Impacts Of Global Change On Tree Physiology And...

We human beings need plants for our survival. Everything we eat consists of plants or animals that depend on plants somewhere along the food chain. Plants also form the backbone of natural ecosystems, and they absorb about 30 percent of all the carbon dioxide emitted by humans each year. But as the impacts of climate change worsen, how are higher levels of CO2 in the atmosphere and warmer temperatures affecting the plant world?

Impacts of Global Change on Tree Physiology and...

Researchers that studied hundreds of plant species between 1980 and 2017 found that most unfertilized terrestrial ecosystems are becoming deficient in nutrients, particularly nitrogen. They attributed this decrease in nutrients to global changes, including rising temperatures and CO2 levels.

Plants are also on the move in response to warming temperatures. Species that are adapted to certain climatic conditions are gradually moving north or to higher elevations where it is cooler. In the last several decades, many North American plants have moved approximately 36 feet to higher elevations or 10.5 miles to higher latitudes every 10 years. The Arctic tree line is also moving 131 to 164 feet northward towards the pole each year. New environments may be less hospitable for the species moving into them as there might be less space or more competition for resources. Some species may have nowhere left to move and ultimately, certain species will be disadvantaged by the changes while others will benefit.

Climate change will bring more frequent and severe extreme weather events, including extreme precipitation, wind disturbance, heat waves, and drought. Extreme precipitation events can disturb plant growth, particularly in recently burned forests, and make plants more vulnerable to flooding and soils to erosion. More frequent high winds can stress tree stands.

Many of the studies into the response of plant life to climate change seem to suggest that most plants will be more stressed and less productive in the future. But there are still many unknowns about how the complex interactions between plant physiology and behavior, resource availability and use, shifting plant communities, and other factors will affect overall plant life in the face of climate change.

Simple, thermal-time based phenology models can provide useful insights for predicting the effects of temperature on the phenology of plants, particularly in those species (e.g., cherries) that are weakly sensitive or insensitive to precipitation [6] and to photoperiod [10], [11]. When tested against the historical phenology records of leaf fall, budburst, and flowering, such models can be powerful tools to forecast the impacts of climate change on phenology, and to help develop effective adaptation strategies in agriculture, horticulture, forestry, conservation planning, restoration, and natural resource management.

These cherry blossom festivals of spring are culturally and economically important events, and successful planning requires that the cherry blossoms appear as expected within the festival period. In Japanese culture, cherry blossoms carry great spiritual significance and their blooming has been celebrated with rituals called hanami since the 9th century [13]. In Washington, DC, the National Cherry Blossom Festival commemorates a 1912 gift of 3020 trees from the Mayor Yukio Ozaki of Tokyo as a symbol of the friendship between the United States and Japan [14]. For these reasons, the timing of cherry blossom engenders strong public interest and cultural attentions worldwide. Furthermore, the cultural and economic significance of the flowering cherries has yielded a series of rich, long-term, phenological data sets in many cultures enabling scientists to study tree responses to climate change [15], [16], [17]. In a rapidly changing climate, predicting the flowering dates based solely on past history is likely to become less reliable; hence a more robust predictive model is needed not only for planning purposes of these cultural events but also, perhaps more importantly, for assessing the agricultural and ecological impacts of climate change.

In the present study, we have modified the thermal-time based phenology model developed by Cesarracio et al. [18] and applied it to predict PBD of Yoshino and Kwanzan cherries in the Tidal Basin. We chose to use this model because 1) it has been successfully used with cherries and other temperate tree species that are highly sensitive to winter and spring temperatures in other regions [16], [18], [19], 2) it is a relatively simple but robust, process-oriented model based on physiological knowledge, and 3) it requires minimal input data (i.e., daily maximum and minimum temperatures). The objectives of the study were to 1) test the model performance for predicting PBD of the two cherry cultivars at the Tidal Basin, Washington, DC against historical records and 2) apply the model to forecast future cherry PBD in Washington, DC and the surrounding Mid-Atlantic region based on future climate projections with A1B or A2 emission scenario [7]. Briefly, the A1B scenario represents a future world of rapid economic growth, global population that peaks in mid-century and declines thereafter, and rapid introduction of novel and efficient technologies that are balanced across various energy sources. The A2 scenario assumes a very heterogeneous world with continuously increasing global population and regionally oriented economic growth that is more fragmented and slower than in other storylines [7].

Genetically, Yoshino cherry is thought to be closely related to several varieties in P. serrulata including var. spontanea [21] but the origin of Yoshino cherry (P.yedoensis) is unknown [20]. Phenologically, the three distinct sets of parameter estimates identified between our study and Jung et al. [19] suggest there are likely to be inherent differences in the physiology associated with dormancy release and thermal induction of flowering in these cultivars. The parameter estimates for the Yoshino cherry indicate that it is likely to be more sensitive to warmer temperatures during the spring than spontanea with a lower base temperature (Tc), a lower chilling requirement (Rc), and a greater heating (i.e., forcing; anti-chilling) requirement (Rh). The early-flowering cherry cultivars have been thought to be more responsive to a changing climate than late-flowering cultivars, potentially affecting gene flow and pollination between genotypes [36]. In addition to the potential genotypic differences, different regional weather patterns could also create variable responses even for closely related cultivars. The influence of the Atlantic Ocean on the Mid-Atlantic States of the U.S. and that of the northern Pacific on Korea are likely to create different weather patterns. Such differences could alter the dormancy and flowering habits of the trees acclimated to each region even for identical cultivars. In our work, PBD are estimated to occur earlier in the coastal areas than in the inland areas; also expected is that the change in the mean PBD over time would be greater in the coastal areas compared to the inland. This is similar to the findings in South Korea, where the dormancy release of cherry trees in the southern coast was predicted to be more irregular compared to the inland because of a further increase in temperature along the coastal areas in the winter [37]. Overall, the model predictions suggest that dormancy release of these cultivars in the region may be substantially delayed whereas the floral development after dormancy release is accelerated in early spring by the end of the century; this may result in unpredictable blooming habits and abnormal floral development of the cherry trees.

We determined that the model performance was reasonable after testing it against the multiple independent datasets that had not been used for model calibration (Fig. 3). Ideally, testing the model against multiple long-term PBD data sets from multiple locations would have furthered our confidence in applying the model towards the future scenarios. To our best knowledge, after an extensive search for additional data sets across the U.S., we have learned that long-term, reliable PBD data availability is limited to the Tidal Basin in the Mid-Atlantic region. Nonetheless, additional recent PBD datasets from Seattle, WA and from Project BudBurst improved our confidence in applying the model towards the future for wider geographic areas. Overall, given the challenges in data availability, potential genetic discrepancies, and climatic differences between locations, the model has successfully accounted for the variability in PBD of Yoshino and Kwanzan cherry trees in the Tidal Basin and other locations. It produced promising performance results that allowed us to apply to the future scenarios and assess the impacts of climate change on tree phenology for an iconic species in the region.

The accuracy of phenology records depends strongly on the observer and the procedure used. Variability in the ecology and age of the trees being observed, microclimates surrounding the trees, and the subjectivity of the observer can all lead to errors in phenological records. Therefore, in order to improve the ability to test and apply the predictive phenology models, a standardized observation method of species-specific phenophases for institutions and scientists observing phenology are critical to create reliable, long-term data sets from multiple locations. As evidenced in our current study, research approaches to engage citizen scientists are likely to be an effective method for achieving this goal, provided well-defined phenophase standards are available for the species of interest (e.g., Project BudBurst, Floral Report Card Project, and USA National Phenology Network) [44], [45]. More independent phenological data on the budburst and leaf fall as well as the PBD of cherry trees for multiple locations and cultivars will greatly aid in improving the model and its usefulness for predicting the impacts of climate change on this temperate tree phenology. 041b061a72