Patterns in woody vegetation cover across forests of a main Mediterranean island in relation to precipitation regime.

2021 ◽  
Author(s):  
Sara Simona Cipolla ◽  
Nicola Montaldo
Keyword(s):  
Forest Canopy ◽  
Forest Type ◽  
Temporal Trends ◽  
Tree Cover ◽  
Mean Annual Precipitation ◽  
Precipitation Regime ◽  
Soil Thickness ◽  
Precipitation Regimes ◽  
Woody Cover ◽  
Cover Density

<p><span>In water-limited ecosystems such as those encountered on Mediterranean mountainous areas of shallow soil, climate-induced changes in precipitation regime are expected to influence the ability of remnants of native forests to resist or adapt to predicted reduced precipitation scenarios. The objective of this work was to understand the role of precipitation and physiographic ecosystem properties in woody cover spatial variability of Mediterranean sclerophyllous forests located within main protected areas of the Sardinia Island (Italy), an excellent reference condition for Mediterranean hydrologic studies due to the relatively low urbanization and human activities. Analyzed forests differ in altitude (0-1500 slm.), mean annual precipitation (450-1200 mm) over 95 years of daily data, exposition, dominant species, density, and soil thickness.</span> <span>Forests have been broken down into 30 * 30 m plots based on their type. Using data from the Landsat satellite sensors, temporal trends in the NDVI (Normalized Difference Vegetation Index) were quantified. We related these trends with different environmental variables to understand the effects of the variation of precipitation regimes and forest type on woody cover density. A significant direct effect of drought has been observed in the dry 2017 in all forests resulting in a significantly reduced NDVI values especially on south facing slopes plots and low soil thickness plots. On the contrary forest canopy were more stable on mesic habitats demonstrating that the availability of soil humidity is more important than solar radiation. Finally, the lowest values of NDVI were observed in semi-arid sclerophyllous forest dominated by species tolerant to drought and very thin stony soil layers. The identification of the factors that contribute the most to the increase in the vulnerability and the decrease of tree cover density of forests will allow to optimize planning and management strategies also under further drier climate changes prospective.</span></p>

scholarly journals The climatic imprint of bimodal distributions in vegetation cover for western Africa

2016 ◽  
Vol 13 (11) ◽  
pp. 3343-3357 ◽  
Author(s):  
Zun Yin ◽  
Stefan C. Dekker ◽  
Bart J. J. M. van den Hurk ◽  
Henk A. Dijkstra
Keyword(s):  
Land Cover ◽  
Congo Basin ◽  
Shortwave Radiation ◽  
Mean Annual Precipitation ◽  
Above Ground Biomass ◽  
Precipitation Regime ◽  
Ground Biomass ◽  
Western Africa ◽  
Precipitation Regimes ◽  
Woody Cover

Abstract. Observed bimodal distributions of woody cover in western Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above-ground biomass, which might closely relate to woody cover due to vegetation–climate interactions. Thus we expect that use of radiation and above-ground biomass enables us to distinguish the two modes of woody cover. However, through conditional histogram analysis, we find that the bimodality of woody cover still can exist under conditions of low mean annual shortwave radiation and low above-ground biomass. It suggests that this specific condition might play a key role in critical transitions between the two modes, while under other conditions no bimodality was found. Based on a land cover map in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water–radiation coupling are analysed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not sufficient to predict potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators cannot predict a stable forest state under the observed climatic conditions, in contrast to observed forest states. A new indicator (the normalized difference of precipitation) successfully expresses the stability of the precipitation regime and can improve the prediction accuracy of forest states. Next we evaluate land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are revealed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility of decreasing significantly. An increase in the area covered by savanna and grass is possible, which coincides with the observed regreening of the Sahara.

scholarly journals The climatic imprint of bimodal distributions in vegetation cover for West Africa

2015 ◽  
Vol 12 (21) ◽  
pp. 18213-18251
Author(s):  
Z. Yin ◽  
S. C. Dekker ◽  
B. J. J. M. van den Hurk ◽  
H. A. Dijkstra
Keyword(s):  
Land Cover ◽  
West Africa ◽  
Congo Basin ◽  
Shortwave Radiation ◽  
Mean Annual Precipitation ◽  
Above Ground Biomass ◽  
Precipitation Regime ◽  
Ground Biomass ◽  
Precipitation Regimes ◽  
Woody Cover

Abstract. Observed bimodal distributions of woody cover in West Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. Understanding the explicit climate conditions where the woody cover bimodality can exist is important to predict crucial transitions of ecosystems due to climate change. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above ground biomass. Through conditional histogram analysis, we find that the bimodality of woody cover can only exist under low mean annual shortwave radiation and low above ground biomass. Based on a land cover map, in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water-radiation coupling are analyzed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not a sufficient predictor of a potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators can only demonstrate the potential occurrence of bimodality but cannot exclude the probability of bimodal vegetation distributions. A new indicator: the normalized difference of precipitation, successfully expresses the stability of the precipitation regime and can improve the accuracy of predictions of forest states. We evaluate the land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are displayed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility to significantly decrease. An increase in the area covered by savanna and grass is possible, which coincides with an observed re-greening of the Sahara.

scholarly journals Forest canopy, a proxi of light intensity, arrests Pinus radiata invasion: basic science to conserve the Coastal Maulino forest, Central Chile

2019 ◽  
Author(s):  
Persy Gómez ◽  
Maureen Murúa ◽  
José San Martín ◽  
Estefany Goncalves ◽  
Ramiro Bustamante
Keyword(s):  
Pinus Radiata ◽  
Forest Canopy ◽  
Forest Type ◽  
Canopy Cover ◽  
Structural Features ◽  
Important Variable ◽  
Tree Cover ◽  
Forest Fragments ◽  
Central Chile ◽  
Maulino Forest

ABSTRACTCoastal Maulino forest is an endemic forest of central Chile, which has suffered a large history of disturbance, being replaced by large extensions of Pinus radiata plantations. This land transformation conveys high rates of pines invasion into native remnants. In this study we examined to what extent structural features of forest patches explains invisibility of this forest-type. Within eight forest fragments, we sampled 162 plots (10 x 10 m2 each). We quantified seedling pine density and related this estimates with tree cover, litter depth, PAR radiation, and diversity of the resident community. Our results indicate that canopy cover was the most important variable to determine seedling pine density within forest fragments. To preserve the Coastal Maulino forest and the biodiversity containing on it, it seems to be necessary to maintain the native canopy cover. These actions can be highly effective even if we cannot avoid a massive seed arrival from pine plantations which will be unable to regenerate under well conserved native forests.

scholarly journals Fractional Woody Cover Mapping of Texas Savanna at Landsat Scale

Land ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 9 ◽  
Author(s):  
Xuebin Yang ◽  
Kelley A. Crews
Keyword(s):  
Woody Plants ◽  
Woody Plant ◽  
Training Data ◽  
Tree Cover ◽  
Mean Annual Precipitation ◽  
Plant Abundance ◽  
The Past ◽  
Woody Cover ◽  
Continuous Fields ◽  
Abundance And Distribution

Texas savanna experienced substantial woody plant encroachment during the past several decades, resulting in habitat fragmentation and species loss. A detailed map of woody plant abundance and distribution in this area is critically needed for management purpose. This study endeavors to map the fractional woody cover of Texas savanna at Landsat scale (30 m) in an affordable way. The top of atmosphere reflectance, thermal bands, and NDVI layer of Web-Enabled Landsat Data (WELD) of 2012 were used as predictors, together with mean annual precipitation. Classification and Regression Trees (CART) were calibrated against training data of a whole range of fractional woody cover, which were derived from 1-m resolution digital orthophotos of 2012. Validation indicates a reasonable pixel level accuracy of the result fractional woody cover map, with a R-squared value of 0.45. Moreover, the result map clearly depicts the distribution of woody plants across the study area, as reflected by the orthophotos. Furthermore, this new map proves an improvement over the existing Landsat Vegetation Continuous Fields (VCF) tree cover product. The method developed here, combining remote sensing and statistical techniques, can contribute to savanna management through revealing the abundance and distribution of woody plants.

scholarly journals European Wide Forest Classification Based on Sentinel-1 Data

2021 ◽  
Vol 13 (3) ◽  
pp. 337 ◽  
Author(s):  
Alena Dostálová ◽  
Mait Lang ◽  
Janis Ivanovs ◽  
Lars T. Waser ◽  
Wolfgang Wagner
Keyword(s):  
Time Series ◽  
Forest Type ◽  
Pearson Correlation ◽  
Tree Cover ◽  
European Continent ◽  
Forest Mapping ◽  
Continental Scale ◽  
Forest Classification ◽  
Forest Maps ◽  
Cover Density

The constellation of two Sentinel-1 satellites provides an unprecedented coverage of Synthetic Aperture Radar (SAR) data at high spatial (20 m) and temporal (2 to 6 days over Europe) resolution. The availability of dense time series enables the analysis of the SAR temporal signatures and exploitation of these signatures for classification purposes. Frequent backscatter observations allow derivation of temporally filtered time series that reinforce the effect of changes in vegetation phenology by limiting the influence of short-term changes related to environmental conditions. Recent studies have already shown the potential of multitemporal Sentinel-1 data for forest mapping, forest type classification (coniferous or broadleaved forest) as well as for derivation of phenological variables at local to national scales. In the present study, we tested the viability of a recently published multi-temporal SAR classification method for continental scale forest mapping by applying it over Europe and evaluating the derived forest type and tree cover density maps against the European-wide Copernicus High Resolution Layers (HRL) forest datasets and national-scale forest maps from twelve countries. The comparison with the Copernicus HRL datasets revealed high correspondence over the majority of the European continent with overall accuracies of 86.1% and 73.2% for the forest/non-forest and forest type maps, respectively, and a Pearson correlation coefficient of 0.83 for tree cover density map. Moreover, the evaluation of both datasets against the national forest maps showed that the obtained accuracies of Sentinel-1 forest maps are almost within range of the HRL datasets. The Sentinel-1 forest/non-forest and forest type maps obtained average overall accuracies of 88.2% and 82.7%, respectively, as compared to 90.0% and 87.2% obtained by the Copernicus HRL datasets. This result is especially promising due to the facts that these maps can be produced with a high degree of automation and that only a single year of Sentinel-1 data is required as opposed to the Copernicus HRL forest datasets that are updated every three years.

scholarly journals A Comparative Study to Evaluate Accuracy on Canopy Height and Density Using UAV, ALS, and Fieldwork

Forests ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 241 ◽  
Author(s):  
Cheonggil Jin ◽  
Che-young Oh ◽  
Sanghyun Shin ◽  
Nkwain Wilfred Njungwi ◽  
Chuluong Choi
Keyword(s):  
Forest Canopy ◽  
Forest Type ◽  
Canopy Cover ◽  
Tree Height ◽  
Field Measurements ◽  
Point Clouds ◽  
Aerial Photographs ◽  
Measurement Unit ◽  
Maximum Height ◽  
Cover Density

Accurate measurement of the tree height and canopy cover density is important for forest biomass and management. Recently, Light Detection and Ranging (LIDAR) and Unmanned Aerial Vehicle (UAV) images have been used to estimate the tree height and canopy cover density for a forest stands. More so, UAV systems with autopilot functions, affordable Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) have created new possibilities, aided by available photogrammetric programs. In this study, we investigated the possibility of data collection methods using an Aerial LIDAR Scanner (ALS) and an UAV together with a fieldworks to evaluate accurate the tree standard metrics in Singyeri, Gyeongjusi, and Gyeongsangbukdo province. The derived metrics via statistical analyses of the ALS and UAV data and validated by field measurements were compared to a published forest type map (scale 1:5000) by the Korea Forest Service; geared towards improving the forest attributes. We collected data and analyzed and compared them with existent the forest type map produced from an aerial photographs and a digital stereo plotter. The ALS data of around 19.5 points·m–2 were collected by an airplane, then processed and classified using the LAStools; while about 362 images of the UAV were processed via Structure from Motion algorithm in the Agisoft Metashape Pro. Thus, we calculated the metrics using the point clouds of both an ALS and an UAV, and then verified their similarity. The fieldwork was manually done on 110 sampled trees. Calculated heights of the UAV were 3.8~5.8 m greater than those for the ALS; and when correlated with the fieldwork, the UAV data overestimated, while the maximum height of the ALS data was more accurate. For the canopy cover, the ALS computed canopy cover was 10%~30% less than that of the UAV. However, the canopy cover above 2 m by an UAV was the best measurement for a forest canopy. Therefore, these results assert that the examined techniques are robust and can significantly complement methods of the conventional data acquisition for the forest type map.

scholarly journals The spatial dimensions of Savanna fire ecology in Kruger National Park, South Africa

2015 ◽  
Author(s):  
◽  
Daniel Godwin
Keyword(s):  
South Africa ◽  
National Park ◽  
Fire Severity ◽  
Kruger National Park ◽  
Tree Cover ◽  
Annual Precipitation ◽  
Fuel Load ◽  
Fire Intensity ◽  
Mean Annual Precipitation ◽  
Woody Cover

Savannas are thought to be bistable with forests potentially occurring above [about]650 mm / yr of Mean Annual Precipitation (MAP) due to the limiting effects of fire on tree cover. This is predicated on two assumptions: 1) fires increasingly limit woody cover in more mesic (> 650 MAP) savannas and 2) increasing tree cover produces feedbacks that reduce fire intensity. These assumptions are investigated in a spatially explicit framework. We use Kruger National Park (KNP), South Africa as our study system, in part due to the wide range of frequency of fires, the large variation in natural communities and rainfall, and the large body of previous research for comparisons and modeling efforts. To investigate whether tree cover produces feedbacks on fire intensity, we measured fire behavior as a function of grass fuel load and woody cover in experimental burns within KNP. We found weak but positive relationships (not negative, as assumed) between woody cover and fire intensity, independent of grass fuel load, and no relationship between tree cover and grass fuel load. At a landscape scale, we modeled the factors predicted to drive fire severity in KNP. We observed that fireline intensity is a strong predictor of many estimations of fire severity in small fires, but across larger fires, rainfall and woody cover likewise can predict impacts on herbaceous consumption and woody cover, respectively. Lastly, to investigate whether trees escape fire less often in more mesic savannas, we used a stochastic model parameterized with real data. After a review of published growth rates, we modeled fire escape probability using mean annual precipitation, fire frequency, and fireline intensity values across KNP. When accounting for species turnover across rainfall gradients, we found a nearly flat relationship between the probability of individuals escaping fire and rainfall. Our research challenges two key assumptions for fire-mediated bistability of mesic savannas.

scholarly journals A Spatial and Temporal Assessment of Vegetation Greening and Precipitation Changes for Monitoring Vegetation Dynamics in Climate Zones over Africa

2021 ◽  
Vol 10 (3) ◽  
pp. 129
Author(s):  
Vincent Nzabarinda ◽  
Anming Bao ◽  
Wenqiang Xu ◽  
Solange Uwamahoro ◽  
Madeleine Udahogora ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forest Type ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Plant Health ◽  
Tree Cover ◽  
Climatic Zones ◽  
Dramatic Decline ◽  
Precipitation Changes

Vegetation is vital, and its greening depends on access to water. Thus, precipitation has a considerable influence on the health and condition of vegetation and its amount and timing depend on the climatic zone. Therefore, it is extremely important to monitor the state of vegetation according to the movements of precipitation in climatic zones. Although a lot of research has been conducted, most of it has not paid much attention to climatic zones in the study of plant health and precipitation. Thus, this paper aims to study the plant health in five African climatic zones. The linear regression model, the persistence index (PI), and the Pearson correlation coefficients were applied for the third generation Normalized Difference Vegetation Index (NDVI3g), with Climate Hazard Group infrared precipitation and Climate Change Initiative Land Cover for 34 years (1982 to 2015). This involves identifying plants in danger of extinction or in dramatic decline and the relationship between vegetation and rainfall by climate zone. The forest type classified as tree cover, broadleaved, deciduous, closed to open (>15%) has been degraded to 74% of its initial total area. The results also revealed that, during the study period, the vegetation of the tropical, polar, and warm temperate zones showed a higher rate of strong improvement. Although arid and boreal zones show a low rate of strong improvement, they are those that experience a low percentage of strong degradation. The continental vegetation is drastically decreasing, especially forests, and in areas with low vegetation, compared to more vegetated areas, there is more emphasis on the conservation of existing plants. The variability in precipitation is excessively hard to tolerate for more types of vegetation.

Evaluation of GPROF V05 Precipitation Retrievals under Different Cloud Regimes

2021 ◽  
Keyword(s):  
Discrete Systems ◽  
The United States ◽  
Precipitation Variability ◽  
Substantial Fraction ◽  
Precipitation Regime ◽  
Surface Type ◽  
Precipitation Regimes ◽  
Channel Configuration ◽  
Global Precipitation ◽  
Cloud Regimes

AbstractPrecipitation retrievals from passive microwave satellite observations form the basis of many widely used precipitation products, but the performance of the retrievals depends on numerous factors such as surface type and precipitation variability. Previous evaluation efforts have identified bias dependence on precipitation regime, which may reflect the influence on retrievals of recurring factors. In this study, the concept of a regime-based evaluation of precipitation from the Goddard Profiling (GPROF) algorithm is extended to cloud regimes. Specifically, GPROF V05 precipitation retrievals under four different cloud regimes are evaluated against ground radars over the United States. GPROF is generally able to accurately retrieve the precipitation associated with both organized convection and less organized storms, which collectively produce a substantial fraction of global precipitation. However, precipitation from stratocumulus systems is underestimated over land and overestimated over water. Similarly, precipitation associated with trade cumulus environments is underestimated over land, while biases over water depend on the sensor’s channel configuration. By extending the evaluation to more sensors and suppressed environments, these results complement insights previously obtained from precipitation regimes, thus demonstrating the potential of cloud regimes in categorizing the global atmosphere into discrete systems.

Urban Trees and Water Use in Arid Climates: Insights from an Integrated Bioeconomic-Health Model

2018 ◽  
Vol 04 (04) ◽  
pp. 1850022 ◽  
Author(s):  
Benjamin A. Jones ◽  
John Fleck
Keyword(s):  
Ecosystem Services ◽  
Water Use ◽  
Forest Canopy ◽  
Urban Forest ◽  
Economic Value ◽  
Urban Trees ◽  
Tree Cover ◽  
Arid Environments ◽  
Value Of Water ◽  
Health Model

Managing outdoor water use while maintaining urban tree cover is a key challenge for water managers in arid climates. Urban trees generate flows of ecosystem services in arid areas, but also require significant amounts of irrigation. In this paper, a bioeconomic-health model of trees and water use is developed to investigate management of an urban forest canopy when irrigation is costly, water has economic value, and trees provide ecosystem services. The optimal tree irrigation decision is illustrated for Albuquerque, New Mexico, an arid Southwest US city. Using a range of monetary values for water, we find that the tree irrigation decision is sensitive to the value selected. Urban deforestation is optimal when the value of water is sufficiently high, or alternatively starts low, but grows to cross a specific threshold. If, however, the value of water is sufficiently low or if the value of tree cover rises over time, then deforestation is not optimal. The threshold value of water where the switch is made between zero and partial deforestation is well within previously identified ranges on actual water values. This model can be applied generally to study the tradeoffs between urban trees and water use in arid environments.

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