Climate change and outbreaks of amphibian chytridiomycosis in a montane area of Central Spain; is there a link?

Amphibian species are declining at an alarming rate on a global scale in large part owing to an infectious disease caused by the chytridiomycete fungus, Batrachochytrium dendrobatidis . This disease of amphibians has recently emerged within Europe, but knowledge of its effects on amphibian assemblages remains poor. Importantly, little is known about the environmental envelope that is associated with chytridiomycosis in Europe and the potential for climate change to drive future disease dynamics. Here, we use long-term observations on amphibian population dynamics in the Peñalara Natural Park, Spain, to investigate the link between climate change and chytridiomycosis. Our analysis shows a significant association between change in local climatic variables and the occurrence of chytridiomycosis within this region. Specifically, we show that rising temperature is linked to the occurrence of chytrid-related disease, consistent with the chytrid-thermal-optimum hypothesis. We show that these local variables are driven by general circulation patterns, principally the North Atlantic Oscillation. Given that B. dendrobatidis is known to be broadly distributed across Europe, there is now an urgent need to assess the generality of our finding and determine whether climate-driven epidemics may be expected to impact on amphibian species across the wider region.

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Quantifying Differences in Circulation Patterns Based on Probabilistic Models: IPCC AR4 Multimodel Comparison for the North Atlantic*

Journal of Climate ◽

10.1175/2010jcli3432.1 ◽

2010 ◽

Vol 23 (24) ◽

pp. 6573-6589 ◽

Cited By ~ 22

Author(s):

Henning W. Rust ◽

Mathieu Vrac ◽

Matthieu Lengaigne ◽

Benjamin Sultan

Keyword(s):

Climate Change ◽

North Atlantic ◽

General Circulation ◽

Gaussian Mixture ◽

Reanalysis Data ◽

Shape Information ◽

Size And Shape ◽

The North ◽

Circulation Patterns ◽

The North Atlantic

Abstract The comparison of circulation patterns (CPs) obtained from reanalysis data to those from general circulation model (GCM) simulations is a frequent task for model validation, downscaling of GCM simulations, or other climate change–related studies. Here, the authors suggest a set of measures to quantify the differences between CPs. A combination of clustering using Gaussian mixture models with a set of related difference measures allows for taking cluster size and shape information into account and thus provides more information than the Euclidean distances between cluster centroids. The characteristics of the various distance measures are illustrated with a simple simulated example. Subsequently, a five-component Gaussian mixture to define circulation patterns for the North Atlantic region from reanalysis data and GCM simulations is used. CPs are obtained independently for the NCEP–NCAR reanalysis and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), as well as for twentieth-century simulations from 14 GCMs of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) database. After discussing the difference of CPs based on spherical and nonspherical clusters for the reanalysis datasets, the authors give a detailed evaluation of the cluster configuration for two GCMs relative to NCEP–NCAR. Finally, as an illustration, the capability of reproducing the NCEP–NCAR probability density function (pdf) defining the Greenland anticyclone CP is evaluated for all 14 GCMs, considering that the size and shape of the underlying pdfs complement the commonly used Euclidean distance of CPs’ mean values.

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Granger Causality of Coupled Climate Processes: Ocean Feedback on the North Atlantic Oscillation

Journal of Climate ◽

10.1175/jcli3653.1 ◽

2006 ◽

Vol 19 (7) ◽

pp. 1182-1194 ◽

Cited By ~ 102

Author(s):

Timothy J. Mosedale ◽

David B. Stephenson ◽

Matthew Collins ◽

Terence C. Mills

Keyword(s):

Time Series ◽

North Atlantic Oscillation ◽

Granger Causality ◽

North Atlantic ◽

General Circulation ◽

Careful Examination ◽

The North ◽

The North Atlantic ◽

The North Atlantic Oscillation

Abstract This study uses a Granger causality time series modeling approach to quantitatively diagnose the feedback of daily sea surface temperatures (SSTs) on daily values of the North Atlantic Oscillation (NAO) as simulated by a realistic coupled general circulation model (GCM). Bivariate vector autoregressive time series models are carefully fitted to daily wintertime SST and NAO time series produced by a 50-yr simulation of the Third Hadley Centre Coupled Ocean–Atmosphere GCM (HadCM3). The approach demonstrates that there is a small yet statistically significant feedback of SSTs on the NAO. The SST tripole index is found to provide additional predictive information for the NAO than that available by using only past values of NAO—the SST tripole is Granger causal for the NAO. Careful examination of local SSTs reveals that much of this effect is due to the effect of SSTs in the region of the Gulf Steam, especially south of Cape Hatteras. The effect of SSTs on NAO is responsible for the slower-than-exponential decay in lag-autocorrelations of NAO notable at lags longer than 10 days. The persistence induced in daily NAO by SSTs causes long-term means of NAO to have more variance than expected from averaging NAO noise if there is no feedback of the ocean on the atmosphere. There are greater long-term trends in NAO than can be expected from aggregating just short-term atmospheric noise, and NAO is potentially predictable provided that future SSTs are known. For example, there is about 10%–30% more variance in seasonal wintertime means of NAO and almost 70% more variance in annual means of NAO due to SST effects than one would expect if NAO were a purely atmospheric process.

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Short-term response to the North Atlantic Oscillation but no long-term effects of climate change on the reproductive success of an alpine bird

Journal of Ornithology ◽

10.1007/s10336-010-0623-8 ◽

2010 ◽

Vol 152 (3) ◽

pp. 631-641 ◽

Cited By ~ 8

Author(s):

Jean-Yves Barnagaud ◽

Pierre André Crochet ◽

Yann Magnani ◽

Ariane Bernard Laurent ◽

Emmanuel Menoni ◽

...

Keyword(s):

Climate Change ◽

Reproductive Success ◽

North Atlantic ◽

Long Term Effects ◽

Short Term ◽

The North ◽

The North Atlantic ◽

The North Atlantic Oscillation ◽

Term Response

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Detecting Climate Driven Changes in Chlorophyll-a in Deep Subalpine Lakes Using Long Term Satellite Data

Water ◽

10.3390/w13060866 ◽

2021 ◽

Vol 13 (6) ◽

pp. 866

Author(s):

Gary Free ◽

Mariano Bresciani ◽

Monica Pinardi ◽

Nicola Ghirardi ◽

Giulia Luciani ◽

...

Keyword(s):

Climate Change ◽

Chlorophyll A ◽

Nutrient Dynamics ◽

Cascading Effects ◽

The North ◽

Subalpine Lakes ◽

Winter Temperatures ◽

Decadal Climate ◽

The North Atlantic Oscillation ◽

Traditional Pattern

Climate change has increased the temperature and altered the mixing regime of high-value lakes in the subalpine region of Northern Italy. Remote sensing of chlorophyll-a can help provide a time series to allow an assessment of the ecological implications of this. Non-parametric multiplicative regression (NPMR) was used to visualize and understand the changes that have occurred between 2003–2018 in Lakes Garda, Como, Iseo, and Maggiore. In all four deep subalpine lakes, there has been a disruption from a traditional pattern of a significant spring chlorophyll-a peak followed by a clear water phase and summer/autumn peaks. This was replaced after 2010–2012, with lower spring peaks and a tendency for annual maxima to occur in summer. There was a tendency for this switch to be interspersed by a two-year period of low chlorophyll-a. Variables that were significant in NPMR included time, air temperature, total phosphorus, winter temperature, and winter values for the North Atlantic Oscillation. The change from spring to summer chlorophyll-a maxima, relatively sudden in an ecological context, could be interpreted as a regime shift. The cause was probably cascading effects from increased winter temperatures, reduced winter mixing, and altered nutrient dynamics. Future trends will depend on climate change and inter-decadal climate drivers.

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Shared socioeconomic pathways for climate change research in Finland: co-developing extended SSP narratives for agriculture

Regional Environmental Change ◽

10.1007/s10113-020-01734-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Heikki S. Lehtonen ◽

Jyrki Aakkula ◽

Stefan Fronzek ◽

Janne Helin ◽

Mikael Hildén ◽

...

Keyword(s):

Climate Change ◽

National Level ◽

Global Scale ◽

Change Scenario ◽

Policy Makers ◽

Climate Change Research ◽

Food And Agriculture ◽

Agriculture And Food ◽

Farm Subsidies

AbstractShared socioeconomic pathways (SSPs), developed at global scale, comprise narrative descriptions and quantifications of future world developments that are intended for climate change scenario analysis. However, their extension to national and regional scales can be challenging. Here, we present SSP narratives co-developed with stakeholders for the agriculture and food sector in Finland. These are derived from intensive discussions at a workshop attended by approximately 39 participants offering a range of sectoral perspectives. Using general background descriptions of the SSPs for Europe, facilitated discussions were held in parallel for each of four SSPs reflecting very different contexts for the development of the sector up to 2050 and beyond. Discussions focused on five themes from the perspectives of consumers, producers and policy-makers, included a joint final session and allowed for post-workshop feedback. Results reflect careful sector-based, national-level interpretations of the global SSPs from which we have constructed consensus narratives. Our results also show important critical remarks and minority viewpoints. Interesting features of the Finnish narratives compared to the global SSP narratives include greater emphasis on environmental quality; significant land abandonment in SSPs with reduced livestock production and increased plant-based diets; continued need for some farm subsidies across all SSPs and opportunities for diversifying domestic production under scenarios of restricted trade. Our results can contribute to the development of more detailed national long-term scenarios for food and agriculture that are both relevant for local stakeholders and researchers as well as being consistent with global scenarios being applied internationally.

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Vulnerability of the North Water ecosystem to climate change

Nature Communications ◽

10.1038/s41467-021-24742-0 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Sofia Ribeiro ◽

Audrey Limoges ◽

Guillaume Massé ◽

Kasper L. Johansen ◽

William Colgan ◽

...

Keyword(s):

Climate Change ◽

Sea Ice ◽

Late Holocene ◽

Sediment Cores ◽

Arctic Ecosystems ◽

Little Auk ◽

The North ◽

Water Ecosystem ◽

North Water

AbstractHigh Arctic ecosystems and Indigenous livelihoods are tightly linked and exposed to climate change, yet assessing their sensitivity requires a long-term perspective. Here, we assess the vulnerability of the North Water polynya, a unique seaice ecosystem that sustains the world’s northernmost Inuit communities and several keystone Arctic species. We reconstruct mid-to-late Holocene changes in sea ice, marine primary production, and little auk colony dynamics through multi-proxy analysis of marine and lake sediment cores. Our results suggest a productive ecosystem by 4400–4200 cal yrs b2k coincident with the arrival of the first humans in Greenland. Climate forcing during the late Holocene, leading to periods of polynya instability and marine productivity decline, is strikingly coeval with the human abandonment of Greenland from c. 2200–1200 cal yrs b2k. Our long-term perspective highlights the future decline of the North Water ecosystem, due to climate warming and changing sea-ice conditions, as an important climate change risk.

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A Regime View of the North Atlantic Oscillation and Its Response to Anthropogenic Forcing

Journal of Climate ◽

10.1175/2009jcli3087.1 ◽

2010 ◽

Vol 23 (6) ◽

pp. 1291-1307 ◽

Cited By ~ 90

Author(s):

Tim Woollings ◽

Abdel Hannachi ◽

Brian Hoskins ◽

Andrew Turner

Keyword(s):

North Atlantic Oscillation ◽

North Atlantic ◽

Anthropogenic Forcing ◽

The Third ◽

The North ◽

Nao Index ◽

Future Behavior ◽

Real Change ◽

The North Atlantic Oscillation

Abstract The distribution of the daily wintertime North Atlantic Oscillation (NAO) index in the 40-yr ECMWF Re-Analysis (ERA-40) is significantly negatively skewed. Dynamical and statistical analyses both suggest that this skewness reflects the presence of two distinct regimes—referred to as “Greenland blocking” and “subpolar jet.” Changes in both the relative occurrence and in the structure of the regimes are shown to contribute to the long-term NAO trend over the ERA-40 period. This is contrasted with the simulation of the NAO in 100-yr control and doubled CO2 integrations of the third climate configuration of the Met Office Unified Model (HadCM3). The model has clear deficiencies in its simulation of the NAO in the control run, so its predictions of future behavior must be treated with caution. However, the subpolar jet regime does become more dominant under anthropogenic forcing and, while this change is small it is clearly statistically significant and does represent a real change in the nature of NAO variability in the model.

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Impact of precipitation intermittency on NAO-temperature signals in proxy records

Climate of the Past ◽

10.5194/cp-9-871-2013 ◽

2013 ◽

Vol 9 (2) ◽

pp. 871-886 ◽

Cited By ~ 23

Author(s):

M. Casado ◽

P. Ortega ◽

V. Masson-Delmotte ◽

C. Risi ◽

D. Swingedouw ◽

...

Keyword(s):

General Circulation ◽

Ice Core ◽

Circulation Model ◽

Ice Cores ◽

Stable Isotope Ratio ◽

Global Network ◽

Temporal Correlations ◽

The North ◽

The North Atlantic Oscillation ◽

The Impact

Abstract. In mid and high latitudes, the stable isotope ratio in precipitation is driven by changes in temperature, which control atmospheric distillation. This relationship forms the basis for many continental paleoclimatic reconstructions using direct (e.g. ice cores) or indirect (e.g. tree ring cellulose, speleothem calcite) archives of past precipitation. However, the archiving process is inherently biased by intermittency of precipitation. Here, we use two sets of atmospheric reanalyses (NCEP (National Centers for Environmental Prediction) and ERA-interim) to quantify this precipitation intermittency bias, by comparing seasonal (winter and summer) temperatures estimated with and without precipitation weighting. We show that this bias reaches up to 10 °C and has large interannual variability. We then assess the impact of precipitation intermittency on the strength and stability of temporal correlations between seasonal temperatures and the North Atlantic Oscillation (NAO). Precipitation weighting reduces the correlation between winter NAO and temperature in some areas (e.g. Québec, South-East USA, East Greenland, East Siberia, Mediterranean sector) but does not alter the main patterns of correlation. The correlations between NAO, δ18O in precipitation, temperature and precipitation weighted temperature are investigated using outputs of an atmospheric general circulation model enabled with stable isotopes and nudged using reanalyses (LMDZiso (Laboratoire de Météorologie Dynamique Zoom)). In winter, LMDZiso shows similar correlation values between the NAO and both the precipitation weighted temperature and δ18O in precipitation, thus suggesting limited impacts of moisture origin. Correlations of comparable magnitude are obtained for the available observational evidence (GNIP (Global Network of Isotopes in Precipitation) and Greenland ice core data). Our findings support the use of archives of past δ18O for NAO reconstructions.

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Soil salinization under different climate change scenarios: A global scale analysis

10.5194/egusphere-egu21-13668 ◽

2021 ◽

Author(s):

Nima Shokri ◽

Amirhossein Hassani ◽

Adisa Azapagic

Keyword(s):

Climate Change ◽

Water Resources ◽

Soil Salinity ◽

Global Scale ◽

Soil Salinization ◽

Water Evaporation ◽

Climate Change Scenarios ◽

Spatio Temporal ◽

Salt Affected Soils

Population growth and climate change is projected to increase the pressure on land and water resources, especially in arid and semi-arid regions. This pressure is expected to affect all driving mechanisms of soil salinization comprising alteration in soil hydrological balance, sea salt intrusion, wet/dry deposition of wind-born saline aerosols &#8212; leading to an increase in soil salinity. Soil salinity influences soil stability, bio-diversity, ecosystem functioning and soil water evaporation (1). It can be a long-term threat to agricultural activities and food security. To devise sustainable action plan investments and policy interventions, it is crucial to know when and where salt-affected soils occur. However, current estimates on spatio-temporal variability of salt-affected soils are majorly localized and future projections in response to climate change are rare. Using Machine Learning (ML) algorithms, we related the available measured soil salinity values (represented by electrical conductivity of the saturated paste soil extract, ECe) to some environmental information (or predictors including outputs of Global Circulation Models, soil, crop, topographic, climatic, vegetative, and landscape properties of the sampling locations) to develop a set of data-driven predictive tools to enable the spatio-temporal predictions of soil salinity. The outputs of these tools helped us to estimate the extent and severity of the soil salinity under current and future climatic patterns at different geographical levels and identify the salinization hotspots by the end of the 21st century in response to climate change. Our analysis suggests that a soil area of 11.73 Mkm2 located in non-frigid zones has been salt-affected in at least three-fourths of the 1980 - 2018 period (2). At the country level, Brazil, Peru, Sudan, Colombia, and Namibia were estimated to have the highest rates of annual increase in the total area of soils with an ECe &#8805; 4 dS m-1. Additionally, the results indicate that by the end of the 21st century, drylands of South America, southern and Western Australia, Mexico, southwest United States, and South Africa will be the salinization hotspots (compared to the 1961 - 1990 period). The results of this study could inform decision-making and contribute to attaining the United Nation&#8217;s Sustainable Development Goals for land and water resources management.1. Shokri-Kuehni, S.M.S., Raaijmakers, B., Kurz, T., Or, D., Helmig, R., Shokri, N. (2020). Water Table Depth and Soil Salinization: From Pore-Scale Processes to Field-Scale Responses. Water Resour. Res., 56, e2019WR026707. https://doi.org/ 10.1029/2019WR0267072. Hassani, A., Azapagic, A., Shokri, N. (2020). Predicting Long-term Dynamics of Soil Salinity and Sodicity on a Global Scale, Proc. Nat. Acad. Sci., 117, 52, 33017&#8211;33027. https://doi.org/10.1073/pnas.2013771117

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Global long-term land surface temperature for NOAA AVHRR: extension from 1981-2000 to 1981-2020

10.5194/egusphere-egu21-14373 ◽

2021 ◽

Author(s):

Jin Ma ◽

Ji Zhou

Keyword(s):

Climate Change ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Global Scale ◽

Mean Bias Error ◽

Bias Error ◽

Important Indicator ◽

Noaa Avhrr

As an important indicator of land-atmosphere energy interaction, land surface temperature (LST) plays an important role in the research of climate change, hydrology, and various land surface processes. Compared with traditional ground-based observation, satellite remote sensing provides the possibility to retrieve LST more efficiently over a global scale. Since the lack of global LST before, Ma et al., (2020) released a global 0.05 &#215;0.05&#160; long-term (1981-2000) LST based on NOAA-7/9/11/14 AVHRR. The dataset includes three layers: (1) instantaneous LST, a product generated based on an ensemble of several split-window algorithms with a random forest (RF-SWA); (2) orbital-drift-corrected (ODC) LST, a drift-corrected version of RF-SWA LST at 14:30 solar time; and (3) monthly averages of ODC LST. To meet the requirement of the long-term application, e.g. climate change, the period of the LST is extended from 1981-2000 to 1981-2020 in this study. The LST from 2001 to 2020 are retrieved from NOAA-16/18/19 AVHRR with the same algorithm for NOAA-7/8/11/14 AVHRR. The train and test results based on the simulation data from SeeBor and TIGR atmospheric profiles show that the accuracy of the RF-SWA method for the three sensors is consistent with the previous four sensors, i.e. the mean bias error and standard deviation less than 0.10 K and 1.10 K, respectively, under the assumption that the maximum emissivity and water vapor content uncertainties are 0.04 and 1.0 g/cm2, respectively. The preliminary validation against in-situ LST also shows a similar accuracy, indicating that the accuracy of LST from 1981 to 2020 are consistent with each other. In the generation code, the new LST has been improved in terms of land surface emissivity estimation, identification of cloud pixel, and the ODC method in order to generate a more reliable LST dataset. Up to now, the new version LST product (1981-2020) is under generating and will be released soon in support of the scientific research community.

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