scholarly journals Enhancing the Resilience of a Mediterranean Forest to Extreme Drought Events and Climate Change: Pinus—Tetraclinis Forests in Europe

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 487
Author(s):  
Juan Miguel Moya-Pérez ◽  
María Francisca Carreño ◽  
Miguel Ángel Esteve-Selma
Keyword(s):  
Climate Change ◽  
Habitat Management ◽  
Forest Decline ◽  
Pinus Halepensis ◽  
Light Availability ◽  
Reproductive Activity ◽  
Extreme Drought ◽  
Light Detection And Ranging ◽  
Lidar Data ◽  
Tetraclinis Articulata

The southeast Iberian Peninsula is the only place in the European Community where Tetraclinis articulata (Vahl) Masters populations are native. In this area, the optimal ecological niche for this species is occupied by Pinus halepensis (Miller). The increasing intensity of extreme drought events induced by climate change causes severe declines in pine forests, while providing expansion opportunities for established Tetraclinis populations. Within the framework of the LIFE-TETRACLINIS project, a study has been designed to simulate the pine forest decline effects on the population dynamics of this protected species. This work investigates the effects of decreasing competition on T. articulata specimens with limited reproductive activity. To induce the reproductive activity of these specimens through increasing the availability of light, the surrounding pines were removed within a 15 m radius. Increased light availability was modelled using “Light Detection And Ranging” (LiDAR) data, and changes in the main reproductive parameters were registered throughout the study period. A significant increase in the reproductive population was achieved, as well as the cones produced per specimen and the recruitment. Findings obtained are promising for the habitat management in continental Europe and enhancing this forest system’s resilience to extreme drought events and climate change.

scholarly journals Modeling Diameter Distributions with Six Probability Density Functions in Pinus halepensis Mill. Plantations Using Low-Density Airborne Laser Scanning Data in Aragón (Northeast Spain)

2021 ◽  
Vol 13 (12) ◽  
pp. 2307
Author(s):  
J. Javier Gorgoso-Varela ◽  
Rafael Alonso Ponce ◽  
Francisco Rodríguez-Puerta
Keyword(s):  
Probability Density ◽  
Linear Models ◽  
Pinus Halepensis ◽  
Beta Function ◽  
Probability Density Functions ◽  
Lidar Data ◽  
Density Functions ◽  
Minimum Diameter ◽  
Location Parameters ◽  
Diameter Distributions

The diameter distributions of trees in 50 temporary sample plots (TSPs) established in Pinus halepensis Mill. stands were recovered from LiDAR metrics by using six probability density functions (PDFs): the Weibull (2P and 3P), Johnson’s SB, beta, generalized beta and gamma-2P functions. The parameters were recovered from the first and the second moments of the distributions (mean and variance, respectively) by using parameter recovery models (PRM). Linear models were used to predict both moments from LiDAR data. In recovering the functions, the location parameters of the distributions were predetermined as the minimum diameter inventoried, and scale parameters were established as the maximum diameters predicted from LiDAR metrics. The Kolmogorov–Smirnov (KS) statistic (Dn), number of acceptances by the KS test, the Cramér von Misses (W2) statistic, bias and mean square error (MSE) were used to evaluate the goodness of fits. The fits for the six recovered functions were compared with the fits to all measured data from 58 TSPs (LiDAR metrics could only be extracted from 50 of the plots). In the fitting phase, the location parameters were fixed at a suitable value determined according to the forestry literature (0.75·dmin). The linear models used to recover the two moments of the distributions and the maximum diameters determined from LiDAR data were accurate, with R2 values of 0.750, 0.724 and 0.873 for dg, dmed and dmax. Reasonable results were obtained with all six recovered functions. The goodness-of-fit statistics indicated that the beta function was the most accurate, followed by the generalized beta function. The Weibull-3P function provided the poorest fits and the Weibull-2P and Johnson’s SB also yielded poor fits to the data.

scholarly journals Impact of Extreme Drought Climate on Water Security in North Borneo: Case Study of Sabah

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1135
Author(s):  
Carolyn Payus ◽  
Lim Ann Huey ◽  
Farrah Adnan ◽  
Andi Besse Rimba ◽  
Geetha Mohan ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resource ◽  
Supply And Demand ◽  
Water Security ◽  
Water Levels ◽  
Extreme Drought ◽  
Northeast Monsoon ◽  
Water Insecurity ◽  
The North ◽  
North Borneo

For countries in Southeast Asia that mainly rely on surface water as their water resource, changes in weather patterns and hydrological systems due to climate change will cause severely decreased water resource availability. Warm weather triggers more water use and exacerbates the extraction of water resources, which will change the operation patterns of water usage and increase demand, resulting in water scarcity. The occurrence of prolonged drought upsets the balance between water supply and demand, significantly increasing the vulnerability of regions to damaging impacts. The objectives of this study are to identify trends and determine the impacts of extreme drought events on water levels for the major important water dams in the northern part of Borneo, and to assess the risk of water insecurity for the dams. In this context, remote sensing images are used to determine the degree of risk of water insecurity in the regions. Statistical methods are used in the analysis of daily water levels and rainfall data. The findings show that water levels in dams on the North and Northeast Coasts of Borneo are greatly affected by the extreme drought climate caused by the Northeast Monsoon, with mild to the high risk recorded in terms of water insecurity, with only two of the water dams being water-secure. This study shows how climate change has affected water availability throughout the regions.

Diatoms in Saline Lakes Paleoclimate and Paleoecology Interpretations

2007 ◽  
Vol 13 ◽  
pp. 149-168 ◽  
Author(s):  
Erik J. Ekdahl
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Global Climate Change ◽  
Water Conservation ◽  
Environmental Changes ◽  
Global Climate ◽  
Light Availability ◽  
Ionic Concentration ◽  
Mitigation Strategies ◽  
Environmental Response

Average global temperatures are predicted to rise over the next century and changes in precipitation, humidity, and drought frequency will likely accompany this global warming. Understanding associated changes in continental precipitation and temperature patterns in response to global change is an important component of long-range environmental planning. For example, agricultural management plans that account for decreased precipitation over time will be less susceptible to the effects of drought through implementation of water conservation techniques.A detailed understanding of environmental response to past climate change is key to understanding environmental changes associated with global climate change. To this end, diatoms are sensitive to a variety of limnologic parameters, including nutrient concentration, light availability, and the ionic concentration and composition of the waters that they live in (e.g. salinity). Diatoms from numerous environments have been used to reconstruct paleosalinity levels, which in turn have been used as a proxy records for regional and local paleoprecipitation. Long-term records of salinity or paleoprecipitation are valuable in reconstructing Quaternary paleoclimate, and are important in terms of developing mitigation strategies for future global climate change. High-resolution paleoclimate records are also important in groundtruthing global climate simulations, especially in regions where the consequences of global warming may be severe.

scholarly journals Analysis and Prediction of Gap Dynamics in a Secondary Deciduous Broadleaf Forest of Central Japan Using Airborne Multi-LiDAR Observations

2020 ◽  
Vol 13 (1) ◽  
pp. 100
Author(s):  
Kazuho Araki ◽  
Yoshio Awaya
Keyword(s):  
Linear Regression Analysis ◽  
Light Detection And Ranging ◽  
Lidar Data ◽  
Gap Dynamics ◽  
Central Japan ◽  
Broadleaf Forest ◽  
Strong Linear Correlation ◽  
Using Data ◽  
Deciduous Broadleaf Forest ◽  
Lidar Observations

Gaps are important for growth of vegetation on the forest floor. However, monitoring of gaps in large areas is difficult. Airborne light detection and ranging (LiDAR) data make precise gap mapping possible. We formulated a method to describe changes in gaps by time-series tracking of gap area changes using three digital canopy height models (DCHMs) based on LiDAR data collected in 2005, 2011, and 2016 over secondary deciduous broadleaf forest. We generated a mask that covered merging or splitting of gaps in the three DCHMs and allowed us to identify their spatiotemporal relationships. One-fifth of gaps merged with adjacent gaps or split into several gaps between 2005 and 2016. Gap shrinkage showed a strong linear correlation with gap area in 2005, via lateral growth of gap-edge trees between 2005 and 2016, as modeled by a linear regression analysis. New gaps that emerged between 2005 and 2011 shrank faster than gaps present in 2005. A statistical model to predict gap lifespan was developed and gap lifespan was mapped using data from 2005 and 2016. Predicted gap lifespan decreased greatly due to shrinkage and splitting of gaps between 2005 and 2016.

scholarly journals Modelling above-ground carbon dynamics using multi-temporal airborne lidar: insights from a Mediterranean woodland

2016 ◽  
Vol 13 (4) ◽  
pp. 961-973 ◽  
Author(s):  
W. Simonson ◽  
P. Ruiz-Benito ◽  
F. Valladares ◽  
D. Coomes
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Critical Role ◽  
Carbon Fluxes ◽  
Carbon Dynamics ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Low Carbon ◽  
Data Set ◽  
Multi Temporal

Abstract. Woodlands represent highly significant carbon sinks globally, though could lose this function under future climatic change. Effective large-scale monitoring of these woodlands has a critical role to play in mitigating for, and adapting to, climate change. Mediterranean woodlands have low carbon densities, but represent important global carbon stocks due to their extensiveness and are particularly vulnerable because the region is predicted to become much hotter and drier over the coming century. Airborne lidar is already recognized as an excellent approach for high-fidelity carbon mapping, but few studies have used multi-temporal lidar surveys to measure carbon fluxes in forests and none have worked with Mediterranean woodlands. We use a multi-temporal (5-year interval) airborne lidar data set for a region of central Spain to estimate above-ground biomass (AGB) and carbon dynamics in typical mixed broadleaved and/or coniferous Mediterranean woodlands. Field calibration of the lidar data enabled the generation of grid-based maps of AGB for 2006 and 2011, and the resulting AGB change was estimated. There was a close agreement between the lidar-based AGB growth estimate (1.22 Mg ha−1 yr−1) and those derived from two independent sources: the Spanish National Forest Inventory, and a tree-ring based analysis (1.19 and 1.13 Mg ha−1 yr−1, respectively). We parameterised a simple simulator of forest dynamics using the lidar carbon flux measurements, and used it to explore four scenarios of fire occurrence. Under undisturbed conditions (no fire) an accelerating accumulation of biomass and carbon is evident over the next 100 years with an average carbon sequestration rate of 1.95 Mg C ha−1 yr−1. This rate reduces by almost a third when fire probability is increased to 0.01 (fire return rate of 100 years), as has been predicted under climate change. Our work shows the power of multi-temporal lidar surveying to map woodland carbon fluxes and provide parameters for carbon dynamics models. Space deployment of lidar instruments in the near future could open the way for rolling out wide-scale forest carbon stock monitoring to inform management and governance responses to future environmental change.

The effects of extreme drought on climate change beliefs, risk perceptions, and adaptation attitudes

2015 ◽  
Vol 135 (2) ◽  
pp. 211-226 ◽  
Author(s):  
J. Stuart Carlton ◽  
Amber S. Mase ◽  
Cody L. Knutson ◽  
Maria Carmen Lemos ◽  
Tonya Haigh ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Perceptions ◽  
Extreme Drought ◽  
Change Beliefs

scholarly journals A Novel Method for Feature Extraction and Classification for an Aerial Image and LiDAR Data with Genetic Algorithm

2012 ◽  
pp. 264-270
Author(s):  
Manjunath B. E ◽  
D. G. Anand ◽  
Mahant. G. Kattimani
Keyword(s):  
Feature Extraction ◽  
Light Detection And Ranging ◽  
Aerial Image ◽  
Lidar Data ◽  
Light Detection ◽  
Aerial Photos ◽  
The Earth ◽  
Digital Elevation ◽  
Land Surveying ◽  
Novel Method

Airborne Light Detection and Ranging (LiDAR) provides accurate height information for objects on the earth, which makes LiDAR become more and more popular in terrain and land surveying. In particular, LiDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. Aerial photos with LiDAR data were processed with genetic algorithms not only for feature extraction but also for orthographical image. DSM provided by LiDAR reduced the amount of GCPs needed for the regular processing, thus the reason both efficiency and accuracy are highly improved. LiDAR is an acronym for Light Detection and Ranging, which is typically defined as an integration of three technologies into a single system, which is capable of acquiring a data to produce accurate Digital Elevation Models.

scholarly journals Lessons from LiDAR data use in the Netherlands

2017 ◽  
Vol 1 (2) ◽  
pp. 661-670 ◽  
Author(s):  
Willem Frans Beex
Keyword(s):  
The Netherlands ◽  
Best Practices ◽  
Cultural Heritage ◽  
Land Surface ◽  
New Technology ◽  
Data Use ◽  
Light Detection And Ranging ◽  
Lidar Data ◽  
Natural Land ◽  
Imaging Detection

Light Detection And Ranging or Laser Imaging Detection And Ranging (LiDAR) is not really a new technology. However, it does provide the data from which accurate models of the natural land surface completely stripped of buildings and vegetation can be derived. Interestingly for Cultural Heritage and Archaeology, most of the data is already freely available for research. This is certainly the case in the Netherlands, with the “Actueel Hoogtemodel Nederland 2”, or “AHN2”. The density of the measured points is at least 50 centimetres, which means that the remains of structures larger than one by one metre can be detected. As a result, many unknown structures have been discovered with it. However, these excellent results have blinded many Cultural Heritage and Archaeology practitioners to obvious mistakes when interpreting LiDAR data. This paper is intended to highlight best-practices for the use of LiDAR data by Cultural Heritage professionals.

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