The niche through time: Considering phenology and demographic stages in plant distribution models

D Zurell, NE Zimmermann, P Brun - Journal of Ecology, 2024 - Wiley Online Library
Species distribution models (SDMs) are widely used to infer species–environment
relationships, predict spatial distributions and characterise species' environmental niches …

[HTML][HTML] Global climate-related predictors at kilometer resolution for the past and future

P Brun, NE Zimmermann, C Hari… - Earth System …, 2022 - essd.copernicus.org
A multitude of physical and biological processes on which ecosystems and human societies
depend are governed by the climate, and understanding how these processes are altered …

High-resolution crop yield and water productivity dataset generated using random forest and remote sensing

M Cheng, X Jiao, L Shi, J Penuelas, L Kumar, C Nie… - Scientific data, 2022 - nature.com
Accurate and high-resolution crop yield and crop water productivity (CWP) datasets are
required to understand and predict spatiotemporal variation in agricultural production …

Combining multi-indicators with machine-learning algorithms for maize yield early prediction at the county-level in China

M Cheng, J Penuelas, MF McCabe, C Atzberger… - Agricultural and Forest …, 2022 - Elsevier
The accurate and timely prediction of crop yield at a large scale is important for food security
and the development of agricultural policy. An adaptable and robust method for estimating …

Comprehensive and quantitative analysis of growth characteristics of winter wheat in China based on growing degree days

Y Liu, L Su, Q Wang, J Zhang, Y Shan, M Deng - Advances in agronomy, 2020 - Elsevier
The characteristics of the growth of winter wheat are the basis for determining a reasonable
amount of irrigation water, regulating wheat growth, improving environmental conditions and …

Cumulative effects of climatic factors on terrestrial vegetation growth

Y Wen, X Liu, Q Xin, J Wu, X Xu, F Pei… - Journal of …, 2019 - Wiley Online Library
Extensive studies have focused on instantaneous and time‐lag impacts of climatic factors on
vegetation growth; however, the chronical and accumulative indirect impacts of antecedent …

Corn nitrogen nutrition index prediction improved by integrating genetic, environmental, and management factors with active canopy sensing using machine learning

D Li, Y Miao, CJ Ransom, GM Bean, NR Kitchen… - Remote Sensing, 2022 - mdpi.com
Accurate nitrogen (N) diagnosis early in the growing season across diverse soil, weather,
and management conditions is challenging. Strategies using multi-source data are …

NDVI indicated inter-seasonal non-uniform time-lag responses of terrestrial vegetation growth to daily maximum and minimum temperature

Y Wen, X Liu, J Yang, K Lin, G Du - Global and Planetary Change, 2019 - Elsevier
Climate warming exhibits asymmetric patterns over a diel cycle, with the trend of daily
minimum temperature (Tmin) exceeds that of daily maximum temperature (Tmax), which is …

Evaluation of prediction and forecasting models for evapotranspiration of agricultural lands in the Midwest US

A Talib, AR Desai, J Huang, TJ Griffis, DE Reed… - Journal of …, 2021 - Elsevier
Evapotranspiration (ET) prediction and forecasting play a vital role in improving water use in
agriculturally intensive areas. Metrological and biophysical predictors that drive ET in …

Vulnerability assessment of water resources–Translating a theoretical concept to an operational framework using systems thinking approach in a changing climate …

A Anandhi, N Kannan - Journal of Hydrology, 2018 - Elsevier
Water is an essential natural resource. Among many stressors, altered climate is exerting
pressure on water resource systems, increasing its demand and creating a need for …