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92 results for “tree cover”
Data from: Going undercover: increasing canopy cover around a host tree drives associational resistance to an insect pest
Neighbouring heterospecific plants are often observed to reduce the probability of herbivore attack on a given focal plant. While this pattern of associational resistance is frequently reported, experimental evidence for underlying mechanisms is rare particularly for potential plant species diversity effects on focal host plants and their physical environment. Here, we used an established forest diversity experiment to determine whether tree diversity effects on an important insect pest are driven by concomitant changes in host tree growth or the light environment. We examined the effects of tree species richness, canopy cover and tree growth on the probability of occurrence, the abundance, and volume of galls caused by the pineapple gall adelgid Adelges abietis on Norway spruce. Although tree diversity had no effect on gall abundance, we observed that both the probability of gall presence and gall volume (an indicator of maternal fecundity) decreased with tree species richness and canopy cover around host spruce trees. Structural equation models revealed that effects of tree species richness on gall presence and volume were mediated by concurrent increases in canopy cover rather than changes in tree growth or host tree density. As canopy cover did not influence tree or shoot growth, patterns of associational resistance appear to be driven by improved host tree quality or more favourable microclimatic conditions in monocultures compared to mixed-stands. Our study therefore demonstrates that changes in forest structure may be critical to understanding the responses of herbivores to plant diversity and may underpin associational effects in forest ecosystems.
The environmental drivers of tree cover and forest-savanna mosaics in Southeast Asia
<p>Forest-savanna mosaics exist across all major tropical regions. Yet, the influence of environmental factors on the distribution of these mosaics is not well explored, limiting our understanding of the environmental constraints on savannas especially in Southeast Asia, where most savannas exist in mosaics. Despite clear structural and functional characteristics indicative of savannas, most SE Asian savannas continue to be classified as forest. This designation is problematic because SE Asian savannas are threatened by both fragmentation and forest-centric management practices. By studying forest-savanna mosaics across SE Asia, we aimed to parse out how landscape mosaics of forest and savanna may be constrained by fire, climate, and soil characteristics. We used remotely sensed data to characterize the distribution of tree cover and forest-savanna mosaics. Using regression models, we quantified the relative effects of precipitation, fire frequency, seasonality, and soil characteristics on average tree cover and landscape patchiness. We found that low tree cover, indicative of savannas, occurs in drier, seasonal subregions that experience frequent fire. Further, our results demonstrate that fire and precipitation strongly shape landscape patchiness. Landscapes were patchiest in subregions with low precipitation and intermediate fire frequency. These results demonstrate that the environmental factors important in delineating the distribution of savannas globally shape the distribution of tree cover and landscape patchiness across SE Asia. Fire especially drives patterns of tree cover across scales. In a region where fire suppression is a common management strategy, our results suggest that further research studying vegetation response to fire and fire suppression is needed to improve management and conservation of these mosaic landscapes. More broadly, this work demonstrates a useful approach for studying the environmental drivers that influence the distribution of forest-savanna mosaics.</p>
Invasive tree cover covaries with environmental factors to explain the functional composition of riparian plant communities
<p>Invasive species are a major cause of biodiversity loss worldwide, but their impact on communities and the mechanisms driving those impacts are varied and not well understood. This study employs functional diversity metrics and guilds - suites of species with similar traits - to assess the influence of an invasive tree (<em>Tamarix</em> spp.) on riparian plant communities in the southwestern United States. We asked: 1) What traits define riparian plant guilds in this system? 2) How do the abundances of guilds vary along gradients of <em>Tamarix </em>cover and abiotic conditions? 3) How does the functional diversity of the plant community respond to the gradients of <em>Tamarix </em>cover and abiotic conditions? We found nine distinct guilds primarily defined by reproductive strategy, as well as height, seed weight, specific leaf area, drought and anaerobic tolerance. Guild abundance varied along a covarying gradient of local and regional environmental factors and <em>Tamarix </em>cover. Guilds relying on sexual reproduction, in particular those producing many light seeds over a long period of time were more strongly associated with drier sites and higher <em>Tamarix </em>cover. <em>Tamarix </em>itself appeared to facilitate more shade tolerant species with higher specific leaf areas than would be expected in resource poor environments. Additionally, we found a high degree of specialization (low functional diversity) in the wettest, most flood-prone, lowest <em>Tamarix </em>cover sites as well as in the driest, most stable, highest <em>Tamarix </em>cover sites. These guilds can be used to anticipate plant community response to restoration efforts and in selecting appropriate species for revegetation.</p>
Preserving the woody plant tree of life in China under future climate and land-cover changes
<p><span>The tree of life (TOL) is severely threatened by climate and land-cover changes. Preserving the TOL is urgent, but has not been included in the post-2020 global biodiversity framework. Protected areas (PAs) are fundamental for biological conservation. However, we know little about the effectiveness of existing PAs in preserving the TOL of plants and how to prioritize PA expansion for better TOL preservation under future climate and land-cover changes. Here, using high-resolution distribution maps of 8732 woody species in China and phylogeny-based Zonation, we find that current PAs perform poorly in preserving the TOL </span><span>both at the present and in the 2070s</span><span>. The geographical coverage of TOL branches by current PAs is ca. 9%, and < 3% of the identified priority areas for preserving the TOL are currently protected. Interestingly, the geographical coverage of TOL branches by PAs will be improved from 9% to 52–79% by the identified priority areas for PA expansion. Human pressures in the identified priority areas are high, leading to high costs for future PA expansion. We thus suggest that besides nature reserves and national parks, other effective area-based conservation measures should be considered. Our study argues for the inclusion of preserving the TOL in the post-2020 conservation framework and provides references for decision-makers </span><span>to preserve the Earth's evolutionary history.</span></p>
Data from: Herbivory on the pedunculate oak along an urbanization gradient in Europe: effects of impervious surface, local tree cover and insect feeding guild
<p><span>Urbanization is recognized as an important driver of the diversity and abundance of tree associated insect herbivores, but its consequences for insect herbivory are controversial. A likely source of variability among studies is the insufficient consideration of intra-urban variability in forest cover. W</span>ith the help of citizen scientists, we investigated the independent and interactive effect of urbanization and local canopy cover on insect herbivory in the pedunculate oak (<em>Quercus robur</em>) throughout most of its geographic range in Europe. We found that the damage caused by chewing insect herbivores as well as the incidence of leaf-mining and gall-inducing herbivores consistently decreased with increasing urbanization around focal oaks. Herbivory by chewing herbivores increased with increasing forest cover, regardless of urbanization. In contrast, an increase in local canopy cover buffered the negative effect of urbanization on leaf-miners and strengthened its effect on gall-inducers. These results show the complexity of plant-herbivore interactions in urbanized areas, highlighting that the presence of local canopy cover within cities has the potential to attenuate or modify the effect of urbanization on biotic interactions.</p>
Luhansk region tree cover change area estimation (1996-2020)
<p><strong>Occupation of Environment: Long-Term Consequences of war in Ukraine on conservation of forested areas of Emerald Network in the Luhansk region - </strong>excel sheets with stratified random sampling area estimation for Luhansk region based on the ground reference data. The division into territories controlled by Ukraine and Russia made based on the demarcation line with consideration of the buffer zone, where Ukrainian institutions were disconnected due to the active warfare in purpose of separation of zones with interruption of Ukrainian environmental policies.</p>
Data from: Ecological legacies of civil war: 35-year increase in savanna tree cover following wholesale large-mammal declines
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Data from: Congruent phylogeographic patterns of eight tree species in Atlantic Central Africa provide insights on the past dynamics of forest cover
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Data from: Going undercover: increasing canopy cover around a host tree drives associational resistance to an insect pest
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Data from: Defoliation by pastoralists affects savanna tree seedling dynamics by limiting the facilitative role of canopy cover
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Data from: Herbivory on the pedunculate oak along an urbanization gradient in Europe: effects of impervious surface, local tree cover and insect feeding guild
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Preserving the woody plant tree of life in China under future climate and land-cover changes
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The environmental drivers of tree cover and forest-savanna mosaics in Southeast Asia
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Data from: Alternative tree-cover states of the boreal ecosystem: a conceptual model
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Data from: Local tropical forest restoration strategies affect tree recruitment more strongly than does landscape forest cover
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Africa tree cover map
<p><strong>Data </strong><strong>description</strong></p> <p>This file is a 100 m resolution map of % tree canopy cover per pixel for Africa in 2019. Tree cover values range from 0-100 % and nodata areas are masked as -1.</p> <p>The map is derived from predictions of tree cover using 3 m PlanetScope imagery, which were resampled to 1 m, and then aggregated to 100 m. Predictions at 1 m resolution (or anything between 1 and 100 m) are available on request.</p> <p>The image data was processed from raw scenes into merged 1x1 degree mosaics. Differences in the quality of raw scenes and processed mosaics can lead to artifacts in the predicted tree cover, visible as seamlines along scene or mosaic edges. Therefore the current version of this map should not be seen as a final product representing the exact tree cover at each location, but as a proof of concept of what is possible with PlanetScope data.</p> <p>The main benefit of this map is the inclusion of cover from scattered single trees in sparse cover areas such as savannahs. Here it can serve as a complement to existing forest cover maps to extend the mapping to include non-forest trees.</p> <p><strong>License</strong></p> <p>This tree cover map is made freely available for non-commercial purposes. All usage of the data must be attributed and should be cited with the paper citation. </p> <p>Please see the NICFI license for full terms of usage, available at: https://assets.planet.com/docs/Planet_ParticipantLicenseAgreement_NICFI.pdf</p> <p><strong>Version differences</strong></p> <p>We recommend to always use the latest version.</p> <p><strong>We are continuously improving the quality and consistency of the tree cover mapped</strong>, and are expecting to release regular version updates, based on an improved model and mosaics. We also plan to release different years in the future.</p> <p><strong>Version 0.1: ps_africa_treecover_2019_100m_v0.1</strong></p> <p>This version was used for the analyses in the paper. It used the first version of the mosaics, which suffered from the inclusion of lower-quality scenes and missing data.</p> <p>Known issues</p> <p>- missing data coverage: incomplete mosaics and mosaics missing scenes</p> <p>- inconsistent predictions between mosaics: visible mosaic edges, see Zimbabwe</p> <p>- underprediction in very sparse cover areas</p> <p>- overprediction of cover in denser shrublands</p> <p>- overprediction (artifacts) in mountains, desert dunes, croplands and some urban areas</p> <p>- flowering trees in closed forests are mapped as gaps</p> <p>- occasional confusion between understory or shrubs and trees in wood- and shrublands</p> <p><strong>Version 1.0: ps_africa_treecover_2019_100m_v1.0</strong></p> <p>This is the latest version available as of March 2023. It is based on improved mosaics and a revised model, leading to better consistency both between and within mosaics.</p> <p>However the current model underpredicts solid tree cover in shrublands and woodlands, leading to an overall underprediction in lower rainfall areas.</p> <p>Improvements over v0.1:</p> <p>- improved mosaic quality</p> <p>- reduced artifacts in croplands and urban areas (though some remain)</p> <p>- better consistency of forest area mapping</p> <p>- better detection rate of small trees in dry areas</p> <p>Known issues</p> <p>- underprediction of tree clusters in shrublands</p> <p>- some (few) false predictions of small trees in dry areas</p> <p>- occasional inconsistent predictions within mosaics: seamlines along scene edges</p> <p>- areas of underprediction in dense tropical forest due to lower quality scenes, see DRC</p> <p>- overprediction (artifacts) in mountains, and occasionally desert dunes</p> <p>- flowering trees in closed forests are mapped as gaps</p> <p>- occasional confusion between understory or shrubs and trees in wood- and shrublands</p> <p>- trees without leaves may not be mapped correctly</p>
Global Forest Cover Change Tree Cover Multi-Year Global 30m V003
The Land Processes Distributed Active Archive Center (LP DAAC) archives and distributes Global Forest Cover Change (GFCC) data products through the NASA Making Earth System Data Records for Use in Research Environments ([MEaSUREs](https://earthdata.nasa.gov/about/competitive-programs/measures)) Program. The GFCC Tree Cover Multi-Year Global dataset is available for four epochs centered on the years 2000, 2005, 2010, and 2015. The dataset is derived from the GFCC Surface Reflectance product ([GFCC30SR](https://doi.org/10.5067/MEaSUREs/GFCC/GFCC30SR.001)), which is based on enhanced Global Land Survey (GLS) datasets. The GLS datasets are composed of high-resolution Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images at 30 meter resolution. GFCC30TC provides tree canopy information and can be used to understand forest changes. Each tree cover product features four files associated with it; a tree cover layer with an embedded color map, a tree cover error (uncertainty) file, and an index (provenance) file, plus a list of path/rows that relate to the Surface Reflectance input files. Note that the index file and file list were not generated for the 2015 epoch. Data follow the Worldwide Reference System-2 tiling scheme. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD).
CMS: LiDAR-derived Tree Canopy Cover for States in the Northeast USA
This data set provides high-resolution (1-m) tree canopy cover for states in the Northeast USA. State-level canopy cover data are currently available for Pennsylvania (data for nominal year 2008), Delaware (2014), and Maryland (2013). The data were derived with a rules-based expert system which facilitated integration of leaf-on LiDAR and imagery data into a single classification workflow, exploiting the spectral, height, and spatial information contained in the datasets. Additional states will be added as data processing is completed.
LBA Regional Tree Cover from AVHRR, 1-km, 1992-1993 (DeFries et al.)
The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) of the 1km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats.Characterization of terrestrial vegetation from the Advanced Very High Resolution Radiometer (AVHRR) on the global to regional scale has traditionally been accomplished using classification schemes with discrete numbers of vegetation classes. Representation of vegetation into a limited number of homogeneous classes does not account for the variability within land cover, nor does the portrayal recognize transition zones between adjacent cover types. An alternative paradigm to describing land cover as discrete classes is to represent land cover as continuous fields of vegetation characteristics using a linear mixture model approach. This prototype data set, created by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland, contains 1-km cells estimating: 1) Percent tree cover; 2) Percentage cover for two layers representing leaf longevity (evergreen and deciduous); and 3) Percentage cover for two layers estimating leaf type (broadleaf and needleleaf).Data acquired in 1992-93 from NOAA's AVHRR at a 1-km spatial resolution and processed under the guidance of the International Geosphere Biosphere Programme (IGBP) were used to derive the tree cover, leaf type and leaf longevity maps. Each pixel in the layers has a value between 10 and 80 percent. These layers can be directly used as parameters in models or aggregated into more conventional land cover maps. For the latter, the product offers the flexibility to derive land cover maps based on user's requirements for a particular application. The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial data sets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks.
CMS: Tree Canopy Cover at 0.5-meter resolution, Vermont, 2016
This dataset contains estimates of tree canopy cover presence at high resolution (0.5m) across the state of Vermont for 2016 in Cloud-Optimized GeoTIFF (*.tif) format. Tree canopy was derived from 2016 high-resolution remotely sensed data as part of the Vermont High-Resolution Land Cover mapping project. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and trees using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected. Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establish tree canopy goals.
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