Interannual Patterns Research Articles

Identifying climatic risks and relevant adaptation strategies for selected smallholder farming regions, Limpopo Province, South Africa

ABSTRACT Due to low adaptive capacities and high reliance on weather-sensitive natural ecosystems for their livelihoods and food production, smallholder farmers are highly vulnerable to risks associated with climate change and variability. Such risks are location-specific; thus, to cope with them, smallholder farmers require tailored adaptation strategies. To support these farmers, this study aimed to identify climatic risks threatening sustainable smallholder farming in the Limpopo Province regions of Gavaza, Ga-Makanye and Giyani. Weather station records spanning up to 1980–2021 were used to identify climatic risks, for the October–April dryland maize growing season. Risks were identified based on temporal trends and/or interannual variability patterns for reference evapotranspiration and a suite of agriculturally relevant rainfall and temperature indices. Based on the identified risks, tailor-made adaptation strategies were devised for application by farmers within the study region. The results revealed the specific risks of growing seasons becoming shorter and increasingly hotter with highly irregular rainfall patterns. To adapt and improve agricultural productivity despite these prevailing climatic risks, farmers within the study region will benefit if they plant drought tolerant, early maturing and higher yielding crop varieties, apply soil water conservation techniques and make use of seasonal and daily weather forecasts to guide their decision-making.

Biogeographic patterns of Pacific white‐sided dolphins based on long‐term passive acoustic records

AbstractAimThis study investigates the biogeographic patterns of Pacific white‐sided dolphins (Lagenorhynchus obliquidens) in the Eastern North Pacific based on long‐term passive acoustic records. We aim to elucidate the ecological and behavioural significance of distinct echolocation click types and their implications for population delineation, geographic distribution, environmental adaptation and management.LocationEastern North Pacific Ocean.Time Period2005–2021.Major Taxa StudiedPacific white‐sided dolphin.MethodsOver 50 cumulative years of passive acoustic monitoring (PAM) data from 14 locations were analyzed using a deep neural network to classify two distinct Pacific white‐sided dolphin echolocation click types. The study assessed spatial, diel, seasonal and interannual patterns of the two click types, correlating them with major environmental drivers such as the El Niño Southern Oscillation and the North Pacific Gyre Oscillation, and modeling long‐term spatial‐seasonal patterns.ResultsDistinct spatial, diel and seasonal patterns were observed for each click type. Significant biogeographical shifts in presence were observed following the 2014–2016 marine heatwave event.Main ConclusionsDistinct spatial distributions of the two click types support the hypothesis that Pacific white‐sided dolphins produce population‐specific echolocation clicks. Seasonal and diel patterns suggest spatiotemporal niche partitioning between the populations in Southern California. Interannual changes, notably initiated during the 2014–2016 marine heatwave, indicate climate‐driven range expansions and contractions related to gradual tropicalization of the Southern California Bight.

Evidence of environmental niche separation between threatened mobulid rays in Aotearoa New Zealand: Insights from species distribution modelling

AbstractAimMobulid rays are a group of threatened batoid fishes susceptible to population decline from targeted fisheries and accidental capture. Spatial distributions of mobulid rays remain poorly known. Prior studies found commonalities between favourable environments and prey among various mobulid species, yet most were conducted in tropical waters. To explore the habitat use and distribution of mobulid rays in a temperate environment we model the habitat suitability of two mobulid rays (Mobula mobular and Mobula birostris) in Aotearoa New Zealand using fisheries and citizen science occurrence data spanning almost two decades.LocationNortheastern coast of Aotearoa, New Zealand.MethodsBoosted Regression Tree models were used to predict the annual habitat suitability and favourable environmental conditions of the two species based on available sightings records in conjunction with high resolution (1 km2) environmental data.ResultsThe sympatric study species had contrasting habitat requirements. We found a separation in their spatial distribution defined by the 200 m isobath – the onshore extent for M. birostris and the offshore extent for M. mobular. While there were only subtle variations in relative habitat suitability for M. mobular over the study period, M. birostris exhibited greater interannual variability. Despite differing interannual patterns, spatial separation, as a function of environmental properties, persisted regardless of the year.Main ConclusionsOur results suggest that associations between mobulid species may differ from tropical regions due to regional adaptations to prey availability or local environmental conditions unique to colder and more productive temperate waters. Our findings highlight the importance of multi‐species surveys and the inclusion of temporal variability in support of separate species‐specific management plans to account for differing stressors impacting each species.

ANALISIS POLA CURAH HUJAN DI WILAYAH SUMATERA BAGIAN UTARA MENGGUNAKAN FAST FOURIER TRANSFORM (FFT)

This research was conducted in North Sumatra, namely at Iskandar Muda, Malikussaleh and Deli Serdang stations in the period 1885 to 2019. The purpose of the study was to analyze seasonal and interannual rainfall patterns. The method used is Fast Fourier Transform (FFT) and correlation between rainfall, sea surface temperature and wind. The results of the study showed that the rainfall pattern at Iskandar Muda, Malikussaleh and Deli Serdang stations had two peaks of rainfall. The peak rainfall of the three stations occurs in May and the second peak has differences between Deli Serdang and Iskandar Muda and Malikussaleh stations. Where the peaks of high periodization are only in the 6-month and 12-month periods. There is also a peak periodogram from each station seen in 18-30 months. Rainfall periodogram analysis shows the magnitude of data frequency for each phase cycle and its frequency. The correlation between rainfall, wind and sea surface temperature (SST) at the three stations has a different pattern. At Deli Serdang station, there is an influence of ENSO and IOD, while at Iskandar Muda and Malikussaleh stations there is no influence of ENSO and IOD. Then in the September, October, November (SON) season at the three stations there is no visible influence of ENSO and IOD.

Coherency and time lag analyses between MODIS vegetation indices and climate across forests and grasslands in the European temperate zone

Abstract. Identifying the climate-induced variability in the condition of vegetation is particularly important in the context of recent climate change and plants' impact on the mitigation of climate change. In this paper, we present the coherence and time lags in the spectral response of three individual vegetation types in the European temperate zone to the influencing meteorological factors in the period 2002–2022. Vegetation condition in broadleaved forest, coniferous forest and pastures was measured with monthly anomalies of two spectral indices – normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI). As meteorological elements we used monthly anomalies of temperature (T), precipitation (P), vapour pressure deficit (VPD), evapotranspiration (ETo), and the teleconnection indices North Atlantic Oscillation (NAO) and North Sea Caspian Pattern (NCP). Periodicity in the time series was assessed using the wavelet transform, but no significant intra- or interannual cycles were detected in both vegetation (NDVI and EVI) and meteorological variables. In turn, coherence between NDVI and EVI and meteorological elements was described using the methods of wavelet coherence and Pearson's linear correlation with time lag. In the European temperate zone analysed in this study, NAO produces strong coherence mostly for forests in a circa 1-year band and a weaker coherence in a circa 3-year band. For pastures these interannual patterns are hardly recognisable. The strongest relationships occur between conditions of the vegetation and T and ETo – they show high coherence in both forests and pastures. There is a significant cohesion with the 8–16-month (ca. 1-year) and 20–32-month (ca. 2-year) bands. More time-lagged significant correlations between vegetation indices and T occur for forests than for pastures, suggesting a significant lag in the forests' response to the changes in T.

Landscape position mediates drought vulnerability in California valley oak (Quercus lobata)

Future climate change will exacerbate drought stress in water-limited ecosystems. However, topography can alter the fine-scale climatic and hydrologic conditions that mediate plant response to meteorological drought. Here, with six new valley oak (Quercus lobata) tree-ring width chronologies, we assess how topography acts as a mediating factor on tree growth and drought sensitivity. Because valley oaks are known to be highly dependent on subsurface water, we predicted that trees growing in riparian sites would be less sensitive to precipitation variability due to greater access to groundwater. Trees were sampled in the Tehachapi Mountains of California across a landscape gradient of sites ranging from 375–1650 m elevation and across upland (55–69 m mean height above nearest drainage) and riparian (2–6 m mean height above the nearest drainage) hillslope positions. Interannual tree growth patterns and drought sensitivity varied substantially in association with hillslope position and elevation. Valley oak radial growth showed a consistently weaker response to precipitation at riparian sites. The influence of hillslope position on drought sensitivity varied with elevation, such that the riparian buffering effect was weakest at sites higher in the watershed and strengthened, progressively, toward the lower elevation sites with greater climatic water deficit. Upland tree growth exhibited a strong response to high-frequency interannual precipitation variability at the high elevation site, whereas trees at lower elevation upland sites responded more to low-frequency decadal trends in precipitation, possibly reflecting hydrogeological processes by which precipitation feeds groundwater lower in the watershed. Our results are consistent with groundwater-dependence of valley oak and indicate that riparian habitats are the most likely refugia for the species during prolonged drought.

Bacterial rarity in a subarctic stream network: Biodiversity patterns, assembly mechanisms and types of rarity.

Dendritic stream networks are an intriguing subject for exploring the spatial and temporal variability of the rare and common bacterial biosphere, yet very few such studies have been conducted. We sampled riverine bacterioplankton at 13 sites in a subarctic riverine network across 3 years, with five sampling times each year. Ordinations showed a consistent pattern of downstream shift for both rare and abundant subcommunities. We also detected a temporal signal, with seasonal community shifts reflecting changes in water temperature and groundwater contribution, and an inter-annual pattern where the year 2018 differed from other years. Phylogenetic turnover of the rare subcommunity indicated homogeneous selection, whereas the abundant subcommunity was mainly stochastically structured. Transiently rare taxa were the dominant type of rarity with the highest proportion at the headwater regions. The bacterioplankton community was characterized by a small group of core taxa that occurred at most sites with little temporal variation, a very large number of permanently or transiently rare taxa, and taxa shifting through time between the rare and abundant biosphere. While this basic structure could have been detected with less extensive temporal replication, a comprehensive understanding of the rare biosphere in riverine bacterioplankton can only be achieved via inter-annual, spatially replicated sampling that covers the whole stream network.

Decoding autumn phenology: Unraveling the link between observation methods and detected environmental cues.

Leaf coloring and fall mark the end of the growing season (EOS), playing essential roles in nutrient cycling, resource allocation, ecological interactions, and as climate change indicators. However, understanding future changes in autumn phenology is challenging due to the multitude of likely environmental cues and substantial variations in timing caused by different derivation methods. Yet, it remains unclear whether these two factors are independent or if methodological uncertainties influence the environmental cues determined. We derived start of growing season (SOS) and EOS at a mixed beech forest in Central Germany for the period 2000-2020 based on four different derivation methods using a unique long-term data set of in-situ data, canopy imagery, eddy covariance measurements, and satellite remote sensing data and determined their influence on a predictor analysis of leaf senescence. Both SOS and EOS exhibited substantial ranges in mean onset dates (39.5 and 28.6 days, respectively) across the different methods, although inter-annual variations and advancing SOS trends were similar across methods. Depending on the data, EOS trends were advanced or delayed, but inter-annual patterns correlated well (mean r = .46). Overall, warm, dry, and less photosynthetically productive growing seasons were more likely to be associated with a delayed EOS, while colder, wetter, and more photosynthetically productive vegetation periods resulted in an earlier EOS. In addition, contrary to recent results, no clear influence of pre-solstice vegetation activity on the timing of senescence was detected. However, most notable were the large differences in sign and strength of potential drivers both in the univariate and multivariate analyses when comparing derivation methodologies. The results suggest that an ensemble analysis of all available phenological data sources and derivation methods is needed for general statements on autumn phenology and its influencing variables and correct implementation of the senescence process in ecosystem models.

Ocean Temperatures Do Not Account for a Record-Setting Winter in the U.S. West

The record-setting winter of 2022–2023 came as an answer to both figurative and literal prayers for political leaders, policy makers, and water managers reliant on snowpacks in the Upper Colorado River Basin, a vital source of water for tens of millions of people across the Western United States. But this “drought-busting” winter was not well-predicted, in part because while interannual patterns of tropical ocean temperatures have a well-known relationship to precipitation patterns across much of the American West, the Upper Colorado is part of a liminal region where these connections tend to be comparatively weak. Using historical sea surface temperature and snowpack records, and leveraging a long-term cross-basin relationship to extend the timeline for evaluation, this analysis demonstrates that the 2022–2023 winter did not present in accordance with other high-snowpack winters in this region, and that the associative pattern of surface temperatures in the tropical Pacific, and snow water equivalent in the regions that stored and supplied most of the water to the Colorado River during the 2022–2023 winter, was not substantially different from a historically incoherent arrangement of long-term correlation. These findings suggest that stochastic variability plays an outsized role in influencing water availability in this region, even in extreme years, reinforcing the importance of other trends to inform water policy and management.

Precision of four calcified structures for age estimation of Black Carp

AbstractObjectiveBlack Carp Mylopharyngodon piceus is an emerging invasive species in North America with an expanding population in the Mississippi River basin. Current aging methods use a suite of structures for age estimation, and a single structure is needed to minimize processing time, to maximize consistency of age and growth measurements, and to allow for back‐calculation of individual fish length at age.MethodsIn total, 236 Black Carp were collected throughout the year from 2017 to 2019 through incidental captures by commercial fishers and biologists. In a subsample, 119 Black Carp from 429 to 1268 mm total length were compared for the precision of annuli counts by two experienced readers for the two anterior pectoral fin rays, the anterior dorsal fin ray, sectioned vertebrae, and lapilli otoliths based on percent exact agreement (PA), percent agreement within 1 year (PA ± 1), coefficient of variation (CV), and bubble plots. Consensus annuli counts were compared by PA and CV between structures. We applied annuli counts, as opposed to age, as fish were collected during all seasons and structures were examined independently by readers without knowledge of capture date.ResultVertebrae and dorsal rays had the highest PA between readers. Dorsal ray had the lowest CV and higher PA ± 1. Pectoral rays and lapilli otoliths had the lowest PA. Between‐structure consensus annuli counts indicated that pectoral rays and the dorsal ray annuli counts were the most similar (PA >70% and CV <12) and lapilli otoliths were the most dissimilar (PA >35% and CV >24). Reader‐reported confidence was highest for vertebrae, then in decreasing order, dorsal ray, pectoral rays, and lapilli otoliths. Lumens were present in all fin rays with only minor effects observed on annuli counts, aside from the anterior‐most pectoral fin ray, in which lumens obscured the presence of one or more potential annuli in 61% of structures.ConclusionThe dorsal ray had the highest agreement between readers, with agreement with ±1 year at 98%; the structure can be efficiently extracted and processed, and the structure's morphology and growth pattern are conducive to aging older fish. Vertebrae had high agreement between readers, but a systematic pattern of double bands in vertebrae increased the between‐reader variation in older fish as the interannual growth pattern compressed the viewable area; this was identified by readers based on aging criteria and highlights the need for training novice readers. Validation of annual growth in the tested suite of structures is still needed.

Nutrient and carbonate chemistry patterns associated with Karenia brevis blooms in three West Florida Shelf estuaries 2020-2023

Ocean acidification (OA) driven by eutrophication, riverine discharge, and other threats from local population growth that affect the inorganic carbonate system is already affecting the eastern Gulf of Mexico. Long-term declines in pH of ~ -0.001 pH units yr-1 have been observed in many southwest Florida estuaries over the past few decades. Coastal and estuarine waters of southwest Florida experience high biomass harmful algal blooms (HABs) of the dinoflagellate Karenia brevis nearly every year; and these blooms have the potential to impact and be impacted by seasonal to interannual patterns of carbonate chemistry. Sampling was conducted seasonally along three estuarine transects (Tampa Bay, Charlotte Harbor, Caloosahatchee River) between May 2020 and May 2023 to obtain baseline measurements of carbonate chemistry prior to, during, and following K. brevis blooms. Conductivity, temperature and depth data and discrete water samples for K. brevis cell abundance, nutrients, and carbonate chemistry (total alkalinity, dissolved inorganic carbonate (DIC), pCO2, and pHT were evaluated to identify seasonal patterns and linkages among carbonate system variables, nutrients, and K. brevis blooms. Karenia brevis blooms were observed during six samplings, and highest pCO2 and lowest pHT was observed either during or after blooms in all three estuaries. Highest average pH and lowest pCO2 were observed in Tampa Bay. In all three estuaries, average DIC and pHT were higher and pCO2 was lower during dry seasons than wet seasons. There was strong influence of net community calcification (NCC) and net community production (NCP) on the carbonate system; and NCC : NCP ratios in Tampa Bay, Charlotte Harbor, and the Caloosahatchee River were 0.83, 0.93, and 1.02, respectively. Linear relationships between salinity and dissolved ammonium, phosphate, and nitrate indicate strong influence of freshwater inflow from river input and discharge events on nutrient concentrations. This study is a first step towards connecting observations of high biomass blooms like those caused by K. brevis and alterations of carbonate chemistry in Southwest Florida. Our study demonstrates the need for integrated monitoring to improve understanding of interactions among the carbonate system, HABs, water quality, and acidification over local to regional spatial scales and event to decadal time scales.

Performance of Regional Climate Model Precipitation Simulations Over the Terrain‐Complex Andes‐Amazon Transition Region

AbstractRegional climate models (RCMs) are widely used to assess future impacts associated with climate change at regional and local scales. RCMs must represent relevant climate variables in the present‐day climate to be considered fit‐for‐purpose for impact assessment. This condition is particularly difficult to meet over complex regions such as the Andes‐Amazon transition region, where the Andean topography and abundance of tropical rainfall regimes remain a challenge for numerical climate models. In this study, we evaluate the ability of 30 regional climate simulations (6 RCMs driven by 10 global climate models) to reproduce historical (1981–2005) rainfall climatology and temporal variability over the Andes‐Amazon transition region. We assess spatio‐temporal features such as spatial distribution of rainfall, focusing on the orographic effects over the Andes‐Amazon “rainfall hotspots” region, and seasonal and interannual precipitation variability. The Eta RCM exhibits the highest spatial correlation (up to 0.6) and accurately reproduces mean annual precipitation and orographic precipitation patterns across the region, while some other RCMs have good performances at specific locations. Most RCMs simulate a wet bias over the highlands, particularly at the eastern Andean summits, as evidenced by the 100%–2,500% overestimations of precipitation in these regions. Annual cycles are well represented by most RCMs, but peak seasons are exaggerated, especially at equatorial locations. No RCM is particularly skillful in reproducing the interannual variability patterns. Results highlight skills and weaknesses of the different regional climate simulations, and can assist in the selection of regional climate simulations for impact studies in the Andes‐Amazon transition zone.

Spatiotemporal variation in clam recruitment among beaches in Washington State (USA)

AbstractAbundant clam populations provide ecosystem services and commercial and recreational shellfish harvests worldwide. Two non‐native clams (Manila clams, Ruditapes philippinarum; eastern soft‐shell clams, Mya arenaria) commonly populate mid‐intertidal zones of coarse‐sediment beaches in Washington State, USA. To better understand factors influencing their abundance, we used passive mid‐intertidal spat collectors to determine the density and distribution of clam recruits (150–500 μm shell length) at eight beaches spanning over 500 km and over two reproductive seasons (2016 and 2017). Cumulative seasonal recruitment (clams <500 μm) in 2016 and 2017 at +1.0 m MLLW ranged from 800 to 125,000 m−2 for Ruditapes philippinarum and 50–85,000 m−2 for M. arenaria, and did not differ by substrate type at small scales (gravel vs. crushed shell). At larger scales, different interannual recruitment patterns across sites did not dramatically shift the ranked order of highest and lowest recruitment sites. Cumulative recruitment tended to be lower at warmer sites, while timing of peak recruitment was not consistently related to temperature. Sites also differed in the relative recruitment of the two clam species, but most beaches had greater densities of R. philippinarum than M. arenaria at both recruitment and juvenile stages. Although recruitment densities differed by two orders of magnitude across sites, post‐settlement factors eliminated initial spatial variation within a year, dampening recruitment variability among these beaches that all contribute to commercial and recreational clam production.

Sea level variability and modeling in the Gulf of Guinea using supervised machine learning

The rising sea levels due to climate change are a significant concern, particularly for vulnerable, low-lying coastal regions like the Gulf of Guinea (GoG). To effectively address this issue, it is crucial to gain a comprehensive understanding of historical sea level variability, and the influencing factors, and develop a reliable modeling system for future projections. This knowledge is essential for informed planning and mitigation strategies aimed at protecting coastal communities and ecosystems. This study presents a comprehensive analysis of mean sea level anomaly (MSLA) trends in the GoG between 1993 and 2020, covering three distinct periods (1993–2002, 2003–2012, and 2013–2020). It investigates the connections between interannual sea level variability and large-scale oceanic and atmospheric forcings. Furthermore, the study evaluates the performance of supervised machine learning techniques to optimize sea level modeling. The findings reveal a consistent rise in MSLA linear trends across the basin, particularly pronounced in the northern region, with a total linear trend of 88 mm over the entire period. The highest decadal trend (38.7 mm) emerged during 2013–2020, with the most substantial percentage increment (100%) occurring in 2003–2012. Spatial variation in decadal sea-level trends was influenced by subbasin physical forcings. Strong interannual signals in the spatial sea level distribution were identified, linked to large-scale oceanic and atmospheric phenomena. Seasonal variations in sea level trends are attributed to seasonal changes in the forcing factors. The evaluation of supervised learning modeling methods indicates that Random Forest Regression and Gradient Boosting Machines are the most accurate, reproducing interannual sea level patterns in the GoG with 97% and 96% accuracy. These models could be used to derive regional sea level projections via downscaling of climate models. These findings provide essential insights for effective coastal management and climate adaptation strategies in the GoG.

Evolution of masting in plants is linked to investment in low tissue mortality

Masting, a variable and synchronized variation in reproductive effort is a prevalent strategy among perennial plants, but the factors leading to interspecific differences in masting remain unclear. Here, we investigate interannual patterns of reproductive investment in 517 species of terrestrial perennial plants, including herbs, graminoids, shrubs, and trees. We place these patterns in the context of the plants’ phylogeny, habitat, form and function. Our findings reveal that masting is widespread across the plant phylogeny. Nonetheless, reversion from masting to regular seed production is also common. While interannual variation in seed production is highest in temperate and boreal zones, our analysis controlling for environment and phylogeny indicates that masting is more frequent in species that invest in tissue longevity. Our modeling exposes masting-trait relationships that would otherwise remain hidden and provides large-scale evidence that the costs of delayed reproduction play a significant role in the evolution of variable reproduction in plants.

Wavelet Analysis of Ozone Driving Factors Based on ~20 Years of Ozonesonde Measurements in Beijing

A long-term vertical ozone observational dataset has been provided during 2001–2019 by ozonesonde measurements in Beijing on the North China Plain. Previous studies using this dataset primarily focused on the vertical characteristics of climatological ozone and its variation; however, the driving factors of ozone variation have not been well discussed. In this study, by applying the wavelet analysis method (including continuous wavelet transform and cross wavelet) and sliding correlation coefficients to ~20 years of ozonesonde measurements collected in Beijing, we analyzed the dominant modes of ozone column variability within three height ranges over Beijing (total column ozone: TOT; stratospheric column ozone: SCO; and tropospheric column ozone: TCO). Moreover, we also preliminarily discussed the relationship between these three ozone columns and the El Niño Southern Oscillation (ENSO), Quasi-biennial Oscillation (QBO), and 11-year solar activity cycle. The results revealed that the ozone columns within the three height ranges predominantly adhered to interannual variability patterns, and the short-term variabilities in TOT and SCO may have been related to eruptive volcanic activity. In comparison to the TOT and SCO, the TCO was more susceptible to the forcing influences of high-frequency factors such as pollutant transport. Similar to the results in other mid-latitude regions, strong ENSO and QBO signals were revealed in the interannual ozone column variability over Beijing. The TOT and SCO showed positive anomalous responses to ENSO warm-phase events, and the peak of the ENSO warm phase led the winter peaks of the TOT and SCO by approximately 3–6 months. During the strong cold–warm transition phase in 2009–2012, the TOT and SCO showed a significant positive correlation with the ENSO index. The strong seasonality of the meridional circulation process driven by the QBO led to a significant positive correlation between the QBO index and the TOT and SCO in the interannual cycle, except for two periods of abnormal QBO fluctuations in 2010–2012 and 2015–2017, whereas the TCO showed a time-lagged correlation of approximately 3 months in the annual cycle relative to the QBO due to the influence of the thermodynamic tropopause. In addition, analysis of the F10.7 index and the ozone columns revealed that the ozone columns over Beijing exhibited lagged responses to the peaks of sunspot activity, and there was no obvious correlation between ozone columns and 11-year solar activity cycle. Given the complex driving mechanism of the climatic factors on local ozone variability, the preliminary results obtained in this study still require further validation using longer time series of observational data and the combination of chemical models and more auxiliary data.

Vegetation dynamics over 18 years in response to seasonal climatic conditions and land use in the Kamiesberg mountains of the succulent Karoo, South Africa

Projections of vegetation change in response to future global change conditions are challenged by the lack of long-term, empirical data on how vegetation responds to the variability in climatic conditions. This is particularly true for biodiverse systems that are threatened by climate change such as the winter-rainfall Succulent Karoo biome of southern Africa. In this study we analyse long-term data (2002–2019) of two biodiversity observatories from the Kamiesberg Mountains in the Succulent Karoo. We employed the R package GLMMtmb to analyse counts of abundance and estimated cover values of vegetation as response variables and seasonal Standardised Precipitation-Evapotranspiration Index (SPEI), annual livestock density, topography and soil surface structure as predictors for the interannual change of life forms under low and high land use intensity. We compared the life form composition at the two contrasting land use types and found the cover and abundance of leaf succulents to be higher under low grazing intensity and that of stem succulents to be higher under high grazing intensity. The cover and abundance of herbaceous life forms varied over the years depending on the seasonal weather conditions. Our GLMM results reveal counts of abundance to be a sensitive predictor for population dynamics in various herbaceous and shrub life form types. Estimated cover values showed less of a response to interannual differences in the environmental drivers. All life forms responded strongly to high humid and cool conditions in the second half of the winter rainfall period, when the temperatures increase again. The abundance of leaf-succulent and non-succulent shrubs also responded positively to moderate conditions towards the end of the dry season. The extensive and hot dry summer season in turn had a significant negative effect on the survival of particularly young plants with low cover. Cover values showed no response to the conditions of the late dry season and were generally less sensitive to the variance in seasonal climatic conditions. Our results suggest that future changes in interannual patterns in climatic conditions will affect life form composition of the vegetation.

Conceptual models of dissolved carbon fluxes in a two-layer stratified lake: interannual typhoon responses under extreme climates

Abstract. Extreme climates affect the seasonal and interannual patterns of carbon (C) distribution in lentic ecosystems due to the regimes of river inflow and thermal stratification. Typhoons rapidly load substantial amounts of terrestrial C into smaller subtropical lakes (i.e., Yuan-Yang Lake in Taiwan, hereafter referred to as YYL), renewing and mixing the water column. We developed a conceptual dissolved C model and hypothesized that allochthonous C loading and river inflow intrusion may affect the dissolved inorganic C (DIC) and dissolved organic C (DOC) distributions in a small subtropical lake under these extreme climates. A two-layer conceptual C model was developed to explore how the DIC and DOC fluxes respond to typhoon disturbances on seasonal and interannual timescales in YYL while simultaneously considering autochthonous processes such as algal photosynthesis, remineralization, and vertical transformation. To compare the temporal patterns of fluxes between typhoon years (2015–2016) and non-typhoon years (2017–2018), monthly field samples were obtained and their DIC, DOC, and chlorophyll a (Chl a) concentrations measured. The results demonstrated that net ecosystem production was 3.14 times higher in typhoon years than in non-typhoon years. These results suggested that a loading of allochthonous C was the most crucial driver of the temporal variation in C fluxes in typhoon years because of changes in physical and biochemical processes, such as photosynthesis, mineralization, and vertical transportation. However, the lowered vertical transportation rate shaped the seasonal C in non-typhoon years due to thermal stratification within this small subtropical lake.

Identifying Outliers of the MODIS Leaf Area Index Data by Including Temporal Patterns in Post-Processing

The moderate resolution imaging spectroradiometer (MODIS) calculates the leaf area index (LAI) for each pixel without incorporating the temporal correlation information, leading to a higher sensitivity for the LAI that produces uncertainties in observed reflectance. As a result, an increased noise level is observed in the timeseries, making the data discontinuous and inconsistent in space and time. Therefore, it is important to identify and handle the outliers during the post-processing of MODIS data. This study proposed a method to identify the MODIS LAI outliers based on the analyses of temporal patterns, including the interannual and seasonal changes in the LAI. The analysis was carried out utilizing the data from 278 global MODIS LAI sites and the results were verified against the measurement obtained from 52 ground stations. The results from the analyses detected 50 and 92 outliers based on 1.5σ and 1.0σ standard deviations, respectively, of the difference between the MODIS LAI and ground measurements; correspondingly, 46 and 65 outliers, respectively, were identified by incorporating temporal patterns during the post-processing of the data. The validation results exhibited improved values of the coefficient of determination (R2) after eliminating the MODIS LAI outliers identified through the interannual and seasonal patterns. Specifically, the R2 between the ground measurement LAI and MODIS LAI increased from 0.51 to 0.54, 0.88, and 0.90 after eliminating MODIS LAI outliers when considering the interannual patterns, seasonal patterns, and both the interannual and seasonal patterns, respectively. The results from the study provided valuable information and theoretical support to improve MODIS LAI post-processing.

Seasonal dynamics of phytoplankton community assembly at the Blanes Bay Microbial Observatory (BBMO), NW Mediterranean Sea

The dynamics of phytoplankton biomass and community composition is important for the functioning of marine ecosystems and ocean biogeochemical cycles. However, there is a shortage of studies addressing the interannual seasonal patterns of phytoplankton community assembly due to sampling limitations. Here we study the seasonal dynamics of eight major phytoplankton groups over a 12 year period (2006 to 2018) using a time-series of taxonomic composition from the Blanes Bay Microbial Observatory (BBMO) in the North Western Mediterranean Sea: dinoflagellates, diatoms, coccolithophores, Prochlorococcus, Synechococcus, picoeukaryotes, nanoeukaryotes, and photosynthetic nanoflagellates. We combine the analysis of biotic factors (primary production, phytoplankton taxa, cell abundance, cell size, chlorophyll-a concentration, and phytoplankton biomass) and abiotic factors (nutrients, temperature, and irradiance) to provide a coherent picture of the observed seasonal patterns of phytoplankton community assembly. The BBMO ecosystem is seasonally heterogeneous in community composition, displaying large fluctuating alternations in phytoplankton group dominance throughout the year. The seasonal succession of phytoplankton groups tends to repeat itself every year in a regular fashion, being the seasonal variability of the phytoplankton groups larger than their interannual variability. We compute α-diversity, a measure of the effective richness of phytoplankton groups. The seasonality of α-diversity shows that it is lowest during winter and highest during summer. We compute temporal β-diversity, a measure of compositional heterogeneity of the phytoplankton community. The data show a sinusoidal behavior of β-diversity as a function of the temporal distance between samples, with a period of one year. We use the mirror index (1 - β-diversity) at a temporal distance of one month to compute the phytoplankton group turnover. The seasonality of turnover shows that it is highest during spring and autumn. To evaluate the validity of niche and neutral theories in predicting the interannual sinusoidal behavior of β-diversity, we performed numerical simulations using a mechanistic model. The results provide support to the niche theory for marine phytoplankton ecology and community assembly. The phytoplankton groups appear to follow their specific ecological niches, tracking the seasonal changes in environmental conditions. The ecological implications of these findings are that marine phytoplankton groups appear to fill distinct environmental niches and thus may have different functional roles in the ecosystem. Furthermore, they may be predictable using both mechanistic and species distribution modeling approaches. The climatological time-series presented here can be an excellent testing ground for evaluating the performance of these marine ecosystem models having an explicit representation of different phytoplankton groups.