Interannual Climate Variability Research Articles

Central-Pacific El Niño-Southern Oscillation less predictable under greenhouse warming

El Niño-Southern Oscillation (ENSO) is the dominant mode of interannual climate variability in the tropical Pacific, whose nature nevertheless may change significantly in a warming climate. Here, we show that the predictability of ENSO may decrease in the future. Across the models in the Coupled Model Intercomparison Project Phase 6 (CMIP6), we find a robust decrease of the persistence and predictability for the Central Pacific (CP) ENSO under global warming, notably in passing through the boreal spring. The strength of spring predictability barrier will be increased by 25% in the future. The reduced predictability of CP ENSO is caused by the faster warming over surface ocean in tropical Pacific and, in turn, the enhanced thermodynamical damping rate on CP ENSO in response to global warming. In contrast, the predictability of Eastern Pacific ENSO will not change. Our results suggest that future greenhouse warming will make the prediction of CP ENSO more challenging, with far-reaching implications on future climate predictions.

Sensitivity of root production to long‐term aridity under environmental perturbations in Chihuahuan Desert ecosystems

Abstract Root production influences carbon and nutrient cycles and subsidizes soil biodiversity. However, the long‐term dynamics and drivers of belowground production are poorly understood for most ecosystems. In drylands, fire, eutrophication, and precipitation regimes could affect not only root production but also how roots track interannual variability in climate. We manipulated the intra‐annual precipitation regime, soil nitrogen, and fire in four common Chihuahuan Desert ecosystem types (three grasslands and one shrubland) in New Mexico, USA, where the 100‐year record indicates both long‐term drying and increasing interannual variability in aridity. First, we evaluated how root production tracked aridity over 10–17 years using climate sensitivity functions, which quantify long‐term, nonlinear relationships between biological processes and climate. Next, we determined the degree to which perturbations by fire, nitrogen addition or intra‐annual rainfall altered the sensitivity of root production to both mean and interannual variability in aridity. All ecosystems had nonlinear climate sensitivities that predicted declines in production with increases in the interannual variance of aridity. However, root production was the most sensitive to aridity in Chihuahuan Desert shrubland, with reduced production under drier and more variable aridity. Among the perturbations, only fire altered the sensitivity of root production to aridity. Root production was more than twice as sensitive to declines with aridity following prescribed fire than in unburned conditions. Neither the intra‐annual seasonal rainfall regime nor chronic nitrogen fertilization altered the sensitivity of roots to aridity. Synthesis. Our results yield new insight into how dryland plant roots respond to climate change. Our comparison of dryland ecosystems of the northern Chihuahuan Desert predicted that root production in shrublands would be more sensitive to future climates that are drier and more variable than root production in dry grasslands. Field manipulations revealed that fire could amplify the climate sensitivity of dry grassland root production, but in contrast, the climate sensitivity of root production was largely resistant to changes in the seasonal rainfall regime or increased soil fertilization.

Global Multiproxy ENSO Reconstruction Over the Past Millennium

AbstractEl Niño‐Southern Oscillation (ENSO) is the leading mode of interannual climate variability that affects climate and society across the world. However, our understanding of ENSO variability is currently lacking due to short instrumental observations, which limit our confidence in predicting its future occurrence and impact. In this study, we use the nested principal component regression method to reconstruct the ENSO index based on a global‐scale proxy network of stable oxygen isotopes (δ18O). We account for the teleconnection changes that influence proxy records corresponding to different ENSO phases by using the isotope‐enabled Community Earth System Model. According to the precipitation δ18O–ENSO relationship, we reconstruct the ENSO index over the last eight hundred years based on the first two leading modes of the selected proxy records. The skill of ENSO reconstruction improves with an increased number of δ18O series distributed over the ENSO‐affected regions. Our new reconstruction shows high consistency with existing ENSO reconstructions during periods of strong ENSO variability, indicating that the global proxy records capture enhanced teleconnection signals during the phase of strong ENSO amplitude. There is a weak El Niño response 1 year after the large volcanic eruptions in our reconstruction, and the amplitude of ENSO is significantly correlated with volcanic intensity. The strengthened energetic interactions between the ocean and atmosphere following large volcanic eruptions result in enhanced sea surface temperature variability.

The interplay between climate and bedrock type determines litter decomposition in temperate forest ecosystems

At regional scale, it is dominantly considered in the European literature that litter decomposition is higher in soils from calcareous than siliceous bedrocks because of higher pH in the former forest ecosystems. We tested the alternative hypothesis that this should rather be due to differences in physical characteristics of the bedrock, with likely higher decomposition on calcareous than siliceous bedrocks in wet climates because of more favourable texture in the former and nutrient leaching in the latter, and the opposite in dry climates because of higher drought stress in calcareous soils. We assessed, four consecutive years with contrasting climates, the litter decomposition of a unified litter of Abies alba needles with the litterbag method in 70 forest sites located on both bedrocks and in wet oceanic and dry continental climates of the European Alps and the Pyrenees. Average and annual climate data were analysed with principal component analyses and the effects of bedrock type, average and annual climate drought stresses on litter decomposition were analysed, separately in the Alps and the Pyrenees, with analyses of variance. We found, in both mountain ranges, a highly significant bedrock type by average climate drought stress interaction on litter decomposition, due to a strong decrease in litter decomposition from wet oceanic to dry continental sites on calcareous bedrocks only. Although litter decomposition did not change over all years in siliceous sites with increasing climate drought stress, it increased during wet years in the dry continental sites only, in particular in the Pyrenees where interannual climate variability was higher. Together our results strongly support the physical hypothesis and not the chemical hypothesis. We argue that the chemical hypothesis was proposed based on studies only conducted in low elevation wet temperate sites comparing mull humus types from deciduous forests on calcareous soils to mor and moder humus types from evergreen forests on highly sandy siliceous bedrocks. Our study conducted on a wider range of climate and bedrock conditions bring strong evidence that litter decomposition is rather dependent on the physical characteristics of the bedrocks.

Spatial and temporal distribution of optimal maize sowing dates in Nigeria.

Climate change and inter-annual variability cause variation in rainfall commencement and cessation which has consequences for the maize growing season length and thus impact yields. This study therefore sought to determine the spatially explicit optimum maize sowing dates to enable site specific recommendations in Nigeria. Gridded weather and soil data, crop management and cultivar were used to simulate maize yield from 1981-2019 at a scale of 0.5°. A total of 37 potential sowing dates between 1 March and 7 November at an interval of 7 days for each year were evaluated. The optimum sowing date was the date which maximizes yield at harvest, keeping all other management factors constant. The results show that optimum sowing dates significantly vary across the country with northern Nigeria having notably delayed sowing dates compared to southern Nigeria which has earlier planting dates. The long-term optimal sowing dates significantly (p<0.05), shifted between the 1980s (1981-1990), and current (2011-2019), for most of the country. The most optimum planting dates of southern Nigeria shifted to later sowing dates while most optimum sowing dates of central and northern Nigeria shifted to earlier sowing dates. There was more variation in optimum sowing dates in the wetter than the drier agro-ecologies. Changes in climate explain changes in sowing dates in wetter agro-ecologies compared to drier agro-ecologies. The study concludes that the optimum sowing dates derived from this study and the corresponding methodology used to generate them can be used to improve cropping calendars in maize farming in Nigeria.

The Hybrid Recharge Delayed Oscillator: A More Realistic El Niño Conceptual Model

Abstract El Niño–Southern Oscillation (ENSO) is the leading mode of climate interannual variability, with large socioeconomical and environmental impacts, potentially increasing with climate change. Improving its understanding may shed further light on its predictability. Here we revisit the two main conceptual models for explaining ENSO cyclic nature, namely, the recharge oscillator (RO) and the advective–reflective delayed oscillator (DO). Some previous studies have argued that these two models capture similar physical processes. Yet, we show here that they actually capture two distinct roles of ocean wave dynamics in ENSO’s temperature tendency equation, using observations, reanalyses, and Climate Model Intercomparison Project (CMIP) models. The slow recharge/discharge process mostly influences central-eastern Pacific by favoring warmer equatorial undercurrent and equatorial upwelling, while the 6-month delayed advective–reflective feedback process dominates in the western-central Pacific. We thus propose a hybrid recharge delayed oscillator (RDO) that combines these two distinct processes into one conceptual model, more realistic than the RO or DO alone. The RDO eigenvalues (frequency and growth rate) are highly sensitive to the relative strengths of the recharge/discharge and delayed negative feedbacks, which have distinct dependencies to mean state. Combining these two feedbacks explains most of ENSO frequency diversity among models. Thanks to the two different spatial patterns involved, the RDO can even capture ENSO spatiotemporal diversity and complexity. We also develop a fully nonlinear and seasonal RDO, even more robust and realistic, investigating each nonlinear term. The great RDO sensitivity may explain the observed and simulated richness in ENSO’s characteristics and predictability. Significance Statement El Niño and La Niña events, and the related Southern Oscillation, cause the largest year-to-year variations of Earth’s climate. Yet the theories behind them are still debated, with two main conceptual models being the recharge oscillator and the delayed oscillator. Our purpose here is to address this debate by developing a more realistic theory, a hybrid recharge delayed oscillator. We show how simple yet realistic it is, with equivalent contributions from the slow recharge process and from the faster delayed feedback. It even captures the observed El Niño and La Niña diversity in space and in frequency. Future studies could use the simple theoretical framework provided here to investigate El Niño–Southern Oscillation (ENSO) in observations, theories, climate models diagnostics and forecasts, and global warming projections.

Strong Green‐Up of Tropical Asia During the 2015/16 El Niño

AbstractEl Niño/Southern Oscillation (ENSO) is the main climate mode that drives the interannual variability in climate and consequently vegetation greenness. While widespread green‐up has been reported and examined in tropical America during El Niño, it remains unclear how vegetation in tropical Asia changes during the period. Here, we used four remote sensing‐based leaf area index (LAI) products to investigate changes in vegetation greenness during the 2015/16 El Niño in tropical Asia. We found a strong green‐up during the 2015/16 El Niño in tropical Asia, with its regional average LAI stronger than that of tropical America. The drivers for the green‐up vary across the region, with radiation being the main driver for continental tropical Asia, and temperature and soil water anomalies in the west and east parts of maritime tropical Asia, respectively. These findings provide important insights into the response of tropical Asia's vegetation to extreme climate anomalies.

Study loss of vegetative cover and increased land surface temperature through remote sensing strategies under the inter-annual climate variability in Jinhua-Quzhou basin, China.

The Jinhua-Quzhou basin in China is one of the most susceptible areas to drought. Due to the loss of vegetation and great fluctuations in rainfall and surface temperature, global warming occurs. Timely, accurate, and effective drought monitoring is crucial for protecting local vegetation and determining which vegetation is most vulnerable to increased LST during the period 1982-2019. It assumes a strong correlation between loss of vegetation cover, changes in monsoon climate, drought, and increases in land surface temperature (LST).Due to significantly increased in LST, low precipitation and vegetation cover, NDVI, TVDI, VCI, and NAP are useful in characterizing drought mitigation strategies.The temperature vegetation drought index (TVDI), normalized difference vegetation index (NDVI), vegetation condition index (VCI), and monthly precipitation anomaly percentage (NAP) can be helped to characterize drought reduction strategies. Monthly NDVI, NAP, VCI, TVDI, normalized vegetation supply water index (NVSWI), temperature condition index (TCI), vegetation health index (VHI), and heat map analysis indicate that the Jinhua-Quzhou basin experienced drought during 1984, 1993, 2000, and 2011. Seasonal SR, WVP, WS, NDVI, VCI, and NAP charts confirm that the Jinhua-Quzhou basin was affected by severe drought in 1984, which continued and led to severe droughts in 1993, 2000, and 2011. Regression analysis showed a significant positive correlation between NDVI, TVDI, VCI, and NAP values, while NVSWI, TVDI, and VHI showed positive signs of good drought monitoring strategies. The research results confirm the correlation between loss of vegetation cover and LST, which is one of the causes of global warming. The distribution of drought changed a trend indicating that compared with the Jinhua region; the Quzhou region has more droughts. The changing trend of drought has characteristics from 1982 to 2019, and there are significant differences in drought changing trends between different Jinhua-Quzhou basin areas. Overall, from 1982 to 2019, the frequency of drought showed a downward trend. We believe that these results will provide useful tools for drought management plans and play a relevant role in mitigating the effects of drought and protecting humanity from climate hazards.

Multivariate analysis of inlet morphodynamics: The mixed sand-gravel ebb-tidal delta of Deben Estuary, Suffolk

The morphodynamics of inlets and ebb-tidal deltas often exhibit cyclic behaviour, controlled by wave-tide interactions and the influence of these on sediment-bypassing processes. Variation in the form and timing of inlet dynamics can occur in response to changes in the key sediment transport processes and sediment supply, and particularly the relative dominance of differential wave direction driving alongshore sediment transport. This paper investigates the morphodynamics of the Deben ebb-tidal delta through multivariate analysis of multi-annual bathymetry and metocean parameters covering the period 1991 to 2023. Results show that sediment bypassing and associated morphological change in this ebb-tidal delta follows variable behaviour mid-cycle, leading to change in the morphology and configuration of the ebb-delta from cycle to cycle. In the most recent cycle (since 2003), delta volume followed a stepwise growth driven by sediment influx periods, evident primarily in the updrift shoal, followed by cross-shore redistribution. Interannual variability in wave climate was clustered into four groups that capture the relative balance between the dominant NE and SW forcing. Sediment influx periods are mostly associated with subdued SW and increased NE forcing, but the summer and winter NE wave climate play different roles on the up- and downdrift, and upper and lower components of the ebb-delta system. Tide level has increased in the last 33 years, which is strongly correlated with ebb-delta volume increase. Wave and tide conditions have discrete and independent effects on the ebb-tidal delta, whereas wave-tide interactions do not significantly change these underlying influences.

Seasonal climate variations during Marine Isotope Stages 3 and 2 inferred from high‐resolution oxygen isotope ratios in horse tooth enamel from Lower Austria

AbstractWe present sequential oxygen isotope records (δ18Ophosphate vs. VSMOW) of horse tooth enamel phosphate of six individuals from two adjacent Palaeolithic sites in Lower Austria. Three molars from the site Krems‐Wachtberg date to 33–31k cal a bp, and three molars from Kammern‐Grubgraben to 24–20k cal a bp. All teeth show seasonal isotope variations, which are used to reconstruct the annual oxygen isotope composition of drinking water (δ18Odw) and palaeotemperatures. Measured δ18Ophosphate values ranged from 8.6 to 13.0‰ and from 10.8 to 13.9‰ at Krems‐Wachtberg and Kammern‐Grubgraben, respectively. An inverse modelling approach was used to reconstruct summer and winter temperatures after a correction for glacial oceanic source water δ18O. Reconstructed annual δ18Odw was −16.4 ± 1.5‰ at Krems‐Wachtberg and −15.3 ± 1.4‰ at Kammern‐Grubgraben, resulting in annual temperatures of −5.7 ± 3.1 and −3.5 ± 2.9°C, respectively. Summer and winter temperatures reconstructed from individual teeth exhibit high seasonal variations with moderate summer temperatures and extremely low winter temperatures typical for a polar tundra climate. Isotopic differences between individuals are attributed to interannual climate variability or to different drinking water sources. Our reconstructed temperatures are, overall, consistent with previously reported values from European horse teeth, when taking regional differences into account.

Phenotypic lags influence rapid evolution throughout a drought cycle.

Climate anomalies are increasing and posing strong selection, which can lead to rapid evolution. This is occurring on a backdrop of interannual variability that might weaken or even reverse selection. However, the effect of interannual climatic variability on rapid evolution is rarely considered. We study the climatic differences that contribute to rapid evolution throughout a 7-year period, encompassing a severe drought across 12 populations of Mimulus cardinalis (scarlet monkeyflower). Plants were grown in a common greenhouse environment under wet and dry treatments, where specific leaf area and date of flowering were measured. We examine the association between trait values and different climate metrics at different time periods, including the collection year, prior years, and cumulative metrics across sequential years. Of the climatic variables we assessed, we find that anomalies in mean annual precipitation best describe trait differences over our study period. Past climates, of 1-2 years prior, are often related to trait values in a conflicting direction to collection-year climate. Uncovering these complex climatic impacts on evolution is critical to better predict and interpret the impacts of climate change.

The impacts of interannual climate variation on pollination network structure of a sub-alpine meadow: from 2008 to 2021

The impacts of interannual climate variation on pollination network structure of a sub-alpine meadow: from 2008 to 2021

Simple hydrological models for assessing the impact of forest cover change on streamflow for large catchments with a dry tropical climate

ABSTRACT Hydrological models are widely used to assess the impact of climate variability and land use change on streamflow. However, it is uncertain whether these models are capable of simulating the impact given parameter interactions and inter-annual climate variability for large dry catchments. Two such catchments with extensive land clearing were selected to test three models – AWBM, Sacramento and SimHyd – in terms of their capacity to simulate streamflow during periods of vastly different levels of forest cover. AWBM outperformed others, and thus was further simplified as AWBM_C a with minimum performance deterioration to have only one transferable parameter: the average storage capacity, C a. A reduction of 21–28% in the C a value for the post-clearing period indicates a decrease in the amount of water stored for transpiration and consequently an increase in runoff-generation capacity. AWBM_C a can be used to predict the impact of forest cover change on streamflow with different C a values.

Growth-climate relationships of four tree species in the subtropical evergreen broad-leaved forests in Southwest China

Subtropical forests are an important carbon sink, yet our understanding on tree growth response to inter-annual climate variability remains limited. This study investigated the growth-climate relationships of four evergreen broad-leaved tree species (Stewartia pteropetiolata W. C. Cheng, Schima noronhae Reinw. ex Bl. Bijdr, Machilus gamblei King ex J. D. Hooker, and Machilus yunnanensis Lec) in the subtropical evergreen broad-leaved forests (EBFs) in the Ailao Mountains of Yunnan province, southwest China. We constructed tree ring-width residual chronologies for each species and correlated them with daily and monthly climate data. Ring-width chronologies of S. pteropetiolata and S. noronhae were positively correlated with precipitation, relative humidity, and self-calibrated Palmer drought index (scPDSI) during autumn of the previous year and spring-to-early summer of the current year, indicating that these two Theaceae species were sensitive to moisture availability. Tree radial growth of two Machilus species was primarily limited by excessive precipitation and dense cloud cover during the rainy season in this middle montane cloud forest. Moving correlations between climate variables and radial growth of all species were temporally unstable, with a weakening response to climate variability in recent decades. We highlight the dendroclimatic potential of evergreen broad-leaved tree species in moist subtropical forests. The findings offer a pertinent perspective, emphasizing the necessity of separately considering distinct ecological indicators for trees in order to obtain a comprehensive understanding of climate-growth responses within highly diverse subtropical forests.

Seedling recruitment in response to stand composition, interannual climate variability, and soil disturbance in the boreal mixed woods of Canada

AbstractAimSeedling recruitment is a vital process for forest regeneration and is influenced by various factors such as stand composition, climate, and soil disturbance. We conducted a long‐term field experiment (18 years) to study the effects of these factors and their interactions on seedling recruitment.LocationOur study focused on five main species in boreal mixed woods of eastern Canada: trembling aspen (Populus tremuloides), paper birch (Betula papyrifera), white spruce (Picea glauca), balsam fir (Abies balsamea), and white cedar (Thuja occidentalis).MethodsSixteen 1‐m2 seedling monitoring subplots were set up in each of seven stands originating from different wildfires (fire years ranging from 1760 to 1944), with a soil scarification treatment applied to every other subplot. Annual new seedling counts were related to growing‐season climate (mean temperature, growing degree days and drought code), scarification, and stand effects via a Bayesian generalized linear mixed model.ResultsSoil scarification had a large positive effect on seedling recruitment for three species (aspen, birch and spruce). As expected, high mean temperatures during the seed production period (two years prior to seedling emergence) increased seedling recruitment for all species but aspen. Contrary to other studies, we did not find a positive effect of dry conditions during the seed production period. Furthermore, high values of growing degree days suppressed conifer seedling recruitment. Except for white cedar, basal area was weakly correlated with seedling abundance, suggesting a small number of reproductive individuals is sufficient to saturate seedling recruitment.ConclusionOur findings underscore the importance of considering multiple factors, such as soil disturbance, climate, and stand composition, as well as their effects on different life stages when developing effective forest management strategies to promote regeneration in boreal mixed‐wood ecosystems.

ENSO phase locking, asymmetry and predictability in the INMCM Earth system model

Abstract Advanced numerical climate models are known to exhibit biases in simulating some features of El Niño–Southern Oscillation (ENSO), which is a key mode of interannual climate variability. In this study we analyze how two fundamental features of observed ENSO – asymmetry between hot and cold states and phase-locking to the annual cycle – are reflected in two different versions of the INMCM Earth system model (state-of-the-art Earth system model participating in the Coupled Model Intercomparison Project). We identify the above ENSO features using the conventional empirical orthogonal functions (EOF) analysis, which is applied to both observed and simulated upper ocean heat content (OHC) data in the tropical Pacific. We obtain that the observed tropical Pacific OHC variability is described well by two leading EOF-modes, which roughly reflect the fundamental recharge-discharge mechanism of ENSO. These modes exhibit strong seasonal cycles associated with ENSO phase locking while the revealed nonlinear dependencies between amplitudes of these cycles reflect ENSO asymmetry.We also assess and compare the predictability of observed and simulated ENSO based on linear inverse modelling. We find that the improved INMCM6 model has significant benefits in simulating described features of observed ENSO as compared with the previous INMCM5 model. The improvements of the INMCM6 model providing such benefits are discussed. We argue that proper cloud parameterization scheme is crucial for accurate simulation of ENSO dynamics with numerical climate models.

Palaeoglacier and palaeoclimate reconstruction since the Neoglacial of the central Gangdise Mountains, southern Tibetan Plateau

Palaeoglacier modelling is a crucial approach for reconstructing palaeoclimate. Although the timing of glaciations during the Little Ice Age (LIA) and Neoglacial in the central Gangdise Mountains has been partially determined, there are still undated fresh-looking moraines. This study utilized coupled mass balance and ice flow models to simulate the palaeoclimate during the five LIA glacial events (LIA-1 to LIA-5) and two Neoglacial glacial events (Neo-1 and Neo-2). The results revealed that the glacial volumes in the Gangdise Mountains during the LIA and Neoglacial periods ranged from ∼1.10 to 1.57 km3. Comparing the reconstructed climate with other proxies, it was found that Neo-2 and Neo-1 exhibited temperatures 0.54 to 0.82 °C and 0.7 to 1.0 °C lower than the present, respectively, with precipitation levels at 110–140% of the present. The temperatures during the LIA periods were 0.36 to 1 °C lower than the present, with precipitation levels at 80–120% of the present. The interannual variability of climate at decadal or centennial scales may have played a significant role in the formation of the LIA moraines.

Can inter-annual climate variability alone explain the glacier retreat since the Little Ice Age in the Hailuogou catchment, southeastern Tibetan Plateau?

Inter-annual climate variability has the potential to induce hundred-to-thousand meters of glacier length change, comparable to the glacier retreats from their Little Ice Age (LIA) positions (Roe and O'Neal, 2009). Distinguishing the roles of inter-annual climate variability and climate change in glacier changes can help us read the true climate signal from the history of glacial activity and provide a basis for detailed attribution of currently observed glacier retreats. Here, we used ArcGIS tools to reconstruct the LIA glacier in the Hailuogou catchment on the southeastern Tibetan Plateau (TP) and calculated the corresponding glacier equilibrium-line altitude (ELA). Based on the LIA ELA, we inferred the climate change supporting the LIA glaciers in the region. Further, we quantified the impact of inter-annual climate variability on the Hailuogou Glacier change using a three-stage linear model. During the LIA, the area of the Hailuogou Glacier was 42.64 km2 and its volume was 3.73 × 109 m3. The LIA ELA was 5068 m above sea level (a.s.l.), lowering by 213 m relatively to the present. The LIA summer temperature was estimated to be ∼1.31–2.21 °C colder than the present with the LIA precipitation constraint being 90–100% of the modern precipitation. Forced by the inter-annual variabilities in summer temperature and annual precipitation, the Hailuogou Glacier has a possible maximum negative excursion of 459 m, which can only explain 19.3% of the actual retreat since the LIA. According to the probability density function (PDF) of the modeled length anomalies, the likelihood is <1% for the actual glacier retreat completely due to the inter-annual climate variability. We therefore argued that the inter-annual climate variability alone cannot explain the glacier retreat since the LIA in the Hailuogou catchment. Further, glacier geometry and topography might be the main factors determining the strength of the response of the Hailuogou Glacier to inter-annual climate variability.

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

BackgroundThe nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate variability.MethodsWe used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery.ResultsSOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions.ConclusionsIn the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.

Multi-Timescale Characteristics of Southwestern Australia Nearshore Surface Current and Its Response to ENSO Revealed by High-Frequency Radar

The surface currents in coastal areas are closely related to the ecological environment and human activities, and are influenced by both local and remote factors of different timescales, resulting in complex genesis and multi-timescale characteristics. In this research, 9-year-long, hourly high-frequency radar (HFR) surface current observations are utilized together with satellite remote sensing reanalysis products and mooring data, and based on the Empirical Orthogonal Function (EOF) and correlation analysis, we revealed the multi-timescale characteristics of the surface currents in Fremantle Sea (32°S), Southwestern Australia, and explored the corresponding driving factors as well as the impact of El Niño-Southern Oscillation (ENSO) on the nearshore currents. Results show that the currents on the slope are dominated by the southward Leeuwin Current (LC), and the currents within the shelf are dominated by winds, which are subject to obvious diurnal and seasonal variations. The strong bathymetry variation there, from a wide shelf in the north to a narrow shelf in this study region, also plays an important role, resulting in the frequent occurrence of nearshore eddies. In addition, the near-zonal winds south of 30°S in winter contribute to the interannual variability of the Leeuwin Current at Fremantle, especially in 2011, when the onshore shelf circulation is particularly strong because of the climatic factors, together with the wind-driven offshore circulation, which results in significant and long-lasting eddies. The southward Leeuwin Current along Southwestern Australia shows a strong response to interannual climatic variability. During La Niña years, the equatorial thermal anomalies generate the westward anomalies in winds and equatorial currents, which in turn strengthen the Leeuwin Current and trigger the cross-shelf current as well as downwelling within the shelf at Fremantle, whereas during El Niño years, the climate anomalies and the response of coastal currents are opposite. This paper provides insights into the multi-timescale nature of coastal surface currents and the relative importance of different driving mechanisms. It also demonstrates the potential of HFR to reveal the response of nearshore currents to climate anomalies when combined with other multivariate data. Meanwhile, the methodology adopted in this research is applicable to other coastal regions with long-term available HFR observations.