scholarly journals Joint Impacts of Drought and Habitat Fragmentation on Native Bee Assemblages in a California Biodiversity Hotspot

Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 135
Author(s):  
Keng-Lou James Hung ◽  
Sara S. Sandoval ◽  
John S. Ascher ◽  
David A. Holway
Keyword(s):  
Habitat Fragmentation ◽  
Large Scale ◽  
Global Climate ◽  
Relative Magnitude ◽  
Urban Environments ◽  
Floral Resources ◽  
Severe Drought ◽  
Drought Event ◽  
Fragmented Habitat ◽  
Native Bee

Global climate change is causing more frequent and severe droughts, which could have serious repercussions for the maintenance of biodiversity. Here, we compare native bee assemblages collected via bowl traps before and after a severe drought event in 2014 in San Diego, California, and examine the relative magnitude of impacts from drought in fragmented habitat patches versus unfragmented natural reserves. Bee richness and diversity were higher in assemblages surveyed before the drought compared to those surveyed after the drought. However, bees belonging to the Lasioglossum subgenus Dialictus increased in abundance after the drought, driving increased representation by small-bodied, primitively eusocial, and generalist bees in post-drought assemblages. Conversely, among non-Dialictus bees, post-drought years were associated with decreased abundance and reduced representation by eusocial species. Drought effects were consistently greater in reserves, which supported more bee species, than in fragments, suggesting that fragmentation either had redundant impacts with drought, or ameliorated effects of drought by enhancing bees’ access to floral resources in irrigated urban environments. Shifts in assemblage composition associated with drought were three times greater compared to those associated with habitat fragmentation, highlighting the importance of understanding the impacts of large-scale climatic events relative to those associated with land use change.

scholarly journals Spatial and Temporal Characterization of Drought Events in China Using the Severity-Area-Duration Method

2020 ◽  
Author(s):  
Xiaoli Yang
Keyword(s):  
Arid Region ◽  
Water Cycle ◽  
Global Climate ◽  
Severity Index ◽  
Drought Severity ◽  
Historical Period ◽  
Severe Drought ◽  
Drought Event ◽  
Long Duration ◽  
Semi Arid Region

<p>Global climate change not only affects the processes within the water cycle but also leads to the frequent occurrences of local and regional extreme drought events. In China, spatial and temporal characterizations of drought events and their future changing trends are of great importance in water resources planning and management. In this study, we employed self-calibrating Palmer drought severity index (SC-PDSI), cluster algorithm, and severity-area-duration (SAD) methods to identify drought events and analyze the spatial and temporal distributions of various drought characteristics in China using observed data and CMIP5 model outputs. Results showed that during the historical period (1961–2000), the drought event of September 1965 was the most severe, affecting 47.07% of the entire land area of China, and shorter duration drought centers (lasting less than 6 months) were distributed all over the country. In the future (2021–2060), under both RCP[CF1]  4.5 and RCP 8.5 scenarios, drought is projected to occur less frequently, but the duration of the most severe drought event is expected to be longer than that in the historical period. Furthermore, drought centers with shorter duration are expected to occur throughout China, but the long-duration drought centers (lasting more than 24 months) are expected to mostly occur in the west of the arid region and in the northeast of the semi-arid region.</p>

scholarly journals Spatial and Temporal Characterization of Drought Events in China Using the Severity-Area-Duration Method

Water ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 230 ◽  
Author(s):  
Xiaoli Yang ◽  
Linyan Zhang ◽  
Yuqian Wang ◽  
Vijay P. Singh ◽  
Chong-Yu Xu ◽  
...  
Keyword(s):  
Arid Region ◽  
Water Cycle ◽  
Global Climate ◽  
Severity Index ◽  
Drought Severity ◽  
Historical Period ◽  
Severe Drought ◽  
Drought Event ◽  
Long Duration ◽  
Semi Arid Region

Global climate change not only affects the processes within the water cycle but also leads to the frequent occurrences of local and regional extreme drought events. In China, spatial and temporal characterizations of drought events and their future changing trends are of great importance in water resources planning and management. In this study, we employed self-calibrating Palmer drought severity index (SC-PDSI), cluster algorithm, and severity-area-duration (SAD) methods to identify drought events and analyze the spatial and temporal distributions of various drought characteristics in China using observed data and CMIP5 model outputs. Results showed that during the historical period (1961–2000), the drought event of September 1965 was the most severe, affecting 47.07% of the entire land area of China, and shorter duration drought centers (lasting less than 6 months) were distributed all over the country. In the future (2021–2060), under both representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios, drought is projected to occur less frequently, but the duration of the most severe drought event is expected to be longer than that in the historical period. Furthermore, drought centers with shorter duration are expected to occur throughout China, but the long-duration drought centers (lasting more than 24 months) are expected to mostly occur in the west of the arid region and in the northeast of the semi-arid region.

scholarly journals Causes and Predictability of the 2012 Great Plains Drought

2014 ◽  
Vol 95 (2) ◽  
pp. 269-282 ◽  
Author(s):  
M. Hoerling ◽  
J. Eischeid ◽  
A. Kumar ◽  
R. Leung ◽  
A. Mariotti ◽  
...  
Keyword(s):  
Great Plains ◽  
Large Scale ◽  
Climate Model ◽  
Decadal Variability ◽  
Substantial Reduction ◽  
Severe Drought ◽  
Drought Event ◽  
Drought Forecasting ◽  
Seasonal Forecasts ◽  
Climate Simulations

Central Great Plains precipitation deficits during May–August 2012 were the most severe since at least 1895, eclipsing the Dust Bowl summers of 1934 and 1936. Drought developed suddenly in May, following near-normal precipitation during winter and early spring. Its proximate causes were a reduction in atmospheric moisture transport into the Great Plains from the Gulf of Mexico. Processes that generally provide air mass lift and condensation were mostly absent, including a lack of frontal cyclones in late spring followed by suppressed deep convection in the summer owing to large-scale subsidence and atmospheric stabilization. Seasonal forecasts did not predict the summer 2012 central Great Plains drought development, which therefore arrived without early warning. Climate simulations and empirical analysis suggest that ocean surface temperatures together with changes in greenhouse gases did not induce a substantial reduction in sum mertime precipitation over the central Great Plains during 2012. Yet, diagnosis of the retrospective climate simulations also reveals a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade, most probably due to natural decadal variability. As a consequence, the probability of the severe summer Great Plains drought occurring may have increased in the last decade compared to the 1980s and 1990s, and the so-called tail risk for severe drought may have been heightened in summer 2012. Such an extreme drought event was nonetheless still found to be a rare occurrence within the spread of 2012 climate model simulations. The implications of this study's findings for U.S. seasonal drought forecasting are discussed.

Urban Environments as a Framework to Study Parallel Evolution

2020 ◽  
pp. 36-53 ◽  
Author(s):  
James S. Santangelo ◽  
Lindsay S. Miles ◽  
Sophie T. Breitbart ◽  
David Murray-Stoker ◽  
L. Ruth Rivkin ◽  
...  
Keyword(s):  
Habitat Fragmentation ◽  
Environmental Factors ◽  
Urban Development ◽  
Large Scale ◽  
Parallel Evolution ◽  
Natural Populations ◽  
Urban Environments ◽  
Diverse Range ◽  
Heat Islands ◽  
Insight Into

Urban environments represent globally replicated, large-scale disturbances to the landscape, providing an ideal opportunity to study parallel evolution in natural populations on a large scale. In recent years, there has been a rapid increase in the number of studies investigating evolutionary responses of a diverse range of taxa across multiple cities. Although parallel evolutionary responses across independent urban environments will depend on the extent to which urban environments converge on similar biotic and abiotic environments, the extent to which cities are environmentally similar has not yet fully been integrated into studies of urban evolution. This chapter begins by asking: Do species display parallel evolutionary responses across independent urban environments? It then briefly reviews a subset of the environmental factors that have driven parallel responses to cities (heat islands, pollution, and habitat fragmentation) and discusses some of the potential causes of non-parallelism. Finally, it ends with practical considerations for the design of future studies aiming to examine parallel evolutionary responses to urbanization. Understanding the shared and unique features of urban environments and identifying parallel species responses to rapid and ongoing urban development will provide important insight into the ubiquity of parallel evolution in nature.

scholarly journals Recurso polínico y ciclo estacional de Thygater aethiops (Hymenoptera: Apidae) en un ambiente urbano (Bogotá-Colombia)

2016 ◽  
Vol 64 (3) ◽  
Author(s):  
Mario Simon Pinilla-Gallego ◽  
Valentina Nieto ◽  
Guiomar Nates-Parra
Keyword(s):  
Urban Areas ◽  
Urban Environments ◽  
Floral Resources ◽  
Foraging Activity ◽  
Ulex Europaeus ◽  
Pollen Loads ◽  
Pollen Types ◽  
Native Bee ◽  
The City ◽  
Dry And Rainy Seasons

Thygater aethiops is a native bee that can be found in parks and gardens in diverse urban areas such as those in the city of Bogotá (Colombia). However, little is known about its biology as well as ecological adaptations to urban areas. This study aimed to describe the seasonal cycle and daily foraging activities of T. aethiops, as well as identify the pollen resources used by this bee over a year in a population nesting in an aggregation in the “Parque Nacional Enrique Olaya Herrera” in Bogotá. Changes in the nest activity were monitored weekly by counting the number of active nests in the aggregation between December/2012 and February/2014. To determine the daily foraging activity, the numbers of bees entering their nests over a period of 10 minutes every hour between 8:00 and 14:00 h were recorded. Females with pollen loads entering to their nest were captured weekly, between September/2012 and August/2013, and their pollen loads analyzed. Three nesting peaks occurred after the precipitation peaks, but the number of active nests was not correlated with precipitation. The nesting activities stopped in a large number of the active nests (20-50 % of nests) after an anthropic disturbance was registered in the nesting area. Bees forage for nectar and pollen between 8:00 and 14:00 h, with a peak at 10:00 h. Daily foraging activity changed during the study period due to anthropic disturbance. There was not a significant relationship between air temperature and the number of females entering their nests. Foraging activities did not change between the dry and rainy seasons. A total of 26 pollen types were found in 169 pollen loads. Ulex europaeus (Fabaceae) and Solanum laxum (Solanaceae) were the most abundant plants represented on the pollen load across the study period. According to these results, T. aethiops would be considered a mesolectic species. The ability of T. aethiops to use different pollen resources both native and exotic, as well as to presumably recover its population after disturbances, are characteristics that may have allowed this bee to adapt to urban environments. Knowledge on the floral resources as well as other biological features of this bee species is important to promote its conservation in urban areas. 

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

scholarly journals Modeling regional impacts and resilience to water service disruptions in urban economies

2021 ◽  
pp. 239980832199870
Author(s):  
Sheree A Pagsuyoin ◽  
Joost R Santos
Keyword(s):  
Case Studies ◽  
Large Scale ◽  
Urban Region ◽  
Economic Losses ◽  
Drought Severity ◽  
Severe Drought ◽  
Time Varying ◽  
National Capital Region ◽  
Economic Sectors ◽  
The Impact

Water is a critical natural resource that sustains the productivity of many economic sectors, whether directly or indirectly. Climate change alongside rapid growth and development are a threat to water sustainability and regional productivity. In this paper, we develop an extension to the economic input-output model to assess the impact of water supply disruptions to regional economies. The model utilizes the inoperability variable, which measures the extent to which an infrastructure system or economic sector is unable to deliver its intended output. While the inoperability concept has been utilized in previous applications, this paper offers extensions that capture the time-varying nature of inoperability as the sectors recover from a disruptive event, such as drought. The model extension is capable of inserting inoperability adjustments within the drought timeline to capture time-varying likelihoods and severities, as well as the dependencies of various economic sectors on water. The model was applied to case studies of severe drought in two regions: (1) the state of Massachusetts (MA) and (2) the US National Capital Region (NCR). These regions were selected to contrast drought resilience between a mixed urban–rural region (MA) and a highly urban region (NCR). These regions also have comparable overall gross domestic products despite significant differences in the distribution and share of the economic sectors comprising each region. The results of the case studies indicate that in both regions, the utility and real estate sectors suffer the largest economic loss; nonetheless, results also identify region-specific sectors that incur significant losses. For the NCR, three sectors in the top 10 ranking of highest economic losses are government-related, whereas in the MA, four sectors in the top 10 are manufacturing sectors. Furthermore, the accommodation sector has also been included in the NCR case intuitively because of the high concentration of museums and famous landmarks. In contrast, the Wholesale Trade sector was among the sectors with the highest economic losses in the MA case study because of its large geographic size conducive for warehouses used as nodes for large-scale supply chain networks. Future modeling extensions could potentially include analysis of water demand and supply management strategies that can enhance regional resilience against droughts. Other regional case studies can also be pursued in future efforts to analyze various categories of drought severity beyond the case studies featured in this paper.

scholarly journals Reanalysis of an Allocentric Navigation Strategy Scale based on Item Response Theory

2020 ◽  
Vol 2 (1) ◽  
pp. 90-105
Author(s):  
Jimmy Y. Zhong
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Large Scale ◽  
Relative Magnitude ◽  
Latent Structure ◽  
Response Theory ◽  
Future Studies ◽  
Bidimensional Model ◽  
Navigation Strategy ◽  
Component Loading

AbstractFocusing on 12 allocentric/survey-based strategy items of the Navigation Strategy Questionnaire (Zhong & Kozhevnikov, 2016), the current study applied item response theory-based analysis to determine whether a bidimensional model could better describe the latent structure of the survey-based strategy. Results from item and model fit diagnostics, categorical response and item information curves showed that an item with the lowest rotated component loading (.27) [SURVEY12], could be considered for exclusion in future studies; and that a bidimensional model with three preference-related items constituting a content factor offered a better representation of the latent structure than a unidimensional model per se. Mean scores from these three items also correlated significantly with a pointing-to-landmarks task to the same relative magnitude as the mean scores from all items, and all items excluding SURVEY12. These findings gave early evidence suggesting that the three preference-related items could constitute a subscale for deriving quick estimates of large-scale allocentric spatial processing in healthy adults in both experimental and clinical settings. Potential cognitive and brain mechanisms were discussed, followed by calls for future studies to gather greater evidence confirming the predictive validity of the full and sub scales, along with the design of new items focusing on environmental familiarity.

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