Field evaluations of the CropManage decision support tool for improving irrigation and nutrient use of cool season vegetables in California

Vegetable growers on the central coast of California are under regulatory pressure to reduce nitrate loading to ground and surface water supplies. California also implemented legislation that limits agricultural pumping in regions such as the central coast where the aquifers have been over-extracted for crop irrigation. Growers could potentially use less N fertilizer, address water quality concerns, and conserve water by improving water management and matching nitrogen applications to the N uptake pattern of their crops. Two tools available to growers, the soil nitrate quick test (SNQT) and reference evapotranspiration (ETo) data have been previously shown to improve the management of water and fertilizer nitrogen in vegetable production systems. However, adoption of these practices has not been widespread. These techniques can be time consuming to use, and vegetable growers often have many crops to manage. To address such time constraints, the CropManage online application (cropmanage.ucanr.edu) was developed to facilitate implementation of the SNQT and evapotranspiration-based irrigation scheduling. CropManage additionally helps growers account for plant available N from background levels of nitrate in irrigation water. Trials were conducted in commercial vegetable fields in the Salinas Valley during 2012–2019 to evaluate CropManage fertilizer and irrigation recommendations relative to the grower practice. Results demonstrated that in many cases fertilizer or irrigation reductions could be attained by following CropManage recommendations without jeopardizing yield. In lettuce, the total fertilizer N applied under CropManage guidance was reduced by an average of 31 % compared to the grower standard practice. Lettuce yield within the CropManage treatment averaged 107 % of the grower practice. CropManage guidance in broccoli reduced N and applied water by 24 % and 27 %, respectively, compared to the grower standard practice, while average yield was similar between treatments. Management tools such as CropManage can support operational efficiencies and compliance with regulatory targets designed to improve groundwater quality

Implications of Climate-Driven Fallowing for Ecological Connectivity of Species At Risk

Context. Climate change and agricultural intensification are modifying the configuration of natural lands within agricultural landscapes, further impacting species’ ability to move freely between remaining natural areas. These working landscapes have inherently high opportunity costs, making the establishment of additional permanent reserves for species movement unlikely. Objectives. Here we explore the potential for opportunistic and dynamic conservation reserves, in the form of temporary fallowed croplands, to increase connectivity in competing land use regions. Methods. We evaluate the potential for fallowed lands to facilitate habitat connectivity for at-risk species in the San Joaquin Valley (SJV), an intensive agricultural landscape in California. We perform landscape connectivity analyses to examine how historic drought-induced fallowing from 2011 to 2017 in the SJV region impacted connectivity within Kern County for the endangered, endemic San Joaquin kit fox (Vulpes macrotis mutica). Results. We found that an increase in temporary fallowing from 2011 to 2015/2017 in Kern County likely increased habitat connectivity for the kit fox. This finding was represented by reductions in average Cost-Weighted Distances (CWD), Effective Resistances, and CWD-to-Least Cost Path Ratios between core habitat areas, indicating that cumulative costs incurred by kit foxes travelling between primary habitats decreased. Conclusions. Our findings highlight that strategic and cooperative, yet temporary, conservation actions have the potential to reduce the conflict between biodiversity preservation and agricultural production in working landscapes while increasing landscape connectivity. Fallowing-based, agri-environmental schemes could help working areas meet statewide groundwater management policy targets while improving species’ mobility in the face of climate change

Speak like a wo(man) : a corpus linguistic and discourse analysis of gendered speech

Traditionally, studies in gender linguistics have been qualitative anecdotes which view gender on a dichotomous plane. Using normative research participants and small amounts of data, researchers in gender linguistics have made an array of assumptions about how men and women speak. Women are commonly thought of as being cooperative speakers while men are typically thought of as operating out of a power hierarchy. The study conducted in this thesis tests these assumptions by applying qualitative, corpus, and discourse analyses. A corpus of transcribed spoken conversational speech was compiled and measured for various linguistic and discourse elements which have historically been touted as paradigms of gendered speech. Using a demographically diverse sample of 185 participants, 50 hours of conversation were recorded and transcribed. From this corpus, various language elements such as theme, thematic conveyors, turn-taking, laughter, referencing, expletives, adjectives, hedges, `polite speech', and verbs were identified and measured for frequency of use by gender and by sexuality. The results from this study indicate that women and men do indeed use language with idiosyncratic linguistic and discourse features and at significantly different frequencies of use. When language use based upon sexuality was examined, the results indicate that queer men speak using a distinct language variety from women and heterosexual men. Thus, the planar dichotomy of gender and language does not appear to be a valid view due to the sharp divergence from the binary by a third group based upon sexuality. The results further demonstrate that using corpus analysis is an effective and optimal approach for analyzing some aspects of language use. The quantitative composition of corpus data has allowed research, to dispel and support many assumptions made by anecdotal observation. It is my hope that the results drawn from this study inspire other researchers to use corpus-based methodology in examining gender, sexuality, and language

Assessing the utility of remote sensing data to accurately estimate changes in groundwater storage

Accurate and timely estimates of groundwater storage changes are critical to the sustainable management of aquifers worldwide, but are hindered by the lack of in-situ groundwater measurements in most regions. Hydrologic remote sensing measurements provide a potential pathway to quantify groundwater storage changes by closing the water balance, but the degree to which remote sensing data can accurately estimate groundwater storage changes is unclear. In this study, we quantified groundwater storage changes in California\u27s Central Valley at two spatial scales for the period 2002 through 2020 using remote sensing data and an ensemble water balance method. To evaluate performance, we compared estimates of groundwater storage changes to three independent estimates: GRACE satellite data, groundwater wells and a groundwater flow model. Results suggest evapotranspiration has the highest uncertainty among water balance components, while precipitation has the lowest. We found that remote sensing-based groundwater storage estimates correlated well with independent estimates; annual trends during droughts fall within 15% of trends calculated using wells and groundwater models within the Central Valley. Remote sensing-based estimates also reliably estimated the long-term trend, seasonality, and rate of groundwater depletion during major drought events. Additionally, our study suggests that the proposed method estimate changes in groundwater at sub-annual latencies, which is not currently possible using other methods. The findings have implications for improving the understanding of aquifer dynamics and can inform regional water managers about the status of groundwater systems during droughts

Forecasting Distributional Responses of Limber Pine to Climate Change at Management-Relevant Scales in Rocky Mountain National Park

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species\u27 physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m2) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species\u27 climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management

NASA Global Daily Downscaled Projections, CMIP6

We describe the latest version of the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). The archive contains downscaled historical and future projections for 1950-2100 based on output from Phase 6 of the Climate Model Intercomparison Project (CMIP6). The downscaled products were produced using a daily variant of the monthly bias correction/spatial disaggregation (BCSD) method and are at 1/4-degree horizontal resolution. Currently, eight variables from five CMIP6 experiments (historical, SSP126, SSP245, SSP370, and SSP585) are provided as procurable from thirty-five global climate models

IrrMapper: A Machine Learning Approach for High Resolution Mapping of Irrigated Agriculture Across the Western U.S.

High frequency and spatially explicit irrigated land maps are important for understanding the patterns and impacts of consumptive water use by agriculture. We built annual, 30 m resolution irrigation maps using Google Earth Engine for the years 1986–2018 for 11 western states within the conterminous U.S. Our map classifies lands into four classes: irrigated agriculture, dryland agriculture, uncultivated land, and wetlands. We built an extensive geospatial database of land cover from each class, including over 50,000 human-verified irrigated fields, 38,000 dryland fields, and over 500,000 km2 of uncultivated lands. We used 60,000 point samples from 28 years to extract Landsat satellite imagery, as well as climate, meteorology, and terrain data to train a Random Forest classifier. Using a spatially independent validation dataset of 40,000 points, we found our classifier has an overall binary classification (irrigated vs. unirrigated) accuracy of 97.8%, and a four-class overall accuracy of 90.8%. We compared our results to Census of Agriculture irrigation estimates over the seven years of available data and found good overall agreement between the 2832 county-level estimates (r2 = 0.90), and high agreement when estimates are aggregated to the state level (r2 = 0.94). We analyzed trends over the 33-year study period, finding an increase of 15% (15,000 km2) in irrigated area in our study region. We found notable decreases in irrigated area in developing urban areas and in the southern Central Valley of California and increases in the plains of eastern Colorado, the Columbia River Basin, the Snake River Plain, and northern California

Mapping Past, Present, and Future Climatic Suitability for Invasive Aedes Aegypti and Aedes Albopictus in the United States: A Process-Based Modeling Approach Using CMIP5 Downscaled Climate Scenarios

The ongoing spread of the mosquitoes, Aedes aegypti and Aedes albopictus, in the continental United States leaves new areas at risk for local transmission of dengue, chikungunya, and Zika viruses. All three viruses have caused major disease outbreaks in the Americas with infected travelers returning regularly to the U.S. The expanding range of these mosquitoes raises questions about whether recent spread has been enabled by climate change or other anthropogenic influences. In this analysis, we used downscaled climate scenarios from the NASA Earth Exchange Global Daily Downscaled Projections (NEX GDDP) dataset to model Ae. aegypti and Ae. albopictus population growth rates across the United States. We used a stage-structured matrix population model to understand past and present climatic suitability for these vectors, and to project future suitability under CMIP5 climate change scenarios. Our results indicate that much of the southern U.S. is suitable for both Ae. aegypti and Ae. albopictus year-round. In addition, a large proportion of the U.S. is seasonally suitable for mosquito population growth, creating the potential for periodic incursions into new areas. Changes in climatic suitability in recent decades for Ae. aegypti and Ae. albopictus have occurred already in many regions of the U.S., and model projections of future climate suggest that climate change will continue to reshape the range of Ae. aegypti and Ae. albopictus in the U.S., and potentially the risk of the viruses they transmit

Development of a Complete Landsat Evapotranspiration and Energy Balance Archive to Support Agricultural Consumptive Water Use Reporting and Prediction in the Central Valley, CA

Mapping evapotranspiration (ET) from agricultural areas in Californias Central Valley is critical for understanding historical consumptive use of surface and groundwater. In addition, long histories of ET maps provide valuable training information for predictive studies of surface and groundwater demands. During times of drought, groundwater is commonly pumped to supplement reduced surface water supplies in the Central Valley. Due to the lack of extensive groundwater pumping records, mapping consumptive use using satellite imagery is an efficient and robust way for estimating agricultural consumptive use and assessing drought impacts. To this end, we have developed and implemented an algorithm for automated calibration of the METRIC remotely sensed surface energy balance model on NASAs Earth Exchange (NEX) to estimate ET at the field scale. Using automated calibration techniques on the NEX has allowed for the creation of spatially explicit historical ET estimates for the Landsat archive dating from 1984 to the near present. Further, our use of spatial NLDAS and CIMIS weather data, and spatial soil water balance simulations within the NEX METRIC workflow, has helped overcome challenges of time integration between satellite image dates. This historical and near present time archive of agricultural water consumption for the Central Valley will be an extremely useful dataset for water use and drought impact reporting, and predictive analyses of groundwater demands