July Maximum Temperature Research Articles

Utilizing Machine Learning Framework to Evaluate the Effect of Climate Change on Maize and Soybean Yield

In recent years, climate change patterns and extreme weather events have adversely affected agricultural production and have raised concerns about its effect on crop yields. These changes can affect the crop yield in many ways including the changes in the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days, etc. So, it is important to analyze the effect of climate change on yield variability for a better understanding of its effect on the crops. This study aims to analyze the historical monthly county-level data for the state of Ohio to quantify maize (Zea mays) and soybean (Glycine max) yield temporal variability and to study the impact of proposed climate change scenarios on the yield. Machine learning algorithms were used to model the effect of monthly temperature and precipitation levels on yield variability, and to study the effect of climate change scenarios on yield. In addition, yield prediction models were integrated with proposed climate change scenarios for higher and lower emissions scenarios to predict the maize and soybean yield for the year 2100. To model the effect of weather parameters on temporal yield variability, the Random Forest model outperformed with RMSE of 0.61 Mt/ha and R2 of 0.73 for maize and with RMSE of 0.21 Mt/ha, R2 of 0.64 for soybean crop. Maximum temperature for July which has a negative correlation with yield was found to be the most dominant parameter for maize yield followed by the precipitation in August, July, and June which have a positive correlation with maize yield. Precipitation in August was found to be the most dominant weather parameter for soybean yield followed by maximum temperature in July. Based on the projected average increase in Ohio’s temperature and precipitation levels alone, maize yield was predicted to drop by 13.2% or 18.5% respectively due to lower emissions and higher emissions climate change scenario of Ohio. Similarly, a 6.64% and a 9.63% drop is expected in the soybean yield by the year 2100 for both lower emissions and higher emissions climate change scenarios. In economic terms based on current commodity values, this is an astounding loss of 254.7 to 369.7 million USD for maize and 535.9 – 751.1 million USD for soybean crop to the state of Ohio.

Headwater stream temperature response to forest harvesting: Do lower flows cause greater warming?

AbstractThis study addressed two hypotheses regarding the relationship between stream temperature response to shade removal and streamflow: (a) that temperature response increases as flow declines and (b) that the relationship can be complicated by shifts in dominant streamflow sources and pathways during low‐flow periods. The study was based on a paired‐catchment design in rain‐dominated headwater catchments in the southern Coast Mountains of British Columbia, Canada, and focused on the effect of a 50% thinning treatment on daily maximum temperature in June, July and August for three sites within the harvest treatment. At the two upstream sites, the treatment response exhibited a negative relationship with daily mean streamflow, especially for days with high incident solar radiation. This result suggests that the effectiveness of forest practice rules for protecting cold‐water habitat may be reduced under future climatic conditions characterized by more frequent extended drought. However, stream temperature response at the most downstream site exhibited a pronounced inverted‐U‐shaped relationship with streamflow measured at a weir. It is hypothesized that the response at the most downstream temperature logger was controlled by the existence of a stable, relatively cool inflow just upstream of the logger, which represented an increasing fraction of flow as streamflow generated higher up in the catchment declined through time. There was a lack of convergent surface topography upstream of the logger, and it is hypothesized that localized inflow may have been controlled by the topography of the soil‐till interface and/or originated as hyporheic discharge.

Tree Ring Width Responses of Pinus densiflora and Robinia pseudoacacia to Climate Variation in the Mount Tai Area of Northern China

To effectively combat climate change and put plans in place to enhance the health and quality of forests, research on the connections between long-term climate change and tree ring width is essential. Here, Pinus densiflora Siebold & Zucc. and Robinia pseudoacacia L. in the Mount Tai area were studied. Specifically, their tree ring width characteristics were investigated according to the principles of dendrochronology, based on the analysis of multiyear climate data (1972–2022). The results showed that (1) the variation in tree ring width of Pinus densiflora Siebold & Zucc. generally decreased. Its basal area increment sequence presented a “growth-decline” change process. The trend for Robinia pseudoacacia L. was stability at first and then a reduction. Its basal area increment sequence presented a “growth-stabilization” change process. (2) The standard chronologies of both tree species contained more environmental information than the residual chronologies, rendering the former more appropriate for analysis. (3) The tree ring width of Pinus densiflora Siebold & Zucc. was positively correlated with the mean maximum temperature in February, March, and July, the mean temperature in May, and the mean precipitation in December of the previous year and June of the current year. The tree ring width of Robinia pseudoacacia L. was positively correlated with the mean and maximum temperatures in October of the previous year, the mean maximum temperature in May of the current year, and the mean temperature in July of the current year. This variable was positively correlated with the mean precipitation in November of the previous year and July of the current year but negatively correlated with the mean minimum temperature in November of the previous year and the mean temperature in December of the current year. (4) During 1987–1988, 1994–1995, 2005–2006, and 2018–2019, the tree ring width was restricted by rising temperatures and low precipitation, with variations in tree ring width observed in various hydrological periods. (5) The moisture index, followed by the warmth index, precipitation and temperature, was the primary climate factor determining the tree ring width in both tree species.

Responses of tree growth and intrinsic water-use efficiency of Robinia pseudoacacia to climate factors

We investigated tree growth in Robinia pseudoacacia plantations at Ansai in Shaanxi Province and at Ji-xian in Shanxi Province by comparing the tree-ring width, basal area increase (BAI), δ13C value, intrinsic water-use efficiency (iWUE), and stomatal regulation. We quantified the responses of tree growth and iWUE to climatic factors at each site. The tree-ring width at Ansai and Jixian decreased with stand age, whereas the BAI at Ansai increased, and that at Jixian decreased after the BAI peaked. The δ13C value and iWUE of trees at Jixian were higher than those at Ansai. The iWUE of trees at both sites was similar to the constant intercellular CO2 concentration/atmospheric CO2 concentration (Ci/Ca) scenario, indicating that the Ci of trees was elevated with increasing Ca, while the stomata remained open. The BAI at Ansai was significantly positively correlated with highest temperature in May, relative humidity in June, precipitation in August, relative humidity in September, and standardized precipitation evapotranspiration index (SPEI) in September and October of current year, but negatively correlated with temperature in June. The BAI at Jixian was significantly positively correlated with SPEI in June and July, and lowest temperature in October of current year. The iWUE of trees at Ansai was significantly positively correlated with relative humidity and precipitation in June of the current year, but negatively correlated with minimum temperature in May, relative humidity in June, and temperature and maximum temperature in July of current year. A significant positive correlation between iWUE of trees at Jixian and lowest temperature in June of current year was detected. At the annual scale, the BAI of trees at Ansai was positively correlated with precipitation and SPEI, but no significant relationship was observed for trees at Jixian. However, the iWUE of trees at both sites was significantly affected by precipitation. Path analysis showed that SPEI and minimum temperature had a direct effect on BAI and iWUE of trees at Ansai, whereas precipitation and average temperature indirectly affected BAI and iWUE through SPEI. The highest temperature had a direct effect on tree growth at Jixian, whereas precipitation, minimum temperature, and average temperature had direct effects on iWUE. These results suggested that SPEI was the main climatic factor that affected the growth of R. pseudoacacia, while Ci was an important physiological factor. Our results could provide reference for the protection and management of R. pseudoacacia plantations under climate change.

Occurrence Regionalization of Kiwifruit Brown Spot in Sichuan.

Kiwifruit brown spot caused by Corynespora cassiicola is the most significant fungal disease in Sichuan, resulting in premature defoliation, which had a significant impact on yield and fruit quality. The objective of the study was to determine the occurrence regularity and suitability of kiwifruit brown spot in Sichuan. The occurrence of the disease in the main producing region was continuously monitored, the maximum entropy (MaxEnt) model was used to predict its potential distribution, and the key environmental variables were identified using the jackknife method. The results indicated that kiwifruit brown spot was widely distributed across the entire producing region in Sichuan, predominantly affecting the variety "Hongyang". The incidence (p < 0.01) and disease index (p < 0.05) showed a significant positive correlation with the cultivar, and decreased with the altitude increasing. The average area under the ROC curve (AUC) of 10 replicates was 0.933 ± 0.012, with an accuracy of 84.44% in a field test, confirming the reliability of the predicted results. The highly suitable distribution areas of kiwifruit brown spot were mainly located in the Chengdu and Ya'an regions. The entire Panzhihua region was an unsuitable distribution area, and the entire Pujiang County and Mingshan District were highly suitable distribution areas. The key environmental variables affecting the potential distribution of kiwifruit brown spot included isothermality (24.3-33.7%), minimum temperature in August (16.3-23.6 °C), maximum temperature in July (25.5-31.2 °C), minimum temperature in June (15.6-20.9 °C), precipitation in August (158-430 mm), and average temperature in October (15.6-18.8 °C). This study provides a theoretical basis for the reasonable layout of the cultivar and the precise prevention and control of the disease.

Three Gorges Dam: Potential differential drivers and trend in the spatio-temporal evolution of the change in snail density based on a Bayesian spatial–temporal model and 5-year longitudinal study

BackgroundSnail abundance varies spatially and temporally. Few studies have elucidated the different effects of the determinants affecting snail density between upstream and downstream areas of the Three Gorges Dam (TGD). We therefore investigated the differential drivers of changes in snail density in these areas, as well as the spatial–temporal effects of these changes.MethodsA snail survey was conducted at 200 sites over a 5-year period to monitor dynamic changes in snail abundance within the Yangtze River basin. Data on corresponding variables that might affect snail abundance, such as meteorology, vegetation, terrain and economy, were collected from multiple data sources. A Bayesian spatial–temporal modeling framework was constructed to explore the differential determinants driving the change in snail density and the spatial–temporal effects of the change.ResultsVolatility in snail density was unambiguously detected in the downstream area of the TGD, while a small increment in volatility was detected in the upstream area. Regarding the downstream area of the TGD, snail density was positively associated with the average minimum temperature in January of the same year, the annual Normalized Difference Vegetation Index (NDVI) of the previous year and the second, third and fourth quartile, respectively, of average annual relative humidity of the previous year. Snail density was negatively associated with the average maximum temperature in July of the previous year and annual nighttime light of the previous year. An approximately inverted “U” curve of relative risk was detected among sites with a greater average annual ground surface temperature in the previous year. Regarding the upstream area, snail density was positively associated with NDVI and with the second, third and fourth quartile, respectively, of total precipitation of the previous year. Snail density was negatively associated with slope.ConclusionsThis study demonstrated a rebound in snail density between 2015 and 2019. In particular, temperature, humidity, vegetation and human activity were the main drivers affecting snail abundance in the downstream area of the TGD, while precipitation, slope and vegetation were the main drivers affecting snail abundance in the upstream area. These findings can assist authorities to develop and perform more precise strategies for surveys and control of snail populations.Graphical

Combining historical agricultural and climate datasets sheds new light on early 20th century barley performance

AbstractBarley (Hordeum vulgare ssp. vulgare) is cultivated globally across a wide range of environments, both in highly productive agricultural systems and in subsistence agriculture and provides valuable feedstock for the animal feed and malting industries. However, as the climate changes there is an urgent need to identify adapted barley varieties that will consistently yield highly under increased environmental stresses. Our ability to predict future local climates is only as good as the skill of the climate model, however we can look back over 100 years with much greater certainty. Historical weather datasets are an excellent resource for identifying causes of historical yield variability. In this research we combined recently digitised historical weather data from the early 20th century with published Irish spring barley trials data for two heritage varieties: Archer and Goldthorpe, following an analysis first published by Student in 1923. Using linear mixed models, we show that interannual variation in observed spring barley yields can be partially explained by recorded weather variability, in particular July maximum temperature and rainfall, and August maximum temperature. We find that while Archer largely yields more highly, Goldthorpe is more stable under wetter growing conditions, highlighting the importance of considering growing climate in variety selection. Furthermore, this study demonstrates the benefits of access to historical trials and climatic data and the importance of incorporating climate data in modern day breeding programmes to improve climate resilience of future varieties.

Temporal and Spatial Variation in Vegetation Coverage and Its Response to Climatic Change in Marshes of Sanjiang Plain, China

Sanjiang Plain is the most extensive marsh distribution region in China. Marshes in this region can protect biodiversity, regulate climate, and provide habitats for wild animals and plants. The normalized difference vegetation index (NDVI) is a crucial indicator of vegetation coverage, which may reflect ecosystem structure and functional features. Clarifying the spatiotemporal change of marsh coverage and its climatic drivers is vital for observing and predicting vegetation change in Sanjiang Plain. Using meteorological dataand MODIS NDVI data from 2000 to 2020, we analyzed the spatiotemporal variation in marsh vegetation coverage and climatic change effects in Sanjiang Plain. We found that the growing season vegetation NDVI of marsh increased significantly at a rate of 0.011/decade, indicating that the marsh vegetation growth has obviously improved during the past 21 years. Furthermore, we found that the increase of minimum (Tmin) and maximum (Tmax) temperature in July can significantly promote the marsh plant growth, and increasing nighttime Tmin has a stronger impact on promoting the growth than increasing daytime Tmax in this month. In addition, the increase of daytime Tmax in August can promote the marsh vegetation growth, whereas the increasing precipitation in August was unfavorable for the growth in Sanjiang Plain.

Distribution patterns and vulnerability of stoneflies (Plecoptera: Insecta) in South Korean streams with conservation perspectives

Biodiversity loss and conservation are major issues at global and regional scales. Plecopteran species have limited distribution areas and are vulnerable to environmental changes. In this study, we evaluated the distribution patterns and environmental characteristics of plecopteran assemblages in South Korean streams to consider the conservation of plecopteran diversity. We used plecopteran assemblage data with environmental data including 32 environmental variables in six categories (geography, meteorology, land use, substrate composition, hydrology, and water quality) surveyed at 412 sampling sites distributed on a nationwide scale in South Korean streams. Self-organizing map classified sampling sites into seven clusters according to the similarities of assemblages. Non-metric multidimensional scaling (NMDS) was used to characterize the relationship between assemblages and abiotic environmental variables. The abundance of 32 plecopteran taxa recorded in the dataset displayed a positive relationship with the number of their occurrence sites, and most species, including the dominant ones, had low abundances in limited distribution areas. More than 78% (25 out of 32) of the recorded plecopteran species were listed in the Korean Red List of Threatened Species, including 17 taxa in the least concern category. The NMDS results presented the habitat preference of species, and the major influential factors from six environmental categories were elevation, maximum temperature in July, proportion of forest in land-use type, proportion of cobbles in substrate, proportion of riffle in flow condition, and turbidity in physicochemical water quality. The results revealed that plecopteran species were diverse and abundant in cold and undisturbed running water on rocky substrates near mountain forests. The dominant species generally displayed similar habitat conditions. However, their habitat preferences varied depending on the species, with different sensitivities and responses to temperature and hydrological flow conditions. Finally, our results revealed that the plecopteran species in South Korea are mostly vulnerable and endangered, and extensive protection policies covering the stream channel and the surrounding areas are required to preserve their biodiversity.

Body size variation in a modern collection of mountain gazelle (Gazella gazella) skeletons

Two-dimensional measurements of skeletal elements are important zooarchaeological tools that not only provide crucial information about the sex and age of an animal, but on past environmental conditions and human-animal interactions as well. The causes of animal body size variation are many and thus problems of equifinality make it difficult to interpret archaeological measurement data. Here, we explore the sources of body size variation in a modern skeletal collection of mountain gazelle (Gazella gazella) composed of individuals of known sex, age and geographic location. We investigate the relative contribution of sex, age and environmental factors (temperature and precipitation) to variation in the 2D measurements of five commonly preserved skeletal elements (scapula, humerus, second phalanx, tibia and astragalus) to determine which factors are most influential. Overall, sex is the most powerful determinant of gazelle body size, while age has little impact on most elements. Importantly, although the breadth of the trochlea of the distal humerus has often been used to sex archaeological gazelle specimens, this element did not differ statistically for males and females. Maximum July temperature also influenced the distal depth of the tibia and the trochlea of the humerus. This may relate to reduced food availability during the critical period of juvenile growth in areas with hotter summers due to higher rates of evaporation and shorter growing seasons. The absence of a significant relationship between the other climatic variables and body size, and the large amount of variability that these factors could not account for, may relate to the confounding impact of anthropogenic activities. In recent decades human landscape modification and agriculture have impacted the natural scheduling of plant and water resources and gazelle population size.

Last Glacial Maximum environmental conditions at Andøya, northern Norway; evidence for a northern ice-edge ecological “hotspot”

Andøya on the NW coast of Norway is a key site for understanding the Last Glacial Maximum (LGM) in northern Europe. Controversy has arisen concerning the local conditions, especially about the timing and extent of local glacial cover, maximum July temperatures and whether pine and/or spruce could have grown there. We reviewed all existing data and add newly analysed ancient sedimentary DNA (sedaDNA), pollen, macrofossils, geochemistry and stable isotopes from three lake sediment cores from Øvre Æråsvatnet. A total of 23 new dates and age-depth modelling suggests the lake has been ice-free since GI2 (<23.4 cal ka BP) and possibly GS3 (<26.7 cal ka BP). Pinus and Picea sedaDNA was found in all three cores but at such low frequencies that it could not be distinguished from background contamination. LGM samples have an exceptionally high organic matter content, with isotopic values indicating that carbon and nitrogen derive from a marine source. Along with finds of bones of the little auk (Alle alle), this indicates that the lake received guano from an adjacent bird colony. SedaDNA, pollen and macrofossil assemblages were dominated by Poaceae, Brassicaceae and Papaver, but scattered occurrence of species currently restricted to the Low Arctic Tundra Zone (July temperature of 8–9 °C) such as Apiaceae (sedaDNA, 8–9 °C), and Alchemilla alpina (macrofossil, 8–9 °C) were also recorded. The review of >14.7 cal ka BP data recorded 94 vascular plant taxa, of which 38% have a northern limit in Shrub Tundra or more southern vegetation zones. This unusual assemblage likely stems from a combination of proximity to ice-free water in summer, geographical isolation linked with stochastic long-distance dispersal events, and the presence of bird-fertilized habitats. The environmental reconstruction based on all records from the area does not preclude local growth of tree species, as the local climate combined with high nutrient input may have led to periodically suitable environmental ‘hotspot’ conditions.

Improved dendroclimatic calibration using blue intensity in the southern Yukon

In north-western North America, the so-called divergence problem (DP) is expressed in tree ring width (RW) as an unstable temperature signal in recent decades. Maximum latewood density (MXD), from the same region, shows minimal evidence of DP. While MXD is a superior proxy for summer temperatures, there are very few long MXD records from North America. Latewood blue intensity (LWB) measures similar wood properties as MXD, expresses a similar climate response, is much cheaper to generate and thereby could provide the means to profoundly expand the extant network of temperature sensitive tree-ring (TR) chronologies in North America. In this study, LWB is measured from 17 white spruce sites ( Picea glauca) in south-western Yukon to test whether LWB is immune to the temporal calibration instabilities observed in RW. A number of detrending methodologies are examined. The strongest calibration results for both RW and LWB are consistently returned using age-dependent spline (ADS) detrending within the signal-free (SF) framework. RW data calibrate best with June–July maximum temperatures (Tmax), explaining up to 28% variance, but all models fail validation and residual analysis. In comparison, LWB calibrates strongly (explaining 43–51% of May–August Tmax) and validates well. The reconstruction extends to 1337 CE, but uncertainties increase substantially before the early 17th century because of low replication. RW-, MXD- and LWB-based summer temperature reconstructions from the Gulf of Alaska, the Wrangell Mountains and Northern Alaska display good agreement at multi-decadal and higher frequencies, but the Yukon LWB reconstruction appears potentially limited in its expression of centennial-scale variation. While LWB improves dendroclimatic calibration, future work must focus on suitably preserved sub-fossil material to increase replication prior to 1650 CE.

Occurrence Prediction of the Citrus Flatid Planthopper (Metcalfa pruinosa (Say, 1830)) in South Korea Using a Random Forest Model

Invasive species cause a severe impact on existing ecosystems. The citrus flatid planthopper (CFP; Metcalfa pruinosa (Say, 1830)) is an invasive species in many countries. Predicting potential occurrence areas of the species related to environmental conditions is important for effective forest ecosystem management. In this study, we evaluated the occurrence patterns of the CFP and predicted its potential occurrence areas in South Korea using a random forest model for a hazard rating of forests considering meteorological and landscape variables. We obtained the occurrence data of the CFP in South Korea from literature and government documents and extracted seven environmental variables (altitude, slope, distance to road (geographical), annual mean temperature, minimum temperature in January, maximum temperature in July, and annual precipitation (meteorological)) and the proportion of land cover types across seven categories (urban, agriculture, forest, grassland, wetland, barren, and water) at each occurrence site from digital maps using a Geographic Information System. The CFP occurrence areas were mostly located at low altitudes, near roads and urbanized areas. Our prediction model also supported these results. The CFP has a high potential to be distributed over the whole of South Korea, excluding high mountainous areas. Finally, factors related to human activities, such as roads and urbanization, strongly influence the occurrence and dispersal of the CFP. Therefore, we propose that these factors should be considered carefully in monitoring and surveillance programs for the CFP and other invasive species.

Negative impacts of summer heat on Sierra Nevada tree seedlings

AbstractUnderstanding the response of forests to climate change is important for predicting changes in biodiversity and ecosystem services, including carbon storage. Seedlings represent a key demographic stage in these responses, because seedling establishment is necessary for population persistence and spread, and because the conditions allowing seedlings to survive and grow are often more restrictive than those adults can tolerate. However, detailed long‐term data on the responses of individual seedlings to climatic variation are rare. Here, we analyze a decade of seedling growth and survival data collected in 25 long‐term plots located in Sequoia and Yosemite National Parks. The forest types represented range from lower‐elevation mixed conifer, to red fir‐dominated, to high‐elevation western white pine stands. Twelve species, including two oaks and ten conifers, are found across these plots. Survival and transition to larger size classes are modeled within a Bayesian framework as a function of species, size, fire, and various climate variables. We initially expected that precipitation‐related variables would have a strong effect on seedling survival and growth in this Mediterranean‐climate region and that some species might respond positively to higher temperatures if they are adapted to warmer low‐elevation areas or to higher‐than‐average temperatures if they are high‐elevation species whose growing seasons are limited by cold. However, we found that higher July maximum temperature or temperature anomalies were associated with lower survival and growth for most species, while precipitation and snow effects were weaker and more variable. Higher precipitation had a positive effect on survival of most species, but snow effects and precipitation effects on growth could be negative. Given the estimated climate responses, under potential future scenarios of higher summer temperatures and altered precipitation, most species are predicted to have lower survival and reduced growth. This is likely to favor species that have relatively high survival and growth and less negative responses to climatic shift (such as several of the pines) and perhaps lead to a more open forest structure—or potentially transition to non‐forest vegetation types where seedling recruitment does not keep pace with adult mortality.

Exploring invasibility with species distribution modeling: How does fire promote cheatgrass (Bromus tectorum) invasion within lower montane forests?

AbstractAimCheatgrass (Bromus tectorum) is notorious for creating positive feedbacks that facilitate vegetation type conversion within sagebrush steppe ecosystems in the western United States. Similar dynamics may exist in adjacent lower montane forest. However, fire‐forest‐cheatgrass dynamics have not been examined. We used species distribution modeling to answer three questions about fire and invasibility in lower montane forests: (Q1) Does fire create more suitable habitat for cheatgrass? (Q2) If so, which site attributes are altered to increase site suitability? (Q3) Does fire increase connectivity among suitable habitat and enhance spread?LocationShoshone National Forest, Wyoming, USA.MethodsWe measured cheatgrass presence–absence in 93 plots within Interior Douglas‐fir (Pseudotsuga menziesii var. glauca) forests. Random Forests predicted cheatgrass distribution with and without fire using nine site attributes: elevation, slope, aspect, solar radiation, annual precipitation, maximum temperature in July, minimum temperature in January, forest canopy cover and distance to nearest trail or road. Additionally, invasion pathways and spread were mapped using Circuitscape.ResultsCheatgrass distribution was controlled by topographic and climate variables in the absence of fire. In particular, cheatgrass was most likely to occur at low elevation along dry, south‐ and east‐facing slopes. High‐severity fire increased potential cheatgrass distribution when forest canopy cover was reduced to below 30%. This process created new invasion pathways, which enhanced cheatgrass spread when modelled in Circuitscape.Main conclusionsOur study showed that in the absence of fire, drier south‐ and east‐facing slopes at low elevation are most susceptible to cheatgrass invasion. However, high‐severity fire increased the total area susceptible to invasion—allowing cheatgrass to expand into previously unsuitable sites within lower montane forests in the western United States. These results are important for present day management and reflect that integrating responses to disturbance in species distribution models can be critical for making predictions about dynamically changing systems.

Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection.

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30-day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species' distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold-water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid-century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.

Quantile Regression–Based Spatiotemporal Analysis of Extreme Temperature Change in China

In this study, temporal trends and spatial patterns of extreme temperature change are investigated at 352 meteorological stations in China over the period 1956–2013. The temperature series are first examined for evidence of long-range dependence at daily and monthly time scales. At most stations there is evidence of significant long-range dependence. Noncrossing quantile regression has been used for trend analysis of temperature series. For low quantiles of daily mean temperature and monthly minimum value of daily minimum temperature (TNn) in January, there is an increasing trend at most stations. A decrease is also observed in a zone ranging from northeastern China to central China for higher quantiles of daily mean temperature and monthly maximum value of daily maximum temperature (TXx) in July. Changes of the large-scale atmospheric circulation partly explain the trends of temperature extremes. To reveal the spatial pattern of temperature changes, a density-based spatial clustering algorithm is used to cluster the quantile trends of daily temperature series for 19 quantile levels (0.05, 0.1, …, 0.95). Spatial cluster analysis identifies a few large clusters showing different warming patterns in different parts of China. Finally, quantile regression reveals the connections between temperature extremes and two large-scale climate patterns: El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation (AO). The influence of ENSO on cold extremes is significant at most stations, but its influence on warm extremes is only weakly significant. The AO not only affects the cold extremes in northern and eastern China, but also affects warm extremes in northeastern and southern China.

A Surprising Discovery of American Pika Sites in the Northwestern Great Basin

Abstract. Although the American pika (Ochotona princeps) continues to receive attention due to documented declines and range retractions, particularly in the Great Basin, thorough range inventories have yet to be completed in many parts of the region. Here we report on recently discovered populations in northwestern Nevada in areas not suspected to support pika activity under current climate regimes. We describe 238 new locations (“sites”) with evidence of past or current occupancy by pikas which cluster into 31 locales, which we interpret as metapopulations or “demes,” in 15 distinct mountain ranges or geographic areas. We documented twice as many relict sites (sites with evidence of former pika occupancy) as currently occupied sites, a result that supports previous observations of local range retraction and site losses within the pika's range. In the overall site data, median elevation and water year precipitation were higher and minimum and maximum July temperatures were lower for occupied sites than f...

Vulnerability of grain crops and croplands in the Midwest to climatic variability and adaptation strategies

Maize (Zea mays L.) and soybean (Glycine max (L.) Merr.) are the dominant grain crops across the Midwest and are grown on 75% of the arable land with small but economically important crops of wheat (Triticum aestivum L.) and oats (Avena sativa L.) but economically important crops. Historically, there have been variations in annual yields for maize and soybean related to the seasonal weather patterns. Key concerns are the impacts of future climate change on maize and soybean production and their vulnerability to future climate changes. To evaluate these, we analyzed the yield gaps as the difference between the attainable and actual yield at the county level and observed meteorological data to determine which seasonal meteorological variables were dominant in quantifying the actual/attainable yields. July maximum temperatures, August minimum temperatures, and July–August total precipitation were found to be the significant factors affecting the yield gap. These relationships were used to estimate the change in the yield gap through 2100 using both the RCP 4.5 and 8.5 climate scenarios for these variables for selected counties across the Midwest. Yield gaps increased with time for maize across the Midwest with the largest increases in the southern portion of the Corn Belt showing a large north-south gradient in the increase of the yield gap and minimal east-west gradient. Soybean was not as sensitive as maize because the projected temperatures do not exceed optimum temperature ranges for growth and reductions in production that are more sensitive to precipitation changes during the reproductive stages. Adaptation strategies for maize and soybean will require more innovation than simple agronomic management and require the linkage between geneticists, agronomists, and agricultural meteorologists to develop innovative strategies to preserve production in the Midwest.

The relationship between climate and adult body size in redback salamanders (Plethodon cinereus)

Several biogeographic studies of salamanders have described relationships between salamander body size and climate. We specifically selected Plethodon cinereus as a widely distributed species that was well represented in museum collections to investigate the effects of warming climate on adult body size. We found a positive correlation between mean maximum July temperature and body size, and a negative correlation between precipitation of the driest month and body size. Surface‐collected adult P. cinereus were 2.3% larger in warmer counties on the coastal plain compared with cooler counties in the Appalachian Mountains. We compared salamanders collected between 1950 and 1970 versus those collected between 1980 and 2000 and found that body size increased 1.8% in counties on the coastal plain where mean maximum July temperatures had also increased by 0.5–1.2 °C. Warming temperatures alone, however, did not adequately account for the observed size increases, because body size also increased 1.3% in places that experienced less than 0.25 °C warming, but that difference was not statistically significant.