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At least 739 records · Page 41Linked to original sources

Examining the role of unusually warm Indo‐Pacific sea‐surface temperatures in recent African droughts

Southern Africa (SA) and eastern Africa (EA) experienced a sequence of severe droughts in December–February (SA DJF) 2015–2016, October–December (EA OND) 2016 and March–April–May 2017 (EA MAM). This sequence contributed to severe food insecurity. While climate variability in these regions is very complex, the goal of this study is to analyse the role played by unusually warm Indo–Pacific SSTs, where unusual is defined as a 1‐in‐6 year event. We use observed sea‐surface temperatures (SST) and satellite–gauge rainfall observations, a 20‐member ensemble of Community Atmospheric Model version 5.1 simulations (CAM5), and a 40‐member ensemble of climate change simulations from the Community Earth Systems Model version 1 (CESM1) Large Ensemble Community Project (LENS) to explore climate conditions associated with warm events identified based on eastern and western Pacific SSTs. Our analysis suggests that strong El Niño's may be followed by warm western Pacific SST conditions, which can lead to conditions conducive to successive and potentially predictable droughts in SA DJF, EA OND and EA MAM. We show that different regions of warm SST are related to recent droughts—SA DJF: Niño 3.4; EA OND: western equatorial Pacific (WEP); and EA MAM: western North Pacific (WNP). For DJF and MAM, respectively, the CAM5 model driven with observed SST and the same model driven within a climate change experiment indicate that warmer El Niño's and WNP events produce more intense atmospheric responses, potentially associated with more severe droughts. OND climate seems to be strongly influenced by the Indian Ocean Dipole, which corresponds with some WEP events. Given global warming, we suggest that the extreme Niño 3.4 and west Pacific SST events responsible for 2015–2017 droughts are likely to reoccur, thus humanitarian agencies should prepare to predict and respond to multi‐year drought and substantial food insecurity in SA and EA.

Journal of the Royal Meteorological Society↗

Effects of variations in recharge on groundwater quality

The predominant regional effect of recharge on municipal groundwater quality in Kansas is the dilution of mineralized water in aquifers with relatively shallow water tables. The individual dissolved constituents contributing most to the water-quality variations are sulfate and chloride, and the calcium and sodium accompanying them, which are derived from the dissolution of evaporite minerals within the aquifer or from saline formation water in bedrock underlying the aquifer. The relationship between recharge and groundwater-quality variation can be quantified by associating certain climatic indices, especially the Palmer Drought Index, with quality observations. The response time of the maximum water-quality change relative to the occurrence of drought or substantial recharge ranges from a month to 3 years depending on the aquifer characteristics, and is generally proportional to the saturated thickness and specific yield. The response time is also affected by discharge to and recharge from nearby streams and by the well construction, particularly the placement of the screened interval, and pumping stress.

Journal of Hydrology↗

Climatic variation and the distribution of an amphibian polyploid complex

1. The establishment of polyploid populations involves the persistence and growth of the polyploid in the presence of the progenitor species. Although there have been a number of animal polyploid species documented, relatively few inquiries have been made into the large-scale mechanisms of polyploid establishment in animal groups. Herein we investigate the influence of regional climatic conditions on the distributional patterns of a diploid-tetraploid species pair of gray treefrogs, Hyla chrysoscelis and H. versicolor (Anura: Hylidae) in the mid-Atlantic region of eastern North America. 2. Calling surveys at breeding sites were used to document the distribution of each species. Twelve climatic models and one elevation model were generated to predict climatic and elevation values for gray treefrog breeding sites. A canonical analysis of discriminants was used to describe relationships between climatic variables, elevation and the distribution of H. chrysoscelis and H. versicolor . 3. There was a strong correlation between several climatic variables, elevation and the distribution of the gray treefrog complex. Specifically, the tetraploid species almost exclusively occupied areas of higher elevation, where climatic conditions were relatively severe (colder, drier, greater annual variation). In contrast, the diploid species was restricted to lower elevations, where climatic conditions were warmer, wetter and exhibited less annual variation. 4. Clusters of syntopic sites were associated with areas of high variation in annual temperature and precipitation during the breeding season. 5. Our data suggest that large-scale climatic conditions have played a role in the establishment of the polyploid H. versicolor in at least some portions of its range. The occurrence of the polyploid and absence of the progenitor in colder, drier and more varied environments suggests the polyploid may posses a tolerance of severe environmental conditions that is not possessed by the diploid progenitor. 6. Our findings support the hypothesis that increased tolerance to severe environmental conditions is a plausible mechanism of polyploid establishment.

Maryland, Virginia↗

Temporal variations of heavy metals in coral Porites lutea from Guangdong Province, China: Influences from industrial pollution, climate and economic factors

The eight heavy metals Cr, Mn, Co, Ni, Cu, Zn, Cd, and Pb have been determined in samples of coral Porites lutea collected from Dafangji Island waters (21°21′N, 111°11′E), Dianbai County, Guangdong Province, China, by the ICP-MS method. The samples represent the growth of coral in the period of 1982–2001. The results showed that the waters were polluted by the heavy metals Cu, Ni, Zn, and Pb in certain years, but not by other metals. The contamination may have come from industrial sources, including electroplating, metallurgy, mining, and aquatic industries in the coastal areas. The correlation coefficients among the metals and climatic and economic factors indicate that the metals Ni, Zn, and Cd behave similarly. Copper and Mn are positively correlated, and cobalt is negatively correlated with Cr, Ni, Zn, and Cd. Lead is not correlated with any other metals but is correlated with sea surface water temperature, air temperature, GDP and industrial-agricultural production in Dianbai County. Lead in corals is related to the enhanced pollution level of ocean waters as a result of increased industrial activities.

Chinese Journal of Geochemistry↗

Probability of streamflow permanence model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest

The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (probabilistic predictions) of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin. Predictions correspond to any pixel on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid. Total annual precipitation and percent forest cover were consistently the most important predictor variables among global and most subregional models, which had error rates between 17 and 22%. Probabilities were converted to wet and dry streamflow permanence classes with an associated confidence. Wet and dry classifications were used to derive descriptors that characterize the statistical and spatial distribution of streamflow permanence in three focal basins. Predicted dry channel segments account for 52 to 92% of the stream network across the three focal basins; streamflow permanence decreased during climatically drier years. Predictions are publicly available through the USGS StreamStats platform. Results demonstrate the utility of the PROSPER model as a tool for identifying areas that may be resilient or sensitive to drought conditions, allowing for management efforts that target protecting critical reaches. Importantly, PROSPER’s successful predictive performance can be improved with new datasets of streamflow permanence underscoring the importance of field observations.

Idaho, Montana, Nevada, Oregon, Utah, Washington↗

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

Mojave Desert↗

Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States

Spatial climate data sets of 1971–2000 mean monthly precipitation and minimum and maximum temperature were developed for the conterminous United States. These 30‐arcsec (∼800‐m) grids are the official spatial climate data sets of the U.S. Department of Agriculture. The PRISM (Parameter‐elevation Relationships on Independent Slopes Model) interpolation method was used to develop data sets that reflected, as closely as possible, the current state of knowledge of spatial climate patterns in the United States. PRISM calculates a climate–elevation regression for each digital elevation model (DEM) grid cell, and stations entering the regression are assigned weights based primarily on the physiographic similarity of the station to the grid cell. Factors considered are location, elevation, coastal proximity, topographic facet orientation, vertical atmospheric layer, topographic position, and orographic effectiveness of the terrain. Surface stations used in the analysis numbered nearly 13 000 for precipitation and 10 000 for temperature. Station data were spatially quality controlled, and short‐period‐of‐record averages adjusted to better reflect the 1971–2000 period. PRISM interpolation uncertainties were estimated with cross‐validation (C‐V) mean absolute error (MAE) and the 70% prediction interval of the climate–elevation regression function. The two measures were not well correlated at the point level, but were similar when averaged over large regions. The PRISM data set was compared with the WorldClim and Daymet spatial climate data sets. The comparison demonstrated that using a relatively dense station data set and the physiographically sensitive PRISM interpolation process resulted in substantially improved climate grids over those of WorldClim and Daymet. The improvement varied, however, depending on the complexity of the region. Mountainous and coastal areas of the western United States, characterized by sparse data coverage, large elevation gradients, rain shadows, inversions, cold air drainage, and coastal effects, showed the greatest improvement. The PRISM data set benefited from a peer review procedure that incorporated local knowledge and data into the development process.

International Journal of Climatology↗

Lake Michigan's late Quaternary limnological and climate history from ostracode, oxygen isotope, and magnetic susceptibility

The limnology of Lake Michigan has changed dramatically since the late Pleistocene in response to the expansion and contraction of continental glaciers, to differential isostatic rebound, and to climate change. The lake sediment's stratigraphic trends, magnetic susceptibility, δ 18 O, and ostracode species abundance ratios provide criteria to identify the lake's response to glacial ice and to differential isostatic rebound. The latter phenomena dominate the lake's late Pleistocene and early Holocene history. The lake's hydrological budget provides the primary linkage between the lake and climate, particularly effective moisture. Dissolved salts were stored in the lake's water column when the lake's output shifted toward evaporation, but were flushed when output shifted toward outflow. The lake's salt storage history may be interpreted from some ostracode, δ 18 O, and magnetic susceptibility records found in sediment cores. Climate change influenced the entire lake's limnological history, but became the primary limnological driver from about the middle-Holocene to the present. The complex limnological history of Lake Michigan resulted in substantial changes in the ostracode species assemblages; from about 12,000 ka to about 5,500 ka, five ostracode intervals can be identified. These ostracode intervals provide a within-lake biostratigraphy and a stratigraphic reference for reconstruction of the paleoenvironmental dynamics of the lake.

Indiana, Illinois, Michigan, Wisconsin↗

Parasite abundance-occupancy relationships across biogeographic regions: Joint effects of niche breadth, host availability and climate

Changing biodiversity and environmental conditions may allow multi-host pathogens to spread among host species and affect prevalence. There are several widely acknowledged theories about mechanisms that may influence variation in pathogen prevalence, including the controversially debated dilution effect and abundance-occupancy relationship hypotheses. Here, we explore such abundance-occupancy relationships for unique lineages of three vector-borne avian blood parasite genera (the avian malaria parasite Plasmodium and the related haemosporidian parasites Parahaemoproteus and Leucocytozoon ) across biogeographical regions.

Journal of Biogeography↗

Estimating occupancy probability of moose using hunter survey data

Monitoring rare species can be difficult, especially across large spatial extents, making conventional methods of population monitoring costly and logistically challenging. Citizen science has the potential to produce observational data across large areas that can be used to monitor wildlife distributions using occupancy models. We used citizen science (i.e., hunter surveys) to facilitate monitoring of moose ( Alces alces ) populations, an especially important endeavor because of their recent apparent declines in the northeastern and upper midwestern regions of the United States. To better understand patterns of occurrence of moose in New York, we used data collected through an annual survey of approximately 11,000 hunters between 2012 and 2014 that recorded detection–non-detection data of moose and other species. We estimated patterns of occurrence of moose in relation to land cover characteristics, climate effects, and interspecific interactions using occupancy models to analyze spatially referenced moose observations. Coniferous and deciduous forest with low prevalence of white-tailed deer ( Odocoileus virginianus ) had the highest probability of moose occurrence. This study highlights the potential of data collected using citizen science for understanding the spatial distribution of low-density species across large spatial extents and providing key information regarding where and when future research and management activities should be focused.

New York↗

The distribution of selected elements and minerals in soil of the conterminous United States

In 2007, the U.S. Geological Survey initiated a low-density (1 site per 1600 km 2 , 4857 sites) geochemical and mineralogical survey of soil of the conterminous United States as part of the North American Soil Geochemical Landscapes Project. Three soil samples were collected, if possible, from each site; (1) a sample from a depth of 0 to 5 cm, (2) a composite of the soil A-horizon, and (3) a deeper sample from the soil C-horizon or, if the top of the C-horizon was at a depth greater than 100 cm, from a depth of approximately 80–100 cm. The < 2 mm fraction of each sample was analysed for a suite of 45 major and trace elements following near-total multi-acid digestion. The major mineralogical components in samples from the soil A- and C-horizons were determined by a quantitative X-ray diffraction method using Rietveld refinement. Sampling ended in 2010 and chemical and mineralogical analyses were completed in May 2013. Maps of the conterminous United States showing predicted element and mineral concentrations were interpolated from actual soil data for each soil sample type by an inverse distance weighted (IDW) technique using ArcGIS software. Regional- and national-scale map patterns for selected elements and minerals apparent in interpolated maps are described here in the context of soil-forming factors and possible human inputs. These patterns can be related to (1) soil parent materials, for example, in the distribution of quartz, (2) climate impacts, for example, in the distribution of feldspar and kaolinite, (3) soil age, for example, in the distribution of carbonate in young glacial deposits, and (4) possible anthropogenic loading of phosphorus (P) and lead (Pb) to surface soil. This new geochemical and mineralogical data set for the conterminous United States represents a major step forward from prior national-scale soil geochemistry data and provides a robust soil data framework for the United States now and into the future.

Journal of Geochemical Exploration↗

Climatic fluctuations and forecasting of streamflow in the lower Colorado River Basin

Water-resource managers need to forecast streamflow in the Lower Colorado River Basin to plan for water-resource projects and to operate reservoirs for water supply. Statistical forecasts of streamflow based on historical records of streamflow can be useful, but statistical assumptions, such as stationarity of flows, need to be evaluated. This study evaluated the relation between climatic fluctuations and stationarity and developed regression equations to forecast streamflow by using climatic fluctuations as explanatory variables. Climatic fluctuations were represented by the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and Southern Oscillation Index (SOI). Historical streamflow within the 25- to 30-year positive or negative phases of AMO or PDO was generally stationary. Monotonic trends in annual mean flows were tested at the 21 sites evaluated in this study; 76% of the sites had no significant trends within phases of AMO and 86% of the sites had no significant trends within phases of PDO. As climatic phases shifted in signs, however, many sites had nonstationary flows; 67% of the sites had significant changes in annual mean flow as AMO shifted in signs. The regression equations developed in this study to forecast streamflow incorporate these shifts in climate and streamflow, thus that source of nonstationarity is accounted for. The R 2 value of regression equations that forecast individual years of annual flow for the central part of the study area ranged from 0.28 to 0.49 and averaged 0.39. AMO was the most significant variable, and a combination of indices from both the Atlantic and Pacific Oceans explained much more variation in flows than only the Pacific Ocean indices. The average R2 value for equations with PDO and SOI was 0.15. ?? 2007 American Water Resources Association.

Journal of the American Water Resources Associatio↗

Carbon distribution in subalpine forests and meadows of the Olympic Mountains, Washington

stimates of C storage in mountainous regions are rare. Forest–meadow ecotones in subalpine ecosystems, which contain a mosaic of forests and meadows, may be particularly sensitive to future changes in climate and are therefore important to include in estimates of terrestrial C storage. In this study, we quantified soil C and ecosystem C pools in subalpine forest and meadow soils of the northeastern (NE, dry climate) and southwestern (SW, wet climate) Olympic Mountains. Carbon concentrations of mineral soil are relatively high in upper horizons, ranging from 43 to 142 g kg −1 in NE soils and 27 to 162 g kg −1 in SW soils. Northeastern meadow soils store more C than NE forests ( P = 0.009) , while SW forest soils store more C than SW meadows ( P = 0.038) Ecosystem C storage is greater in forests than in meadows. Under a warmer climatic scenario with drier summers and wetter winters, subalpine C storage may decrease in the NE and increase in the SW, and changes in C storage will be closely related to vegetation distribution, ecosystem productivity, decomposition rates, and local disturbance regimes. Because ecosystem processes and associated C storage differ between high- and low-elevation ecosystems, it is important that data from both high- and low-elevation sites are included in estimates of C storage in terrestrial ecosystems.

Soil Science Society of America Journal↗

The Circumpolar Arctic vegetation map

Question: What are the major vegetation units in the Arctic, what is their composition, and how are they distributed among major bioclimate subzones and countries? Location: The Arctic tundra region, north of the tree line. Methods: A photo-interpretive approach was used to delineate the vegetation onto an Advanced Very High Resolution Radiometer (AVHRR) base image. Mapping experts within nine Arctic regions prepared draft maps using geographic information technology (ArcInfo) of their portion of the Arctic, and these were later synthesized to make the final map. Area analysis of the map was done according to bioclimate subzones, and country. The integrated mapping procedures resulted in other maps of vegetation, topography, soils, landscapes, lake cover, substrate pH, and above-ground biomass. Results: The final map was published at 1:7 500 000 scale map. Within the Arctic (total area = 7.11 x 106 km 2), about 5.05 ?? 106 km2 is vegetated. The remainder is ice covered. The map legend generally portrays the zonal vegetation within each map polygon. About 26% of the vegetated area is erect shrublands, 18% peaty graminoid tundras, 13% mountain complexes, 12% barrens, 11% mineral graminoid tundras, 11% prostrate-shrub tundras, and 7% wetlands. Canada has by far the most terrain in the High Arctic mostly associated with abundant barren types and prostrate dwarf-shrub tundra, whereas Russia has the largest area in the Low Arctic, predominantly low-shrub tundra. Conclusions: The CAVM is the first vegetation map of an entire global biome at a comparable resolution. The consistent treatment of the vegetation across the circumpolar Arctic, abundant ancillary material, and digital database should promote the application to numerous land-use, and climate-change applications and will make updating the map relatively easy. ?? IAVS; Opulus Press.

Journal of Vegetation Science↗

Assessing the geologic and climatic forcing of biodiversity and evolution surrounding the Gulf of California

For almost a century the Baja California peninsula (Peninsula), Gulf of California (Gulf), and broader Sonoran Desert region (figure 1) have drawn geologists and biologists alike to study its unique physical and evolutionary processes (e.g., Wittich 1920; Darton 1921; Nelson 1921; Johnston 1924; Beal 1948; Durham and Allison 1960). The challenge remains to untangle the long, intricate, and at times enigmatic geological and climatological histories that have shaped the high levels of endemism and biodiversity observed in the region today (Van Devender 1990; Grismer 2000; Riddle et al. 2000).

Gulf of California↗

The role of genome duplication in big sagebrush growth and fecundity

Premise Adaptive traits can be dramatically altered by genome duplication. The study of interactions among traits, ploidy, and the environment are necessary to develop an understanding of how polyploidy affects niche differentiation and to develop restoration strategies for resilient native ecosystems. Methods Growth and fecundity were measured in common gardens for 39 populations of big sagebrush ( Artemisia tridentata ) containing two subspecies and two ploidy levels. General linear mixed-effect models assessed how much of the trait variation could be attributed to genetics (i.e., ploidy and climatic adaptation), environment, and gene–environment interactions. Results Growth and fecundity variation were explained well by the mixed models (80% and 91%, respectively). Much of the trait variation was attributed to environment, and 15% of variation in growth and 34% of variation in seed yield were attributed to genetics. Genetic trait variation was mostly attributable to ploidy, with much higher growth and seed production in diploids, even in a warm-dry environment typically dominated by tetraploids. Population-level genetic variation was also evident and was related to the climate of each population's origin. Conclusions Ploidy is a strong predictor growth and seed yield, regardless of common-garden environment. The superior growth and fecundity of diploids across environments raises the question as to how tetraploids can be more prevalent than diploids, especially in warm-dry environments. Two hypotheses that may explain the abundance of tetraploids on the landscape include selection for drought resistance at the seedling stage, and greater competitive ability in water uptake in the upper soil horizon.

American Journal of Botany↗

Effects of river floods and sedimentation on a naturally dynamic Great Lakes estuary

Some of the most biologically diverse coastal wetlands and estuaries are found along the Great Lakes, but the spatial extent and timing of river-related inundation and sedimentation vary greatly among natural and altered systems. We used hydrologic data, geomorphic change detection, and satellite imagery to study inundation and sedimentation patterns in the naturally dynamic estuary of the Bad River ( Mashkiiziibii ) that flows into Lake Superior ( Anishinaabeg-gichigami ), and the Kakagon River ( Ogaakaagaang-ziibii ) that flows into a sheltered bay ( Chi-Kaamigong ). In 2016, an extreme summer flood (annual exceedance probability < 0.2 %) caused total inundation of the 46-km 2 estuary. Floods from the sediment-rich Bad River, with an annual exceedance probability of ≤ 50 %, have overflowed into the upper wetlands and channels of the Kakagon River about 60 times over the last 75 years, including 20 floods during the most recent 10-year wet period. Sedimentation patterns were associated with proximity to river channels, shoreline erosion, and wind action. Early winter ice-up coupled with a storm surge and an early spring snowmelt into the iced-over bay changed inundation duration and sedimentation patterns. Climate-change projections for more intense rainfall and warmer temperatures will likely cause more frequent flooding and sedimentation; however, patterns may differ depending on the timing of the floods relative to storm surges and ice formation, or other factors. The approach of integrating readily available data helped give a broader temporal and spatial context to the possible causes for inundation and sedimentation, some expected and others not, in natural and restored estuaries of the Great Lakes.

Wisconsin↗

Contemporary spatial extent and environmental drivers of larval coregonine distributions across Lake Ontario

Coregonine fishes are important to Laurentian Great Lakes food webs and fisheries and are central to basin-wide conservation initiatives. In Lake Ontario, binational management objectives include conserving and restoring spawning stocks of cisco ( Coregonus artedi ) and lake whitefish ( C. clupeaformis ), but the spatial extent of contemporary coregonine spawning habitat and the environmental factors regulating early life success are not well characterized. In Spring 2018, we conducted a binational ichthyoplankton assessment to describe the spatial extent of coregonine spawning habitat across Lake Ontario. We then quantified the relative importance of a suite of biophysical variables hypothesized to influence coregonine early life success using generalized additive mixed models and multimodel inference. Between April 10 and May 14, we conducted 1,092 ichthyoplankton tows and captured 2,350+ coregonine larvae across 17 sampling areas, predominantly within embayments. Although 95% of catches were in the eastern basin, coregonine larvae were also found in historical south shore spawning areas. Most coregonine larvae were cisco; <6% were lake whitefish. Observed catches of both species across sampling areas were strongly and similarly associated with ice cover duration, but the importance of site-specific characteristics varied, such as distance to shore and site depth for cisco and lake whitefish, respectively. These results suggest that regional-scale climatic drivers and local environmental habitat characteristics interact to regulate early life stage success. Furthermore, strong regional and cross-species variation in larval distributions emphasize the importance of lake-wide assessments for monitoring both the current eastern basin populations and potential expansions into western Lake Ontario habitats.

Lake Ontario↗