skip to main content

Title: Empirical Bayes small area prediction under a zero‐inflated lognormal model with correlated random area effects
; ;
Award ID(s):
Publication Date:
Journal Name:
Biometrical journal
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract The United States of America ranked first in maize export and second in soybean export in the world. Accurate and timely data and information on maize and soybean production in the Contiguous United States (CONUS) are important for food security at the regional and global scales. In this study, we firstly compare the maize and soybean planted area from cropland data layer (CDL) with NASS area statistics over the CONUS during 2008-2018, and evaluate the interannual changes of planted and harvested area based on the two datasets. Secondly, we investigate the relationship between grain production and gross primary productionmore »(GPP) simulated by Vegetation Photosynthesis Model (VPM) at national and county scales. Finally, we evaluate the linear regression models between grain production and cumulated GPPVPM over time at 8-day resolution. We found strong spatial-temporal consistency between CDL and NASS datasets in maize and soybean planted areas. Maize and soybean planted areas increased by mid-2010s, largely driven by markets and international trade. Severe summer drought in 2012 had little impact on soybean planted and harvested area and maize planted area, but substantially reduced maize harvested area. and grain production. Annual county-level GPPVPM had strong linear relationship with NASS grain production for maize and soybean. The Harvest Index, defined as the ratio between grain production and GPPVPM (HIGPP_VPM), ranged from 0.25 (2012) to 0.36 for maize and from 0.13 to 0.15 for soybean. The linear regression models between grain production and cumulated GPPVPM (GPPVPM_CUM) over time at 8-day resolution showed that by the end of July, GPPVPM_CUM accounted for ~90% of variance in maize and soybean grain production, which was approximately two months before farmers started to harvest. This study clearly shows that VPM and GPPVPM data are useful for monitoring and in-season forecasting of maize and soybean grain production in the CONUS.« less
  2. Abstract
    Arctic landscapes are in a state of transition due to changes in climate occurring during both the summer and winter seasons. Scattered observations indicate that beavers (Castor canadensis) have moved from the forest into tundra areas during the last 20 years, likely in response to broader physical and ecosystem changes occurring in Arctic and Boreal regions. The implications of beaver inhabitation in the Arctic and Boreal are unique relative to other ecosystems due to the presence of permafrost and its vulnerability associated with beaver dams and inundation. Our study specifically examines the role of beavers in controlling surface waterMore>>