A variety-specific analysis of climate change effects on California winegrapes.

California contains a broad geography over which climate conditions can be suitable for cultivating multiple varieties of winegrapes. However, climate change is projected to make winegrape cultivation more challenging across many of California's winegrowing regions. In order to understand the potential effects of climate change on winegrapes, this study models variety-specific phenology for six winegrape varieties and quantifies the change in phenology and viticulturally-important agroclimate metrics over 12 of California's American Viticultural Areas (AVAs) by the mid-21st century. Results show more rapid development for winegrapes with earlier budburst, flowering, veraison, and maturation across all varieties and AVAs. Cabernet Sauvignon shows the greatest change in phenology timing, while Chardonnay shows the least change. Likewise, the West Sonoma Coast AVA shows the greatest average change in phenology timing across varieties and development stages and Lodi AVA shows the least. Projected changes in agroclimatic metrics include an additional month of potentially damaging heat days (above 35 °C) in some AVAs, and decreases in frost days. These results have implications for numerous factors related to viticultural production, including water resources management and crop yield and quality, and underscore the need for California winegrape growers to improve their resilience to climate change by adopting strategies such as increasing soil health and water use efficiency and selecting cultivars suited for future climate conditions. By conducting climate effects analyses at the variety-specific and AVA scale, important information is provided to the winegrowing industry at a resolution that can support decision-making towards resilience.

Landscape genetics of a sub-alpine toad: climate change predicted to induce upward range shifts via asymmetrical migration corridors.

Climate change is expected to have a major hydrological impact on the core breeding habitat and migration corridors of many amphibians in the twenty-first century. The Yosemite toad (Anaxyrus canorus) is a species of meadow-specializing amphibian endemic to the high-elevation Sierra Nevada Mountains of California. Despite living entirely on federal lands, it has recently faced severe extirpations, yet our understanding of climatic influences on population connectivity is limited. In this study, we used a previously published double-digest RADseq dataset along with numerous remotely sensed habitat features in a landscape genetics framework to answer two primary questions in Yosemite National Park: (1) Which fine-scale climate, topographic, soil, and vegetation features most facilitate meadow connectivity? (2) How is climate change predicted to influence both the magnitude and net asymmetry of genetic migration? We developed an approach for simultaneously modeling multiple toad migration paths, akin to circuit theory, except raw environmental features can be separately considered. Our workflow identified the most likely migration corridors between meadows and used the unique cubist machine learning approach to fit and forecast environmental models of connectivity. We identified the permuted modeling importance of numerous snowpack-related features, such as runoff and groundwater recharge. Our results highlight the importance of considering phylogeographic structure, and asymmetrical migration in landscape genetics. We predict an upward elevational shift for this already high-elevation species, as measured by the net vector of anticipated genetic movement, and a north-eastward shift in species distribution via the network of genetic migration corridors across the park.

Impacts of large-scale teleconnection indices on chill accumulation for specialty crops in California.

Although the impacts of teleconnection indices on climate metrics such as precipitation and temperature in California have been widely studied, less attention has been given to the impact on integrated climate indices such as chill accumulation. This study investigates the linkages between large-scale teleconnections and winter chill accumulation for specialty crops in California, which may enable more effective and dynamic adaptation to in-season climate variability. Three large-scale teleconnection indices were selected: Oceanic Nino Index (ONI), Pacific-North American teleconnection pattern (PNA), and Pacific Decadal Oscillation (PDO) index to assess their effects on chill accumulation. The Chill Hours Model and Dynamic Model are adopted to calculate chill accumulation in Chill Hours (CH) and Chill Portions (CP) from November to January. Three major crop-producing regions, including the Central Coast, Sacramento Valley, and San Joaquin Valley, are used as the focused regions. Our results suggest CP generally has a stronger response to teleconnection patterns than CH in California. The correlations between chill accumulation and teleconnections are generally weaker during the summer than other seasons, and significant correlation can be observed 2-10 months before the start of the chill accumulation period. Among the three teleconnection indices, ONI is most weakly correlated to chill accumulation in focused regions, while PDO shows the strongest positive correlation and explains up to 39% variability of CP. PNA presents the most widespread negative correlation with chill accumulation. When aggregated to different teleconnection modes, +3.6 above-average CP is expected during ONI positive mode; +2.3 above-average CP is expected during PDO positive mode, while +2.1 above-average CP is expected during PNA negative mode. This study provides insights on early-season chill prediction and feasible management and adaptation strategies, and the methodology presented here can be used to develop decision support tools of risk control for agricultural producers and policymakers.

Extreme heat effects on perennial crops and strategies for sustaining future production.

Extreme heat events will challenge agricultural production and raise the risk of food insecurity. California is the largest agricultural producer in the United States, and climate change and extreme heat may significantly affect the state's food production. This paper provides a summary of the current literature on crop responses to extreme heat, with a focus on perennial agriculture in California. We highlight contemporary trends and future projections in heat extremes, and the range of plant responses to extreme heat exposure, noting the variability in plant tolerance and response across season, crop, and cultivar. We also review practices employed to mitigate heat damage and the capacity for those practices to serve as adaptation options in a warmer and drier future. Finally, we discuss current and future research directions aimed at increasing the adaptive capacity of perennial agriculture to the increased heat exposure anticipated with climate change. Collectively, the literature reviewed makes clear the need to understand crop responses and tolerances to heat within the context of climate change and climate extremes in order to sustain crop production, preserve agricultural communities, and bolster food security at local, national, and global scales.

Pleistocene glacial cycles drove lineage diversification and fusion in the Yosemite toad (Anaxyrus canorus).

Species endemic to alpine environments can evolve via steep ecological selection gradients between lowland and upland environments. Additionally, many alpine environments have faced repeated glacial episodes over the past two million years, fracturing these endemics into isolated populations. In this "glacial pulse" model of alpine diversification, cycles of allopatry and ecologically divergent glacial refugia play a role in generating biodiversity, including novel admixed ("fused") lineages. We tested for patterns of glacial pulse lineage diversification in the Yosemite toad (Anaxyrus [Bufo] canorus), an alpine endemic tied to glacially influenced meadow environments. Using double-digest RADseq on populations densely sampled from a portion of the species range, we identified nine distinct lineages with divergence times ranging from 18 to 724 thousand years ago (ka), coinciding with multiple Sierra Nevada glacial events. Three lineages have admixed origins, and demographic models suggest these fused lineages have persisted throughout past glacial cycles. Directionality indices supported the hypothesis that some lineages recolonized Yosemite from east of the ice sheet, whereas other lineages remained in western refugia. Finally, refugial niche reconstructions suggest that low- and high-elevation lineages have convergently adapted to similar climatic niches. Our results suggest glacial cycles and refugia may be important crucibles of adaptive diversity across deep evolutionary time.

A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada.

We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within "dry" meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in "wet" meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes.

Vegetation response to invasive Tamarix control in southwestern U.S. rivers: a collaborative study including 416 sites.

Most studies assessing vegetation response following control of invasive Tamarix trees along southwestern U.S. rivers have been small in scale (e.g., river reach), or at a regional scale but with poor spatial-temporal replication, and most have not included testing the effects of a now widely used biological control. We monitored plant composition following Tamarix control along hydrologic, soil, and climatic gradients in 244 treated and 172 reference sites across six U.S. states. This represents the largest comprehensive assessment to date on the vegetation response to the four most common Tamarix control treatments. Biocontrol by a defoliating beetle (treatment 1) reduced the abundance of Tamarix less than active removal by mechanically using hand and chain-saws (2), heavy machinery (3) or burning (4). Tamarix abundance also decreased with lower temperatures, higher precipitation, and follow-up treatments for Tamarix resprouting. Native cover generally increased over time in active Tamarix removal sites, however, the increases observed were small and was not consistently increased by active revegetation. Overall, native cover was correlated to permanent stream flow, lower grazing pressure, lower soil salinity and temperatures, and higher precipitation. Species diversity also increased where Tamarix was removed. However, Tamarix treatments, especially those generating the highest disturbance (burning and heavy machinery), also often promoted secondary invasions of exotic forbs. The abundance of hydrophytic species was much lower in treated than in reference sites, suggesting that management of southwestern U.S. rivers has focused too much on weed control, overlooking restoration of fluvial processes that provide habitat for hydrophytic and floodplain vegetation. These results can help inform future management of Tamarix-infested rivers to restore hydrogeomorphic processes, increase native biodiversity and reduce abundance of noxious species.

Detecting the influence of rare stressors on rare species in Yosemite National Park using a novel stratified permutation test.

Statistical models often use observational data to predict phenomena; however, interpreting model terms to understand their influence can be problematic. This issue poses a challenge in species conservation where setting priorities requires estimating influences of potential stressors using observational data. We present a novel approach for inferring influence of a rare stressor on a rare species by blending predictive models with nonparametric permutation tests. We illustrate the approach with two case studies involving rare amphibians in Yosemite National Park, USA. The endangered frog, Rana sierrae, is known to be negatively impacted by non-native fish, while the threatened toad, Anaxyrus canorus, is potentially affected by packstock. Both stressors and amphibians are rare, occurring in ~10% of potential habitat patches. We first predict amphibian occupancy with a statistical model that includes all predictors but the stressor to stratify potential habitat by predicted suitability. A stratified permutation test then evaluates the association between stressor and amphibian, all else equal. Our approach confirms the known negative relationship between fish and R. sierrae, but finds no evidence of a negative relationship between current packstock use and A. canorus breeding. Our statistical approach has potential broad application for deriving understanding (not just prediction) from observational data.

A network extension of species occupancy models in a patchy environment applied to the Yosemite Toad (Anaxyrus canorus).

A central challenge of conservation biology is using limited data to predict rare species occurrence and identify conservation areas that play a disproportionate role in regional persistence. Where species occupy discrete patches in a landscape, such predictions require data about environmental quality of individual patches and the connectivity among high quality patches. We present a novel extension to species occupancy modeling that blends traditional predictions of individual patch environmental quality with network analysis to estimate connectivity characteristics using limited survey data. We demonstrate this approach using environmental and geospatial attributes to predict observed occupancy patterns of the Yosemite toad (Anaxyrus (= Bufo) canorus) across >2,500 meadows in Yosemite National Park (USA). A. canorus, a Federal Proposed Species, breeds in shallow water associated with meadows. Our generalized linear model (GLM) accurately predicted ~84% of true presence-absence data on a subset of data withheld for testing. The predicted environmental quality of each meadow was iteratively 'boosted' by the quality of neighbors within dispersal distance. We used this park-wide meadow connectivity network to estimate the relative influence of an individual Meadow's 'environmental quality' versus its 'network quality' to predict: a) clusters of high quality breeding meadows potentially linked by dispersal, b) breeding meadows with high environmental quality that are isolated from other such meadows, c) breeding meadows with lower environmental quality where long-term persistence may critically depend on the network neighborhood, and d) breeding meadows with the biggest impact on park-wide breeding patterns. Combined with targeted data on dispersal, genetics, disease, and other potential stressors, these results can guide designation of core conservation areas for A. canorus in Yosemite National Park.