Performing Department
(N/A)
Non Technical Summary
This project supports the mission of the Agricultural Experiment Station by addressing the Hatch Act areas of (i) soil and water conservation and use, (ii) plant and animal production, protection, and health, (iii) processing, distribution, safety, marketing, and utilization of food and agricultural products, and (iv) sustainable agriculture.We will analyze the effects of weather, climate change, adaptation, and natural resource scarcity through the lens of Californian irrigated agriculture. We begin by exploring the effect of weather and climate change on specialty crop production, highly relevant to the topic area of plant production. Previous work in this literature focuses almost exclusively on the effect on quantity. But quality matters - upstream buyers value quality and so farmers are paid depending on the quality of their production. We will quantify the effect of weather and climate change on the revenue of specialty crop growers through both quantity and quality pathways. We will also measure the effects on post-harvest losses, which relates to the topic area on processing and distribution of food and agricultural products.Our analysis on specialty crops benefits from active collaboration with industry partners. We use observational data on quality, yield, price, and grower practices for thousands of fields in California. Thanks to this uniquely detailed data, we are able uncover common pitfalls that bias most estimates of climate change impacts.Against a backdrop of extreme drought, heat waves, and a changing climate, climate-smart practices are critical to improving resilience in the agriculture sector. We also ask how all irrigated crop producers in California engage with climate-smart practices. We explore how growers' characteristics, decisions, and technology adoption affect their climate resilience. This work strongly relates to the topic areas on sustainable agriculture and soil and water conservation and use.
Animal Health Component
0%
Research Effort Categories
Basic
100%
Applied
(N/A)
Developmental
(N/A)
Goals / Objectives
We will analyze the effects of weather, climate change, adaptation, and natural resource scarcity through the lens of Californian irrigated agriculture.Our first objective is to explore the effect of weather and climate change on the revenue of irrigated specialty crop producers. While most agricultural producers are paid a price that depends on the quality of their product, prior work has largely ignored the impact of weather on quality. Failing to account for quality may lead to biased estimates of the impact of weather and climate change on farm income. We explore how growers' characteristics and decisions change their resilience to the effects of extreme weather. We study this question through the lens of California's $1 billion processing tomato industry, which produces nearly one third of the world's processing tomatoes.Our second objective is to explore econometric pitfalls that may bias most estimates of the effect of weather and climate on yield and quality in many settings. We simulate (a) selection bias from the common practice of selectively screening out low-quality products, (b) aggregation bias in county-level results from spatial averaging of weather, and (c) post-harvest bias, the effect of omitting a distinct and potentially important channel through which weather and climate change affect agricultural production. By documenting and quantifying these sources of biases, our work highlights the importance for researchers working in other settings to consider possible error in their estimation.The third objective asks how all irrigated crop producers in California engage with climate-smart practices. We will open the "black box" of adaption and quantify the economic consequences of different responses. Moreover, we explore how growers' characteristics, decisions, and technology adoption affect their climate resilience. Novel remotely-sensed data on irrigation activity gives us a unique insight into whether growers use water more efficiently.
Project Methods
Our project brings together data from many public and proprietary sources. We use observational data on quality, yield, price, and grower practices for thousands of fields in California. Gridded, daily weather data is publicly available from PRISM. We use satellite imagery on land use from the USDA's Cropland Data Layer, and new high frequency remotely sensed evapotranspiration data from OpenET to estimate irrigation. We calculate year-to-year variation in water availability using data on surface water allocations from the California Department of Water Resources and the U.S. Bureau of Reclamation.We use frontier techniques to estimate the key causal relationships of interest. Our modeling is at either the grower- or field-level, which allows us to explore grower heterogeneity. We propose to use a machine learning classification algorithm to identify the characteristics of growers who are more resilient to the effects of extreme weather and climate change.