Climate variability and breeding parameters of a transhemispheric migratory seabird over seven decades

2020 ◽  
Vol 642 ◽  
pp. 191-205 ◽  
Author(s):  
CA Price ◽  
K Hartmann ◽  
TJ Emery ◽  
EJ Woehler ◽  
CR McMahon ◽  
...  

Climate variability affects physical oceanographic systems and environmental conditions at multiple spatial and temporal scales. These changes can influence biological and ecological processes, from primary productivity to higher trophic levels. Short-tailed shearwaters Ardenna tenuirostris are transhemispheric migratory procellariiform seabirds that forage on secondary consumers such as fish (myctophids) and zooplankton (euphausiids). In this study, we investigated the breeding parameters of the short-tailed shearwater from a colony of 100 to 200 breeding pairs at Fisher Island, Tasmania, Australia, for the period 1950 to 2012, with the aim to quantify the relationship between breeding parameters with large-scale climate indices in the Northern (i.e. Northern Pacific Index and Pacific Decadal Oscillation) and Southern Hemispheres (i.e. El Niño-Southern Oscillation and Southern Annular Mode). Through the use of generalised linear models, we found that breeding participation among short-tailed shearwaters was affected by climate variability with a 12-mo temporal lag. Furthermore, breeding success decreased in years of increased rainfall at the colony. These findings demonstrate that both large-scale climate indices and local environmental conditions could explain some of the variability among breeding parameters of the short-tailed shearwater.

2021 ◽  
Author(s):  
Abolfazl Rezaei

Abstract The ability to predict future variability of groundwater resources in time and space is of critical
importance in society’s adaptation to climate variability and change. Periodic control of large scale ocean-atmospheric circulations on groundwater levels proposes a potentially effective source of longer term forecasting capability. In this study, as a first national-scale assessment, we use the continues wavelet transform, global power spectrum, and wavelet coherence analyses to quantify the controls of the Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and El Niño Southern Oscillation (ENSO) over the representative groundwater levels of the 24 principal aquifers, scattered across different 14 climate zones of Iran. The results demonstrate that aquifer storage variations are partially controlled by annual to interdecadal climate variability and are not solely a function of pumping variations. Moreover, teleconnections are observed to be both frequency and time specific. The significant coherence patterns between the climate indices and groundwater levels are observed at five frequency bands of the annual (~1-yr), interannual (2-4- and 4-6-yr), decadal (8-12-yr), and interdecadal (14-18yr), consistent with the dominant modes of climate indices. AMO’s strong footprint is observed at interdecadal and annual modes of groundwater levels while PDO’s highest imprint is seen in interannual, decadal, and interdecadal modes. The highest controlling influence of ENSO is observed across the decadal and interannual modes whereas the NAO’s footprint is marked at annual and interdecadal frequency bands. Further, it is observed that the groundwater variability being higher modulated by a combination of large-scale atmospheric circulations rather than each individual index. The decadal and interdecadal oscillation modes constitute the dominant modes in Iranian aquifers. Findings also mark the unsaturated zone contribution in damping and lagging of the climate variability modes, particularly for the higher frequency indices of ENSO and NAO where the groundwater variability is observed to be more correlated with lower frequent climate circulations such as PDO and AMO, rather than ENSO and NAO. Finally, it is found that the data length can significantly affect the teleconnections if the time series are not contemporaneous and only one value of coherence/correlation is computed for each particular series instead of separate computations for different frequency bands and different time spans.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
José Abreu ◽  
Richard A. Phillips ◽  
Filipe R. Ceia ◽  
Louise Ireland ◽  
Vítor H. Paiva ◽  
...  

Abstract Long-term studies of pelagic nekton in the Southern Ocean and their responses to ongoing environmental change are rare. Using stable isotope ratios measured in squid beaks recovered from diet samples of wandering albatrosses Diomedea exulans, we assessed decadal variation (from 1976 to 2016) in the habitat (δ13C) and trophic level (δ15N) of five important Southern Ocean squid species in relation to indices of environmental conditions—Southern Oscillation Index (SOI) and Southern Annular Mode (SAM). Based on δ13C values, corrected for the Suess effect, habitat had changed over the last 50 years for Taonius sp. B (Voss), Gonatus antarcticus, Galiteuthis glacialis and Histioteuthis atlantica but not Moroteuthopsis longimana. By comparison, mean δ15N values were similar across decades for all five species, suggesting minimal changes in trophic levels. Both SAM and SOI have increased in strength and frequency over the study period but, of the five species, only in Taonius sp. B (Voss) did these indices correlate with, δ13C and δ15N values, indicating direct relationships between environmental conditions, habitat and trophic level. The five cephalopod species therefore changed their habitats with changing environmental conditions over the last 50 years but maintained similar trophic levels. Hence, cephalopods are likely to remain important prey for top predators in Southern Ocean food webs, despite ongoing climate change.


2012 ◽  
Vol 25 (16) ◽  
pp. 5451-5469 ◽  
Author(s):  
Graham R. Simpkins ◽  
Laura M. Ciasto ◽  
David. W. J. Thompson ◽  
Matthew H. England

Abstract The observed relationships between anomalous Antarctic sea ice concentration (SIC) and the leading patterns of Southern Hemisphere (SH) large-scale climate variability are examined as a function of season over 1980–2008. Particular emphasis is placed on 1) the interactions between SIC, the southern annular mode (SAM), and El Niño–Southern Oscillation (ENSO); and 2) the contribution of these two leading modes to the 29-yr trends in sea ice. Regression, composite, and principal component analyses highlight a seasonality in SH sea ice–atmosphere interactions, whereby Antarctic sea ice variability exhibits the strongest linkages to the SAM and ENSO during the austral cold season months. As noted in previous work, a dipole in SIC anomalies emerges in relation to the SAM, characterized by centers of action located near the Bellingshausen/Weddell and Amundsen/eastern Ross Seas. The structure and magnitude of this SIC dipole is found to vary considerably as a function of season, consistent with the seasonality of the overlying atmospheric circulation anomalies. Relative to the SAM, the pattern of sea ice anomalies linked to ENSO exhibits a similar seasonality but tends to be weaker in amplitude and more diffuse in structure. The relationships between ENSO and sea ice also exhibit a substantial nonlinear component, highlighting the need to consider both season and phase of the ENSO cycle when diagnosing ENSO–SIC linkages. Trends in SIC over 1980–2008 are not significantly related to trends in either the SAM or ENSO during any season, including austral summer when the trend in the SAM is most pronounced.


2015 ◽  
Vol 28 (6) ◽  
pp. 2475-2493 ◽  
Author(s):  
Liang Ning ◽  
Raymond S. Bradley

Abstract The relationship between winter climate extremes across the northeastern United States and adjacent parts of Canada and some important modes of climate variability are examined to determine how these circulation patterns are related to extreme events. Linear correlations between 15 extreme climate indices related to winter daily precipitation, maximum and minimum temperature, and three dominant large-scale patterns of climate variability [the North Atlantic Oscillation (NAO), Pacific–North American (PNA) pattern, and El Niño–Southern Oscillation (ENSO)] were analyzed for the period 1950–99. The mechanisms behind these teleconnections are analyzed by applying composite analysis to the geopotential height, sea level pressure (SLP), moisture flux, and wind fields. Pressure anomalies and associated airflow patterns related with the different modes of climate variability explain the patterns of temperature and precipitation extremes across the region. The responses of the daily scale climate extremes to the seasonally averaged large-scale circulation patterns are achieved through shifts in the probability distributions.


2021 ◽  
Author(s):  
Mark D. Risser ◽  
Michael F. Wehner ◽  
John P. O’Brien ◽  
Christina M. Patricola ◽  
Travis A. O’Brien ◽  
...  

AbstractWhile various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.


2018 ◽  
Vol 22 (6) ◽  
pp. 3105-3124 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Howard Simon Wheater ◽  
Barrie Bonsal ◽  
Saman Razavi ◽  
Sopan Kurkute

Abstract. Drought is a recurring extreme climate event and among the most costly natural disasters in the world. This is particularly true over Canada, where drought is both a frequent and damaging phenomenon with impacts on regional water resources, agriculture, industry, aquatic ecosystems, and health. However, nationwide drought assessments are currently lacking and impacted by limited ground-based observations. This study provides a comprehensive analysis of historical droughts over the whole of Canada, including the role of large-scale teleconnections. Drought events are characterized by the Standardized Precipitation Evapotranspiration Index (SPEI) over various temporal scales (1, 3, 6, and 12 consecutive months, 6 months from April to September, and 12 months from October to September) applied to different gridded monthly data sets for the period 1950–2013. The Mann–Kendall test, rotated empirical orthogonal function, continuous wavelet transform, and wavelet coherence analyses are used, respectively, to investigate the trend, spatio-temporal patterns, periodicity, and teleconnectivity of drought events. Results indicate that southern (northern) parts of the country experienced significant trends towards drier (wetter) conditions although substantial variability exists. Two spatially well-defined regions with different temporal evolution of droughts were identified – the Canadian Prairies and northern central Canada. The analyses also revealed the presence of a dominant periodicity of between 8 and 32 months in the Prairie region and between 8 and 40 months in the northern central region. These cycles of low-frequency variability are found to be associated principally with the Pacific–North American (PNA) and Multivariate El Niño/Southern Oscillation Index (MEI) relative to other considered large-scale climate indices. This study is the first of its kind to identify dominant periodicities in drought variability over the whole of Canada in terms of when the drought events occur, their duration, and how often they occur.


2013 ◽  
Vol 33 ◽  
pp. 3-12 ◽  
Author(s):  
C. Collins ◽  
A. Mascarenhas ◽  
R. Martinez

Abstract. From 27 March to 5 April 2009, upper ocean velocities between the Galápagos Islands and Ecuador were measured using a vessel mounted ADCP. A region of possible strong cross-hemisphere exchange was observed immediately to the east of the Galápagos, where a shallow (200 m) 300 km wide northeastward surface flow transported 7–11 Sv. Underlying this strong northeastward surface current, a southward flowing undercurrent was observed which was at least 600 m thick, 100 km wide, and had an observed transport of 7–8 Sv. Next to the Ecuador coast, the shallow (< 200 m) Ecuador Coastal Current was observed to extend offshore 100 km with strongest flow, 0.33 m s−1, near the surface. Immediately to the west of the Ecuador Coastal Current, flow was directed eastward and southward into the beginnings of the Peru-Chile Countercurrent. The integral of the surface currents between the Galápagos and Ecuador agreed well with observed sea level differences. Although the correlation of the sea level differences with large scale climate indices (Niño3 and the Southern Oscillation Index) was significant, more than half of the sea level variability was not explained. Seasonal variability of the sea level difference indicated that sea level was 2 cm higher at the Galápagos during late winter and early spring, which could be associated with the pattern of northward surface flows observed by R/V Knorr.


2020 ◽  
Vol 33 (10) ◽  
pp. 4009-4025
Author(s):  
Shuyu Zhang ◽  
Thian Yew Gan ◽  
Andrew B. G. Bush

AbstractUnder global warming, Arctic sea ice has declined significantly in recent decades, with years of extremely low sea ice occurring more frequently. Recent studies suggest that teleconnections with large-scale climate patterns could induce the observed extreme sea ice loss. In this study, a probabilistic analysis of Arctic sea ice was conducted using quantile regression analysis with covariates, including time and climate indices. From temporal trends at quantile levels from 0.01 to 0.99, Arctic sea ice shows statistically significant decreases over all quantile levels, although of different magnitudes at different quantiles. At the representative extreme quantile levels of the 5th and 95th percentiles, the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), and the Pacific–North American pattern (PNA) have more significant influence on Arctic sea ice than El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), and the Atlantic multidecadal oscillation (AMO). Positive AO as well as positive NAO contribute to low winter sea ice, and a positive PNA contributes to low summer Arctic sea ice. If, in addition to these conditions, there is concurrently positive AMO and PDO, the sea ice decrease is amplified. Teleconnections between Arctic sea ice and the climate patterns were demonstrated through a composite analysis of the climate variables. The anomalously strong anticyclonic circulation during the years of positive AO, NAO, and PNA promotes more sea ice export through Fram Strait, resulting in excessive sea ice loss. The probabilistic analyses of the teleconnections between the Arctic sea ice and climate patterns confirm the crucial role that the climate patterns and their combinations play in overall sea ice reduction, but particularly for the low and high quantiles of sea ice concentration.


2012 ◽  
Vol 70 (2) ◽  
pp. 319-328 ◽  
Author(s):  
Antoni Quetglas ◽  
Francesc Ordines ◽  
Manuel Hidalgo ◽  
Sebastià Monserrat ◽  
Susana Ruiz ◽  
...  

Abstract Quetglas, A., Ordines, F., Hidalgo, M., Monserrat, S., Ruiz, S., Amores, Á., Moranta, J., and Massutí, E. 2013. Synchronous combined effects of fishing and climate within a demersal community. – ICES Journal of Marine Science, 70: 319–328. Accumulating evidence shows that fishing exploitation and environmental variables can synergistically affect the population dynamics of exploited populations. Here, we document an interaction between fishing impact and climate variability that triggered a synchronic response in the population fluctuations of six exploited species in the Mediterranean from 1965–2008. Throughout this period, the fishing activity experienced a sharp increase in fishing effort, which caused all stocks to shift from an early period of underexploitation to a later period of overexploitation. This change altered the population resilience of the stocks and brought about an increase in the sensitivity of its dynamics to climate variability. Landings increased exponentially when underexploited but displayed an oscillatory behaviour once overexploited. Climatic indices, related to the Mediterranean mesoscale hydrography and large-scale north Atlantic climatic variability, seemed to affect the species with broader age structure and longer lifespan, while the global-scale El Niño Southern Oscillation index (ENSO) positively influenced the population abundances of species with a narrow age structure and short lifespan. The species affected by ENSO preferentially inhabit the continental shelf, suggesting that Mediterranean shelf ecosystems are sensitive to the hydroclimatic variability linked to global climate.


Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 374 ◽  
Author(s):  
Taereem Kim ◽  
Ju-Young Shin ◽  
Hanbeen Kim ◽  
Sunghun Kim ◽  
Jun-Haeng Heo

Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential information about climate variability, as they usually have a direct or indirect correlation with hydrologic variables. This study aims to use large-scale climate indices in monthly reservoir inflow forecasting for considering climate variability. For this purpose, time series and artificial intelligence models, such as Seasonal AutoRegressive Integrated Moving Average (SARIMA), SARIMA with eXogenous variables (SARIMAX), Artificial Neural Network (ANN), Adaptive Neural-based Fuzzy Inference System (ANFIS), and Random Forest (RF) models were employed with two types of input variables, autoregressive variables (AR-) and a combination of autoregressive and exogenous variables (ARX-). Several statistical methods, including ensemble empirical mode decomposition (EEMD), were used to select the lagged climate indices. Finally, monthly reservoir inflow was forecasted by SARIMA, SARIMAX, AR-ANN, ARX-ANN, AR-ANFIS, ARX-ANFIS, AR-RF, and ARX-RF models. As a result, the use of climate indices in artificial intelligence models showed a potential to improve the model performance, and the ARX-ANN and AR-RF models generally showed the best performance among the employed models.


Sign in / Sign up

Export Citation Format

Share Document