◽

Forest Canopy ◽

Forest Degradation ◽

Google Earth ◽

Model Parameters ◽

Low Grade ◽

Activity Data ◽

Canopy Disturbance ◽

Disturbance Detection

While deforestation has traditionally been the focus for forest canopy disturbance detection, forest degradation must not be overlooked. Both deforestation and forest degradation influence carbon loss and greenhouse gas emissions and thus must be included in activity data reporting estimates, such as for the Reduced Emissions from Deforestation and Degradation (REDD+) program. Here, we report on efforts to develop forest degradation mapping capacity in Nepal based on a pilot project in the country’s Terai region, an ecologically complex physiographic area. To strengthen Nepal’s estimates of deforestation and forest degradation, we applied the Continuous Degradation Detection (CODED) algorithm, which uses a time series of the Normalized Degradation Fraction Index (NDFI) to monitor forest canopy disturbances. CODED can detect low-grade degradation events and provides an easy-to-use graphical user interface in Google Earth Engine (GEE). Using an iterative process, we were able to create a model that provided acceptable accuracy and area estimates of forest degradation and deforestation in Terai that can be applied to the whole country. We found that between 2010 and 2020, the area affected by disturbance was substantially larger than the deforested area, over 105,650 hectares compared to 2753 hectares, respectively. Iterating across multiple parameters using the CODED algorithm in the Terai region has provided a wealth of insights not only for detecting forest degradation and deforestation in Nepal in support of activity data estimation but also for the process of using tools like CODED in applied settings. We found that model performance, measured using producer’s and user’s accuracy, varied dramatically based on the model parameters specified. We determined which parameters most altered the results through an iterative process; those parameters are described here in depth. Once CODED is combined with the description of each parameter and how it affects disturbance monitoring in a complex environment, this degradation-sensitive detection process has the potential to be highly attractive to other developing countries in the REDD+ program seeking to accurately monitor their forests.

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Strong temporal variation in treefall and branchfall rates in a tropical forest is explained by rainfall: results from five years of monthly drone data for a 50-ha plot

10.5194/bg-2021-102 ◽

2021 ◽

Author(s):

Raquel Fernandes Araujo ◽

Samuel Grubinger ◽

Carlos Henrique Souza Celes ◽

Robinson I. Negrón-Juárez ◽

Milton Garcia ◽

...

Keyword(s):

Tropical Forest ◽

Temporal Variation ◽

Forest Canopy ◽

Barro Colorado Island ◽

Weibull Function ◽

Wet Season ◽

Canopy Disturbance ◽

Dead Trees ◽

Standing Dead ◽

Standing Dead Trees

Abstract. A mechanistic understanding of how tropical tree mortality responds to climate variation is urgently needed to predict how tropical forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used five years of approximately monthly drone-acquired RGB imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure, temporal variation, and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or collapse of standing dead trees. Treefalls accounted for 77 % of the total area and 60 % of the total number of canopy disturbances in treefalls and branchfalls combined. The size distribution of canopy disturbances was close to a power function for sizes above 25 m2, and best fit by a Weibull function overall. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though windspeeds were lower in the wet season. The strongest correlate of temporal variation in canopy disturbance rates was the frequency of 1-hour rainfall events above the 99.4th percentile (here 35.7 mm hour−1, r = 0.67). We hypothesize that extreme high rainfall is associated with both saturated soils, increasing risk of uprooting, and with gusts having high horizontal and vertical windspeeds that increase stresses on tree crowns. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates over large spatial scales at fine temporal and spatial resolution, thereby enabling strong tests of linkages to drivers. Future studies should include high frequency measurements of vertical and horizontal windspeeds and soil moisture to better capture proximate drivers, and incorporate additional image analyses to quantify standing dead trees in addition to treefalls.

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Seedling responses to forest canopy disturbance following a spruce budworm outbreak in Maine

Canadian Journal of Forest Research ◽

10.1139/x94-111 ◽

1994 ◽

Vol 24 (4) ◽

pp. 850-859 ◽

Cited By ~ 33

Author(s):

Akira Osawa

Keyword(s):

Forest Canopy ◽

Tree Mortality ◽

Basal Area ◽

Patch Dynamics ◽

Spruce Budworm ◽

Distribution Patterns ◽

Balsam Fir ◽

White Birch ◽

Canopy Disturbance ◽

Long Run

Patterns of tree mortality and seedling responses to canopy disturbance were investigated in northern Maine, where an outbreak of the spruce budworm (Choristoneurafumiferana (Clem.)) affected the forests of balsam fir (Abiesbalsamea (L.) Mill.) and spruce (Picea spp.) continuously between 1972 and 1984. The outbreak created a gradient of canopy tree mortality that ranged between 8.5 and 100% of the cumulative basal area in 1984. This was a result of the difference in vulnerability among the host species (balsam fir > spruce) and of their spatial distribution patterns along the site drainage gradient. Two groups of plant species responded differently to the gradient of canopy disturbance: balsam fir, spruce, and white birch (Betulapapyrifera Marsh.) regenerated mostly at the intermediate levels of mortality (≈20%by basal area) of the canopy balsam fir; raspberry (Rubusidaeus L.) and pin cherry (Prunuspensylvanica L.) were most abundant at ≈100% fir mortality. Overall, the observed responses in space and time of the seedlings to budworm-caused canopy disturbance could be mostly explained by the concept of patch dynamics. Long-term changes in species composition of the spruce–fir forests cannot be predicted with precision with the present knowledge. However, I hypothesize, based on the species-specific vulnerability to budworm damage and patterns of regeneration, that the proportion of spruce to fir trees would not differ very much in the long run regardless of extensive tree mortality by the spruce budworm.

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Development of apical pits in chloride cells of the gills of Pimephales promelas after chronic exposure to acid water

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100076044 ◽

1983 ◽

Vol 41 ◽

pp. 462-463

Author(s):

Richard L. Leino ◽

Jon G. Anderson ◽

J. Howard McCormick

Keyword(s):

Confidence Interval ◽

Chronic Exposure ◽

Lake Superior ◽

Pimephales Promelas ◽

Chloride Cells ◽

Fathead Minnows ◽

Secondary Lamellae ◽

Untreated Water ◽

Water Ph ◽

Flow Through

Groups of 12 fathead minnows were exposed for 129 days to Lake Superior water acidified (pH 5.0, 5.5, 6.0 or 6.5) with reagent grade H2SO4 by means of a multichannel toxicant system for flow-through bioassays. Untreated water (pH 7.5) had the following properties: hardness 45.3 ± 0.3 (95% confidence interval) mg/1 as CaCO3; alkalinity 42.6 ± 0.2 mg/1; Cl- 0.03 meq/1; Na+ 0.05 meq/1; K+ 0.01 meq/1; Ca2+ 0.68 meq/1; Mg2+ 0.26 meq/1; dissolved O2 5.8 ± 0.3 mg/1; free CO2 3.2 ± 0.4 mg/1; T= 24.3 ± 0.1°C. The 1st, 2nd and 3rd gills were subsequently processed for LM (methacrylate), TEM and SEM respectively.Three changes involving chloride cells were correlated with increasing acidity: 1) the appearance of apical pits (figs. 2,5 as compared to figs. 1, 3,4) in chloride cells (about 22% of the chloride cells had pits at pH 5.0); 2) increases in their numbers and 3) increases in the % of these cells in the epithelium of the secondary lamellae.

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