Annual Patterns Research Articles

PREDICTING THE IMPACT OF RAPID URBANISATION ON URBAN GROUNDWATER LEVEL VARIATIONS AND ANALYZING CLIMATE DYNAMICS IN PUNJAB'S CITIES, INDIA: AN APPROACH TOWARDS SUSTAINABLE CITIES

Abstract. In the past few decades, India has witnessed an unparallel population growth across its urban centres. The significant rise in urban population has led to acute demands for resources to sustain them, contributing to anthropogenic activities that impact urban resources and climate. This study was carried out to analyse the impact of rapid urbanisation on the groundwater level variation and climate dynamics. Focus was laid on Ludhiana and Patiala urban centres of Punjab state, India. Multi-temporal analysis of LULC was computed using Landsat-4, 5, 7 & 8 datasets to analyse urban sprawl during 1990–2023 for both the cities. A significant increase of 30% urban area was observed during 1990–2023. Further, to analyse the impact of urbanisation on ground water levels, the groundwater water storage variation was analysed using the GRACE and GRACE-FO mission datasets. It was found that the groundwater withdrawal was greater than the amount of total groundwater recharge during 1990–2023. Both these cities Ludhiana and Patiala has experienced an extreme decline in groundwater storage levels. Further, the time-series statistical relationships were explored to understand the relation between urban sprawl and annual temperature, rainfall patterns and total water storage for these cities during the years 2000-2022 for analysing the effect of rapid urbanization.

A decadal atmospheric ammonia reanalysis product in China

Atmospheric ammonia has great environmental implications due to its important role in ecosystem and nitrogen cycle, as well as contribution to formation of secondary particles. China is recognized as a hotspot of NH3 pollution owing to agricultural and livestock intensification. In the quest to achieve a comprehensive understanding of atmospheric ammonia load and to quantify its environmental impacts in China, relying solely either on existing measurements or on model simulations falls short. Their limitations, either in spatial coverage and integrity or in data quality, fails to meet the needs. Available reanalysis products exhibit a marked deficiency in ammonia data. We therefore aim to propose an integrated ammonia reanalysis product in China, adeptly melding satellite observations from the Infrared Atmospheric Sounding Interferometer (IASI) NH3 retrievals with chemical transport model simulation, capitalizing on the robust Ensemble Kalman Filter (EnKF) data assimilation methodology. The product is validated in high quality via the comparison against independent measurements from ground monitoring stations. Spanning a decade from 2013 to 2022, our reanalysis uncovers not just the spatial intricacies of NH3 concentrations but also their temporal dynamics. Our findings pinpointed the spatial disparities in atmospheric ammonia intensities, highlighting regional hotspots in the NCP, SCB, and Northeast China, and identified annual and seasonal patterns. Our research provides crucial insights for shaping future NH3 pollution prevention and control strategies in China.

Unlocking geothermal energy for sustainable greenhouse farming in arid regions: a remote-sensed assessment in Egypt’s New Delta

This study introduces a novel approach for assessing geothermal potential in arid regions, specifically Egypt’s New Delta Agriculture Mega Project area. The challenge of limited sub-soil temperature profile data was addressed by integrating Global Land Data Assimilation System (GLDAS) weather data. Using the Earth-to-Air Heat Exchanger (EAHE) model, the extracted air and sub-soil temperature profiles the potential for geothermal energy production was estimated. We modeled the annual sinusoidal soil surface periodic heating pattern by utilizing GLDAS ambient air temperature (AAT) and land surface temperature (LST). Using either AAT or LST yielded a Root-Mean-Square Error (RSME) of 0.2°C. The generated sub-soil profiles for the New Delta region showed a temperature variation of no more than 1.5°C at a 4-m depth, making it an optimal depth for EAHE installation. One-pipe EAHE demonstrated a cooling/heating capacity ranging from 400 W (cooling) to −300 W (heating). The study highlights the New Delta region’s strong geothermal potential for greenhouse cooling and heating, underlining its suitability as a sustainable energy source in arid areas. It also offers a practical guide for the EAHE application and it emphasizes the global potential for geothermal energy exploration, using innovative GLDAS data to expand sub-soil temperature profile accessibility.

Analyzing the Impact of Rainfall Patterns on Agriculture, Economy and Tourism in India: A Statistical Approach

The current study examines rainfall trends in India, encompassing its effect on various economic aspects and forecasting for 2023-2030. The Mann-Kendall test and Sen’s slope estimator are utilized to analyze annual and seasonal rainfall patterns. Results reveal a pronounced winter decline (2001-2022) alongside significant pre- monsoon, monsoon, and post-monsoon increases. Annual rainfall consistently de- creases, contrasting with rising pre-monsoon, monsoon, and post-monsoon trends. Annual rainfall exhibits the steepest decline (-1.0891 mm/year), while the monsoon season displays the highest increase (3.2538 mm/year). Further, the present study explores relationships between rainfall and economic growth, tourism, and agriculture. A statistically insignificant yet positive correlation is found between annual rainfall and per-capita GDP, indicating other economic drivers. Tourism shows a weak, statistically insignificant link with annual rainfall. In contrast, a robust statistically significant correlation emerges between annual rainfall and food- grain production, highlighting its role in agriculture. Finally, the present research forecasts annual rainfall (2023-2030) using the ARIMA (1,0,0) model, predicting a continued decline. This has profound implications for water resources, agriculture, and the economy, necessitating proactive measures such as water conservation, drought-resistant farming, and alternative energy investments.

Spatiotemporal distribution and potential risks of metals and total petroleum hydrocarbons (TPHs) in seawater from the Zhifu Bay and its surrounding areas, Yellow Sea, China (2015–2019)

To investigate the concentrations, spatiotemporal distribution, correlation with environmental factors, and potential risks of four metals (Hg, Cu, Pb, and Cd) and total petroleum hydrocarbons (TPHs) in seawater from the Zhifu Bay and its surrounding areas, surface seawater samples were collected from 10 stations in spring, summer, and autumn of 2015–2019. Compared with values from other regions, the average concentrations of metals and TPHs were in the low and medium levels, respectively. Concentrations of all the study pollutants decreased in the offshore direction, suggesting that most of these pollutants are from land and nearshore sources. Annual variation patterns indicated decreasing trends of Cu and TPHs, and due to the seasonal differences in river discharges, rainfalls, and human activities, wet seasons (summer and/or autumn) exhibited higher concentrations of Hg, Cu, and TPHs than dry season (spring). The potential ecological risk of Cu and carcinogenic health risk of Cd suggest that the discharge of metals from the sea should be more strictly controlled.

Trends of High and Low Values of Annual and Seasonal Precipitation in Turkey

The exploration of precipitation data trends using innovative analysis methods is anticipated to offer significant contributions to sustainability across various domains, including water resources management, agricultural planning, climate change understanding, environmental protection, risk assessment, and preparedness. This study employs an improved visualization of the innovative trend analysis (IV-ITA) method for detecting annual and seasonal trends in precipitation variables across 194 stations in Turkey over the period 1969–2020. The outcomes derived from the IV-ITA method were further juxtaposed with the results obtained from the classical Mann–Kendall (MK) test. Using the MK test, statistically significant increasing trends were detected in the annual pattern along the northern coasts of Turkey. Based on the results obtained from the IV-ITA, substantial decreasing trends were identified in the basins within the Southeastern Anatolia Region of Turkey. Conversely, an increasing trend was observed in the basins situated in the northwest. It was also established that an increasing trend was observed throughout Turkey, except for some stations in the low-data group. The most significant increasing trend was noted in the basins along the southern coastline, characterized by the prevalence of the Mediterranean climate. In the high-data group, an increase of up to 50% was noted along the southwest coast. Upon comparing the outcomes derived from the IV-ITA method with those obtained using the MK test, it becomes apparent that the IV-ITA yields significantly more detailed results than the MK test. Additionally, applying the IV-ITA method in climate-sensitive regions and basins is envisioned to enhance the accuracy of assessments, foster a sustainable environment, and improve the effective management of water resources.

Using generalised additive models to visualise the annual cycle of primary feather moult patterns

Moult is a vital but energy-demanding event in a bird's phenological cycle. Primary moult is the shedding of old feathers and the regeneration of new flight feathers to maintain efficient functioning of these critical structures. Life history events, such as moult, breeding and migration, are typically separated from one another temporally because of the costs associated with moult Thus, extrapolation of other life-history events is possible from an understanding of the primary moult schedule in species for which data are easier to collect This study aimed to explore the primary moult patterns of nine nectarivorous species (seven Sunbirds and two Sugarbirds) using data extracted from the South African Bird Ringing Unit (SAFRING) database. Logistic generalised additive models (GAMs) were fitted to active/inactive moult observations to explore annual primary moult patterns. Breeding patterns based on the presence of brood patches in females were also analysed using GAMs for species with sufficient data. The GAMs illustrated the annual patterns well, with the probability of moult having clear peaks and troughs, allowing intuitive understanding of annual life-history patterns, such as the probability of breeding. Generally, GAMs hold potential to be used as a supplementary tool to study the timing of primary moult GAMs appear especially useful for species with no well-defined annual moult period.

Annual patterns of green tides blooms in the coastal waters of Qinhunagdao from 2018 to 2020

Green tide disasters have been occurring along the Qinhuangdao coastal area for several years since 2015. This study investigated the interannual changes of green tides in Qinhuangdao from 2018 to 2020 and found that the green algae biomass was significantly reduced in 2020. The peak biomass of the green tide in July was only 151.5 g m−3, which is significantly lower than 7789.4 g m−3 in July 2018 and 5873.9 g m−3 in July 2019. Further comparative analysis showed that the decrease in nutrients, reduction in the density of Ulva microscopic propagules, and low biomass of attached macroalgae on the seaweed beds along the Jinmenghaiwan bath coastal area were the main causes for the decrease in the scale of green tides in Qinhuangdao in 2020. This paper also summarizes the factors of green tide formation in Qinhuangdao and proposes relevant prevention and control suggestions for the local governments based on the previous research.

Analysis of Spatiotemporal Variations and Influencing Factors of Sea Ice Extent in the Arctic and Antarctic

The 44 years (1979–2022) of satellite-derived sea ice extent in the Arctic and Antarctic reveals the details and new trends in the process of polar sea ice coverage changes. The speed of Arctic sea ice extent reduction and the interannual difference significantly increased after 2004. Trend analysis suggests that the Arctic Ocean may experience an ice-free period around 2060. The maximum anomaly of Arctic sea ice extent has gradually transitioned from September to October, indicating a trend of prolonged melting period. The center of gravity of sea ice in the Arctic Ocean is biased towards the Pacific side, and the spatial distribution pattern of sea ice is greatly influenced by the Atlantic warm current. The dynamism of the sea ice extent on the Atlantic side is significantly greater than in other regions. Since 2014, the Antarctic sea ice extent has shifted from slow growth to a rapid decreasing trend; the sea ice extent reached a historical minimum in 2022, decreasing by 2.02 × 106 km2 compared to 2014. The Antarctic experiences seven months of ice growth each year and five months of ice melting period, the annual change patterns of sea ice extent in the Arctic and Antarctic are slightly different.

A Spatio-Temporal Encoding Neural Network for Semantic Segmentation of Satellite Image Time Series

Remote sensing image semantic segmentation plays a crucial role in various fields, such as environmental monitoring, urban planning, and agricultural land classification. However, most current research primarily focuses on utilizing the spatial and spectral information of single-temporal remote sensing images, neglecting the valuable temporal information present in historical image sequences. In fact, historical images often contain valuable phenological variations in land features, which exhibit diverse patterns and can significantly benefit from semantic segmentation tasks. This paper introduces a semantic segmentation framework for satellite image time series (SITS) based on dilated convolution and a Transformer encoder. The framework includes spatial encoding and temporal encoding. Spatial encoding, utilizing dilated convolutions exclusively, mitigates the loss of spatial accuracy and the need for up-sampling, while allowing for the extraction of rich multi-scale features through a combination of different dilation rates and dense connections. Temporal encoding leverages a Transformer encoder to extract temporal features for each pixel in the image. To better capture the annual periodic patterns of phenological phenomena in land features, position encoding is calculated based on the image’s acquisition date within the year. To assess the performance of this framework, comparative and ablation experiments were conducted using the PASTIS dataset. The experiments indicate that this framework achieves highly competitive performance with relatively low optimization parameters, resulting in an improvement of 8 percentage points in the mean Intersection over Union (mIoU).

Assessment of seasonal and annual patterns in phosphorus content in a monitored catchment through a partitioning approach based on hydrometeorological data

High amounts of phosphorus (P) in rivers come mainly from two sources: fertilizers washed off from agricultural and urban areas by runoff water (non-point sources) and urban and industrial development which are translated in P discharges from wastewater treatment plants (WWTP). This work analyses the content of P in water for nearly 40 years inquiring into the origin of the sources, based on the hypothesis of runoff generation from the detection of river streamflow increases during the P contribution episode and the previous precipitation. For this purpose, the Guadaira River, which is located in the South of Spain and has a drainage surface of 1524 km2, was selected. In this watershed agricultural land use converges with numerous human activities resulting in high pressures on water quality. We found 40% of the P contribution episodes found seem to come from the runoff generated after the heaviest rainfall events, which normally occur between November and May. The remaining 60% of the P contribution episodes were found to be linked to point sources, which become more relevant from June to September, reaching the highest concentration values (6–17 mg/L). The results highlight that the target phosphate concentration value of 0.34 mg PO4/L imposed by the national legislation for a good state following the Water Framework Directive 2000/60/EC is exceeded by 96% of the measurements during the period from 1981 to 2022. On a monthly basis, PO4 loads showed a linear relationship with river streamflow (R2 = 0.94). However, on field measurements scale, a potential relationship between both variables was found, which changed according to the improvement in the wastewater treatment and facilities for 1982–1994, 1995–2017 and 2018–2022. In these three periods, different significant decreasing trends of the P content were found, mainly marked by the setup of each individual WWTP.

Phonology and Maharah Kalam in Scopus Publications: Content Analysis and Development Trends

This study explores the relationship between phonology and Arabic language learning by analyzing document publications indexed in Scopus from 1980 to 2022. Focusing on maharah kalam (speaking skills) phonology, this study investigates its integration into Arabic education, the prominent affiliations, and researchers' search approaches. Using bibliometric analysis, the findings reveal an irregular annual publication pattern, mostly articles (181 document articles). The University of Haifa leads with 19 articles, and Amayreh MM. is the most prolific author (five articles). Sub-content trends vary over the decade. Recommendations include increased publications, exploring the University of Haifa's role, and encouraging Indonesian researchers. The study concludes with future research avenues, emphasizing expanded publications and exploring the University of Haifa's impact. In summary, it provides insights into phonology and maharah kalam studies, identifies contributors, and suggests future directions within Scopus publications from 1980 to 2022.

Springing forward: Migrating songbirds catch up with the start of spring in North America.

In temperate regions, the annual pattern of spring onset can be envisioned as a 'green wave' of emerging vegetation that moves across continents from low to high latitudes, signifying increasing food availability for consumers. Many herbivorous migrants 'surf' such resource waves, timing their movements to exploit peak vegetation resources in early spring. Although less well studied at the individual level, secondary consumers such as insectivorous songbirds can track vegetation phenology during migration as well. We hypothesized that four species of ground-foraging songbirds in eastern North America-two warblers and two thrushes-time their spring migrations to coincide with later phases of vegetation phenology, corresponding to increased arthropod prey, and predicted they would match their migration rate to the green wave but trail behind it rather than surfing its leading edge. We further hypothesized that the rate at which spring onset progresses across the continent influences bird migration rates, such that individuals adjust migration timing within North America to phenological conditions they experience en route. To test our hypotheses, we used a continent-wide automated radio telemetry network to track individual songbirds on spring migration between the U.S. Gulf Coast region and northern locations closer to their breeding grounds. We measured vegetation phenology using two metrics of spring onset, the spring index first leaf date and the normalized difference vegetation index (NDVI), then calculated the rate and timing of spring onset relative to bird detections. All individuals arrived in the southeastern United States well after local spring onset. Counter to our expectations, we found that songbirds exhibited a 'catching up' pattern: Individuals migrated faster than the green wave of spring onset, effectively closing in on the start of spring as they approached breeding areas. While surfing of resource waves is a well-documented migration strategy for herbivorous waterfowl and ungulates, individual songbirds in our study migrated faster than the green wave and increasingly caught up to its leading edge en route. Consequently, songbirds experience a range of vegetation phenophases while migrating through North America, suggesting flexibility in their capacity to exploit variable resources in spring.

Analysis of Daytime and Night-Time Aerosol Optical Depth from Solar and Lunar Photometry in Valladolid (Spain)

Aerosol optical depth (AOD) at night-time has become a hot topic in recent years due to the development of new instruments recording accurate ground-based lunar irradiance measurements, and the development of calibration methods and extraterrestrial irradiance models adapted to lunar photometry. This study uses all daytime and night-time AOD data available at Valladolid (Spain) from October 2016 to March 2022 in order to analyze its behavior and the added contribution of night data. The annual, monthly and daily AOD evolution is studied comparing daytime and night-time values and checking the correlation between them. For this purpose, the daily averages are computed, showing an annual pattern, with low AOD values throughout the year (mean value of AOD at 440 nm: 0.122), where winter months have the lower and summer the higher values, as observed in previous studies. All these AOD values are modulated by frequent desert dust events over the Iberian Peninsula, with a strong influence on daily and monthly mean values in February and March, where the strongest desert outbreaks occurred. The added new data confirm these results and the good correlation between daytime and night-time data. Also, a complete daily evolution is shown, observing that AOD and Ångström exponent (AE) mean values vary by only ±0.02 in 24 h, with a maximum value at 06:00 UTC and minimum at 18:00 UTC for both parameters.

Stochasticity-driven weekly fluctuations distinguished the temporal pattern of particle-associated microorganisms from its free-living counterparts in temperate coastal seawater

Microbial community dynamics directly determine their ecosystem functioning. Despite the well-known annual recurrence pattern, little is known how different lifestyles affect the temporal variation and how community assembly mechanisms change over different temporal scales. Here, through a high-resolution observation of size fractionated samples over 60 consecutive weeks, we investigate the distinction in weekly distribution pattern and assembly mechanism between free-living (FL) and particle-associated (PA) communities in highly dynamic coastal environments. A clear pattern of annual recurrence was observed, which was more pronounced in FL compared to PA, resulting in higher temporal specificity in the former samples. Both the two size fractions displayed significant temporal distance-decay patterns, yet the PA community showed a higher magnitude of community variation between adjacent weeks, likely caused by sudden, drastic and long-lived blooms of heterotrophic bacteria. Generally, determinism (environmental selection) had a greater effect on the community assembly than stochasticity (random birth, death, and dispersal events), with significant contributions from temperature and inorganic nutrients. However, a clear shift in the temporal assembly pattern was observed, transitioning from a prevalence of stochastic processes driving short-term (within a month) fluctuations to a dominance of deterministic processes over longer time intervals. Between adjacent weeks, stochasticity was more important in the community assembly of PA than FL. This study revealed that stochastic processes can lead to rapid, dramatic and irregular PA community fluctuations, indicating weak resistance and resilience to disturbances, which considering the role of PA microbes in carbon processing would significantly affect the coastal carbon cycle. Our results provided a new insight into the microbial community assembly mechanisms in the temporal dimension.

Climatic effects on the synchrony and stability of temperate headwater invertebrates over four decades.

Important clues about the ecological effects of climate change can arise from understanding the influence of other Earth-system processes on ecosystem dynamics but few studies span the inter-decadal timescales required. We, therefore, examined how variation in annual weather patterns associated with the North Atlantic Oscillation (NAO) over four decades was linked to synchrony and stability in a metacommunity of stream invertebrates across multiple, contrasting headwaters in central Wales (UK). Prolonged warmer and wetter conditions during positive NAO winters appeared to synchronize variations in population and community composition among and within streams thereby reducing stability across levels of ecological organization. This climatically mediated synchronization occurred in all streams irrespective of acid-base status and land use, but was weaker where invertebrate communities were more functionally diverse. Wavelet linear models indicated that variation in the NAO explained up to 50% of overall synchrony in species abundances at a timescale of 4-6 years. The NAO appeared to affect ecological dynamics through local variations in temperature, precipitation and discharge, but increasing hydrochemical variability within sites during wetter winters might have contributed. Our findings illustrate how large-scale climatic fluctuations generated over the North Atlantic can affect population persistence and dynamics in inland freshwater ecosystems in ways that transcend local catchment character. Protecting and restoring functional diversity in stream communities might increase their stability against warmer, wetter conditions that are analogues of ongoing climate change. Catchment management could also dampen impacts and provide options for climate change adaptation.

New particle formation leads to enhanced cloud condensation nuclei concentrations on the Antarctic Peninsula

Abstract. Few studies have investigated the impact of new particle formation (NPF) on cloud condensation nuclei (CCN) in remote Antarctica, and none has elucidated the relationship between NPF and CCN production. To address that knowledge gap, we continuously measured the number size distribution of 2.5–300 nm particles and CCN number concentrations at King Sejong Station on the Antarctic Peninsula from 1 January to 31 December 2018. Ninety-seven NPF events were detected throughout the year. Clear annual and seasonal patterns of NPF were observed: high concentration and frequency of nucleation-mode particles in summer (December–February: 53 NPF cases) and undetected nucleation-mode particles in winter (June–August: no NPF cases). We estimated the spatial scale of NPF by multiplying the time during which a distinct nucleation mode can be observed at the sampling site by the locally measured wind speed. The estimated median spatial scale of NPF around the Antarctic Peninsula was found to be approximately 155 km, indicating the large scale of NPF events. Air back-trajectory analysis revealed that 80 cases of NPF events were associated with air masses originating over the ocean, followed by sea-ice (12 cases), multiple (3 cases), and land (2 cases) regions. We present and discuss three major NPF categories: (1) marine NPF, (2) sea-ice NPF, and (3) multiple NPF. Satellite estimates for sea-surface dimethylsulfoniopropionate (DMSP; a precursor of gaseous dimethyl sulfide) data showed that the production of oceanic biogenic precursors could be a key component in marine NPF events, whereas halogen compounds released from ice-covered areas could contribute to sea-ice NPF events. Terrestrial sources (wildlife colonies, vegetation, and meltwater ponds) from Antarctica could affect aerosol production in multiple air masses. Out of 97 observed NPF events, 83 cases were characterized by the simultaneous increase in the CCN concentration by 2 %–270 % (median 44 %) in the following 1 to 36 h (median 8 h) after NPF events. Overall, Antarctic NPF events were found to be a significant source of particles with different physical characteristics and related to biogenic sources in and around the Antarctic Peninsula, which subsequently grew to cloud condensation nuclei.

Patterns, timing, and environmental drivers of secondary growth in two physiologically distinct Mediterranean alpine shrub species

Alpine plants are particularly sensitive to climate change, and in the Mediterranean, less frequent winter cold and prolonged summer drought are expected to shift the growth patterns of species, altering their range and strategies to cope with these dual climatic stressors. However, adaptive strategies for drought and frost and their impact on performance of species are poorly explored, with critical timescales relevant for growth insufficiently reflected and a focus on a limited set of environmental drivers. Here, we explored the growth processes of two physiologically distinct Mediterranean alpine shrub species: Cytisus galianoi (green-stemmed species) and Astragalus granatensis (dimorphic species). By measuring the daily stem diameter changes of 26 specimens over six consecutive years (2015–2020) using dendrometers, as well as the corresponding soil temperature and soil moisture conditions, we identified bimodal annual growth patterns (i.e. two phases of growth), water-related timing of growth, and drought- and frost-related environmental constraints. By implementing correlation analyses, linear mixed effects models, and partial least-squares regression, we found pregrowth temperature and moisture drivers to be highly relevant for growth in both species, suggesting a temporal decoupling of growth and resource acquisition. However, the underlying mechanisms were contrasting. While the spring growth of C. galianoi was promoted by pregrowth winter conditions, the autumn growth of A. granatensis was promoted by pregrowth summer conditions. Thus, resource acquisition is likely to be optimized when the traits of species allow physiological activity at high gain and low costs, i.e. when adaptive mechanisms reduce resource consumption to cope with frost and drought. This is during winter for frost-tolerant green-stemmed species and during summer for drought-avoidant dimorphic species, leading to species-specific time windows of growth. Understanding these species-specific growth mechanisms contributes to answering the overarching question of when and how woody plants grow and helps in understanding their adaptability to future climate variability, particularly in sensitive alpine environments, where plant species are evolutionally adapted to physical peculiarities and reach their low-temperature limit.

Exploring the spatio-temporal patterns of global mangrove gross primary production and quantifying the factors affecting its estimation, 1996–2020

Mangrove ecosystems, as an important component of “Blue Carbon”, play a curial role on global carbon cycling; however, the lack of the global estimates of mangrove ecosystem gross primary production (GPP) and the underlying environmental controls on its estimation remain a gap in knowledge. In this study, we utilized global mangrove eddy covariance data and applied Gaussian Process Regression (GPR) to estimate GPP for global mangrove ecosystems, aiming to elucidate the factors influencing these estimates. The optimal GPR achieved favorable estimation performance through cross-validation (R2 = 0.90, RMSE = 0.92 gC/m2/day, WI = 0.86). Over the study period, the globally annual averaged GPP was 2054.53 ± 38.51 gC/m2/yr (comparable to that of evergreen broadleaf forests and exceeds the GPP of most other plant function types), amounting to a total of 304.82 ± 7.71TgC/yr, hotspots exceeding 3000 gC/m2/yr observed near the equator. The analysis revealed a decline in global mangrove GPP during 1996–2020 of −0.89 TgC/yr. Human activities (changes in mangrove cover area) played a relatively consistent role in contributing to this decrease. Conversely, variations in external environmental conditions showed distinct inter-annual differences in their impact. The spatio-temporal distribution patterns of mangrove ecosystems GPP (e.g., the bimodal annual pattern, latitudinal gradients, etc.) demonstrated the regulatory influence of external environmental conditions on GPP estimates. The model ensemble attribution analysis indicated that the fraction of absorbed photosynthetically active radiation exerted the dominant control on GPP estimations, while temperature, salinity, and humidity acted as secondary constraints. The findings of this study provide valuable insights for monitoring, modeling, and managing mangrove ecosystems GPP; and underscore the critical role of mangroves in global carbon sequestration. By quantifying the influences of environmental factors, we enhance our understanding of mangrove carbon cycling estimates, thereby helping sustain of these disproportionately productive ecosystems.

Stream hydrology and a pulse subsidy shape patterns of fish foraging.

Pulsed subsidy events create ephemeral fluxes of hyper-abundant resources that can shape annual patterns of consumption and growth for recipient consumers. However, environmental conditions strongly affect local resource availability for much of the year, and can heavily impact consumer foraging and growth patterns prior to pulsed subsidy events. Thus, a consumer's capacity to exploit pulse subsidy resources may be influenced by antecedent environmental conditions, but this has rarely been shown in nature and is unknown in aquatic ecosystems. Here, we sought to understand the importance of hydrologic variation and a salmon pulse subsidy on the foraging and growth patterns of two stream salmonids in a coastal southeast Alaska drainage. To do this, we sampled fish stomach contents at a high temporal frequency (daily-weekly measurements) and analyzed fish consumption rates in relation to streamflow and pulse subsidy resource availability. We then explored the influence of interannual hydrologic variation on access to pulse subsidy resources (i.e. whether fish exceeded an egg consumption gape limit) in a bioenergetic simulation. Prior to Pink Salmon spawning, Dolly Varden and Coho Salmon displayed distinct and nonlinear flow-foraging relationships, where forage for both species consisted primarily of macroinvertebrates. During this time period, consumption maxima coincided with baseflow and the highest observed flow conditions, and consumption minima were observed at severe low-water and intermediate flow values. After salmon spawning began, forage was not significantly related to flow and consisted primarily of salmon eggs. Further, consumption rates increased overall, and foraging patterns did not appear to be affected by flow in either species. Bioenergetic simulations revealed that patterns of interannual hydrologic variation may shift Coho Salmon growth trajectories among years. Together, our results suggest that access to marine pulse subsidy resources may depend on whether antecedent hydrologic conditions are suitable for juvenile salmonids to grow large enough to consume salmon eggs by the onset of spawning.