Investigating the species-specific association between anuran calling phenology and air temperature

2021 ◽  
Author(s):  
Samantha Wong
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Management Strategies ◽  
Temporal Trends ◽  
Interspecific Variation ◽  
Northern Ontario ◽  
Anuran Species ◽  
Calling Behaviour ◽  
Survival And Development ◽  
Species Specific

Climate change has been associated in phenological shifts for a variety of taxa. Amphibians, specifically the order Anura (frogs and toads), are considered particularly vulnerable due to their sensitivity to anthropogenic and environmental change. Previous research has documented shifts in the timing of anuran breeding that can be attributed, in part, to climate change, with potential implications for reproduction, survival, and development. This study aims to investigate how air temperature is associated with anuran calling phenology. I will examine the temporal trends in spring and summer air temperature in a lake in northern Ontario, Canada. and quantify seasonal patterns of calling anuran species using acoustic monitoring over a four-month period. I predict that there will be interspecific variation in peak calling associated with air temperature. Additionally, I expect to find asymmetrical association between air temperature and anuran species’ calling behaviour – wherein prolonged breeding species will have a larger optimal temperature range for calling compared to explosive breeding species. The findings of this research will aid in future conservation and provide insight for management strategies of anurans in Canada in response to anticipated climate warming.

scholarly journals Historical and future temporal trends in the summer Urban Heat Island of Athens (Greece) 

2021 ◽  
Author(s):  
Tim van der Schriek ◽  
Konstantinos V. Varotsos ◽  
Dimitra Founda ◽  
Christos Giannakopoulos
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Temperature ◽  
Temporal Trends ◽  
Temperature Data ◽  
Climate Change Scenarios ◽  
Heat Island ◽  
Hot Days ◽  
The Future ◽  
Urban Heat

<p>Historical changes, spanning 1971–2016, in the Athens Urban Heat Island (UHI) over summer were assessed by contrasting two air temperature records from established meteorological stations in urban and rural settings. When contrasting two 20-year historical periods (1976–1995 and 1996–2015), there is a significant difference in summer UHI regimes. The stronger UHI-intensity of the second period (1996–2015) is likely linked to increased pollution and heat input. Observations suggest that the Athens summer UHI characteristics even fluctuate on multi-annual basis. Specifically, the reduction in air pollution during the Greek Economic Recession (2008-2016) probable subtly changed the UHI regime, through lowering the frequencies of extremely hot days (T<sub>max</sub> > 37 °C) and nights (T<sub>min</sub> > 26 °C).</p><p>Subsequently, we examined the future temporal trends of two different UHIs in Athens (Greece) under three climate change scenarios. A five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11° (~12 × 12 km) simulated air temperature data, spanning the period 1976–2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5 and RCP8.5) were implanted in the simulations after 2005. The observed daily maximum and minimum air temperature data (T<sub>max</sub> and T<sub>min</sub>) from two historical UHI regimes (1976–1995 and 1996–2015, respectively) were used, separately, to bias-adjust the model simulations thus creating two sets of results.</p><p>This novel approach allowed us to assess future temperature developments in Athens under two different UHI intensity regimes. We found that the future frequency of days with T<sub>max</sub> > 37 °C in Athens was only different from rural background values under the intense UHI regime. There is a large increase in the future frequency of nights with T<sub>min</sub> > 26 °C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site.</p><p>This study shows a large urban amplification of the frequency of extremely hot days and nights which is likely forced by increasing air pollution and heat input. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be also effective in reducing urban temperatures during extreme heat events in Athens under all future climate change scenarios. Such policies therefore have multiple benefits, including: reducing electricity (energy) needs, improving living quality and decreasing heat- and pollution related illnesses/deaths.</p><p> </p>

scholarly journals Projected Future Temporal Trends of Two Different Urban Heat Islands in Athens (Greece) under Three Climate Change Scenarios: A Statistical Approach

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 637 ◽  
Author(s):  
Tim van der Schriek ◽  
Konstantinos V. Varotsos ◽  
Christos Giannakopoulos ◽  
Dimitra Founda
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Temperature ◽  
Temporal Trends ◽  
Temperature Data ◽  
Rural Site ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Future ◽  
The Impact

This is the first study to look at future temporal urban heath island (UHI) trends of Athens (Greece) under different UHI intensity regimes. Historical changes in the Athens UHI, spanning 1971–2016, were assessed by contrasting two air temperature records from stable meteorological stations in contrasting urban and rural settings. Subsequently, we used a five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11° (~12 × 12 km) to simulate air temperature data, spanning the period 1976–2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5, and RCP8.5) were implanted in the simulations after 2005 covering the period 2006–2100. Two 20-year historical reference periods (1976–1995 and 1996–2015) were selected with contrasting UHI regimes; the second period had a stronger intensity. The daily maximum and minimum air temperature data (Tmax and Tmin) for the two reference periods were perturbed to two future periods, 2046–2065 and 2076–2095, under the three RCPs, by applying the empirical quantile mapping (eqm) bias-adjusting method. This novel approach allows us to assess future temperature developments in Athens under two UHI intensity regimes that are mainly forced by differences in air pollution and heat input. We found that the future frequency of days with Tmax > 37 °C in Athens was only different from rural background values under the intense UHI regime. Thus, the impact of heatwaves on the urban environment of Athens is dependent on UHI intensity. There is a large increase in the future frequency of nights with Tmin > 26 °C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site. This large urban amplification of the frequency of extremely hot nights is likely caused by air pollution. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be highly effective in reducing urban temperatures and extreme heat events in Athens under future climate change scenarios. Such policies directly have multiple benefits, including reduced electricity (energy) needs, improved living quality and strong health advantages (heat- and pollution-related illness/deaths).

scholarly journals Importance of phenological observations and predictions in agriculture

2005 ◽  
Vol 50 (2) ◽  
pp. 217-225 ◽  
Author(s):  
Mirjana Ruml ◽  
Todor Vulic
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climatic Conditions ◽  
Agricultural Activities ◽  
Valuable Data ◽  
Scientific Disciplines ◽  
Wide Range ◽  
Crop Development ◽  
Physiologically Based ◽  
Species Specific

Phenology can contribute to many scientific disciplines from climate change, biodiversity, agriculture and forestry to human health. The knowledge of timing of phenological events and their variability can provide valuable data for planning, organizing and timely execution of certain standard and special (preventive and protective) agricultural activities that require advanced information on the dates of specific stages of crop development. Mathematical models are the basic tools to predict the timing of phenological events. There are two types of phenological models: physiologically-based and statistical. Most of the existing models are statistical and serve to predict the onset of different phenophases according to the air temperature. These models are site- and species-specific and cannot be applied to a wide range of species and climatic conditions.

scholarly journals The role of irrigation expansion on historical climate change during the last 115 years: insights from CMIP6

2021 ◽  
Author(s):  
Amen Al-Yaari ◽  
Agnes Ducharne ◽  
Wim Thiery ◽  
Frederique Cheruy ◽  
David Lawrence
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Air Temperature ◽  
Land Management ◽  
Climate Models ◽  
Temporal Trends ◽  
World Population ◽  
The World ◽  
Over Time

<p>Irrigated areas have increased, faster than the growth of the world population, from around 0.63 million km<sup>2</sup> at the start of the 20th century to 3.1 million km<sup>2</sup> of land in 2005, that is five times of area in 1900 (0.6 million km<sup>2</sup>). Irrigation is one of the land management practices with the largest biogeochemical and biogeophysical effects on climate. However, incorporating land management factors (including irrigation) into most of the state‐of‐the‐art climate models under the Coupled Model Intercomparison Project, Phase 6 (CMIP6) coordinated by the World Climate Research Programme (WCRP) is still overlooked. To our best knowledge, three models, however, take into account irrigation activities: namely NorESM2‐LM, GISS‐E2‐H, and CESM2. The overall objective of the study is to investigate the role of irrigation on climate change at the global scale by looking at temporal trends of Essential Climate variables (ECVs) that characterize the Earth's climate (Evapotranspiration, leaf area index, precipitation, soil moisture, radiation, and air temperature) over the last 115 years (i.e. 1900-2014). Within this investigation, we compared models with irrigation vs. models without irrigation using 20 models from different CMIP6 experiments: coupled land-atmosphere amip (observed sea surface temperatures and sea ice concentrations), coupled land-atmosphere-ocean historical simulation, and offline land-hist (land only simulations). Temporal trends over the 1900-2014 period were computed then spatially binned by the "FAO Global Map of Irrigation Areas", which represents area equipped for irrigation expressed as percentage of total area around the year 2005. For the three CMIP6 experiments, the three models with irrigation switched on showed similar and distinguished behavior from all other models with irrigation switched off over intensively irrigated areas: mean annual evapotranspiration and soil moisture increased over time (positive trends vs. negative or no trends for all other none-irrigation models). This increase in evapotranspiration over time was reflected in the negative trends (i.e. cooling) of annual maximum air temperature for the irrigation models vs. positive trends for most of the none-irrigation models. The ET temporal positive trends over intensively irrigated areas were detected and confirmed by four different satellite-based ET products. The consistent results among the three experiments and confirmed by different satellite data imply the importance of incorporating anthropogenic factors in the next generation of climate models.</p>

scholarly journals Surface Water Temperature Predictions at a Mid-Latitude Reservoir under Long-Term Climate Change Impacts Using a Deep Neural Network Coupled with a Transfer Learning Approach

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1109
Author(s):  
Nobuaki Kimura ◽  
Kei Ishida ◽  
Daichi Baba
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Water Temperature ◽  
Transfer Learning ◽  
Air Temperature ◽  
Climate Models ◽  
Temporal Variations ◽  
Training Data ◽  
Surface Water Temperature

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.

scholarly journals Projection of Hydro-Climatic Extreme Events under Climate Change in Yom and Nan River Basins, Thailand

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 665
Author(s):  
Chanchai Petpongpan ◽  
Chaiwat Ekkawatpanit ◽  
Supattra Visessri ◽  
Duangrudee Kositgittiwong
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Extreme Events ◽  
River Basins ◽  
Annual Rainfall ◽  
Extreme Floods ◽  
Extreme Flood ◽  
Rcp 8.5 ◽  
Near Future ◽  
Far Future

Due to a continuous increase in global temperature, the climate has been changing without sign of alleviation. An increase in the air temperature has caused changes in the hydrologic cycle, which have been followed by several emergencies of natural extreme events around the world. Thailand is one of the countries that has incurred a huge loss in assets and lives from the extreme flood and drought events, especially in the northern part. Therefore, the purpose of this study was to assess the hydrological regime in the Yom and Nan River basins, affected by climate change as well as the possibility of extreme floods and droughts. The hydrological processes of the study areas were generated via the physically-based hydrological model, namely the Soil and Water Assessment Tool (SWAT) model. The projected climate conditions were dependent on the outputs of the Global Climate Models (GCMs) as the Representative Concentration Pathways (RCPs) 2.6 and 8.5 between 2021 and 2095. Results show that the average air temperature, annual rainfall, and annual runoff will be significantly increased in the intermediate future (2046–2070) onwards, especially under RCP 8.5. According to the Flow Duration Curve and return period of peak discharge, there are fluctuating trends in the occurrence of extreme floods and drought events under RCP 2.6 from the future (2021–2045) to the far future (2071–2095). However, under RCP 8.5, the extreme flood and drought events seem to be more severe. The probability of extreme flood remains constant from the reference period to the near future, then rises dramatically in the intermediate and the far future. The intensity of extreme droughts will be increased in the near future and decreased in the intermediate future due to high annual rainfall, then tending to have an upward trend in the far future.

scholarly journals Methodology for classifying the ecosystem integrity of forests in Germany using quantified indicators

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Martin Jenssen ◽  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Climate Change ◽  
National Park ◽  
Temporal Trends ◽  
Water Flux ◽  
Ecosystem Functions ◽  
Specific Reference ◽  
Atmospheric Nitrogen ◽  
Complete Coverage ◽  
Ecosystem Integrity ◽  
Quantitative Indicators

Abstract Background Atmospheric deposition of nitrogen and climate change can have impacts on ecological structures and functions, and thus on the integrity of ecosystems and their services. Operationalization of ecosystem integrity is still an important desideratum. Results A methodology for classifying the ecosystem integrity of forests in Germany under the influence of climate change and atmospheric nitrogen deposition is presented. The methodology was based on 14 indicators for six ecosystem functions: habitat function, net primary function, carbon sequestration, nutrient and water flux, resilience. It allows assessments of ecosystem integrity changes by comparing current or prospective ecosystem states with ecosystem-type-specific reference states as described by quantitative indicators for 61 forest ecosystem types based on data before 1990. Conclusion The method developed enables site-specific classifications of ecosystem integrity as well as classifications with complete coverage and determinations of temporal trends as shown using examples from the Thuringian Forest and the “Kellerwald-Edersee” National Park (Germany).

scholarly journals Changes in Coastal Agricultural Land Use in Response to Climate Change: An Assessment Using Satellite Remote Sensing and Household Survey Data in Tien Hai District, Thai Binh Province, Vietnam

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 627
Author(s):  
Duong H. Nong ◽  
An T. Ngo ◽  
Hoa P. T. Nguyen ◽  
Thuy T. Nguyen ◽  
Lan T. Nguyen ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Management Strategies ◽  
Household Survey ◽  
Extreme Weather Events ◽  
Agricultural Land Use ◽  
Landsat 8 ◽  
Land Uses

We analyzed the agricultural land-use changes in the coastal areas of Tien Hai district, Thai Binh province, in 2005, 2010, 2015, and 2020, using Landsat 5 and Landsat 8 data. We used the object-oriented classification method with the maximum likelihood algorithm to classify six types of land uses. The series of land-use maps we produced had an overall accuracy of more than 80%. We then conducted a spatial analysis of the 5-year land-use change using ArcGIS software. In addition, we surveyed 150 farm households using a structured questionnaire regarding the impacts of climate change on agricultural productivity and land uses, as well as farmers’ adaptation and responses. The results showed that from 2005 to 2020, cropland decreased, while aquaculture land and forest land increased. We observed that the most remarkable decreases were in the area of rice (485.58 ha), the area of perennial crops (109.7 ha), and the area of non-agricultural land (747.35 ha). The area of land used for aquaculture and forest increased by 566.88 ha and 772.60 ha, respectively. We found that the manifestations of climate change, such as extreme weather events, saltwater intrusion, drought, and floods, have had a profound impact on agricultural production and land uses in the district, especially for annual crops and aquaculture. The results provide useful information for state authorities to design land-management strategies and solutions that are economic and effective in adapting to climate change.

scholarly journals The Benefits of Combining Global and Local Data—A Showcase for Valuation and Mapping of Mangrove Climate Regulation and Food Provisioning Services within a Protected Area in Pará, North Brazil

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 432
Author(s):  
Robin Gutting ◽  
Ralf-Uwe Syrbe ◽  
Karsten Grunewald ◽  
Ulf Mehlig ◽  
Véronique Helfer ◽  
...  
Keyword(s):  
Global Climate ◽  
Structural Parameters ◽  
Management Strategies ◽  
Small Scale ◽  
Mangrove Forests ◽  
Food Provisioning ◽  
Local Data ◽  
Climate Regulation ◽  
North Brazil ◽  
Species Specific

Mangrove forests provide a large variety of ecosystem services (ES) to coastal societies. Using a case study focusing on the Ajuruteua peninsula in Northern Brazil and two ES, food provisioning (ES1) and global climate regulation (ES2), this paper proposes a new framework for quantifying and valuing mangrove ES and allow for their small-scale mapping. We modelled and spatialised the two ES from different perspectives, the demand (ES1) and the supply (ES2) side respectively. This was performed by combining worldwide databases related to the global human population (ES1) or mangrove distribution and canopy height (ES2) with locally derived parameters, such as crab catches (ES1) or species-specific allometric equations based on local estimates of tree structural parameters (ES2). Based on this approach, we could estimate that the area delivers the basic nutrition of about 1400 households, which equals 2.7 million USD, and that the mangrove biomass in the area contains 2.1 million Mg C, amounting to 50.9 million USD, if it were paid as certificates. In addition to those figures, we provide high-resolution maps showing which areas are more valuable for the two respective ES, information that could help inform management strategies in the future.

scholarly journals Predicting Impacts of Climate Change on Northward Range Expansion of Invasive Weeds in South Korea

Plants ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1604
Author(s):  
Sun Hee Hong ◽  
Yong Ho Lee ◽  
Gaeun Lee ◽  
Do-Hun Lee ◽  
Pradeep Adhikari
Keyword(s):  
Climate Change ◽  
South Korea ◽  
Habitat Suitability ◽  
Management Strategies ◽  
Southern Region ◽  
Suitable Habitat ◽  
Invasive Weeds ◽  
Northern Regions ◽  
Suitable Habitats ◽  
Control And Management

Predicting the distribution of invasive weeds under climate change is important for the early identification of areas that are susceptible to invasion and for the adoption of the best preventive measures. Here, we predicted the habitat suitability of 16 invasive weeds in response to climate change and land cover changes in South Korea using a maximum entropy modeling approach. Based on the predictions of the model, climate change is likely to increase habitat suitability. Currently, the area of moderately suitable and highly suitable habitats is estimated to be 8877.46 km2, and 990.29 km2, respectively, and these areas are expected to increase up to 496.52% by 2050 and 1439.65% by 2070 under the representative concentration pathways 4.5 scenario across the country. Although habitat suitability was estimated to be highest in the southern regions (<36° latitude), the central and northern regions are also predicted to have substantial increases in suitable habitat areas. Our study revealed that climate change would exacerbate the threat of northward weed invasions by shifting the climatic barriers of invasive weeds from the southern region. Thus, it is essential to initiate control and management strategies in the southern region to prevent further invasions into new areas.

Sign in / Sign up

Export Citation Format

Share Document