Decadal Time Series Research Articles

TIRVolcH: Thermal Infrared Recognition of Volcanic Hotspots. A single band TIR-based algorithm to detect low-to-high thermal anomalies in volcanic regions.

Detecting early signs of impending eruptions and monitoring the evolution of volcanic phenomena are fundamental objectives of applied volcanology, both essential for timely assessment of associated hazards. Thermal remote sensing proves to be a cost-effective, yet reliable, information source for these purposes, especially for the hundreds of volcanoes still lacking conventional ground-based monitoring networks. In this work, we present an innovative and effective single band TIR-based (11.45 μm) algorithm (TIRVolcH), capable of detecting thermal anomalies in a broad range of volcanic settings, from low-temperature hydrothermal systems to high-temperature effusive events. Based on the processing of Visible Infrared Imaging Radiometer Suite (VIIRS) scenes, the algorithm offers an unprecedented trade-off between spatial (375 m) and temporal resolution (multiple acquisitions per day), having the potential to detect thermal anomalies for pixel-integrated temperatures as low as 0.5 K above the background, while maintaining a false positive rate of ∼1.8 %. The analysis of decadal time series of VIIRS data (2012−2023), acquired at three different volcanoes, reveals how the algorithm can: (i) detect hydrothermal crises at fumarolic fields (Vulcano, Italy), (ii) unveil thermal unrest preceding dome extrusions and explosive eruptions (Agung, Indonesia), and (iii) spatially trace lava flows extent and quantify their advancement rate, as well as track their long-term cooling behaviour (La Palma, Spain).We envisage that the algorithm will prove instrumental for detecting early signs of volcanic activity and following the evolution of eruptive phenomena, providing a useful tool for hazard management and risk reduction applications. Furthermore, the compilation of statistically robust multidecadal thermal datasets will provide novel insights and new perspectives into volcano monitoring, laying the ground for forthcoming higher-resolution TIR missions.

Trends in climate change observed under tropical wet and tropical montane climates; A case study from Sri Lanka

Climate change-related changes in temperature and precipitation trends must be investigated at local, regional and global levels. Temperature and precipitation trends in two selected regions having tropical wet and tropical montane climates (i.e., Colombo and Nuwara Eliya respectively) in Sri Lanka were studied for a 30 year period from 1989 to 2019, to evaluate the temporal dynamics of climate change. Precipitation trends were analyzed on annual, monthly, and seasonal scales, while the trends in mean, minimum, and maximum temperatures were examined on annual and monthly scales. Decadal time series plots were used to study decadal variations in average temperature and precipitation. The trends in extreme temperature and precipitation events were also evaluated. In addition, the trends in diurnal temperature range (DTR), cool and warm nights, and heat index (HI) were studied. The significance of trends was evaluated using the Mann-Kendall test, while the magnitude of the slope was assessed by Sen’s slope estimator. Clear statistically significant increasing trends were observed for the mean annual temperatures under the tropical wet and tropical montane climates, and no clear trends were observed in annual precipitation in both districts. There were decreasing trends in south-west monsoon rainfall, with a significant decrease in Nuwara Eliya under the tropical montane climate. Increasing trends were observed for the average monthly precipitation in November (i.e., during the inter-monsoonal rains) and average monthly temperature in April (i.e., the hottest month) over the last decade (i.e., 2010-2019) in Colombo. The DTR has significantly decreased over the last three decades in Colombo. A significant upward trend was observed for HI values during the last decade in Colombo. Colombo also showed a statistically significant decreasing trend in the number of cool nights and a statistically significant decreasing trend in the number of warm nights over the last decade.

Interannual variability (2000–2013) of mesopelagic and bathypelagic particle fluxes in relation to variable sea ice cover in the eastern Fram Strait

The Fram Strait connects the Atlantic and Arctic Oceans and is a key conduit for sea ice advected southward by the Transpolar Drift and northward inflow of warm Atlantic Waters. Continued sea ice decline and “Atlantification” are expected to influence pelagic–benthic coupling in the Fram Strait and Arctic as a whole. However, interannual variability and the impact of changing ice conditions on deepwater particle fluxes in the Arctic remain poorly characterized. Here, we present long-term sediment trap records (2000–2013) from mesopelagic (200 m) and bathypelagic (2,300 m) depths at two locations (HGIV and HGN) in the Fram Strait subjected to variable ice conditions. Sediment trap catchment areas were estimated and combined with remote sensing data and a high-resolution model to determine the ice cover, chlorophyll concentration, and prevailing stratification regimes. Surface chlorophyll increased between 2000 and 2013, but there was no corresponding increase in POC flux, suggesting a shift in the efficiency of the biological carbon pump. A decrease in particulate biogenic Si flux, %opal, Si:POC, and Si:PIC at mesopelagic depths indicates a shift away from diatom-dominated export as a feasible explanation. Biogenic components accounted for 72% ± 16% of mass flux at 200 m, but were reduced to 34% ± 11% at 2,300 m, substituted by a residual (lithogenic) material. Total mass fluxes of biogenic components, including POC, were higher in the bathypelagic. Biomarkers and ∂13C values suggest both lateral advection and ice-rafted material contribute to benthic carbon input, although constraining their precise contribution remains challenging. The decadal time series was used to describe two end-members of catchment area conditions representing the maximum temperatures of Atlantic inflow water in 2005 at HGIV and high ice coverage and a meltwater stratification regime at HGN in 2007. Despite similar chlorophyll concentrations, bathypelagic POC flux, Si flux, Si:POC, and Si:PIC were higher and POC:PIC was lower in the high-ice/meltwater regime. Our findings suggest that ice concentration and associated meltwater regimes cause higher diatom flux. It is possible this will increase in the future Arctic as meltwater regimes increase, but it is likely to be a transient feature that will disappear when no ice remains.

Function Model Based on Nonlinear Transient Rheology of Rocks: An Analysis of Decadal GNSS Time Series After the 2011 Tohoku‐oki Earthquake

AbstractThe postseismic Global Navigation Satellite System (GNSS) time series after the 2011 Tohoku‐oki earthquake is often empirically explained by one or more logarithmic and exponential decay functions. However, a function model with these decay functions struggles to illuminate various deformation mechanisms. Here, we propose a new function model incorporating laboratory‐derived constitutive laws (power‐law flow and velocity‐strengthening friction) utilized in mechanical postseismic models of the last decade. We demonstrated that our function model accurately predicts the decade‐long time series of inland GNSS stations, including coastal areas where significant postseismic uplift continues now. Moreover, it decomposes them into displacements due to viscoelastic relaxation and afterslip, similar to results produced by previous stress‐dependent postseismic models of the 2011 Tohoku‐oki earthquake. This physics‐based function model is an effective tool to ease the process of forecasting long‐term GNSS time series by dividing them into two dominant mechanisms at the plate interface and the surrounding viscoelastic mantle.

Long-Term Observations of Sea Surface Temperature Variability in the Gulf of Mannar

In this study, we conducted long-term temporal and spatial observations of monthly, interannual, and decadal sea surface temperature (SST) variation in the Gulf of Mannar (GoM) for the period from 1870 to 2018. We obtained climatological data from the Met Office Hadley Centre, UK. The monthly time series revealed that April and August were the warmest and coolest months of the year, respectively. The mean SSTs for April and August were 29.85 ± 0.44 °C and 27.15 ± 0.49 °C, respectively. The mean annual highest and lowest SSTs were observed in 2015 and 1890 with SSTs of 28.93 ± 0.31 °C and 27.45 ± 0.31 °C, respectively, and the annual time series revealed a warming SST trend of 0.004 °C. Decadal time series also revealed a warming SST trend of 0.04 °C, with the highest and lowest mean decadal SSTs being 28.56 ± 0.21 °C in 2010–2018 and 27.78 ± 0.25 °C in 1890–1889, respectively. Throughout the study period, the spatial distribution of climate trends over decades across the GoM revealed a strong spatial gradient, and the region between 6–8° N and 77–78° E was warmer than all other regions of the GoM.

Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth

Abstract. The moisture content of vegetation canopies controls various ecosystem processes such as plant productivity, transpiration, mortality, and flammability. Leaf moisture content (here defined as the ratio of leaf water mass to leaf dry biomass, or live-fuel moisture content, LFMC) is a vegetation property that is frequently used to estimate flammability and the danger of fire occurrence and spread, and is widely measured at field sites around the globe. LFMC can be retrieved from satellite observations in the visible and infrared domain of the electromagnetic spectrum, which is however hampered by frequent cloud cover or low sun elevation angles. As an alternative, vegetation water content can be estimated from satellite observations in the microwave domain. For example, studies at local and regional scales have demonstrated the link between LFMC and vegetation optical depth (VOD) from passive microwave satellite observations. VOD describes the attenuation of microwaves in the vegetation layer. However, neither were the relations between VOD and LFMC investigated at large or global scales nor has VOD been used to estimate LFMC. Here we aim to estimate LFMC from VOD at large scales, i.e. at coarse spatial resolution, globally, and at daily time steps over past decadal timescales. Therefore, our objectives are: (1) to investigate the relation between VOD from different frequencies and LFMC derived from optical sensors and a global database of LFMC site measurements; (2) to test different model structures to estimate LFMC from VOD; and (3) to apply the best-performing model to estimate LFMC at global scales. Our results show that VOD is medium to highly correlated with LFMC in areas with medium to high coverage of short vegetation (grasslands, croplands, shrublands). Forested areas show on average weak correlations, but the variability in correlations is high. A logistic regression model that uses VOD and additionally leaf area index as predictor to account for canopy biomass reaches the highest performance in estimating LFMC. Applying this model to global VOD and LAI observations allows estimating LFMC globally over decadal time series at daily temporal sampling. The derived estimates of LFMC can be used to assess large-scale patterns and temporal changes in vegetation water status, drought conditions, and fire dynamics.

Interannual variability of the initiation of the phytoplankton growing period in two French coastal ecosystems

Abstract. Decadal time series of chlorophyll a concentrations sampled at high and low frequencies are explored to study climate-induced impacts on the processes inducing interannual variations in the initiation of the phytoplankton growing period (IPGP) in early spring. We specifically detail the IPGP in two contrasting coastal temperate ecosystems under the influence of rivers highly rich in nutrients: the Bay of Brest and the Bay of Vilaine. In both coastal ecosystems, we observed a large interannual variation in the IPGP influenced by sea temperature, river inputs, light availability (modulated by solar radiation and water turbidity), and turbulent mixing generated by tidal currents, wind stress, and river runoff. We show that the IPGP is delayed by around 30 d in 2019 in comparison with 2010. In situ observations and a one-dimensional vertical model coupling hydrodynamics, biogeochemistry, and sediment dynamics show that the IPGP generally does not depend on one specific environmental factor but on the interaction between several environmental factors. In these two bays, we demonstrate that the IPGP is mainly caused by sea surface temperature and available light conditions, mostly controlled by the turbidity of the system before first blooms. While both bays are hydrodynamically contrasted, the processes that modulate the IPGP are similar. In both bays, the IPGP can be delayed by cold spells and flood events at the end of winter, provided that these extreme events last several days.

The lower shoreface of the Dutch coast – An overview

The lower shoreface, defined here as between about 8 and 20 m water depth, forms the transition between the inner shelf and upper shoreface. Knowledge of lower shoreface hydro- and morphodynamics is essential for coastal management and maintenance.The shoreface of the Dutch coast is a complex area. It is partly determined by its evolution in the past, whereas present-day processes are influencing or even changing it. The present situation and large-scale anthropogenic supply of sediment will determine its future development.The shoreface morphology varies along the Dutch coast, depending on the coastal slope and superposition of ridges (central Holland coast) and ebb-tidal deltas (Delta area, Wadden Sea). The architecture of the shoreface-connected ridges off the central Holland coast indicates that they are still active today. The development of most ebb-tidal deltas along the Dutch coast is largely influenced by interventions in the tidal inlets and tidal basins.The Kustgenese 2.0 Lower Shoreface project comprised both field data collection in 2017 and 2018 and numerical modelling. Field data was collected in study areas at Ameland Inlet, Terschelling and Noordwijk. Sediment cores and multibeam sonar surveys provided information on the Holocene deposits, geomorphology and sediments. Instrumented frames placed at the seabed collected a wealth of process data.The variation in shoreface composition and morphology is larger than anticipated previously. In general, the lower part of the shoreface consists of older Holocene deposits overlain by an active sand layer that responds to variations in tidal, wave and wind conditions. The deposits at the lower shoreface of Terschelling were comparable to the ebb-delta channel deposits at the ebb-delta front at Ameland Inlet. At Noordwijk, deposits of the Late-Holocene prograded barrier shoreface overlie those of back-barrier tidal channels and river channels. The large-scale morphology of the lower shoreface seems rather stable. Decadal time series show an erosional trend. Small-scale bedforms can change over an interval of days to weeks.The multibeam surveys revealed unexpected details such as geology-based shoreface irregularities between −12m and −18m that probably act as conduits for downslope currents and sand transport. After a high-energy wave event, more erosional features were discovered that suggest seaward sand transport.Measured orbital velocities at the seabed at 14–16 m depth reached 1.5 m per second under high-wave events. This caused high sediment mobility under sheet-flow conditions with abundant sediment suspension. It is not clear what this means for the net sand transport at the lower shoreface.The modelled alongshore-directed sand transport is much larger than the cross-shore transport. The largest transports at the 20m depth contour occurs along the northern part of the Holland coast. Here, transport is parallel to the coast or directed to deeper water. Transports at 20 m depth along the other parts of the coast are directed to shallower water.The modelled total landward sand transport over the −20m contour is c. 4 million m3 per year and c. 7 million m3 per year over the −16m contour. This suggests a yearly erosion of c. 4 million m3 in-between, in case of no alongshore transport gradients.The results of the sand transport calculations imply a net landward sediment transfer that needs to be further tested against the morphological changes in the shoreface.

Exploring VIIRS Night Light Long-Term Time Series with CNN/SI for Urban Change Detection and Aerosol Monitoring

There is a great need to study the decadal long-term time series of urban night-light changes since the launch of Suomi NPP, NOAA-20, to future JPSS-2, 3, and 4 in the next decades. The recently recalibrated and reprocessed Suomi NPP VIIRS/DNB dataset overcomes a number of limitations in the operational data stream for time series studies. However, new methodologies are desirable to explore the large volume of historical data to reveal long-term socio-economic and environmental changes. In this study, we introduce a novel algorithm using convolutional neural network similarity index (CNN/SI) to rapidly and automatically identify cloud-free observations for selected cities. The derived decadal clear sky mean radiance time series allows us to study the urban night light changes over a long period of time. Our results show that the radiometric changes for some metropolitan areas changed on the order of 29% in the past decade, while others had no appreciable change. The strong seasonal variation in the mean radiance appears to be highly correlated with seasonal aerosol optical thickness. This study will facilitate the use of recalibrated/reprocessed data, and improve our understanding of urban night light changes due to geophysical, climatological, and socio-economic factors.

Long-term variation of sea surface temperature in relation to sea level pressure and surface wind speed in southern Indian Ocean

Sea surface temperature (SST) is an essential parameter associated with fish habitat and changes in oceanic conditions. Long-term SST variation in relation to sea level pressure (SLP) and surface wind speed (SWS) was observed based on the National Oceanic and Atmospheric Administration (NOAA) data of southern Indian Ocean. Mean monthly time series showed that February and November were the warmest and coolest months, respectively. Spatial distribution showed that 0°S–30°S was warm with SST of 20°–30°C, which was higher than that at all other places throughout the year. SLP (> 1010 millibar) and SWS (> 12 m/s) were high at 20°S–40°S and 45°S–50°S, respectively. SST was strongly negatively correlated with SWS but strongly positively correlated with SLP. Long-term yearly time series of SST showed that 2016 and 1948 were the warmest and coolest years, respectively, during the study period. Decadal time series showed that 1978–1987 had the highest decadal change. SST anomalies were almost negative before 1970, positive after 1970, high after 2008, and the highest in 2016. Southwest Indian Ocean was warmer than southeast Indian Ocean in summer and vice versa in winter. SST changes during 1948–2018 were higher than those during 1948–1972 and 1973–2018 for all the 4 months.

Characterizing the Long-Term, Wide-Band and Deep-Water Soundscape Off Hawai’i

Many animals use sound for communication, navigation, and foraging, particularly in deep water or at night when light is limited, so describing the soundscape is essential for understanding, protecting, and managing these species and their environments. The nearshore deep-water acoustic environment off the coast of Kona, Hawai’i, is not well documented but is expected to be strongly influenced by anthropogenic activities such as fishing, tourism, and other vessel activity. To characterize the deep-water soundscape in this area we used High-frequency Acoustic Recording Packages (HARPs) to record acoustic data year-round at a 200 or 320 kHz sampling rate. We analyzed data spanning more than 10 years (2007-2018) by producing measurements of frequency-specific energy and using a suite of detectors and classifiers for general and specific sound sources. This provided a time series for sounds coming from biological, anthropogenic and physical sources. The soundscape in this location is dominated by signals generated by humans and odontocete cetaceans (mostly delphinids), generally alternating on a diel cycle. During daylight hours the dominant sound sources are vessels and echosounders, with strong signals ranging from 10 Hz to 80 kHz and above, while during the night the clicks from odontocetes dominate the soundscape in mid-to-high frequencies, generally between 10 and 90 kHz. Winter-resident humpback whales are present seasonally and produce calls in lower frequencies (200-2,000 Hz). Overall, seasonal variability is relatively subtle, which is unsurprising given the tropical latitude and deep-water environment. These results, and particularly the inclusion of sounds from frequencies above 2 kHz, represent the first long-term analysis of a marine soundscape in the North Pacific, and the first assessment of the intense, daily presence of manmade noise at this site. The decadal time series allows us to characterize the dynamic nature of this location, and to begin to identify changes in the soundscape over time. This type of analysis facilitates protection of natural resources and effective management of human activities in an ecologically important area.

Spectral Recalibration of NOAA HIRS Longwave CO2 Channels toward a 40+ Year Time Series for Climate Studies

The High-Resolution Infrared Radiation Sounder (HIRS) on NOAA and MetOp A/B satellites has been observing the Earth continuously for over four decades, providing essential data for operational numerical weather prediction, retrieval of atmospheric vertical profile, and total column information on atmospheric temperature, moisture, water vapor, ozone, cloud climatology, and other geophysical parameters globally. Although the HIRS data meets the needs of the short-term weather forecast, there are inconsistencies when the long-term decadal time series is used for time series analysis. The discrepancies are caused by several factors, including spectral response differences between the HIRS models on the satellites and spectral response uncertainties and other calibration issues. Previous studies have demonstrated that significant improvements can be achieved by recalibrating some of the HIRS longwave CO2 channels (Channels 4, 5, 6, and 7), which has helped make the time series more consistent. The current study aims to extend the previous study to the remaining longwave infrared sounding channels, including Channels 1, 2, 3, and 8, using a similar approach. Similar to previous findings, the spectral shift of the HIRS bands has helped improve the consistency in the time series from NOAA-06 to MetOp-A and B for these channels. We also found that HIRS channels on MetOp-B also have bias relative to Infrared Atmospheric Sounding Interferometer (IASI) on the same satellite, especially Channel 4, and a spectral shift significantly reduced the bias. To bridge the observation gap in time series in the mid-1980s between NOAA-07 and NOAA-09, the global mean method has been used since no transfer radiometers between them was available for this period, and the spectral response function corrections, therefore, can be applied to the earliest satellites (NOAA-06) for these channels. The recalibration parameters have been provided to other scientists at the University of Wisconsin for improving the time series in their long-term studies using historical HIRS data and are now made available to the science community.

Decadal patterns and trends in benthic-pelagic exchange processes

In marine environments, the exchange of particles and solutes between the seafloor and overlying water column, known as benthic-pelagic (B/P) coupling is an important component in many biological and biogeochemical cycles. Key processes and drivers involved in this exchange display strongly seasonal variability, especially in temperate coastal environments. The magnitude and timings of these seasonal patterns however are not identical year-on-year, and the influence of this inter-annual variability on the rate and direction of B/P exchange, as well as the influence of longer term, multi-year trends, are less well understood. In this current study, multi-year temporal patterns of benthic-pelagic solute and particle exchange were investigated on the examples of particulate organic carbon and dissolved inorganic nitrogen time series data, to assess connections between inter- and multi-annual processes and characterize their nature and what drives them. To this end, a decadal (2009–2018) time-series dataset that combines biological, physical, meteorological and chemical measurements from the Western Channel Observatory, Plymouth, UK was analysed in combination with supplementary data from several environmental monitoring agencies. Time-series decomposition using seasonal decomposition with locally estimated scatterplot smoothing revealed that the main causes of inter-annual variability were extreme outlier events, some of which were influential enough to cause multi-annual trends. Stochastic meteorological and biological extremes, such as exceptional storms and phytoplankton blooms explained a large proportion of outlier events in the time series. Global-scale climatic fluctuations, such as North Atlantic Oscillation (NAO) and Southern Oscillation Index were reflected in benthic-pelagic exchange trends when they co-occurred in an additive manner (e.g. positive NAO and El Niño). The importance of multi-parameter long-term observatories, such as the Western Channel Observatory, is highlighted, and the use of transdisciplinary time-series datasets to identify individual events which have large ecosystem-level impacts is demonstrated. In order to identify and monitor long-term effects, such as climate trends or decadal global ocean cycles, multi-decadal sustained observations are of vital importance.

First retrievals of peroxyacetyl nitrate (PAN) from ground-based FTIR solar spectra recorded at remote sites, comparison with model and satellite data

Peroxyacetyl nitrate (PAN) is the main tropospheric reservoir of NOx (NO + NO2). Its lifetime can reach several months in the upper cold troposphere. This enables the long-range transport of NOx radicals, under the form of PAN, far from the regions of emission. The subsequent release of NOx through the PAN thermal decomposition leads to the efficient formation of tropospheric ozone (O3), with important consequences for tropospheric oxidative capacity and air quality. The chemical properties of PAN have stimulated the progressive development of remote-sensing products by the satellite community, and recent additions open the prospect for the production of decadal and near-global time series. These products will provide new constraints on the distribution and evolution of this key trace gas in the Earth’s atmosphere, but they will also require reliable measurements for validation and characterization of performance. We present an approach that has been developed to retrieve PAN total columns from ground-based high-resolution solar absorption Fourier transform infrared (FTIR) spectra. This strategy is applied to observations recorded at remote FTIR stations of the Network for the Detection of Atmospheric Composition Change (NDACC). The resulting data sets are compared with total column time series derived from IASI (Infrared Atmospheric Sounding Interferometer) satellite observations and to a global chemical transport model. The results are discussed in terms of their overall consistency, mutual agreement, and seasonal cycles. Noticeable is the fact that the FTIR data point to substantial deficiencies in the global model simulation over high latitudes, a poorly sampled region, with an underestimation of the PAN columns during spring, at the peak of the seasonal cycle. Finally, we suggest avenues for development that should make it possible to limit intra- or intersite biases and extend the retrieval of PAN to other NDACC stations that are more affected by water vapor interferences.

Local and non-local controls on seasonal variations in water availability and use by riparian trees along a hydroclimatic gradient

As global climate change continues to impact regional water cycles, we may expect further shifts in water availability to forests that create challenges for certain species and biomes. Lowland deciduous riparian forests are particularly vulnerable because tree species cannot migrate out of the stream corridor, and they rely on root zone water availability that is controlled by variations in both local climate conditions (e.g. precipitation, evaporation, and infiltration) and non-local hydroclimatic forcing (e.g. streamflow, snowmelt, recharge). To determine how the seasonal water source usage of riparian trees is controlled by local versus non-local variability in hydroclimatic regime, we reconstructed the seasonal oxygen isotope (δ 18 O) signature of water used by two riparian tree species with contrasting rooting depths, comprising ∼800 δ 18 O tree-ring cellulose measurements from 12 tree-level decadal time-series at sub-annual resolution (six samples per year), along a strong hydroclimatic gradient within the Rhône River basin, SE France. These results were evaluated alongside δ 18 O measurements made from potential endmember water sources and independent hydroclimatic metrics. Thus we characterize the seasonal evolution of both potential water availability at distinct rooting depths and tree water source use and investigate the generalized riparian tree response to seasonal variations in local versus non-local hydroclimatic forcing over a decade. We show: (a) distinct seasonal water use between species, based on differential access to groundwater; (b) substantial source switching in both species based on evolving water availability; and (c) that riparian trees are more dependent on locally controlled soil moisture with distance downstream, creating increased vulnerability to locally increasing temperatures. We also find that deeply rooted trees in lowland riparian floodplains are potentially vulnerable to climate change because of their high dependence on water supply from mountains. This effect is more pronounced downstream, where seasonal water table decline may lead to loss of water required for deeply rooted trees.

Catastrophic loss of tropical seagrass habitats at the Cocos (Keeling) Islands due to multiple stressors

Seagrass habitats at the Cocos (Keeling) Islands (CKI), a remote atoll in the Indian Ocean, have suffered a catastrophic decline over the last decade. Seagrass monitoring (1996–2020) in relation to dredging and coastal development works (2009 to 2011) provide a historical baseline, and document the decline of mixed tropical seagrass Thalassia hemprichii and macroalgal (predominantly Caulerpa spp.) beds over a decadal scale time series. Attribution of loss to coastal development is confounded by lagoon-wide die-off events in 2007, 2009 and 2012 and high air and water temperatures from 2009 to 2016, with evidence of broad scale changes, visible in satellite imagery between 2006 and 2018. We conclude that up to 80% of seagrass habitats in the CKI lagoon (~1200 ha) have been lost due to multiple stressors including episodic die-off events related to high temperatures and calm conditions, and loss due to sediment disturbance and increased turbidity. Grazing pressure from the resident green sea turtles (Chelonia mydas) may have also exacerbated the loss of seagrass, which in turn poses a dire threat to their ongoing health and survival. This study highlights the fragility of tropical seagrass habitats and the cascading effect of system imbalance as a result of anthropogenic pressures and climate drivers. Although small in comparison to global estimates, the loss of seagrass habitats at CKI could change the entire ecosystem of a remote atoll. Due to the significance of the Thalassia beds for coastal stability, as food for an isolated population of green sea turtles and as a fish nursery, rehabilitation efforts are warranted.

Warming temperatures lead to reduced summer carbon sequestration in the U.S. Corn Belt

The response of highly productive croplands at northern mid-latitudes to climate change is a primary source of uncertainty in the global carbon cycle, and a concern for future food production. We present a decadal time series (2007 to 2019) of hourly CO2 concentration measured at a very tall tower in the United States Corn Belt. Analyses of this record, with other long-term data in the region, reveal that warming has had a positive impact on net CO2 uptake during the early crop growth stage, but has reduced net CO2 uptake in both croplands and natural ecosystems during the peak growing season. Future increase in summer temperature is projected to reduce annual CO2 sequestration in the Corn Belt by 10–20%. These findings highlight the dynamic control of warming on cropland CO2 exchange and crop yields and challenge the paradigm that warming will continue to favor CO2 sequestration in northern mid-latitude ecosystems.

Multiple climate-driven cascading ecosystem effects after the loss of a foundation species

Climate change is evolving so fast that the related adverse effects on the environment are becoming noticeable. Thus, there is an urgent need to explore and understand the effects generated by multiple extreme climatic events (MECEs) on marine ecosystem functioning and the services provided. Accordingly, we combined long-term in-situ empirical observations in the Mediterranean Sea with a mesocosm manipulation to investigate the concurrence of increasing temperature and hypoxia events. By focussing on a foundation mussel species, we were able to detect several cascade events triggered by a mass mortality event caused by stressful temperature and oxygen conditions, and resulting in a loss of ecosystem services. The measured rates of chlorophyll-a, carbohydrates, proteins and lipids - in both particulate and sedimentary organic matter - were used as proxies of ecosystem functioning during pre- and post- disturbance events (MECEs). In the past, MECEs were crucial for individual performance, mussel population dynamics and biomass. Their effect propagated along the ecological hierarchy negatively affecting the associated community and ecosystem. Our results suggest that the protection and/or restoration of coastal areas requires careful consideration of ecosystem functioning. Significance statementOur decadal time-series recorded by a near-term ecological forecasting network of thermal sensor allowed us to record and monitor multiple extreme climatic events (MECEs; heat wave and hypoxia events), warning on the environmental change recorded on a pond system. By integrating observational and manipulative approaches, we showed how a MECE triggered cascade events, from individual-based impaired functioning up to biodiversity loss (community composition and structure changes). Our results emphasize the key role played by a foundation species in driving ecosystem functioning, and the synergistic effects of climatic drivers acting simultaneously.

Mapping bull kelp canopy in northern California using Landsat to enable long-term monitoring

Extending from central California to Alaska, bull kelp (Nereocystis luetkeana) forms seasonal kelp forests that are iconic coastal ecosystems in much of the eastern Pacific. Historical and ongoing field surveys and aerial imagery are used to provide biological data on kelp canopy cover and health, but satellite remote sensing provides the opportunity to generate consistent, long-term datasets over a large spatial scale. Robust satellite-based timeseries measurements of giant kelp (Macrocystis pyrifera) are available for much of the California coastline (e.g., Santa Barbara to Santa Cruz), but there have been no equivalent publications for bull kelp. Recent loss of bull kelp in northern California emphasized the need for more expansive long-term monitoring of canopy trends. We tested various kelp classification approaches using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to Landsat imagery, which allowed sufficient temporal and spatial data collection during bull kelp's narrow seasonal maximum, and compare with the California Department of Fish and Wildlife (CDFW) aerial survey canopy area product. We addressed five main topics that have relevance to enabling Landsat in long-term monitoring of bull kelp canopy coverage in northern California: (1) the effect of MESMA configurations applied to Landsat imagery, including software dependencies and endmember configurations, (2) comparison of Landsat to traditional surveys, (3) differences across Landsat sensors, (4) tidal influence on canopy area, and (5) trends in the decadal timeseries. We found that there was no statistical difference (p = 0.53) between MESMA platforms (IDL-based and a Python-scripted method; RMSE 1.5 km2 or 17.6% when normalized by the range in CDFW), and that a 7-endmember MESMA model provided the lowest RMSE (1.4 km2 or 16.9%). Furthermore, while tidal phases can submerge or emerge kelp canopy and thus potentially affect kelp detection, we found a weak and statistically insignificant correlation between tides and performance of our remote estimate of kelp canopy area. Canopy estimations from Landsat-8 images yielded a higher NRMSE than Landsat-4 and -5 images, but the lack of matchup limits comparison. Imagery from early fall yielded the largest coverage estimates. Overall, our results show that Landsat enables broad remote measurement of bull kelp canopy coverage to supplement existing survey methods and increase continuity of timeseries for monitoring long-term trends.

Does Satellite Chlorophyll‐a Respond to Southernmost Patagonian Dust? A Multi‐year, Event‐Based Approach

AbstractMineral aerosols may affect global climate indirectly by enhancing net primary productivity (NPP) upon deposition to the oceans and associated atmosphere‐to‐ocean CO2 flux. This mechanism is hypothesized to have contributed significantly to the last interglacial‐to‐glacial climatic transition. However, the dust‐NPP connection remains contentious for the present‐day climate system. We analyze the impact of southernmost Patagonian dust emissions on southwestern Atlantic Ocean continental shelf and proximal open ocean satellite chlorophyll‐a concentration. We use the first decadal time series of surface dust mass flux in southern Patagonia, along with in situ visibility data, to model dust emission, transport, and deposition to the ocean. We then perform a dust event‐based analysis of chlorophyll‐a time series, using a novel approach by which time series are corrected for post‐depositional particle advection due to ocean currents. Finally, we performed chemical analysis of iron in dust samples, a key micronutrient limiting phytoplankton biomass in high‐nutrient, low‐chlorophyll oceans such as offshore of the 200‐m isobath off Patagonia. We find no compelling evidence for an influence of dust as an enhancer of phytoplankton biomass either on shelf or proximal open ocean waters of the southwestern Atlantic Ocean. For open ocean waters this is consistent with a lack of source‐inherited bioavailable iron in dust samples. Future case studies addressing similar questions should concentrate on dust sources with identified high contents of bioavailable iron, particularly in the Southern Hemisphere where atmospheric processing of iron is weak.