Disentangling Soil, Shade, and Tree Canopy Contributions to Mixed Satellite Vegetation Indices in a Sparse Dry Forest DOI Creative Commons
Huanhuan Wang, Jonathan Müller, Fyodor Tatarinov

et al.

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(15), P. 3681 - 3681

Published: Aug. 1, 2022

Remote sensing (RS) for vegetation monitoring can involve mixed pixels with contributions from and background surfaces, causing biases in signals their interpretations, especially low-density forests. In a case study the semi-arid Yatir forest Israel, we observed mismatch between satellite (Landsat 8 surface product) tower-based (Skye sensor) multispectral data contrasting seasonal cycles near-infrared (NIR) reflectance. We tested hypothesis that this was due to different fractional of various components unique Employing an unmanned aerial vehicle (UAV), obtained high-resolution images over selected plots estimated fraction, reflectance, cycle three main (canopy, shade, sunlit soil). determined Landsat were dominated by soil (70%), while canopy (95%). then developed procedure resolve (i.e., tree foliage) normalized difference index (NDVI) data. The retrieved corrected canopy-only resolved original indicated spatial variations NDVI differences stand density, spatially uniform, providing confidence local flux tower measurements.

Language: Английский

Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh DOI

Swades Pal,

Sonali Kundu, Susanta Mahato

et al.

Journal of Cleaner Production, Journal Year: 2020, Volume and Issue: 257, P. 120311 - 120311

Published: Feb. 11, 2020

Language: Английский

Citations

108

Long-term thinning effects on tree growth, drought response and water use efficiency at two Aleppo pine plantations in Spain DOI
Àngela Manrique‐Alba, Santiago Beguerı́a, Antonio J. Molina

et al.

The Science of The Total Environment, Journal Year: 2020, Volume and Issue: 728, P. 138536 - 138536

Published: April 17, 2020

Language: Английский

Citations

99

Meta-analysis Reveals Different Competition Effects on Tree Growth Resistance and Resilience to Drought DOI Creative Commons
Daniele Castagneri, Giorgio Vacchiano, Andrew Hacket‐Pain

et al.

Ecosystems, Journal Year: 2021, Volume and Issue: 25(1), P. 30 - 43

Published: May 6, 2021

Abstract Drought will increasingly threaten forest ecosystems worldwide. Understanding how competition influences tree growth response to drought is essential for management aiming at climate change adaptation. However, published results from individual case studies are heterogeneous and sometimes contradictory. We reviewed 166 cases the peer-reviewed literature assess influence of stand-level on drought. monitored five indicators response: mean sensitivity (inter-annual ring width variability); association between inter-annual variability water availability; resistance; recovery; resilience Vote counting did not indicate a consistent effect sensitivity. Conversely, higher resources strengthened availability rates. Meta-analysis showed that reduced resistance ( p < 0.001) improved recovery 0.05), but consistently affect resilience. Species, site stand characteristics, intensity were insignificant or poor predictors large among investigated cases. Our review meta-analysis show does in unidirectional universal way. Although density reduction (thinning) can alleviate declines during drought, effects after stress uncertain. The suggests local-scale processes play crucial role determining such responses should be explicitly evaluated integrated into specific strategies adaptation forests change.

Language: Английский

Citations

98

The uncertain role of rising atmospheric CO2 on global plant transpiration DOI Creative Commons
Sergio M. Vicente‐Serrano, Diego G. Miralles, Nate G. McDowell

et al.

Earth-Science Reviews, Journal Year: 2022, Volume and Issue: 230, P. 104055 - 104055

Published: May 12, 2022

As CO2 concentration in the atmosphere rises, there is a need for improved physical understanding of its impact on global plant transpiration. This knowledge gap poses major hurdle robustly projecting changes hydrologic cycle. For this reason, here we review different processes by which atmospheric affects transpiration, several uncertainties related to complex physiological and radiative involved, gaps be filled order improve predictions Although high degree certainty that rising will exact nature remains unclear due interactions between climate, key aspects morphology physiology. The interplay these factors has substantial consequences not only future climate vegetation, but also water availability needed sustaining productivity terrestrial ecosystems. Future transpiration response enhanced are expected driven availability, evaporative demand, processes, emergent disturbances increasing temperatures, modification physiology coverage. Considering universal sensitivity natural agricultural systems argue reliable projections an issue highest priority, can achieved integrating monitoring modeling efforts representation effects next generation earth system models.

Language: Английский

Citations

60

The impact of planting density on forest monospecific plantations: An overview DOI
Mônica Moreno Gabira, Miguel Montoro Girona, Annie DesRochers

et al.

Forest Ecology and Management, Journal Year: 2023, Volume and Issue: 534, P. 120882 - 120882

Published: Feb. 22, 2023

Language: Английский

Citations

25

Development of a multi-objective decision support system for eco-hydrological forest management that quantifies and optimizes ecosystem services related to Carbon, Water, Fire-risk and Eco-resilience (CAFE) DOI
Javier Pérez-Romero, María González-Sanchis, Laura Blanco-Cano

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 125103 - 125103

Published: April 1, 2025

Language: Английский

Citations

1

Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality modelling in Asir region, Saudi Arabia DOI
Javed Mallick, Swapan Talukdar, Majed Alsubih

et al.

Geocarto International, Journal Year: 2021, Volume and Issue: 37(15), P. 4361 - 4389

Published: Jan. 21, 2021

Groundwater scarcity is one of the most concerning issues in arid and semi-arid regions. In this study, we develop validate a novel artificial intelligence that coupling five ensemble benchmark algorithms e.g., neural network (ANN), reduced-error pruning trees (REPTree), radial basis function (RBF), M5P random forest (RF) with particle swarm optimization (PSO) for delineating GWP zones. Further, nine parameters used modelling to test train proposed PSO-based models. Additionally, study proposes receiver operating characteristic (ROC) based sensitivity analysis modelling. Multicollinearity test, information gain ratio, correlation attribute evaluation methods choose important model. The result shows drainage density, elevation, land use/land cover have higher influence on using methods. Results showed hybrid PSO-RF model performed better than other

Language: Английский

Citations

44

The Counteracting Effects of Snowmelt Rate and Timing on Runoff DOI
Theodore B. Barnhart, C. Tague, N. P. Molotch

et al.

Water Resources Research, Journal Year: 2020, Volume and Issue: 56(8)

Published: Aug. 1, 2020

Abstract The declining mountain snowpack is expected to melt earlier and more slowly with climate warming. Previous work indicates that lower snowmelt rates are associated decreased runoff. However, could increase runoff via vegetation water use in early spring. relative importance of these factors regard linked site‐specific conditions such as plant available storage (PAWS) energy availability. To disentangle the effects rate timing on production, we conducted a hydrologic modeling experiment at sites Colorado (NR1) California (P301) controlled for multicollinearity. We tested sensitivity season potential ( R ), changes subsurface (Δ S other budget components sm r ) t using multiple linear regression global analysis (GSA). Regression results confirmed was governed by competing influence . At both sites, Δ sensitive than while P301 NR1, reflecting limitation NR1. GSA analyses mirrored regressions , confirming important NR1 P301. This suggests increases from may counteract losses due slower this process mediated PAWS These suggest will be susceptible future greater energy.

Language: Английский

Citations

45

A hidden mechanism of forest loss under climate change: The role of drought in eliminating forest regeneration at the edge of its distribution DOI

Ella Pozner,

Peleg Bar-On,

Stav Livne‐Luzon

et al.

Forest Ecology and Management, Journal Year: 2021, Volume and Issue: 506, P. 119966 - 119966

Published: Dec. 22, 2021

Language: Английский

Citations

37

Management can mitigate drought legacy effects on the growth of a moisture-sensitive conifer tree species DOI
Bo Wang, Tuo Chen, Guobao Xu

et al.

Forest Ecology and Management, Journal Year: 2023, Volume and Issue: 544, P. 121196 - 121196

Published: June 19, 2023

Language: Английский

Citations

14