988 resultados para Scale Climate Variability


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We use the oxygen isotopic composition of planktonic foraminifera Globigerinoides ruber (white) from Ocean Drilling Program Site 1058 in the subtropical northwestern Atlantic to construct a high-resolution (~800 year) climate record spanning the mid-Pleistocene climate transition (~410 ka to 1350 ka). We investigate whether or not millennial-scale instabilities in the proxy record are associated with the extent of continental glaciation. G. ruber d18O values display high-frequency fluctuations throughout the record, but the amplitude about mean glacial and interglacial d18O values increases at marine isotope stage (MIS) 22 (880 ka) and is highest during MIS 12. These observations support that millennial-scale climate instabilities are associated with ice sheet size. Time series analysis illustrates that these variations have significant concentration of spectral power centered on periods of ~10-12 ka and ~5 ka. The timing of these fluctuations agrees well, or coincides with, the periodicities of the second and fourth harmonics, respectively, of precessional forcing at the equator. An insolation-based origin of the millennial-scale instabilities would be independent of ice volume and explains the presence of these fluctuations before the mid-Pleistocene climate transition as well as during interglacial intervals (e.g., MIS 37 and 17). Because the amplitude of the millennial-scale variations increases during the mid-Pleistocene transition, feedback mechanisms associated with the growth of large, 100-ka-paced, polar ice sheets may be important amplifiers of regional surface water hydrographic changes.

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The middle Miocene delta18O increase represents a fundamental change in earth's climate system due to a major expansion and permanent establishment of the East Antarctic Ice Sheet accompanied by some effect of deepwater cooling. The long-term cooling trend in the middle to late Miocene was superimposed by several punctuated periods of glaciations (Mi-Events) characterized by oxygen isotopic shifts that have been related to the waxing and waning of the Antarctic ice-sheet and bottom water cooling. Here, we present a high-resolution benthic stable oxygen isotope record from ODP Site 1085 located at the southwestern African continental margin that provides a detailed chronology for the middle to late Miocene (13.9-7.3 Ma) climate transition in the eastern South Atlantic. A composite Fe intensity record obtained by XRF core scanning ODP Sites 1085 and 1087 was used to construct an astronomically calibrated chronology based on orbital tuning. The oxygen isotope data exhibit four distinct delta18O excursions, which have astronomical ages of 13.8, 13.2, 11.7, and 10.4 Ma and correspond to the Mi3, Mi4, Mi5, and Mi6 events. A global climate record was extracted from the oxygen isotopic composition. Both long- and short-term variabilities in the climate record are discussed in terms of sea-level and deep-water temperature changes. The oxygen isotope data support a causal link between sequence boundaries traced from the shelf and glacioeustatic changes due to ice-sheet growth. Spectral analysis of the benthic delta18O record shows strong power in the 400-kyr and 100-kyr bands documenting a paleoceanographic response to eccentricity-modulated variations in precession. A spectral peak around 180-kyr might be related to the asymmetry of the obliquity cycle indicating that the response of the dominantly unipolar Antarctic ice-sheet to obliquityinduced variations probably controlled the middle to late Miocene climate system. Maxima in the delta18O record, interpreted as glacial periods, correspond to minima in 100-kyr eccentricity cycle and minima in the 174-kyr obliquity modulation. Strong middle to late Miocene glacial events are associated with 400-kyr eccentricity minima and obliquity modulation minima. Thus, fluctuations in the amplitude of obliquity and eccentricity seem to be the driving force for the middle to late Miocene climate variability.

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Climate variability and changes in the frequency of extremes events have a direct impact on crop yield and damages. Climate anomalies projections at monthly and yearly timescale allows us for adapting a cropping system (crops, varieties and management) to take advantage of favorable conditions or reduce the effect of adverse conditions. The objective of this work is to develop indices to evaluate the effect of climatic variability in summer cropping systems of Iberian Peninsula, in an attempt of relating yield variability to climate variability, extending the work of Rodríguez-Puebla (2004).

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La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

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Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.

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The relative roles of high- versus low-latitude forcing of millennial-scale climate variability are still not well understood. Here we present terrestrial–marine climate profiles from the southwestern Iberian margin, a region particularly affected by precession, that show millennial climate oscillations related to a nonlinear response to the Earth's precession cycle during Marine Isotope Stage (MIS) 19. MIS 19 has been considered the best analogue to our present interglacial from an astronomical point of view due to the reduced eccentricity centred at 785 ka. In our records, seven millennial-scale forest contractions punctuated MIS 19 superimposed to two orbitally-driven Mediterranean forest expansions. In contrast to our present interglacial, we evidence for the first time low latitude-driven 5000-yr cycles of drying and cooling in the western Mediterranean region, along with warmth in the subtropical gyre related to the fourth harmonic of precession. These cycles indicate repeated intensification of North Atlantic meridional moisture transport that along with decrease in boreal summer insolation triggered ice growth and may have contributed to the glacial inception, at ∼774 ka. The freshwater fluxes during MIS 19ab amplified the cooling events in the North Atlantic promoting further cooling and leading to MIS 18 glaciation. The discrepancy between the dominant cyclicity observed during MIS 1, 2500-yr, and that of MIS 19, 5000-yr, challenges the similar duration of the Holocene and MIS 19c interglacials under natural boundary conditions.

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Lake Annie is a small (37 ha), relatively deep (21 m) sinkhole lake on the Lake Wales Ridge (LWR) of central Florida with a long history of study, including monthly limnological monitoring since June, 1983. The record shows high variability in Secchi disc transparency, which ranged from < 1 to 15 m with a trend toward decreasing values over the latter decade of record. We examined available regional meteorological, groundwater and limnological data to determine the drivers and thermal consequences of variability in water transparency. While total nutrient concentrations and chlorophyll-a were highest during years of low transparency, stepwise regression showed that none of these had a signifi cant effect on transparency after water color was taken into account. Repeated years of high precipitation between 1993–2005 caused an increase in water table height, increasing the transport of dissolved substances from the vegetated watershed into the lake. Groundwater stage explained 73 % of the interannual variability in water transparency. Transparency, in turn, explained 85 % of the interannual variability in the heat budget for the lake, which ranged from 1.8 × 108 to 4.1 × 108 Joules m–2 yr–1, encompassing the range reported across Florida lakes. While surface water temperature was not affected by transparency, depths below 5 m warmed faster during the stratifi ed period during years having a lower rate of light extinction. We show that an increase in precipitation of 20 cm per year reduces the depth of the summer euphotic zone and thermocline by 1.9 and 1.6 m, respectively, and causes a 1-month reduction in the duration of winter mixing in this monomictic lake. Because biota have been shown to respond to shifts in light and heat distribution of much smaller magnitude than exhibited here, our work suggests that subtle changes in precipitation linked to climate fl uctuations may have signifi cant physical as well as biotic consequences.

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Shallow marine ecosystems are experiencing significant environmental alterations as a result of changing climate and increasing human activities along coasts. Intensive urbanization of the southeast Florida coast and intensification of climate change over the last few centuries changed the character of coastal ecosystems in the semi-enclosed Biscayne Bay, Florida. In order to develop management policies for the Bay, it is vital to obtain reliable scientific evidence of past ecological conditions. The long-term records of subfossil diatoms obtained from No Name Bank and Featherbed Bank in the Central Biscayne Bay, and from the Card Sound Bank in the neighboring Card Sound, were used to study the magnitude of the environmental change caused by climate variability and water management over the last ~ 600 yr. Analyses of these records revealed that the major shifts in the diatom assemblage structures at No Name Bank occurred in 1956, at Featherbed Bank in 1966, and at Card Sound Bank in 1957. Smaller magnitude shifts were also recorded at Featherbed Bank in 1893, 1942, 1974 and 1983. Most of these changes coincided with severe drought periods that developed during the cold phases of El Niño Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), or when AMO was in warm phase and PDO was in the cold phase. Only the 1983 change coincided with an unusually wet period that developed during the warm phases of ENSO and PDO. Quantitative reconstructions of salinity using the weighted averaging partial least squares (WA-PLS) diatom-based salinity model revealed a gradual increase in salinity at the three coring locations over the last ~ 600 yr, which was primarily caused by continuously rising sea level and in the last several decades also by the reduction of the amount of freshwater inflow from the mainland. Concentration of sediment total nitrogen (TN), total phosphorus (TP) and total organic carbon (TOC) increased in the second half of the 20th century, which coincided with the construction of canals, landfills, marinas and water treatment plants along the western margin of Biscayne Bay. Increased magnitude and rate of the diatom assemblage restructuring in the mid- and late-1900s, suggest that large environmental changes are occurring more rapidly now than in the past.

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Shallow marine ecosystems are experiencing significant environmental alterations as a result of changing climate and increasing human activities along coasts. Intensive urbanization of the southeast Florida coast and intensification of climate change over the last few centuries changed the character of coastal ecosystems in the semi-enclosed Biscayne Bay, Florida. In order to develop management policies for the Bay, it is vital to obtain reliable scientific evidence of past ecological conditions. The long-term records of subfossil diatoms obtained from No Name Bank and Featherbed Bank in the Central Biscayne Bay, and from the Card Sound Bank in the neighboring Card Sound, were used to study the magnitude of the environmental change caused by climate variability and water management over the last ~ 600 yr. Analyses of these records revealed that the major shifts in the diatom assemblage structures at No Name Bank occurred in 1956, at Featherbed Bank in 1966, and at Card Sound Bank in 1957. Smaller magnitude shifts were also recorded at Featherbed Bank in 1893, 1942, 1974 and 1983. Most of these changes coincided with severe drought periods that developed during the cold phases of El Niño Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), or when AMO was in warm phase and PDO was in the cold phase. Only the 1983 change coincided with an unusually wet period that developed during the warm phases of ENSO and PDO. Quantitative reconstructions of salinity using the weighted averaging partial least squares (WA-PLS) diatom-based salinity model revealed a gradual increase in salinity at the three coring locations over the last ~ 600 yr, which was primarily caused by continuously rising sea level and in the last several decades also by the reduction of the amount of freshwater inflow from the mainland. Concentration of sediment total nitrogen (TN), total phosphorus (TP) and total organic carbon (TOC) increased in the second half of the 20th century, which coincided with the construction of canals, landfills, marinas and water treatment plants along the western margin of Biscayne Bay. Increased magnitude and rate of the diatom assemblage restructuring in the mid- and late-1900s, suggest that large environmental changes are occurring more rapidly now than in the past.

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We provide new evidence on sea surface temperature (SST) variations and paleoceanographic/paleoenvironmental changes over the past 1500 years for the north Aegean Sea (NE Mediterranean). The reconstructions are based on multiproxy analyses, obtained from the high resolution (decadal to multi-decadal) marine record M2 retrieved from the Athos basin. Reconstructed SSTs show an increase from ca. 850 to 950 AD and from ca. 1100 to 1300 AD. A cooling phase of almost 1.5 °C is observed from ca. 1600 AD to 1700 AD. This seems to have been the starting point of a continuous SST warming trend until the end of the reconstructed period, interrupted by two prominent cooling events at 1832 ± 15 AD and 1995 ± 1 AD. Application of an adaptive Kernel smoothing suggests that the current warming in the reconstructed SSTs of the north Aegean might be unprecedented in the context of the past 1500 years. Internal variability in atmospheric/oceanic circulations systems as well as external forcing as solar radiation and volcanic activity could have affected temperature variations in the north Aegean Sea over the past 1500 years. The marked temperature drop of approximately ~2 °C at 1832 ± 15 yr AD could be related to the 1809 ?D 'unknown' and the 1815 AD Tambora volcanic eruptions. Paleoenvironmental proxy-indices of the M2 record show enhanced riverine/continental inputs in the northern Aegean after ca. 1450 AD. The paleoclimatic evidence derived from the M2 record is combined with a socio-environmental study of the history of the north Aegean region. We show that the cultivation of temperature-sensitive crops, i.e. walnut, vine and olive, co-occurred with stable and warmer temperatures, while its end coincided with a significant episode of cooler temperatures. Periods of agricultural growth in Macedonia coincide with periods of warmer and more stable SSTs, but further exploration is required in order to identify the causal links behind the observed phenomena. The Black Death likely caused major changes in agricultural activity in the north Aegean region, as reflected in the pollen data from land sites of Macedonia and the M2 proxy-reconstructions. Finally, we conclude that the early modern peaks in mountain vegetation in the Rhodope and Macedonia highlands, visible also in the M2 record, were very likely climate-driven.