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Climate change affects various scales of biotic interaction through phenological shifts. The emergence phenology of cicadas is ecologically important because these insects have large effects on the ecosystem as herbivores, as food resources, and in nutrient flux from subterranean resources. However, little is known about the weather factors affecting their emergence patterns in the field because their nymphal stages grow underground for several years.Here, we used long‐term observation data on the first singing date (i.e. the first emergence of male individuals) of Graptopsaltria nigrofuscata, recorded by the Japan Meteorological Agency and citizen scientists throughout Japan, to (1) explore the most influential weather factors across a variety of time spans on the first singing date of G. nigrofuscata and (2) determine whether the temporal trend of the first singing date could be explained by temporal weather trends caused by climate change by using a state space model.Our results indicated that higher temperatures from midsummer to early winter in the previous year are bringing the cicadas' emergence forward, and the annual increase in temperature is causing the advancement of emergence patterns. Other weather factors, such as precipitation and humidity, did not have a strong effect.Our findings suggest that increased growth rates at the nymphal stage due to warming in the previous year influence cicada emergence timing. To understand the mechanisms of how rising temperatures are advancing cicada emergence, we need an approach based on the physiology and ecology of their nymphs. [ABSTRACT FROM AUTHOR]

Both Arctic and Antarctic sea ice are affected by climate change. While Arctic sea ice has been declining for several decades, Antarctic sea ice extent slowly increased until 2015, followed by a sharp drop in 2016. Quantifying sea ice changes is essential to assess their impacts on the ocean, atmosphere, ecosystems and Arctic communities. In this study, we combine sea ice thickness estimates from four satellite radar altimeters to derive the longest time series of homogeneous sea ice thickness for both hemispheres over 30 years (1994–2023). The record supports the rapid loss of sea ice in the Arctic for each month of the year and the heterogeneous changes in sea ice thickness in the Antarctic. The study confirms that most of the volume variability is due to the thickness variability, which holds true for both hemispheres. The sea ice thickness time series presented here offer new insights for models, in particular the possibility to evaluate sea ice reanalyses and to initialize forecasts, especially in the Antarctic, where the data set presented here has no equivalent in terms of spatial and temporal coverage. Plain Language Summary: Arctic and Antarctic sea ice respond significantly to climate change, as documented by decades of satellite records of sea ice coverage. Arctic sea ice coverage has declined steadily over the past 40 years, while Antarctic sea ice coverage increased until 2016, followed by a rapid decline. In contrast, changes in sea ice thickness, which contribute to changes in sea ice volume, are much less well documented due to the lack of long‐term observations. In this study, we address this gap by producing a 30‐year time series of sea ice thickness (1994–2023) using data from four satellite radar altimeters, representing the longest consistent data set for both polar regions. This was made possible by using machine learning to align the different satellite missions and incorporating an ensemble of snow depth products to cover the entire period. The resulting time series shows a rapid decrease in Arctic sea ice thickness over the study period. In contrast, Antarctic sea ice shows thickness changes with significant spatial variability. This new data set provides critical insights into sea ice dynamics, their causes, and their impacts on climate, ecosystems, and Arctic communities. Key Points: A 30‐year data set from four satellite radar altimeters provides the longest sea ice thickness record for both polar regionsArctic sea ice is significantly thinning for each month of the year, whereas Antarctic undergoes complex regional thickness changesSea ice volume variability can be explained by sea ice thickness variability in both polar hemispheres [ABSTRACT FROM AUTHOR]

The University of Genova (Italy) maintains a historical meteorological station that has provided daily rainfall measurements over a quasi-bicentennial period since 1833. The daily rainfall series is analyzed here to assess the impact of long-term precipitation trends on the performance of a rainwater harvesting system. The collected rainwater is used for the irrigation of urban green areas. A behavioral model is applied, involving a dedicated procedure to evaluate the actual soil water content available for vegetation and its decay over time. Non-dimensional indicators are obtained to support adaptation strategies and the sustainable design of the required storage tank. Since both irrigation demand and available water storage depend on the amount of rainfall received, fluctuations in daily rainfall and their trend do affect the performance of the system in a non-trivial way. The results demonstrate that the installation of an RWH system for landscape irrigation is a reliable and resilient solution, at least considering the measured rainfall variations of the last 200 years. In the town of Genoa, no specific adaptation seems necessary in terms of the design of the storage tank other than the usual oversizing, typical of engineering design, to account for uncertainties in the hydrological assessment of any RWH system. [ABSTRACT FROM AUTHOR]

Lake Dianchi is one of the most eutrophic lakes in China. The decline in water quality and the occurrence of massive algal blooms pose a significant threat to the health and environmental safety of the water ecosystem, making Lake Dianchi a key concern for algal bloom management in China. Obtaining the spatiotemporal dynamics of algal blooms for the longest time possible is crucial to algal bloom management and future prediction. However, it is difficult to acquire a long-term record of algal blooms from a single sensor in order to cover a more extended period of eutrophication in the lake due to the limitation of the spatial and temporal resolution of the sensors. In this study, Landsat and Moderate-Resolution Imaging Spectroradiometer (MODIS) images were combined with the Floating Algae Index (FAI) to reconstruct a unified time series of bloom areas to analyze the algal bloom dynamics in Lake Dianchi in recent decades. Regarding the interannual variation, the bloom area showed an increasing trend from 1987 to 2021, with larger bloom areas in 1991–1992, 2000–2003, 2012–2013, and 2020–2021. In terms of seasonal characteristics, the bloom area was significantly more prominent in the rainy season compared with the dry season during the year. The spatial distribution of the bloom frequency showed a pattern of higher frequencies in the north and lower frequencies in the south. From 2000 to 2021, the initial bloom time and bloom duration showed a trend of delaying and then advancing and decreasing and then increasing, respectively. We analyzed the importance of long-term records of algal blooms and found that the percentage of rainy season images is an essential factor in reconstructing time series based on different sensors. In addition, the relationship between environmental factors and algal blooms was analyzed. The results show that wind speed and air temperature were the main meteorological factors controlling the interannual variation in algal blooms in Lake Dianchi. Water quality factors such as nutrients have less of an influence on the variation in algal blooms because the algal growth demand has been met. Environmental management measures taken by local governments have led to improvements in the lake's trophic state, and continued strengthening of environmental pollution control is expected to curb the algal blooms in Lake Dianchi. This study provides a long-term record of algal blooms in Lake Dianchi, which provides essential reference information for a comprehensive understanding of the development process of algal blooms in Lake Dianchi and its sustainable development. [ABSTRACT FROM AUTHOR]

Historical samples collected from 1985 to 2020 in coastal and open ocean regions of the Northeast Pacific were utilised to explore salp assemblage composition, morphometrics, and ontogeny of dominant species, as well as spatial, seasonal, and interannual distribution patterns at subarctic latitudes. Species richness was low, however, three of the seven observed species (Cyclosalpa bakeri, Salpa aspera, and S. fusiformis) were dominant and widely distributed in oceanic waters. Salpa maxima and Ihlea punctata were sporadically encountered, while Thalia democratica and Thetys vagina were observed exclusively during the 2014–2016 heatwave. Of the regions sampled, salps occurred at the shelf break and offshore, only occasionally on the shelf and never in inner waterways. Although salps were encountered year-round, salps were most prevalent between late spring and autumn. Over the 35 years, no clear up- or downward trend in the percentage of presence was detected due to high and perhaps cyclic variability. For some species, abundance was significantly affected by season, year, bottom depth, and Multivariate El Niño/Southern Oscillation Index. There is an urgent need for detailed research to realistically incorporate pelagic thaliaceans in North Pacific ecosystem models. The present study lays the foundation for future research on salps at high northern latitudes, utilising a unique and rich sample collection. [ABSTRACT FROM AUTHOR]

Knowledge of species inventory is crucial for identifying when and where species occur historically and geographically; yet few studies have gathered heterogeneous data from different sources to understand long-term spatio-temporal species dynamics in response to ongoing global environmental change. Hainan Island, China is a global biodiversity hotspot and an important transit station on the longest bird migratory flyway in the world. Here, we compiled a comprehensive database including 452 bird species recorded on Hainan Island. The records covered 150 years (1868–2017) and were sourced from published reports, museum specimens, field surveys, and citizen bird watching data. We showed that, since the first scientific report by Swinhoe (1869), the bird records on Hainan Island have increased with more intensive sampling efforts, wider survey areas, and more diverse investigation objectives. Overall, the birds recorded on Hainan Island were of the Oriental type, and the majority were tropical residents. Natural forests and coastal wetlands hosted the highest species richness, but some species were only recorded before 1910, indicating a high probability of species extinction owing to the loss of natural forest and wetland habitats. The spatial distribution of the birds showed a clear altitudinal pattern with more species below altitudes of 500 m. These species are not under effective protection because most of the protected areas are located between 500 and 1000 m. Our study provides a fundamental baseline dataset of the historical bird records on Hainan Island. We suggest that future conservation efforts on Hainan’s birds should target the tropical endemic species and those sensitive to climate change to maximise the preservation of avian biodiversity in China.

Pacific oysters (Crassostrea gigas) were introduced to the US west coast in the early 1900's, but only regularly spawned in several discrete estuarine locations like Willapa Bay where conditions allowed for adult oyster gametogenesis as well as larval survival, retention, and settlement. Oyster industry participants have long recognized that the condition of marketable oysters was related to proximity of their growing areas to the ocean. This prompted resource managers to routinely collect data and identify trends in oyster condition index (CI) in this estuary. An analysis of this almost seven- decade long CI record revealed consistent trends across four sampling locations in Willapa Bay where 50–70% of the variability in CI was explained by a single component. This component of variability in CI was related most strongly to variability in the upwelling index (UI) which was positively correlated with CI during the summer upwelling season. A relationship with the Pacific Decadal Oscillation (PDO), a broader basin-scale index of temperature was also significant, but weaker and PDO was negatively correlated with CI. Shifts or breaks in the long-term CI record occurred in 1977/78 and 1999/2000 with another shift related to the second component of variation in CI that occurred in 1988/1989. The change in 1977/78 has previously been shown to correspond with a shift in the basin scale PDO, but more recent shifts appear to be correlated with local fluctuations in both temperature and upwelling intensity. Further investigation into shifts in the seasonal timing of temperature and phytoplankton as variables that control the oyster gametogenic cycle seem warranted. • Examination of a multi-decade record of condition index for Crassostrea gigas revealed two shifts associated with the Pacific Decadal Oscillation in 1977/78 and with changes in upwelling intensity in 1999/2000. • Consistent trends were identified across four estuarine locations and a single component explained 50–70% of interannual variability • Highest condition occurred at locations closer to the ocean and seasonal patterns were likely associated with gametogenesis. [ABSTRACT FROM AUTHOR]

* Premise of the study: Most alpine plants in the Northeast United States are perennial and flower early in the growing season, extending their limited growing season. Concurrently, they risk the loss of reproductive efforts to late frosts. Quantifying longterm trends in northeastern alpine flower phenology and late-spring/early-summer frost risk is limited by a dearth of phenology and climate data, except for Mount Washington, New Hampshire (1916 m a.s.l.). * Methods: Logistic phenology models for three northeastern US alpine species (Diapensia lapponica, Carex bigelowii and Vaccinium vitis-idaea) were developed from 4 yr (2008-2011) of phenology and air temperature measurements from 12 plots proximate to Mount Washington's long-term summit meteorological station. Plot-level air temperature, the logistic phenology models, and Mount Washington's climate data were used to hindcast model yearly (1935-2011) floral phenology and frost damage risk for the focal species. * Key results: Day of year and air growing degree-days with threshold temperatures of -4°C (D. lapponica and C. bigelowii) and -2°C (V. vitis-idaea) best predicted flowering. Modeled historic flowering dates trended significantly earlier but the 77-yr change was small (1.2-2.1 d) and did not significantly increase early-flowering risk from late-spring/early-summer frost damage. * Conclusions: Modeled trends in phenological advancement and sensitivity for three northeastern alpine species are less pronounced compared with lower elevations in the region, and this small shift in flower timing did not increase risk of frost damage. Potential reasons for limited earlier phenological advancement at higher elevations include a slower warming trend and increased cloud exposure with elevation and/or inadequate chilling requirements. [ABSTRACT FROM AUTHOR]

Abstract: In recent decades, temporal variations in nitrate fluxes and concentrations in temperate rivers have resulted from the interaction of anthropogenic and climatic factors. The effect of climatic drivers remains unclear, while the relative importance of the drivers seems to be highly site dependent. This paper focuses on 2–6 year variations called meso-scale variations, and analyses the climatic drivers of these variations in a study site characterized by high N inputs from intensive animal farming systems and shallow aquifers with impervious bedrock in a temperate climate. Three approaches are developed: 1) an analysis of long-term records of nitrate fluxes and nitrate concentrations in 30 coastal rivers of Western France, which were well-marked by meso-scale cycles in the fluxes and concentration with a slight hysteresis; 2) a test of the climatic control using a lumped two-box model, which demonstrates that hydrological assumptions are sufficient to explain these meso-scale cycles; and 3) a model of nitrate fluxes and concentrations in two contrasted catchments subjected to recent mitigation measures, which analyses nitrate fluxes and concentrations in relation to N stored in groundwater. In coastal rivers, hydrological drivers (i.e., effective rainfall), and particularly the dynamics of the water table and rather stable nitrate concentration, explain the meso-scale cyclic patterns. In the headwater catchment, agricultural and hydrological drivers can interact according to their settings. The requirements to better distinguish the effect of climate and human changes in integrated water management are addressed: long-term monitoring, coupling the analysis and the modelling of large sets of catchments incorporating different sizes, land uses and environmental factors. [ABSTRACT FROM AUTHOR]

Observation‐based long‐term gridded snow water equivalent (SWE) products are important assets for hydrological and climate research. However, an evaluation of the currently available SWE products has been limited due to the lack of independent SWE data that extend over a large range of environmental conditions. In this study, three daily long‐term SWE products (Special Sensor Microwave Imager and Sounder [SSMI/S] SWE, GlobSnow‐2 SWE, and University of Arizona [UA] SWE) were evaluated by seasonal snow cover and land cover classifications over the conterminous United States from 1982 to 2017, using the historical airborne gamma radiation SWE observations (20,738 measurements). We found that there are similar patterns in SSMI/S and GlobSnow‐2 SWE when compared against the gamma SWE. However, GlobSnow‐2 SWE had better agreement with gamma SWE than SSMI/S SWE in some forested‐type classes and maritime and prairie snow classes. As compared to SSMI/S and GlobSnow‐2 SWE, UA SWE has much better agreement with gamma SWE in all land cover types and snow classes. Tree cover and topographic heterogeneity affect the agreement between the gamma and gridded SWE and accuracy of gamma SWE itself with the largest differences typically occurring when the percent tree cover was 80% or higher, the terrain slope was steeper than 2.5°, and the elevation range exceeded 100 m. The results demonstrate the reliability of the UA SWE products and the benefits of the gamma radiation approach to measure SWE, especially in forested regions. Plain Language Summary: Long‐term gridded snowpack data are essential for effective water resource management and flood risk assessments under a changing climate in the United States. However, the currently available snowpack data have large uncertainties, and the evaluations have been limited due to the lack of reliable independent data sets. Here, we evaluate three daily long‐term (>30 years) snow water equivalent (SWE) products—empirically based SWE from passive microwave, GlobSnow‐2 SWE, and University of Arizona SWE from 1982 to 2017 over the conterminous United States—using the historical airborne gamma SWE observations collected by the National Oceanic and Atmospheric Administration. Two key findings are that (1) the UA SWE product is the most reliable and (2) the long‐term airborne SWE record is of great value, especially in forested regions. Key Points: Long‐term airborne gamma radiation observations provide reliable SWE observations even over forest regionsUniversity of Arizona (UA) SWE has the strongest agreement with gamma SWE regardless of seasonal snow and land cover classLarge differences occur when the tree cover is 80% or higher, the slope is steeper than 2.5°, and the elevation range exceeds 100 m [ABSTRACT FROM AUTHOR]