Visualization and modeling of smoke transport over landscape scales

Parasites are linked to the decline of some bee populations; thus, understanding defense mechanisms has important implications for bee health. Recent advances have improved our understanding of factors mediating bee health ranging from molecular to landscape scales, but often as disparate literatures. Here, we bring together these fields and summarize our current understanding of bee defense mechanisms including immunity, immunization, and transgenerational immune priming in social and solitary species. Additionally, the characterization of microbial diversity and function in some bee taxa has shed light on the importance of microbes for bee health, but we lack information that links microbial communities to parasite infection in most bee species. Studies are beginning to identify how bee defense mechanisms are affected by stressors such as poor-quality diets and pesticides, but further research on this topic is needed. We discuss how integrating research on host traits, microbial partners, and nutrition, as well as improving our knowledge base on wild and semi-social bees, will help inform future research, conservation efforts, and management.

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Faculty Opinions recommendation of Conserving Biodiversity Through Certification of Tropical Agroforestry Crops at Local and Landscape Scales.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725923747.793511160 ◽

2015 ◽

Author(s):

Joern Fischer

Keyword(s):

Landscape Scales

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Hard times for high expectations from hydraulics: predicting drought‐induced forest mortality at landscape scales remains a challenge

New Phytologist ◽

10.1111/nph.17317 ◽

2021 ◽

Author(s):

Lucy Rowland ◽

Jordi Martínez‐Vilalta ◽

Maurizio Mencuccini

Keyword(s):

High Expectations ◽

Forest Mortality ◽

Hard Times ◽

Landscape Scales

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Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales

Remote Sensing ◽

10.3390/rs13020257 ◽

2021 ◽

Vol 13 (2) ◽

pp. 257 ◽

Cited By ~ 1

Author(s):

Shaun R. Levick ◽

Tim Whiteside ◽

David A. Loewensteiner ◽

Mitchel Rudge ◽

Renee Bartolo

Keyword(s):

Remote Sensing ◽

Vegetation Structure ◽

Laser Scanning ◽

Canopy Cover ◽

Structural Diversity ◽

Point Clouds ◽

Large Area ◽

Calibration And Validation ◽

Savanna Vegetation ◽

Landscape Scales

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.

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Organic farming enhances parasitoid diversity at the local and landscape scales

Journal of Applied Ecology ◽

10.1111/1365-2664.12457 ◽

2015 ◽

Vol 52 (4) ◽

pp. 1102-1109 ◽

Cited By ~ 24

Author(s):

Diego J. Inclán ◽

Pierfilippo Cerretti ◽

Doreen Gabriel ◽

Tim G. Benton ◽

Steven M. Sait ◽

...

Keyword(s):

Organic Farming ◽

Landscape Scales

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Broaden your horizon: The use of remotely sensed data for modeling populations of forest species at landscape scales

Forest Ecology and Management ◽

10.1016/j.foreco.2021.119640 ◽

2021 ◽

Vol 500 ◽

pp. 119640

Author(s):

Paul O. Jensen ◽

Arjan J.H. Meddens ◽

Scott Fisher ◽

Aaron J. Wirsing ◽

Dennis L. Murray ◽

...

Keyword(s):

Remotely Sensed ◽

Forest Species ◽

Remotely Sensed Data ◽

Landscape Scales

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Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2013.0194 ◽

2014 ◽

Vol 369 (1643) ◽

pp. 20130194 ◽

Cited By ~ 35

Author(s):

Michael D. Madritch ◽

Clayton C. Kingdon ◽

Aditya Singh ◽

Karen E. Mock ◽

Richard L. Lindroth ◽

...

Keyword(s):

Remote Sensing ◽

Populus Tremuloides ◽

Spatial Scales ◽

Imaging Spectroscopy ◽

Spectral Signature ◽

Spectral Variation ◽

Fine Scale ◽

Below Ground ◽

Landscape Scales ◽

Spectrometer Data

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales.

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BRI2002: TWO LAYER ZONE SMOKE TRANSPORT MODEL -INTRODUCTION-

Fire Science and Technology ◽

10.3210/fst.23.iv ◽

2004 ◽

Vol 23 (1) ◽

pp. IV-VIII ◽

Cited By ~ 11

Author(s):

Takeyoshi Tanaka ◽

Shigeru Yamada

Keyword(s):

Transport Model ◽

Smoke Transport

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Portrait préindustriel dans un contexte de grande variabilité naturelle: une étude de cas dans le centre du Québec (Canada)

The Forestry Chronicle ◽

10.5558/tfc2011-068 ◽

2011 ◽

Vol 87 (05) ◽

pp. 612-624 ◽

Cited By ~ 5

Author(s):

Eric Alvarez ◽

Louis Bélanger ◽

Louis Archambault ◽

Frédéric Raulier

Keyword(s):

Temperate Forest ◽

Forest Cover ◽

Sustainable Forest Management ◽

Forest Succession ◽

Black Spruce ◽

Spatial Scales ◽

White Birch ◽

Industrial Landscape ◽

Industrial Forest ◽

Landscape Scales

Pre-industrial forest cover portrait is a recognized method for establishing the bases of sustainable forest management. However, it is a spatially and temporally dependant concept that should be used with caution in presence of big fires. The objective of the study was to portray the pre-industrial landscape in a mixedwood temperate forest in central Quebec at different spatial scales. The study was based on archival records from a forest company. The pre-industrial forest cover landscape of our study area was mainly composed of mature or old-growth (>100 years) stands and dominated by mixedwood forest stands with intolerant hardwoods. The main tree species were white birch, black spruce and jack pine, three species associated to forest succession after fire in the boreal forest. Considering the great variability caused by the fires and partial knowledge of this variability, for each spatial scale considered, we propose some management targets based on the main pre-industrial characteristics of this forest. To respect the pre-industrial variability, our study suggested that silviculture should be adapted at different landscape scales. Cover types and age class targets should be based on main preindustrial characteristics at each landscape scale analyzed.

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