Forest Drought Resistance at Large Geographic Scales

Adam: A Method for Stochastic Optimization

Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946 · see citing works

Biodiversity hotspots for conservation priorities

Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. B., & Kent, J. (2000) · Nature · doi:10.1038/35002501 · Cited by 31,710 · see citing works

Resilience and Stability of Ecological Systems

Holling, C. S. (1973) · Annual Review of Ecology and Systematics · doi:10.1146/annurev.es.04.110173.000245 · Cited by 18,995 · see citing works

Google Earth Engine: Planetary-scale geospatial analysis for everyone

Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.06.031 · Cited by 15,523 · see citing works

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Abadi, M., Agarwal, A., Barham, P., Brevdo, E., Chen, Z., Citro, C., Corrado, G. S., Davis, A., Dean, J., Devin, M., et al. (2016) · arXiv · doi:10.48550/arxiv.1603.04467 · Cited by 9,408 · see citing works

An Approach toward a Rational Classification of Climate

Thornthwaite, C. W. (1948) · Geographical Review · doi:10.2307/210739 · Cited by 9,141 · see citing works

A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests

Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D. D., Hogg, E. H. (., et al. (2010) · Forest Ecology and Management · doi:10.1016/j.foreco.2009.09.001 · Cited by 7,763 · see citing works

Vive la différence: plant functional diversity matters to ecosystem processes

Dı́az, S., & Cabido, M. (2001) · Trends in Ecology & Evolution · doi:10.1016/s0169-5347(01)02283-2 · Cited by 3,306 · see citing works

Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States

Daly, C., Halbleib, M. D., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J. B., & Pasteris, P. P. (2008) · International Journal of Climatology · doi:10.1002/joc.1688 · Cited by 3,113 · see citing works

The complexity and stability of ecosystems

Pimm, S. L. (1984) · Nature · doi:10.1038/307321a0 · Cited by 3,062 · see citing works

On underestimation of global vulnerability to tree mortality and forest die‐off from hotter drought in the Anthropocene

Allen, C. D., Breshears, D. D., & McDowell, N. G. (2015) · Ecosphere · doi:10.1890/es15-00203.1 · Cited by 2,654 · see citing works

Biodiversity and stability in grasslands

Tilman, D. G., & Downing, J. (1994) · Nature · doi:10.1038/367363a0 · Cited by 2,298 · see citing works

Biodiversity increases the resistance of ecosystem productivity to climate extremes

Isbell, F., Craven, D., Connolly, J., Loreau, M., Schmid, B., Beierkuhnlein, C., Bezemer, T. M., Bonin, C., Bruelheide, H., de Luca, E., et al. (2015) · Nature · doi:10.1038/nature15374 · Cited by 1,869 · see citing works

Triggers of tree mortality under drought

Choat, B., Brodribb, T. J., Brodersen, C. R., Duursma, R. A., López, R., & Medlyn, B. E. (2018) · Nature · doi:10.1038/s41586-018-0240-x · Cited by 1,817 · see citing works

Cross-scale Drivers of Natural Disturbances Prone to Anthropogenic Amplification: The Dynamics of Bark Beetle Eruptions

Raffa, K. F., Aukema, B. H., Bentz, B., Carroll, A. L., Hicke, J. A., Turner, M. G., & Romme, W. H. (2008) · BioScience · doi:10.1641/b580607 · Cited by 1,783 · see citing works

Biodiversity and Stability in Grasslands

Tilman, D. G., & Downing, J. (1996) · Springer eBooks · doi:10.1007/978-1-4612-4018-1_1 · Cited by 1,495 · see citing works

Consequences of widespread tree mortality triggered by drought and temperature stress

Anderegg, W. R. L., Kane, J. M., & Anderegg, L. D. L. (2012) · Nature Climate Change · doi:10.1038/nclimate1635 · Cited by 1,485 · see citing works

Anthropogenic warming has increased drought risk in California

Diffenbaugh, N. S., Swain, D. L., & Touma, D. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1422385112 · Cited by 1,389 · see citing works

Sensitivity of global terrestrial ecosystems to climate variability

Seddon, A. W. R., Macias‐Fauria, M., Long, P. R., Benz, D., & Willis, K. J. (2016) · Nature · doi:10.1038/nature16986 · Cited by 1,385 · see citing works

Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models

Anderegg, W. R. L., Schwalm, C. R., Biondi, F., Camarero, J. J., Koch, G. W., Litvak, M. E., Ogle, K., Shaw, J. D., Shevliakova, E., Williams, P., et al. (2015) · Science · doi:10.1126/science.aab1833 · Cited by 1,337 · see citing works

Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests

Lefsky, M. A., Cohen, W. B., Acker, S. A., Parker, G. G., Spies, T. A., & Harding, D. (1999) · Remote Sensing of Environment · doi:10.1016/s0034-4257(99)00052-8 · Cited by 904 · see citing works

Plant adaptation to drought stress

Basu, S., Ramegowda, V., Kumar, A., & Pereira, A. (2016) · F1000Research · doi:10.12688/f1000research.7678.1 · Cited by 890 · see citing works

Climatic control of vegetation distribution: the role of the water balance

Stephenson, N. L. (1990) · The American Naturalist · doi:10.1086/285067 · Cited by 848 · see citing works

The impacts of increasing drought on forest dynamics, structure, and biodiversity in the United States

Clark, J. S., Iverson, L., Woodall, C. W., Allen, C. D., Bell, D. M., Bragg, D. C., D'Amato, A. W., Davis, F. W., Hersh, M. H., Ibanez, I., et al. (2016) · Global Change Biology · doi:10.1111/gcb.13160 · Cited by 606 · see citing works

Long-term climate and competition explain forest mortality patterns under extreme drought

Young, D. J. N., Stevens, J. T., Earles, J. M., Moore, J., Ellis, A., Jirka, A. L., & Latimer, A. M. (2017) · Ecology Letters · doi:10.1111/ele.12711 · Cited by 443 · see citing works

Column atmospheric water vapor and vegetation liquid water retrievals from Airborne Imaging Spectrometer data

Gao, B., & Goetz, A. F. H. (1990) · Journal of Geophysical Research Atmospheres · doi:10.1029/jd095id04p03549 · Cited by 438 · see citing works

Atmospheric correction algorithms for hyperspectral remote sensing data of land and ocean

Gao, B., Montes, M. J., Davis, C. O., & Goetz, A. F. H. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2007.12.015 · Cited by 434 · see citing works

Structural overshoot of tree growth with climate variability and the global spectrum of drought‐induced forest dieback

Jump, A. S., Ruiz‐Benito, P., Greenwood, S., Allen, C. D., Kitzberger, T., Fensham, R. J., Martínez‐Vilalta, J., & Lloret, F. (2017) · Global Change Biology · doi:10.1111/gcb.13636 · Cited by 402 · see citing works

Progressive forest canopy water loss during the 2012–2015 California drought

Asner, G. P., Brodrick, P. G., Anderson, C. B., Vaughn, N., Knapp, D. E., & Martin, R. E. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1523397113 · Cited by 397 · see citing works

Tree carbon allocation explains forest drought‐kill and recovery patterns

Trugman, A. T., Detto, M., Bartlett, M. K., Medvigy, D., Anderegg, W. R. L., Schwalm, C. R., Schaffer, B. E., & Pacala, S. W. (2018) · Ecology Letters · doi:10.1111/ele.13136 · Cited by 347 · see citing works

The fire frequency‐severity relationship and the legacy of fire suppression in California forests

Steel, Z. L., Safford, H. D., & Viers, J. H. (2015) · Ecosphere · doi:10.1890/es14-00224.1 · Cited by 339 · see citing works

Carnegie Airborne Observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion

Asner, G. P., Knapp, D., Boardman, J., Green, R. O., Kennedy-Bowdoin, T., Eastwood, M. L., Martin, R. E., Anderson, C. B., & Field, C. B. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.06.012 · Cited by 327 · see citing works

Carnegie Airborne Observatory: in-flight fusion of hyperspectral imaging and waveform light detection and ranging for three-dimensional studies of ecosystems

Asner, G. P., Knapp, D., Kennedy-Bowdoin, T., Jones, M., Martin, R. E., Boardman, J. W., & Field, C. B. (2007) · Journal of Applied Remote Sensing · doi:10.1117/1.2794018 · Cited by 322 · see citing works

Incorporating Second-Order Functional Knowledge for Better Option Pricing

Dugas, C., Bengio, Y., Bélisle, F., Nadeau, C., & García, R. (2000) · neural information processing systems · Cited by 307 · see citing works

Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation

Asner, G. P., Martin, R. E., Knapp, D., Tupayachi, R., Anderson, C. B., Sinca, F., Vaughn, N. R., & Llactayo, W. (2017) · Science · doi:10.1126/science.aaj1987 · Cited by 266 · see citing works

Developmental changes in mesophyll diffusion conductance and photosynthetic capacity under different light and water availabilities in Populus tremula: how structure constrains function

Tosens, T., Niinemets, Ü., Vislap, V., Eichelmann, H. Y., & Castro‐Díez, P. (2011) · Plant Cell & Environment · doi:10.1111/j.1365-3040.2011.02457.x · Cited by 251 · see citing works

Morpho-Anatomical Traits for Plant Adaptation to Drought

Micco, V. D., & Aronne, G. (2012) · Springer eBooks · doi:10.1007/978-3-642-32653-0_2 · Cited by 224 · see citing works

Not all droughts are created equal: translating meteorological drought into woody plant mortality

Anderegg, L. D. L., Anderegg, W. R. L., & Berry, J. A. (2013) · Tree Physiology · doi:10.1093/treephys/tpt044 · Cited by 223 · see citing works

Revisiting the recent California drought as an extreme value

Robeson, S. M. (2015) · Geophysical Research Letters · doi:10.1002/2015gl064593 · Cited by 215 · see citing works

Estimating Canopy Water Content of Chaparral Shrubs Using Optical Methods

Ustin, S. L., Roberts, D. A., Pinzón, J. E. D., Jacquemoud, S., Gardner, M., Scheer, G., Castañeda, C. M., & Palacios‐Orueta, A. (1998) · Remote Sensing of Environment · doi:10.1016/s0034-4257(98)00038-8 · Cited by 214 · see citing works

Revising the evolutionary computation abstraction

Lehman, J., & Stanley, K. O. (2010) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/1830483.1830503 · Cited by 182 · see citing works

Exposure of trees to drought‐induced die‐off is defined by a common climatic threshold across different vegetation types

Mitchell, P. J., O’Grady, A. P., Hayes, K. R., & Pinkard, E. A. (2014) · Ecology and Evolution · doi:10.1002/ece3.1008 · Cited by 155 · see citing works

Geographic variation in growth response of Douglas‐fir to interannual climate variability and projected climate change

CHEN, P., Welsh, C., & Hamann, A. (2010) · Global Change Biology · doi:10.1111/j.1365-2486.2010.02166.x · Cited by 150 · see citing works

Incorporating Second-Order Functional Knowledge for Better Option PricingPreprint

Bélisle, F., Bengio, Y., Dugas, C., García, R., & Nadeau, C. (2002) · RePEc: Research Papers in Economics · Cited by 140 · see citing works

Measuring the expressed abundance of the three phases of water with an imaging spectrometer over melting snow

Green, R. O., Painter, T. H., Roberts, D. A., & Dozier, J. (2006) · Water Resources Research · doi:10.1029/2005wr004509 · Cited by 106 · see citing works

What mediates tree mortality during drought in the southern Sierra Nevada?

Paz‐Kagan, T., Brodrick, P. G., Vaughn, N. R., Das, A. J., Stephenson, N. L., Nydick, K. R., & Asner, G. P. (2017) · Ecological Applications · doi:10.1002/eap.1620 · Cited by 97 · see citing works

Remotely sensed predictors of conifer tree mortality during severe drought

Brodrick, P. G., & Asner, G. P. (2017) · Environmental Research Letters · doi:10.1088/1748-9326/aa8f55 · Cited by 76 · see citing works

Tracking Interannual Streamflow Variability with Drought Indices in the U.S. Pacific Northwest

Abatzoglou, J. T., Barbero, R., Wolf, J. W., & Holden, Z. A. (2014) · Journal of Hydrometeorology · doi:10.1175/jhm-d-13-0167.1 · Cited by 52 · see citing works

Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought

Martin, R. E., Asner, G. P., Francis, E. J., Ambrose, A. R., Baxter, W. L., Das, A. J., Vaughn, N. R., Paz‐Kagan, T., Dawson, T. E., Nydick, K. R., et al. (2017) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.12.002 · Cited by 46 · see citing works

Landscape-scale variation in canopy water content of giant sequoias during drought

Paz‐Kagan, T., Vaughn, N. R., Martin, R. E., Brodrick, P. G., Stephenson, N. L., Das, A. J., Nydick, K. R., & Asner, G. P. (2017) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.11.018 · Cited by 28 · see citing works

Visual interpretation and time series modeling of Landsat imagery highlight drought's role in forest canopy declines

Bell, D. M., Cohen, W. B., Reilly, M. J., & Yang, Z. (2018) · Ecosphere · doi:10.1002/ecs2.2195 · Cited by 22 · see citing works

Leaf to landscape responses of giant sequoia to hotter drought: An introduction and synthesis for the special section

Nydick, K. R., Stephenson, N. L., Ambrose, A. R., Asner, G. P., Baxter, W. L., Das, A. J., Dawson, T. E., Martin, R. E., & Paz‐Kagan, T. (2018) · Forest Ecology and Management · doi:10.1016/j.foreco.2018.03.028 · Cited by 18 · see citing works

Untitled work

Carretero (1998) · doi:10.1175/1520-0477(1998)079

Hanging by a thread? Forests and drought

Brodribb, T. J., Powers, J. S., Cochard, H., & Choat, B. (2020) · Science · doi:10.1126/science.aat7631 · Cited by 860 · see citing works

California forest die-off linked to multi-year deep soil drying in 2012–2015 drought

Goulden, M. L., & Bales, R. C. (2019) · Nature Geoscience · doi:10.1038/s41561-019-0388-5 · Cited by 369 · see citing works

Tackling climate change with machine learning

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works

Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future

Jiao, W., Wang, L., & McCabe, M. F. (2021) · Remote Sensing of Environment · doi:10.1016/j.rse.2021.112313 · Cited by 285 · see citing works

Tree growth sensitivity to climate is temporally variable

Peltier, D. M. P., & Ogle, K. (2020) · Ecology Letters · doi:10.1111/ele.13575 · Cited by 158 · see citing works

SAR-enhanced mapping of live fuel moisture content

Rao, K., Williams, P., Flefil, J. F., & Konings, A. G. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2020.111797 · Cited by 128 · see citing works

Topographic, soil, and climate drivers of drought sensitivity in forests and shrublands of the Pacific Northwest, USA

Cartwright, J., Littlefield, C. E., Michalak, J., Lawler, J. J., & Dobrowski, S. Z. (2020) · Scientific Reports · doi:10.1038/s41598-020-75273-5 · Cited by 100 · see citing works

Vegetation Responses to 2012–2016 Drought in Northern and Southern California

Dong, C., MacDonald, G. M. S. D., Willis, K. S., Gillespie, T. W., Okin, G. S., & Williams, P. (2019) · Geophysical Research Letters · doi:10.1029/2019gl082137 · Cited by 94 · see citing works

Forest vulnerability to drought controlled by bedrock composition

Callahan, R. P., Riebe, C. S., Sklar, L. S., Pasquet, S., Ferrier, K. L., Hahm, W. J., Taylor, N. J., Graña, D., Flinchum, B. A., Hayes, J. L., et al. (2022) · Nature Geoscience · doi:10.1038/s41561-022-01012-2 · Cited by 90 · see citing works

Significant water stress on gross primary productivity during flash droughts with hot conditions

Xi, X., & Yuan, X. (2022) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2022.109100 · Cited by 82 · see citing works

Drought sensitivity of vegetation photosynthesis along the aridity gradient in northern China

Xu, H., Wang, X., & Zhao, C. (2021) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2021.102418 · Cited by 81 · see citing works

Evaluating the potential of airborne hyperspectral LiDAR for assessing forest insects and diseases with 3D Radiative Transfer Modeling

Zhao, X., Qi, J., Xu, H., Yu, Z., Yuan, L., Chen, Y., & Huang, H. (2023) · Remote Sensing of Environment · doi:10.1016/j.rse.2023.113759 · Cited by 79 · see citing works

Soil moisture variation drives canopy water content dynamics across the western U.S.

Lyons, D. S., Dobrowski, S. Z., Holden, Z. A., Maneta, M., & Sala, A. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2020.112233 · Cited by 62 · see citing works

Soil moisture dominates the variation of gross primary productivity during hot drought in drylands

Qiu, R., Han, G., Li, S., Tian, F., Ma, X., & Gong, W. Y. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.165686 · Cited by 62 · see citing works

Higher Sensitivity of Planted Forests' Productivity Than Natural Forests to Droughts in China

Zhong, Z., He, B., Chen, Y., Yuan, W., Huang, L., Guo, L., Zhang, Y., & Xie, X. (2021) · Journal of Geophysical Research Biogeosciences · doi:10.1029/2021jg006306 · Cited by 50 · see citing works

Drought changes the dominant water stress on the grassland and forest production in the northern hemisphere

Zhang, W., Luo, G., Hamdi, R., Ma, X., Termonia, P., & Maeyer, P. D. (2023) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2023.109831 · Cited by 49 · see citing works

Growth and Tree Water Deficit of Mixed Norway Spruce and European Beech at Different Heights in a Tree and under Heavy Drought

Schäfer, C., Rötzer, T., Thurm, E. A., Biber, P., Kallenbach, C., & Pretzsch, H. (2019) · Forests · doi:10.3390/f10070577 · Cited by 41 · see citing works

Toward climate change refugia conservation at an ecoregion scale

Balantic, C., Adams, A. J., Gross, S. E., Mazur, R., Sawyer, S. C., Tucker, J. M., Vernon, M. E., Mengelt, C., Morales, J., Thorne, J. H., et al. (2021) · Conservation Science and Practice · doi:10.1111/csp2.497 · Cited by 35 · see citing works

Drought-induced ecosystem resistance and recovery observed at 118 flux tower stations across the globe

Shao, X., Zhang, Y., Ma, N., Zhang, X., Tian, J., Xu, Z., & Liu, C. (2024) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2024.110170 · Cited by 35 · see citing works

High-resolution planet satellite imagery and multi-temporal surveys to predict risk of tree mortality in tropical eucalypt forestry

Pascual, A., Tupinambá‐Simões, F., Guerra-Hernández, J., & Bravo, F. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2022.114804 · Cited by 34 · see citing works

Prolonged drought duration, not intensity, reduces growth recovery and prevents compensatory growth of oak trees

Lv, P., Rademacher, T., Huang, X., Zhang, B., & Zhang, X. (2022) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2022.109183 · Cited by 32 · see citing works

Recent California tree mortality portends future increase in drought-driven forest die-off

Madakumbura, G. D., Goulden, M. L., Hall, A. D., Fu, R., Moritz, M. A., Koven, C. D., Kueppers, L. M., Norlen, C. A., & Randerson, J. T. (2020) · Environmental Research Letters · doi:10.1088/1748-9326/abc719 · Cited by 30 · see citing works

Assessing the impact of multi-year droughts on German forests in the context of increased tree mortality

Holtmann, A., Huth, A., Bohn, F. J., & Fischer, R. (2024) · Ecological Modelling · doi:10.1016/j.ecolmodel.2024.110696 · Cited by 28 · see citing works

Anthropogenic warming drives earlier wildfire season onset in California

Madakumbura, G. D., Moritz, M. A., McKinnon, K. A., Williams, P., Rahimi, S., Bass, B., Norris, J., Fu, R., & Hall, A. D. (2025) · Science Advances · doi:10.1126/sciadv.adt2041 · Cited by 21 · see citing works

A generalizable framework for enhanced natural climate solutions

Silva, L. C. R., Wood, M. C., Johnson, B. R., Coughlan, M. R., Brinton, H., McGuire, K. L., & Bridgham, S. D. (2022) · Plant and Soil · doi:10.1007/s11104-022-05472-8 · Cited by 20 · see citing works

Assessing multi-year-drought vulnerability in dense Mediterranean-climate forests using water-balance-based indicators

Cui, G., Ma, Q., & Bales, R. C. (2022) · Journal of Hydrology · doi:10.1016/j.jhydrol.2022.127431 · Cited by 21 · see citing works

Unraveling the response of forests to drought with explainable artificial intelligence (XAI)

Vulova, S., Horn, K., Rocha, A. D., Brill, F., Somogyvári, M., Okujeni, A., Förster, M., & Kleinschmit, B. (2025) · Ecological Indicators · doi:10.1016/j.ecolind.2025.113308 · Cited by 18 · see citing works

Leveraging the NEON Airborne Observation Platform for socio‐environmental systems research

Ordway, E. M., Elmore, A. J., Kolstoe, S. H., Quinn, J. E., Swanwick, R. H., Cattau, M. E., Taillie, D., Guinn, S. M., Chadwick, K. D., Atkins, J. W., et al. (2021) · Ecosphere · doi:10.1002/ecs2.3640 · Cited by 18 · see citing works

Responses of Tree Growth and Intrinsic Water Use Efficiency to Environmental Factors in Central and Northern China in the Context of Global Warming

Ren, M., Liu, Y., Li, Q., Song, H., Cai, Q., & Sun, C. (2022) · Forests · doi:10.3390/f13081209 · Cited by 15 · see citing works

Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Liu, L., Liu, P., Yu, J., Feng, G., Zhang, Q., & Svenning, J. (2024) · Geography and sustainability · doi:10.1016/j.geosus.2024.01.007 · Cited by 15 · see citing works

The Unstable Relationship Between Drought Status and Leaf Water Content Complicates the Remote Sensing of Tree Drought Stress

Boving, I., Allen, J., Brodrick, P. G., Chadwick, K. D., Trugman, A. T., & Anderegg, L. D. L. (2025) · Global Change Biology · doi:10.1111/gcb.70188 · Cited by 12 · see citing works

Remote sensing of cytotype and its consequences for canopy damage in quaking aspen

Blonder, B. W., Brodrick, P. G., Walton, J. A., Chadwick, K. D., Breckheimer, I., Marchetti, S. B., Ray, C. A., & Mock, K. E. (2021) · Global Change Biology · doi:10.1111/gcb.16064 · Cited by 12 · see citing works

Forest Canopy Water Content Monitoring Using Radiative Transfer Models and Machine Learning

Liu, L., Li, S., Yang, W., Wang, X., Luo, X., Ran, P., & Zhang, H. (2023) · Forests · doi:10.3390/f14071418 · Cited by 11 · see citing works

Tracking effects of extreme drought on coniferous forests from space using dynamic habitat indices

Safaei, M., Kleinebecker, T., Weis, M., & Große‐Stoltenberg, A. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e27864 · Cited by 10 · see citing works

Monitoring functional traits of complex temperate forests using Sentinel-2 data during a severe drought period

Savinelli, B., Panigada, C., Tagliabue, G., Vignali, L., Gentili, R., Fassnacht, F. E., Padoa‐Schioppa, E., & Rossini, M. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.177428 · Cited by 9 · see citing works

Tree vitality predicts plant-pathogenic fungal communities in beech forest canopies

Duan, Y., Siegenthaler, A., Skidmore, A. K., Abdullah, H. J., Chariton, A. A., Laros, I., Rousseau, M., & de Groot, G. A. (2025) · Forest Ecology and Management · doi:10.1016/j.foreco.2025.122588 · Cited by 6 · see citing works

Seasonal increases in global dryland gross primary production are modulated by root soil moisture and temperature

Lan, L., Munson, S. M., Yu, K., Fang, Z., Chen, X., Zhao, W., Sun, S., Wang, Z., He, F., & Yuan, L. (2025) · Global and Planetary Change · doi:10.1016/j.gloplacha.2025.105133 · Cited by 6 · see citing works

Canopy water content is related to variability in leaf water over time but not across space in an oak savanna ecosystem

Allen, J., Boving, I., Love-Anderegg, L. D., Brodrick, P. G., Chadwick, K. D., Roberts, D. A., & Trugman, A. T. (2026) · Remote Sensing of Environment · doi:10.1016/j.rse.2026.115374 · Cited by 4 · see citing works

Functional Traits From Imaging Spectroscopy Inform Patterns of Forest Mortality During Sierra Nevada Drought

Queally, N., Zheng, T., Ye, Z., Kovach, K. R., Pavlick, R., Shafron, E., Schneider, F., & Townsend, P. A. (2025) · Global Change Biology · doi:10.1111/gcb.70246 · Cited by 4 · see citing works

Analysis of Forest Inventory Data Shows Disparity in Tree Mortality and Resistance in Texas National Forests

Dewez, N. P., Xi, W., Duffie, D. R., Subedi, M. R., Chaudhary, T., Rideout–Hanzak, S., Anoruo, A. O., & Estabrook, T. (2024) · Journal of Forestry · doi:10.1093/jofore/fvad059 · Cited by 4 · see citing works

WATcycle: A software for terrestrial water cycle and budget analysis with case studies on the Amazon and Mississippi Basins

Anjaneyulu, R., Kashyap, P., Xiong, J., & Abhishek, A. (2025) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2025.106656 · Cited by 3 · see citing works

Pre‐Fire Fuel Conditions Are Dominant Drivers of Burn Severity in the 2025 Los Angeles County Fires

Ward-Baranyay, M., Lee, C., Pascolini‐Campbell, M., Sousa, D. J., & Kinoshita, A. M. (2026) · AGU Advances · doi:10.1029/2025av002179 · Cited by 3 · see citing works

A flexible data‐driven approach to co‐producing drought vulnerability assessments

Crausbay, S. D., Hall, K. R., Cross, M. S., Halabisky, M. A., Rangwala, I., Anderson, J., & Schwend, A. (2024) · Ecosphere · doi:10.1002/ecs2.70040 · Cited by 3 · see citing works

Divergence between in situ and satellite-based estimates of forest canopy water content

Kesselring, J., Humphrey, V., Niederberger, M., Feigenwinter, I., Shekhar, A., Buchmann, N., & Damm, A. (2025) · Remote Sensing of Environment · doi:10.1016/j.rse.2025.115097 · Cited by 2 · see citing works

Detecting drought stress from the leaf to the landscape: is canopy structure or leaf desiccation more influential in tree canopy spectral responses to declining water?

Allen, J., Anderegg, L. D. L., Roberts, D. A., & Trugman, A. T. (2026) · New Phytologist · doi:10.1111/nph.71450 · Cited by 1 · see citing works

Forests and woodlands resistant to drought revealed in remotely sensed foliar moisture content using probabilistic modelsPreprint

Kotzur, I., Moore, B. D., Boer, M., Yebra, M., & Youngentob, K. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.10.692240

Drought resistance is greater in montane conifers compared to coastal conifers in northern California

Roletti, G., Sherriff, R. L., Kerhoulas, L. P., Robinson, W., Beckmann, J. J., & van Mantgem, P. J. (2026) · Forest Ecology and Management · doi:10.1016/j.foreco.2026.123744

High ecosystem stability of evergreen broadleaf forests under severe droughts

Huang, K., & Xia, J. (2019) · Global Change Biology · doi:10.1111/gcb.14748 · Cited by 195 · see citing works

Biome-scale heterogeneity in Scots pine drought resilience across EurasiaPreprint

del Castillo, E. M., Torbenson, M. C. A., Reinig, F., Ziaco, E., Serrano‐Notivoli, R., Yue, W., Svoboda, M., Arzac, A., Treml, V., van der Maaten, E., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-8066041/v1

Increasing and widespread vulnerability of intact tropical rainforests to repeated droughts

Tao, S., Chave, J., Frison, P., Toan, T. L., Ciais, P., Fang, J., Wigneron, J., Santoro, M., Yang, H., Li, X., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2116626119 · Cited by 98 · see citing works

Bridging Single‐Tree Processes and Regional‐Scale Patterns to Explain Vegetation Drought Resistance and Resilience in a Sierra Nevada Headwater Catchment

Tucker, A., Dumont, M., Singley, J., Lenssen, N., Callahan, R. P., Marshall, A. M., Jacobsen, L., & Singha, K. (2026) · Journal of Geophysical Research Biogeosciences · doi:10.1029/2025jg009585

Temporal trade-off between gymnosperm resistance and resilience increases forest sensitivity to extreme drought

Li, X., Piao, S. L., Wang, K., Wang, X., Wang, T., Ciais, P., Chen, A., Lian, X., Peng, S., & Peñuelas, J. (2020) · Nature Ecology & Evolution · doi:10.1038/s41559-020-1217-3 · Cited by 322 · see citing works