Climate Commons^™

Evaluation Of Topographic Effect Parameterizations In Weather Research And Forecasting Model Over Complex Mountainous Terrain In Wildfire-Prone Regions, Yonghan Jo, Seung Hee Kim, Yungon Lee, Changki Kim, Jinkyu Hong, Junhong Lee, Keunchang Jang

Institute for ECHO Articles and Research

Recent trends of intense forest fires in the Korean Peninsula have increased concerns about more extreme burning in the future under a warming climate. Accurate and reliable fire weather information has become more critical to reduce the risk of forest-related disasters over complex terrain. In this study, two parameterizations reflecting complex topographic effects were implemented in the Weather Research and Forecasting (WRF) model. The model performance was evaluated over the mountainous region in Gangwon-do, South Korea’s most significant forest area. The simulation results of the wildfire case in 2019 show that subgrid-scale orographic parameterization considerably improves model performance regarding wind …

Climate Constrains The Enhancement Of Co2 Fertilization On Forest Gross Primary Productivity, Xinyuan Wei, Daniel J. Hayes, Christopher R. Schwalm, Joshua B. Fisher, Deborah N. Huntzinger, Lei Ma, Rodrigo Vargas, Nathaniel A. Brunsell

Mathematics, Physics, and Computer Science Faculty Articles and Research

Forest gross primary production (GPP) is influenced by the interplay between climate conditions and atmospheric CO₂ levels, which interact in complex ways, generating both compensating and amplifying effects. In this study, eddy covariance flux measurements from 50 forest ecosystems were integrated with simulations from 14 terrestrial biosphere models to investigate how climate conditions and atmospheric CO₂ concentrations regulate forest GPP. This approach bridges site-level observations with biome-scale model estimates to develop a global understanding. Our findings suggest that in boreal and cold temperate regions, temperature primarily constrains the enhancement of the CO₂ fertilization on forest GPP; however, …

Monitoring Mangrove Dynamics And Evaluating Future Afforestation Potential In The Egyptian Red Sea, Rasha M. Abou Samra, Mansour Almazroui, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Mangrove forests are vital for ecosystem services and coastal management but face stressors from anthropogenic activities and climate change. This study estimates the extent and afforestation potential of mangroves along the Egyptian Red Sea coast from 1984 to 2022 using NDVI derived from Landsat-5 and Sentinel-2 data in Google Earth Engine. Aboveground biomass (AGB), belowground biomass (BGB), carbon (C) stock, and CO₂ sequestration potential were evaluated using Sentinel-2 and elevation data. Future afforestation suitability (2020–2050) under SSP2-4.5 and SSP5-8.5 scenarios was assessed with the MaxEnt model. Mangrove area increased from 0.95 km² in 1984 to 1.46 km^{2 …}

Innovative Soil Classification Approach For Achieving Global Biodiversity Framework Utilizing Integrated Data Fusion Of Emit And Multispectral Satellite Observations: Case Study Of Imam Turki Bin Abdullah Royal Reserve, Kingdom Of Saudi Arabia, Hesham Morgan, Ali Elgendy, Surendra Maharjan, Wenzhao Li, Tamer Ismail, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Muburak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Soil classification is essential for sustainable land management, ecological conservation, and combating desertification, particularly in arid and semi-arid regions. This study integrates hyperspectral data from the Earth Surface Mineral Dust Source Investigation (EMIT) and multispectral imagery from Sentinel-2 to achieve accurate soil classification for the Imam Turki bin Abdullah Royal Reserve (ITBA) in Saudi Arabia. Using advanced Machine Learning (ML) techniques, including Extreme Gradient Boosting (XGBoost), the study highlights the power of data fusion in addressing the limitations of standalone remote sensing methods. The integration of hyperspectral and multispectral data combines the spectral richness of hyperspectral imaging with the spatial …

Predicting Precipitation And Ndvi Utilization Of The Multi-Level Linear Mixed-Effects Model And The Ca-Markov Simulation Model, Fatima Belhaj, Hlila Rachid, Ouallali Abdessalam, Aqil Tariq, Belkendil Abdeldjalil, Beroho Mohamed, Hassan Alzahrani, Hajra Mustafa, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

The current work intends to reconstruct the spatiotemporal evolution of precipitation and the Normalized Differentiate Vegetation Index (NDVI) in the Loukkos watershed and provide scenarios for their recent and future evolution, therefore determining the degree of association. We conducted a study on the time series data of precipitation and NDVI from 1999 to 2019. The NDVI prediction is conducted using the CA-Markov model and the linear mixed-effects multi-level model (LME) with precipitation data from 2019 to 2040. The CA-Markov model was employed to predict the vegetation indices for 2029 and 2040 using 1999, 2009, and 2019 data. The model simulates …

Variation In Thermal Tolerance Plasticity And The Costs Of Heat Exposure In The Estuarine Sea Hare, Phyllaplysia Taylori, Richelle L. Tanner, Rauri C. K. Bowie, Cynthia Y. Wang-Claypool, Jonathan H. Stillman

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Climate change is increasing average temperatures and the frequency and intensity of thermal extremes in coastal marine environments. Organisms in coastal marine habitats are accustomed to environmental fluctuations and possess physiological plasticity that may be advantageous in response to increased occurrence of extremes. To examine whether such plasticity is locally adapted to environmental conditions, we investigated the relationship between genetic diversity and thermal tolerance plasticity in 11 populations of the direct-developing intertidal sea hare, Phyllaplysia taylori, on the western coast of the United States. Using whole-organism metrics of muscle function and metabolic rate and a ddRADseq genomic approach, we …

Increasing Atmospheric Evaporative Demand Across The Tibetan Plateau And Implications For Surface Water Resources, Shiqin Xu, Dennis P. Lettenmaier, Tom R. Mcvicar, Pierre Gentine, Hylke E. Beck, Joshua B. Fisher, Zhongbo Yu, Ningpeng Dong, Akash Koppa, Matthew F. Mccabe

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Tibetan Plateau, known as the “Asian water tower,” is a hotspot for complex hydroclimatic changes. We reveal that the previously decreasing atmospheric evaporative demand (Eo) trend at the end of the 20th century has reversed over the last two decades. Although both wind stilling and solar dimming have persisted, their effects on Eo rates have been overshadowed by increasing air temperatures and decreasing relative humidity, leading to a net rise in Eo for 1980−2015. Using the empirical “top-down” Budyko approach, we estimate that across seven sub-catchments draining the Tibetan Plateau, a 10% increase in annual-averaged …

Scaling Arctic Landscape And Permafrost Features Improves Active Layer Depth Modeling, Wouter Hantson, Daryl Yang, Shawn P. Serbin, Joshua B. Fisher, Daniel J. Hayes

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Tundra ecosystems in the Arctic store up to 40% of global below-ground organic carbon but are exposed to the fastest climate warming on Earth. However, accurately monitoring landscape changes in the Arctic is challenging due to the complex interactions among permafrost, micro-topography, climate, vegetation, and disturbance. This complexity results in high spatiotemporal variability in permafrost distribution and active layer depth (ALD). Moreover, these key tundra processes interact at different scales, and an observational mismatch can limit our understanding of intrinsic connections and dynamics between above and below-ground processes. Consequently, this could limit our ability to model and anticipate how ALD …

Glacial Lakes Outburst Susceptibility And Risk In The Eastern Himalayas Using Analytical Hierarchy Process And Backpropagation Neural Network Models, Sandeep Kumar Mondal, Jyotindra Narayan, Chitesh Sharma, Rishikesh Bharti, Santosha Kumar Dwivedy, Pinaki Roy Chowdhury

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Himalayan cryosphere is dynamic, and changing climate conditions threaten breach of glacial lakes. A number of glacial lake outburst floods (GLOFs) occurred in the Himalayas in the recent past, affecting people and infrastructures. Assessment of high-altitude glacial lakes is required to avoid associated hazards and mitigate the impacts. In this study, we have made an inventory of naturally formed lakes within the Sikkim Himalayas, including Nepal, Bhutan, and China, and discussed the GLOF susceptibility. A total of 399 lakes have been identified, out of which 281 lakes have an areal coverage greater than 0.01 Km2. Monitoring temporal changes shows …

Global Estimates Of The Storage And Transit Time Of Water Through Vegetation, Andrew Felton, Joshua B. Fisher, Koen Hufkens, Adam J. Purdy, Seth A. Spawn-Lee, Lou F. Duloisy, Gregory R. Goldsmith

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The time it takes for water to transit from the ground back to the atmosphere affects weather, climate, biogeochemistry and ecosystem function. The transit time of water through vegetation, defined as the age of water transpiring from vegetation since time of entry, is a particularly understudied aspect of the terrestrial hydrologic cycle. Here we use a synergy of satellite remote sensing measurements over a five-year period to estimate global aboveground vegetation water storage to be on average 484 km³, roughly half of which is stored in Earth’s water-limited savannah, grassland and shrubland ecosystems. We then combine these storage …

Unfolding Cascading Impacts Of Changing South Asia Monsoon On A Hindu Kush Himalayas Basin, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Arshad Ansari, Suraj Tiwari, Roma Thakurathi, Rejoice Thomas, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Study region

Study focus

New hydrological insights for the region

Extraordinary 21st Century Drought In The Po River Basin (Italy), Abel Andrés Ramírez Molina, Glenn Tootle, Giuseppe Formetta, Thomas Piechota, Jiaqi Gong

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Recent research identified 2022 as being the year of lowest seasonal April–May–June–July (AMJJ) observed streamflow for the Po River Basin (PRB) in the past two centuries. Expanding upon this research, we applied filters (2-year to 30-year filters) to the AMJJ observed streamflow and identified the late 20th and 21st century as displaying extreme drought. In this study, we introduce PALEO-RECON, an automated reconstruction tool developed to leverage tree ring-based proxies and streamline regression processes. Using PALEO-RECON, we reconstructed the AMJJ streamflow, applying traditional regression techniques and using a nested approach in which 30-, 40-, and 50-year windows within the ~200-year …

Invasion Stress Mitigates Climate Stress In A Brackish Marsh Amphipod, Lorna E. Haworth, Sarah Nancollas, Susie N. Landa, Anne E. Todgham, Richelle L. Tanner

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

1. Organisms in coastal brackish ecosystems face not only highly variable environmental conditions, but the intensity and stochasticity of these environmental conditions are anticipated to increase due to climate change. While environmental changes are often presented unilaterally as stressors, there are some anthropogenic environmental transformations, such as the introduction of habitat forming plant species, that may mitigate physiological stress imposed by warming. In Suisun Marsh in the California Delta, native plant canopies allow light and heat to penetrate to the understory yet the canopies of the introduced Phragmites australis reed block out sunlight and heat for organisms living below.
2. We set …

Time Series Decomposition Of Land Surface Temperature For Long-Term Trend Forecasting And Impact On Nesting Sea Turtle Habitats In The Arabian Gulf, Sachi Perera, Rommel H. Maneja, Mohamed Allali, Cyril Rakovski, Erik Linstead, Daniele Struppa, Ali Qasem, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Improving land surface temperature (LST) modeling is vital for mitigating climate change effects on various ecosystems and marine habitats such as important sea turtle habitats. Over the past decade, extreme temperatures have likely significantly affected nesting sea turtle habitats in the Arabian Gulf, with predominantly female hatchlings creating an imbalance in the sex ratio. Such shifts have profound implications for these habitats’ long-term survival and conservation management. This study leverages statistical machine learning models to measure ongoing temporal variations in LST. We break down the LST time series into trend, seasonal, and noise components using classical decomposition methods like X11, …

Multi-Temporal Analysis Of Urbanization-Driven Slope And Ecological Impact Using Machine-Learning And Remote Sensing Techniques, Zhang Hao, Muhammad Haseeb, Zheng Xiangtian, Zainab Tahir, Syed Amer Mahmood, Aqil Tariq, Rana Waqar Aslam, M. Abdullah-Al-Wadud, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Rapid urbanization in Lahore, Pakistan, has led to significant ecological and thermal challenges, particularly the intensification of Urban Heat Island (UHI) effects and increased thermal stress as measured by the Urban Thermal Field Variance Index (UTFVI). This study employs a multi-temporal evaluation of Landsat satellite imagery and GIS-based analysis to investigate the Spatio-temporal trends in land-use and land-cover (LULC) changes from 1994 to 2024. We detected substantial changes in urban growth, vegetation cover, and barren areas using supervised classification (Random Forest) methods and remote sensing indices such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), NDBI (Normalized …

Spatial Gap-Filling Of Himawari-8 Hourly Aod Products Using Machine Learning With Model-Based Aod And Meteorological Data: A Focus On The Korean Peninsula, Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, …

Climatological Trends And Effects Of Aerosols And Clouds On Large Solar Parks: Application Examples In Benban (Egypt) And Al Dhafrah (Uae), Harshal Dhake, Panagiotis Kosmopoulos, Antonis Mantakas, Yashwant Kashyap, Hesham El-Askary, Omar Elbadawy

Mathematics, Physics, and Computer Science Faculty Articles and Research

Solar energy production is vastly affected by climatological factors. This study examines the impact of two primary climatological factors, aerosols and clouds, on solar energy production at two of the world’s largest solar parks, Benban and Al Dhafrah Solar Parks, by using Earth observation data. Cloud microphysics were obtained from EUMETSAT, and aerosol data were obtained from the CAMS and assimilated with MODIS data for higher accuracy. The impact of both factors was analysed by computing their trends over the past 20 years. These climatological trends indicated the variations in the change in each of the factors and their resulting …

Bottom-Up Global Change: Stealth Action In A Decentralized World, Art Blaser, Trinity Huynh

Political Science Faculty Articles and Research

The climate justice and disability rights movements reflect a paradigm shift from a top-down approach to policy-making to one that emphasizes local efforts by non-state actors.

Changing Characteristics Of Land Cover, Landscape Pattern And Ecosystem Services In The Bohai Rim Region Of China, Jiaqi Liu, Wei Chen, Hu Ding, Zhanhang Liu, Min Xu, Ramesh P. Singh, Congqiang Liu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Since the Anthropocene, ecosystems have been continuously deteriorating due to global climate change and human intervention. Exploring the changing characteristics of land use/land cover (LULC), landscape pattern and ecosystem service (ES) and their drivers is crucial for regional ecosystem management and sustainable development. Taking the Bohai Rim region of China as an example, we used the land use transfer matrix, landscape pattern index and InVEST model to analyze the changing characteristics of LULC, landscape pattern and six key ESs [crop production (CP), water yield (WY), carbon storage (CS), soil conservation (SC), habitat quality (HQ), landscape aesthetics (LA)] during 2000–2020. Detailed …

Coupling Between Evapotranspiration, Water Use Efficiency, And Evaporative Stress Index Strengthens After Wildfires In New Mexico, Usa, Ryan C. Joshi, Annalise Jensen, Madeleine Pascolini-Campbell, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Aim

Methods

Results …

Examining Wildfire Dynamics Using Ecostress Data With Machine Learning Approaches: The Case Of South-Eastern Australia's Black Summer, Yuanhui Zhu, Shakthi B. Murugesan, Ivone K. Masara, Soe W. Myint, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfires are increasing in risk and prevalence. The most destructive wildfires in decades in Australia occurred in 2019–2020. However, there is still a challenge in developing effective models to understand the likelihood of wildfire spread (susceptibility) and pre-fire vegetation conditions. The recent launch of NASA's ECOSTRESS presents an opportunity to monitor fire dynamics with a high resolution of 70 m by measuring ecosystem stress and drought conditions preceding wildfires. We incorporated ECOSTRESS data, vegetation indices, rainfall, and topographic data as independent variables and fire events as dependent variables into machine learning algorithms applied to the historic Australian wildfires of 2019–2020. …

Carbon Restoration Potential On Global Land Under Water Resource Constraints, Shouzhang Peng, César Terrer, Benjamin Smith, Philippe Ciais, Qinggong Han, Jialan Nan, Joshua B. Fisher, Liang Chen, Lei Deng, Kailiang Yu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ecosystem restoration is a critical nature-based solution to mitigate climate change. However, the carbon sequestration potential of restoration, defined as the maximum achievable carbon storage, has likely been overestimated because previous studies have not adequately accounted for the competition between ecosystem water demands for maximizing carbon sequestration and human water needs. Here we used a comprehensive process-based model combined with extensive land-use data and evaporation recycling accounting for land–atmosphere feedback to estimate the water requirements associated with ecosystem restoration. We found that achieving the carbon sequestration potential of restoration would significantly reduce global water availability per capita by 26%, posing …

Local Hydroclimate Alters Interpretation Of Speleothem Δ18o Records, E. W. Patterson, V. Skiba, A. Wolf, M. L. Griffiths, D. Mcgee, T. N. Bùi, M. X. Trần, T. H. Đinh, Q. Đỗ-Trọng, Gregory R. Goldsmith, V. Ersek, K. R. Johnson

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Oxygen isotopes (δ¹⁸O) are the most commonly utilized speleothem proxy and have provided many foundational records of paleoclimate. Thus, understanding processes affecting speleothem δ¹⁸O is crucial. Yet, prior calcite precipitation (PCP), a process driven by local hydrology, is a widely ignored control of speleothem δ¹⁸O. Here we investigate the effects of PCP on a stalagmite δ¹⁸O record from central Vietnam, spanning 45 – 4 ka. We employ a geochemical model that utilizes speleothem Mg/Ca and cave monitoring data to correct the δ¹⁸O record for PCP effects. The resulting record …

"The Words We Do Not Yet Have." A Creative Inquiry Into Human-Plant Relationships, Maliheh Ghajargar

Art Faculty Articles and Research

Climate change, loss of plant biodiversity, and ocean pollution signal the drastic changes in our ecology that call us to attend to the needs of more than human forms of life on Earth. Sustainable design and HCI research are responding to this call by offering methods and approaches to design more sustainable products and systems and recently, more than human design is building momentum. This agenda seeks to reform traditional design processes by decentering the creative agency of the dominant socio-economical group of humans and foregrounding those of diverse Others. In this paper, I focus on plants as a nonhuman …

Seasonal Dynamics In Land Surface Temperature In Response To Land Use Land Cover Changes Using Google Earth Engine, Lei Feng, Sajjad Hussain, Narcisa G. Pricope, Sana Arshad, Aqil Tariq, Li Feng, Muhammad Mubeen, Rana Waqar Aslam, Mohammed S. Fnais, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Changes in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, …

A Generalized Machine Learning Model For Long-Term Coral Reef Monitoring In The Red Sea, Justin J. Gapper, Surendra Maharjan, Wenzhao Li, Erik Linstead, Surya Prakash Tiwari, Mohamed A. Qurban, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Coral reefs, despite covering less than 0.2 % of the ocean floor, harbor approximately 35 % of all known marine species, making their conservation critical. However, coral bleaching, exacerbated by climate change and phenomena such as El Niño, poses a significant threat to these ecosystems. This study focuses on the Red Sea, proposing a generalized machine learning approach to detect and monitor changes in coral reef cover over an 18-year period (2000–2018). Using Landsat 7 and 8 data, a Support Vector Machine (SVM) classifier was trained on depth-invariant indices (DII) derived from the Gulf of Aqaba and validated against ground …

Linkages Of The 2022 Unprecedented Global Heatwave Events To Triple-Dip La Niña, Sachi Perera, Joshua B. Fisher, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Heatwaves are influenced significantly by El Niño-Southern Oscillation (ENSO), which alters temperature and precipitation patterns throughout the world. Since 2020, we have witnessed a "triple dip" La Niña conditions persisting for three consecutive years resulting in severe weather and climate driven events globally. In this study, we identified the dominant frequency of Niño 3.4 Sea Surface Temperature (SST) signals and correlated them with regions experiencing unprecedented heat waves in 2022, namely, the Indian Ocean, the North Atlantic around England and Spain, and the Mediterranean Sea. The signal's power spectrum and its three highest power components are determined based on the …

Enhancing Sustainable Development Goals Through Future Vapor Pressure Deficit Analysis In The Nile River Basin, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Hani Sewilam, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vapor Pressure Deficit (VPD) is crucial in meteorology and agriculture for understanding plant-environment interactions. Its application as an indicator in agricultural practices notably advances Sustainable Development Goals such as Zero Hunger (SDG 2) and Climate Action (SDG 13). This research focuses on the impact of climate change on agricultural productivity and food security in the Nile River Basin (NRB), emphasizing the role of VPD, temperature, and precipitation. Utilizing Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets from NEX-GDDP-CMIP6, the study analyzes key climatic variables that influence agricultural conditions. The study applies the Mann-Kendall test to evaluate VPD trends from 2000 …

Assessment And Prediction Of Meteorological Drought Using Machine Learning Algorithms And Climate Data, Khalid En-Nagre, Mourad Aqnouy, Ayoub Ouarka, Syed Ali Asad Naqvi, Ismail Bouizrou, Jamal Eddine Stitou El Messari, Aqil Tariq, Walid Soufan, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Monitoring drought in semi-arid regions due to climate change is of paramount importance. This study, conducted in Morocco’s Upper Drâa Basin (UDB), analyzed data spanning from 1980 to 2019, focusing on the calculation of drought indices, specifically the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at multiple timescales (1, 3, 9, 12 months). Trends were assessed using statistical methods such as the Mann-Kendall test and the Sen’s Slope estimator. Four significant machine learning (ML) algorithms, including Random Forest, Voting Regressor, AdaBoost Regressor, and K-Nearest Neighbors Regressor, were evaluated to predict the SPEI values for both three …

The Ecosystem As Super-Organ/Ism, Revisited: Scaling Hydraulics To Forests Under Climate Change, Jeffrey D. Wood, Matteo Detto, Marvin Browne, Nathan J.B. Kraft, Alexandra G. Konings, Joshua B. Fisher, Gregory R. Quetin, Anna T. Trugman, Troy S. Magney, Camila D. Medeiros, Nidhi Vinod, Thomas N. Buckley, Lawren Sack

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO₂) uptake and water vapor loss, important for predicting and managing the future of Earth's ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals, or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for …