Northern Subregions Research Articles

Local and regional variation in kelp loss and stability across coastal British Columbia

Kelp forests are among the most abundant coastal marine habitats but are vulnerable to climate change. The Northeast Pacific has experienced recent large-scale changes in kelp abundance and distribution, but little is known about changes north of the British Columbia (BC)-Washington border. Here, we assessed whether and how floating canopy kelp (Macrocystis pyrifera, Nereocystis luetkeana) distributions have changed in recent decades along the extensive coast of BC. We assembled and analysed available kelp distributional data, comparing snapshots of kelp linear extent from 1.5-3 decades ago (1994-2007) to recently collected data (2017-2021) across 11 different subregions spanning the province. We then leveraged timeseries, where available (n = 7 data sets), to contextualise patterns of change. In aggregate, the data suggest that kelp forests have declined considerably in some parts of the province, but with variable patterns of change across BC. In the warmest areas (southern BC), kelp persistence was negatively correlated with mean summer sea surface temperatures, which at times exceeded known thermal tolerances. In contrast, in northern subregions, top-down control by sea urchins and otters appeared to modulate kelp dynamics, with declines occurring in 2 subregions despite cool ocean temperatures. Timeseries data suggest that many declines occurred around the 2014-2016 marine heatwave, an event associated with sustained warming and altered trophic dynamics. Our results suggest that the extent of BC’s kelp forests has declined in some places in recent decades, but that regional and local-scale factors influence their responses to environmental change.

On-Orbit Response Characteristics of Fengyun-4A Lightning Mapping Imager (LMI) and Their Impacts on LMI Detection

Abstract The effects of the response characteristics of the Fengyun-4A Lightning Mapping Imager (LMI) on its detection capability were studied using the raw event data of LMI in 2020. The simultaneous observation data of the Lightning Imaging Sensor (LIS) on the International Space Station (ISS) were used to evaluate the LMI detection capability. The results reveal that the minimum detectable radiance of lightning events in the 16 subregions of LMI has shown regional differences, with the southern subregions lower than the northern subregions, indicating that the southern ones are more conducive to the identification of events. The diurnal variation of the detectable event radiance in all subregions presents the main peak around noon, which comes from the influence of the bright background and varies largely in different subregions depending on the subregions’ response capability. The overall high values and regional differences of flash properties observed by LMI also show strong correlation with the variation of the minimum detectable radiance of events. Moreover, it is found that the southwest subregions have the highest coincidence ratio (CR) with ISS LIS, followed by the southeast subregions and the northeast subregions, and the northwest subregions have the lowest CR, which is closely related to the response of each subregion. The LIS flashes that can be detected by LMI are brighter, larger, and last longer compared to the total LIS flashes. The findings in this study will help explain the inconsistency of the LMI detection capability and promote the LMI data processing associated with pixel energy distribution. Significance Statement The Fengyun-4A (FY-4A) Lightning Mapping Imager (LMI) is the first geostationary satellite-borne lightning imager developed in China, which has the ability to continuously observe lightning within a large field of view. However, in the application of the data, it was found that the detection capability of the LMI differed significantly in different regions and exhibited diurnal variations, which may be related to the response characteristics of the LMI detector. This study reveals the effect of the response characteristics of the LMI detector on its detection results. The findings will help improve the usability of LMI data and improve the processing of these data to adjust the observation inconsistency.

Evaluation of precipitation extremes over the Tibetan plateau using the NASA global daily downscaled datasets NEX-GDDP-CMIP6

The utility of statistically downscaled data is in its provision of detailed, high-resolution insights, surpassing global models, which is essential for precise assessments of climate impact. This study delves into the changes in extreme precipitation across the Tibetan Plateau (TP) and its five subregions, thereby deepening our understanding of climate impacts in the region. Employing NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6), which are bias-corrected and statistically downscaled, in conjunction with three gauge-based datasets (CN05.1, CMFD, GMFD) spanning from 1979 to 2014, this study conducts an extensive analysis using eight extreme precipitation indices in the TP. The findings reveal significant spatial disparities in extreme precipitation, with the southern subregion experiencing a significant increase while the two northern subregions show statistically insignificant changes. NEX-GDDP-CMIP6 performs best in the eastern subregion but fails to capture extreme precipitation characteristics in the southern and western subregions. Averaging over the whole period of 1979–2014 (climatology), the NEX-GDDP-CMIP6 dataset performs better on the intensity and persistence indices than on the absolute and relative threshold indices. NEX-GDDP-CMIP6's performance on climate trends is significantly below that of climatology. The NEX-GDDP-CMIP6 dataset has limitations over the TP because of its reliance on the underperforming GMFD reference data. This study provides a comprehensive understanding of the variability of extreme precipitation and disparities among different subregions of the TP, laying a robust scientific groundwork for climate impact studies and future projection in this region.

Synchronized Structure and Teleconnection Patterns of Meteorological Drought Events over the Yangtze River Basin, China

Investigating the synchronized structure and teleconnection patterns of meteorological drought events (MDEs) contributes to elucidating drought’s evolution. In this study, the CN05.1 gridded meteorological dataset from 1961 to 2021 was utilized to calculate the 3-month standardized precipitation evapotranspiration index (SPEI-3) for each grid in the Yangtze River Basin (YRB). Based on these SPEI-3 series, the grid-based MDEs were then extracted. Subsequently, event synchronization and complex networks were employed to construct the MDE synchronized network over the YRB. This network was used to identify the MDEs’ topological structure, synchronized subregions, and representative grids. Finally, the MDE characteristics and MDE teleconnection patterns of individual subregions were investigated. The results of the MDE topological structure show that the northeastern portion of the YRB tends to experience widespread MDEs, while specific areas in the upper reaches are prone to localized MDEs. Synchronous MDEs mainly propagate along the central pathway and the eastern pathway, which display relatively low MDE spatial coherence. The YRB is partitioned into eight MDE synchronized subregions, each exhibiting distinct characteristics in terms of the frequency, duration, total severity, and peak of MDEs, as well as MDE temporal frequency distributions. Among all teleconnection factors, El Niño–Southern Oscillation (ENSO) exerts a strong influence on MDEs in all subregions, the Pacific Decadal Oscillation (PDO) shows a significant association with MDEs in all subregions except for Subregion 3 in the southeast, the North Atlantic Oscillation (NAO) displays a significant influence on MDEs in the southern subregions of the YRB, and the Arctic Oscillation (AO) has a more pronounced influence on MDEs in the northern subregions. This study provides valuable insights on drought’s evolution within the YRB and offers guidance to policymakers for advanced preventive measures.

Prevalence of asymptomatic Leishmania infection and knowledge, perceptions, and practices in blood donors in mainland Portugal

BackgroundAsymptomatic infection is the most common outcome of exposure to Leishmania parasites. In the Mediterranean region, where Leishmania infantum is endemic, studies on the prevalence of asymptomatic infection have often relied on serological testing in blood donors. In Spain, regional studies have shown seroprevalence in blood donors between 1 and 8%; in Portugal, values of 0 and 2% were suggested by two localized studies, in different populations. The purpose of this study was (i) to estimate the prevalence of asymptomatic Leishmania infection in blood donors in mainland Portugal, and (ii) to study the association between the detection of antibodies to Leishmania and sociodemographic factors, and also the knowledge, perceptions and practices (KPP) of the blood donors regarding leishmaniasis.MethodsA cross-sectional study targeted the population of people who donated blood in mainland Portugal. Participants, distributed proportionally by municipality and aged between 18 and 65 years, were selected randomly in 347 blood collection points between February and June 2022, and completed a sociodemographic and a KPP questionnaire. Detection of anti-Leishmania antibodies in serum was performed using an ELISA commercial kit. Individual KPP scores were calculated by adding grades defined for each question.ResultsGlobally, 201/3763 samples were positive. The estimated national true seroprevalence was 4.8% (95% CI 4.1–5.5%). The proportion of positive results was significantly different between NUTS (Nomenclature of Territorial Units for Statistics) regions. Models suggested that seropositivity was significantly higher in male sex, people older than 25 years, or residing in the Centro NUTS2 region, but not in dog owners nor people with lower KPP scores. Overall, 72.3% of participants had previously heard of leishmaniasis and, in multivariate analysis, a higher Knowledge score was associated with age 25–40 years, female sex, ownership of dogs, and higher education.ConclusionsGlobal estimated true seroprevalence (4.8%) was similar to previous regional studies in blood donors in neighboring Spain. Higher seroprevalence values in the NUTS2 Centro region were consistent with incidence data from humans and seroprevalence studies in dogs. On the other hand, the low values in the Alentejo and the high values in the northern subregions may be the result of geographical shifts in parasite circulation due to climate change and should prompt localized and integrated, vector, canine, and human research, following a One Health approach.Graphical

Detection and Assessment of Changing Drought Events in China in the Context of Climate Change Based on the Intensity–Area–Duration Algorithm

Drought can have a significant impact on both society and the economy, resulting in issues such as scarcity of water and shortages of food and energy, as well as elevated health risks. However, as global temperatures continue to rise, the impact of drought events is increasingly exacerbated, manifested by an increase in the frequency, intensity, duration, and spatial extent of their effects. Therefore, studying the changing characteristics of drought events with the background of climate change is of great significance. Based on the high-precision and high-resolution CN05.1 dataset, this study obtained the monthly Standardized Precipitation Evapotranspiration Index (SPEI) dataset from 1961 to 2020, and then identified regional drought events in China using the Intensity–Area–Duration (IAD) method, which considers both temporal continuity and spatial dynamics. On this basis, the spatiotemporal variations in frequency, intensity, duration, and affected area of drought events in China and its seven subregions were analyzed. The results showed that the subregions located in the northern region of China generally have lower mean, maximum, and minimum temperatures than those located in the southern region, but the associated interannual change rate of the subregions in the north is higher than that in the south. As for the annual total precipitation, results show a clear pattern of decreasing southeast–northwest gradient, with an increasing trend in the northern subregions and a decreasing trend in the southern subregions except for the subregion south China (SC). The northeast of China (NE), SC, the southwest of China (SW) and north China (NC) are the regions with a high frequency of drought events in China, while the frequency of drought events in NW and Qinghai–Tibetan Plateau (QTP), although lower, is on a significantly increasing trend, and the increasing rate is higher than for the other regions. For drought intensity, Xinjiang (XJ) and QTP had greater drought intensity, and the change rate of these regions with greater drought intensity was also greater. The drought impact area in China showed a significant increasing trend, mainly concentrated in QTP, NW and NE. Particular attention needs to be focused on the southwest of QTP, where drought events in this region show a significant increase in frequency, intensity, duration and impact area.

Small and patchy is enough: An example about how toxic HAB events can spread through low resting cyst loads

The frequency of harmful algal blooms (HABs) has increased over the last two decades, a phenomenon enhanced by global climate change. However, the effects of climate change will not be distributed equally, and Chile has emerged as one important, vulnerable area. The Chilean Patagonian region (41‒56°S) hosts two marine ecoregions that support robust blue economies via wild fisheries, aquaculture, and tourism. However, the harmful algal bloom-forming dinoflagellate Alexandrium catenella, a causative agent of paralytic shellfish poisoning outbreaks, threatens the viability of blue industries in this region and others worldwide. Despite the proliferation of A. catenella blooms over the last few decades, the role of sedimentary resting cysts in the recurrence of harmful algal blooms and the species’ northward expansion across Chilean Patagonia is not well understood. As a resting cyst-producing species, the sediment-cyst dynamics of A. catenella likely contribute to the geographical expansion and bloom recurrence of this species. For this purpose, we analyzed a decade of A. catenella surface sediment cyst records across the two ecoregions of the Chilean Patagonian System that were further stratified into five subregions based on water temperature, salinity, dissolved oxygen, and nutrient characteristics. We also analyzed spatio-temporal cyst dynamics in a pre-, during-, and post-bloom scenario of the Chiloense ecoregion (more northern) of the Magellanic province. Our results indicated highly variable A. catenella resting cyst abundances, with a maximum of 221 cysts cm−3 recorded in 2002 after an intense bloom. Generalized linear mixed models and linear mixed models found that sampling season, subregion, and Total Organic Matter (%) explained resting cyst presence and density. The results also demonstrated the presence of A. catenella cysts in northern subregions, evidencing the northward geographical expansion observed during the last few decades. The risks of A. catenella bloom recurrence from small, patchy resting cyst distributions across broad geographical areas and under changing environmental conditions are discussed.

Investigating Whether the Ensemble Average of Multi-Global-Climate-Models Can Necessarily Better Project Seasonal Drought Conditions in China

Global drought patterns are substantially impacted by climate change, with far-reaching implications for socioeconomic and ecological systems. Existing global climate models (GCMs) are unable to accurately project precipitation and drought characteristics, particularly in countries or regions with complex topography and significant seasonal variability, such as China. Consequently, the purpose of this study is to assess the efficacy of GCMs, and their multi-model ensemble mean, as well as to investigate the seasonal drought characteristics in China using precipitation data from CMIP6 under various “possible future” scenarios. This study selected five GCMs with historical (1961–2014) and future (2015–2100) periods, namely CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-HR, MPI-ESM1-2-LR, and NorESM2-MM, as well as their ensemble mean ENS-CGMMN. Based on the China Daily Precipitation Analysis Product (CPAP) as the reference precipitation, the performance of these models is evaluated using the DISO index and the quantile mapping (QM) method for calibration, as well as seasonal-scale drought using the standardized precipitation index (SPI) and spatiotemporal variability analysis methods. In comparison to other climate models and the ensemble mean, the calibrated MPI-ESM1-2-HR model can more precisely describe the actual precipitation conditions at the seasonal scale. Under four scenarios, China’s climate will shift from arid to moist in the future period (2015–2100) (SSP126, SSP245, SSP370, and SSP585). Autumn and summer will see a considerable increase in China’s moisture levels. During the autumn, winter, and spring, the moisture will generally increase in the northern subregions of China, including the Qinghai-Tibet Plateau (QTP), Xinjiang (XJ), Northwest (NW), Northeast (NE), and North China (NC). Dryness will decrease in southern subregions, such as the Southwest (SW) and South China (SC). In contrast to these three seasons, summer in XJ exhibits a distinct trend of aridity, especially in the SSP245 scenario, whereas the NE, NC, and SC exhibit a distinct trend of moisture. To be more specific, the aridity changes in subregions during various seasons under different future climate scenarios vary significantly. This study’s findings can provide significant support for future research on climate change and drought, which can help improve the accuracy of future climate projections and serve as a reference for drought risk management and policy formulation.

The Role of Old Relicts in Structuring the Boreal/Tropical Transitional Zone: The Case of East Asian Planktonic Cladocera (Crustacea)

Previous studies provided evidence of the mixing of boreal–tropical cladocerans (Crustacea) in the Far East of Eurasia, as well as the presence of numerous pre-Pleistocene relict endemics. In this study, we hypothesize that the colonization history is reflected in the proportions of endemic/boreal/tropical taxa among different habitat types within this region. We analyzed 442 qualitative samples collected from seven sub-regions of the Far East of Russia and South Korea along a latitudinal transect of approximately 2200 km, where we identified 101 Cladocera species. Our results showed a significantly higher proportion of endemic taxa in the plankton compared to the littoral and benthic zones. The proportions of endemic/boreal/tropical taxa in the permanent and temporary waters were similar. We observed a distinct shift in dominance in benthos and littoral zone across our transect: boreal taxa were prevalent in the northern sub-regions (1–4), while tropical taxa were prevalent in the southern sub-regions (5–7), with a pronounced boreal–tropical transition zone (sub-regions 4–5). Our findings suggest that this pattern arose due to the unhindered dispersion of the two faunas in a latitudinal direction until they met at the boundary during their arrival in the Late Pleistocene. In contrast, the proportions of the boreal and tropical taxa in plankton did not exceed 16% in any of the studied sub-regions, and the proportion of boreal taxa decreased from 16% to 10%, while that of the tropical taxa increased from 0% to 10% from north to south. We propose that the lower proportions and the absence of mixing of fauna in the plankton can be explained by the strong presence (sometimes dominance) of relics that occupy these water bodies before the arrival of colonizers from the north and south. Our findings highlight the significant role of biotic interactions in the formation of biogeographic boundaries, which was previously underestimated.

The impact of China's trade and FDI on Africa's GVC participation and economic upgrading

PurposeThis study examines the impact of China's trade and foreign direct investment (FDI) on Africa's global value chain (GVC) participation and economic upgrading.Design/methodology/approachThe study covered 48 African countries, cutting across the western, eastern, central, southern and northern subregions to cover the heterogeneity of the continent. The study adopted feasible generalized least squares panel VAR-Granger causality Wald test and system generalized methods of moments techniques for estimation.FindingsOverall, China's FDI to Africa and US-Africa trade have a linear relationship with Africa's GVC involvement and economic upgrading. The findings suggest that although China-Africa trade has a positive impact on GVC engagement and upgrading, the marginal effect decreases in the face of US-Africa and EU-Africa trade.Originality/valueThis study provides new evidence on the impact of China's FDI and trade on African economies' GVC participation and economic upgrading. To the best of the authors’ knowledge, this is the first study to empirically explore the effects of China's FDI and trade on Africa's GVC integration and economic upgrading as well as from the perspectives of backward and forward GVC participation. Furthermore, the study empirically examines whether the effects of Africa's economic cooperation with China relative to its GVC engagement differ from those of Europe (EU) and the US via a comparative regression.

A Climatology of Extreme Convective Storms in Tropical and Subtropical East Asia and Their Ingredients for Heavy Rainfall as Seen by TRMM.

Heavy rainfall is a challenge to forecast due to the variety of rainfall intensities and durations across a wide spectrum of high-impact storm types. In this study, we analyze extreme storms in Tropical and Subtropical East Asia, a moisture-rich environment with complex terrain and oceanic regions. The Tropical Rainfall Measuring Mission's Precipitation Radar is utilized to characterize the frequency and rainfall intensity of four extreme storm types. Extreme storms producing heavy precipitation are categorized into four types: deep convective cores (DCCs), deepwide convective cores (DWCCs), wide convective cores (WCCs), and broad stratiforms regions (BSRs). DCCs and DWCCs occur more frequently and produce stronger rain intensities over land compared to those over ocean. However, WCCs and BSRs occur more frequently over oceans, especially in association with the Meiyu front season and climatological progression in the northern subregions. Although the Convective Cores show higher rain intensities than the BSRs, they show lower volumetric rain rate due to their comparatively smaller horizontal area. An ingredients-based framework is applied to find key similarities across the different heavy rainfall-producing storms near Taiwan using ERA5 reanalysis. The analysis shows that the broader systems (i.e., WCCs and BSRs) are associated with larger in area and longer timescales of vertical moisture flux and low-level wind shear that support the development of the horizontally large, organized storms. Smaller DCCs do not show strong vertical moisture flux on the spatial scales resolved by the reanalysis, suggesting their more local nature and less meso- or synoptic scale support.

Clarifying rural-urban disparities in alcohol-related emergency department visits and hospitalizations in Ontario, Canada: A spatial analysis.

Rates of alcohol-related harm are higher in rural versus urban Canada. This study characterized the spatial distribution and regional determinants of alcohol-related emergency department (ED) visits and hospitalizations in Ontario to better understand this rural-urban disparity. This was a cross-sectional spatial analysis of rates of alcohol-related ED visits and hospitalizations by Ministry of Health subregion (n = 76) in Ontario, Canada between 2016 and 2019. Regional hot- and cold-spots of alcohol-related harm were identified using spatial autocorrelation methods. Rurality was measured as the population weighted geographic remoteness of a subregion. The associations between rurality and rates of alcohol-related ED visits and hospitalizations were evaluated using hierarchical Bayesian spatial regression models. Rates of alcohol-related ED visits and hospitalizations varied substantially between subregions, with high rates clustering in Northern Ontario. Overall, increasing rurality was associated with higher subregion-level rates of alcohol-related ED visits (males adjusted relative rate [aRR]: 1.67, 95% credible interval [CI]: 1.49-1.87; females aRR: 1.78, 95% CI: 1.60-1.98) and hospitalizations (males aRR: 1.34, 95% CI: 1.24-1.45; females aRR: 1.59, 95% CI: 1.45-1.74). However, after the province was separated into Northern and Southern strata, this association only held in Northern subregions. In contrast, increasing rurality was associated with lower rates of alcohol-related ED visits in Southern subregions (males aRR: 0.87, 95% CI: 0.79-0.96; females aRR: 0.88, 95% CI: 0.81-0.97). There are regional differences in the association between rurality and alcohol-related health service use. This regional variation should be considered when developing health policies to minimize geographic disparities in alcohol-related harm.

Analyzing the Spatial Correspondence between Different Date Fruit Cultivars and Farms’ Cultivated Areas, Case Study: Al-Ahsa Oasis, Kingdom of Saudi Arabia

Diversity in date palm (DP) cultivars plays a crucial role in the agroecosystems of several countries, such as the Kingdom of Saudi Arabia (KSA). This study aims to map and analyze the spatial distribution of the most grown DP cultivars (Khlas, Ruziz, and Shishi) in the Al-Ahsa oasis in the KSA and to highlight their spatial correlation with the corresponding cultivated patches within farms. Descriptive and spatial data on 288 farms were analyzed using GIS, data curation, cross-TAB statistics, clustering maps, and spatial autocorrelation techniques. The obtained results revealed that most of the oasis’s DP farms are within a cultivated area of <500 m2. The larger cultivated areas are mostly in the oasis’s northern and central subregions, agreeing with the spatial distribution of trees. In total, 56.9% of the studied farms grew the cultivars together within the least rank (<500 m2) of cultivated area, having the greatest tendency for DP cultivation. Khlas was the most dominant cultivar being the least absent from cultivation with 3.1% compared to Ruziz (31.9%) and Shishi (37.8%). The spatial distribution of DP plantations in the oasis was also consistent with the spatial variation in soils and irrigation water salinity, necessitating the need for special agricultural extension programs. In conclusion, these outcomes indicate that this study is essential for DP sustainability, growers, authorities, and policy makers.

Evaluation of CMIP6 models in the representation of observed extreme temperature indices trends in South America

The consequences of climate change are particularly noticeable through extreme events, which have already changed in intensity and frequency worldwide. This study aims to evaluate the ability of 33 CMIP6 models to simulate the observed trends of four extreme temperature indices in South America during the period 1979–2014. We use daily minimum and maximum temperatures from an observational database, ERA5 reanalysis, and CMIP6 models to estimate the international indices: cold nights, warm nights, cold days, and warm days. Trends are calculated using Sen’s slope for different seasons and spatial scales (continental, sub-regional, and at each grid point) and tested with the Mann–Kendall test. All databases agree on an increase (decrease) in the frequency of warm (cold) extremes in South America, with the most intense changes in the austral spring. In particular, the warm nights index and the northern sub-regions of South America show the most pronounced trends. In contrast, in the southern sub-regions of South America, the observations do not indicate significant trends of the minimum temperature indices, which differ from the trends estimated by the CMIP6 ensemble median and most of the individual models. In general, the ensemble median simulates significant long-term changes at almost all grid points, unlike the observations and reanalysis. Finally, the simulated trends related to minimum temperature are slightly better represented than those related to maximum temperatures. Nevertheless, neither model stands out as the best, and all of them have difficulty simulating trends, especially for cold days.

Separating the impacts of heat stress events from rising mean temperatures on winter wheat yield of China

Warming due to climate change has profound impacts on regional crop yields, and this includes impacts from rising mean growing season temperature and heat stress events. Adapting to these two impacts could be substantially different, and the overall contribution of these two factors on the effects of climate warming and crop yield is not known. This study used the improved WheatGrow model, which can reproduce the effects of temperature change and heat stress, along with detailed information from 19 location-specific cultivars and local agronomic management practices at 129 research stations across the main wheat-producing region of China, to quantify the regional impacts of temperature increase and heat stress separately on wheat in China. Historical climate, plus two future low-warming scenarios (1.5 °C/2.0 °C warming above pre-industrial) and one future high-warming scenario (RCP8.5), were applied using the crop model, without considering elevated CO2 effects. The results showed that heat stress and its yield impact were more severe in the cooler northern sub-regions than the warmer southern sub-regions with historical and future warming scenarios. Heat stress was estimated to reduce wheat yield in most of northern sub-regions by 2.0%–4.0% (up to 29% in extreme years) under the historical climate. Climate warming is projected to increase heat stress events in frequency and extent, especially in northern sub-regions. Surprisingly, higher warming did not result in more yield-impacting heat stress compared to low-warming, due to advanced phenology with mean warming and finally avoiding heat stress events during grain filling in summer. Most negative impacts of climate warming are attributed to increasing mean growing-season temperature, while changes in heat stress are projected to reduce wheat yields by an additional 1.0%–1.5% in northern sub-regions. Adapting to climate change in China must consider the different regional and temperature impacts to be effective.

The impact of China's trade, aid and FDI on African economies

PurposeThis study examines the impact of China’s trade, aid and foreign direct investment (FDI) on the economic growth of Africa.Design/methodology/approachOur study covered 41 countries in Africa, cutting across the western, eastern, central, southern and northern sub-regions. The study adopted the dynamic system generalized method of moments (SGMM), feasible generalized least squares (FGLS) and Dumitrescu–Hurlin Panel Granger causality techniques for estimations.FindingsOverall, FDI, trade and aid from China have a nonlinear relationship with Africa’s economic growth. The findings reveal a key novelty in that the marginal effect on real per capita GDP increases when China’s FDI interacts with the manufacturing sector in Africa. These findings are robust to long-run estimations.Research limitations/implicationsGiven that we have examined the short-and long-run symbiotic effects of China’s FDI and Africa’s manufacturing sector and China’s aid and Africa’s manufacturing sector, more studies are warranted in this area, particularly to produce further empirical evidence of these findings. Moreover, future work could focus on investigating the country-specific effects of China’s trade, China’s FDI and China’s aid on real GDP per capita in each African country as our results reflect within-country elasticities.Originality/valueThis study provides new evidence on the impact of China’s trade, aid and FDI on the growth of African economies. To the best of our knowledge, this is the first study to empirically explore the long-run effects of China’s trade, FDI and aid on economic growth in African countries. This study also tests the claim of the displacement of Africa’s manufacturing industry by its Chinese counterparts.

Tracking the origins of moisture over Vietnam: The role of moisture sources and atmospheric drivers on seasonal hydroclimatic conditions

AbstractA Lagrangian approach is used to identify the seasonal climatological moisture sources of the seven climate subregions of Vietnam during 1980–2017. Using the outputs from the FLEXPART model, three main oceanic moisture sources, located in the Arabian Sea, Bay of Bengal, and China Seas, and three terrestrial moisture sources, located in the Indian Peninsula, East Asia, and South Asia, are identified. The most important moisture source during the rainy season (May–October) is the Bay of Bengal, followed by the East Asia continental source for the North‐East and North Plain subregions, while for the remaining sub‐regions Arabian Sea is the main source. For the dry season (November–April), the China Sea supplies more than the half of the total moisture over almost all subregions, while the continental South Asia source is the primary one for the North‐West subregion. The moisture contributions from oceanic moisture sources are the major contributions to the Vietnam subregions, except for the North‐West subregion where the terrestrial sources form the major percentage. Severe and extremely dry conditions are identified for both the rainy and dry seasons in all subregions using the 6‐month Standardised Precipitation Evapotranspiration Index (SPEI6), and a positive significant linear relationship is found between the SPEI6 time series and the anomalies of moisture contribution from the sources. Thus, for both seasons, a reduction in moisture supply from the most important sources is found during severe and extreme droughts. The dependence on ENSO phase is also assessed. Finally, although the correlations are not statistically significant, we found that the rainy (dry) season in the northern subregions show a tendency towards wetting (drying), while the opposite was found for the southern subregions. This behaviour is consistent with the trends observed in precipitation, potential evapotranspiration, and moisture contribution values from the different sources.

Ecosystem Services in Working Lands of the Southeastern USA

Agriculture and natural systems interweave in the southeastern US, including Florida, Georgia, and Alabama, where topographic, edaphic, hydrologic, and climatic gradients form nuanced landscapes. These are largely working lands under private control, comprising mosaics of timberlands, grazinglands, and croplands. According to the “ecosystem services” framework, these landscapes are multifunctional. Generally, working lands are highly valued for their provisioning services, and to some degree cultural services, while regulating and supporting services are harder to quantify and less appreciated. Trade-offs and synergies exist among these services. Regional ecological assessments tend to broadly paint working lands as low value for regulating and supporting services. But this generalization fails to consider the complexity and tight spatial coupling of land uses and land covers evident in such regions. The challenge of evaluating multifunctionality and ecosystem services is that they are not spatially concordant. While there are significant acreages of natural systems embedded in southeastern working lands, their spatial characteristics influence the balance of tradeoffs between ecosystem services at differing scales. To better understand this, we examined the configuration of working lands in the southeastern US by comparing indicators of ecosystem services at multiple scales. Indicators included measurements of net primary production (provisioning), agricultural Nitrogen runoff (regulating), habitat measured at three levels of land use intensity, and biodiversity (supporting). We utilized a hydrographic and ecoregional framework to partition the study region. We compared indicators aggregated at differing scales, ranging from broad ecoregions to local landscapes focused on the USDA Long-Term Agroecosystem Research (LTAR) Network sites in Florida and Georgia. Subregions of the southeastern US differ markedly in contributions to overall ecosystem services. Provisioning services, characterized by production indicators, were very high in northern subregions of Georgia, while supporting services, characterized by habitat and biodiversity indicators, were notably higher in smaller subregions of Florida. For supporting services, the combined contributions of low intensity working lands with embedded natural systems made a critical difference in their regional evaluation. This analysis demonstrated how the inclusion of working lands combined with examining these at different scales shifted our understanding of ecosystem services trade-offs and synergies in the southeastern United States.

Evaluating the African food supply against the nutrient intake goals set for preventing diet-related non-communicable diseases: 1990 to 2017 trend analysis.

Population intake goals intended to prevent diet-related non-communicable diseases (NCDs) have been defined for multiple nutrients. Yet, little is known whether the existing food supply in Africa is in conformity with these goals or not. We evaluated the African food balances against the recommendations for macronutrients, free sugars, types of fatty acids, cholesterol and fruits and vegetables over 1990 to 2017, and provided regional, sub-regional and country-level estimates. The per capita supply of 95 food commodities for 45 African countries (1990-2017) was accessed from the FAOSTAT database and converted into calories, carbohydrate, fat, protein, free sugars, cholesterol, saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids contents using the Food Data Central database. The supply of fruits and vegetables was also computed. In Africa the energy supply increased by 16.6% from 2,685 in 1990 to 3,132 kcal/person/day in 2017. However, the energy contribution of carbohydrate, fat and protein remained constant and almost within acceptable range around 73, 10 and 9%, respectively. In 2017, calories from fats surpassed the 20% limit in upper-middle- or high-income and Southern Africa countries. Energy from SFA remained within range (<10%) but that of PUFA was below the minimum desirable level of 6% in 28 countries. Over the period, energy from free sugars remained constant around 7% but the figure exceeded the limit of 10% in upper-middle- or high-income countries (14.7%) and in Southern (14.8%) and Northern (10.5%) sub-regions. Between 1990 and 2017 the availability of dietary cholesterol per person surged by 14% but was below the upper limit of 300 mg/day. The supply of fruits and vegetables increased by 27.5% from 279 to 356 g/capita/day; yet, with the exception of Northern Africa, the figure remained below the target of 400 g/capita/day in all sub-regions. According to this population level data, in Africa most population intake goals are within acceptable range. Yet, the supply of fruits and vegetables and PUFAs are suboptimal and the increasing energy contributions of free sugars and fats are emerging concerns in specific sub-regions.

Resource-driven colonization by cod in a high Arctic food web.

Climate change is commonly associated with many species redistributions and the influence of other factors may be marginalized, especially in the rapidly warming Arctic.The Barents Sea, a high latitude large marine ecosystem in the Northeast Atlantic has experienced above‐average temperatures since the mid‐2000s with divergent bottom temperature trends at subregional scales.Concurrently, the Barents Sea stock of Atlantic cod Gadus morhua, one of the most important commercial fish stocks in the world, increased following a large reduction in fishing pressure and expanded north of 80°N.We examined the influence of food availability and temperature on cod expansion using a comprehensive data set on cod stomach fullness stratified by subregions characterized by divergent temperature trends. We then tested whether food availability, as indexed by cod stomach fullness, played a role in cod expansion in subregions that were warming, cooling, or showed no trend.The greatest increase in cod occupancy occurred in three northern subregions with contrasting temperature trends. Cod apparently benefited from initial high food availability in these regions that previously had few large‐bodied fish predators.The stomach fullness in the northern subregions declined rapidly after a few years of high cod abundance, suggesting that the arrival of cod caused a top‐down effect on the prey base. Prolonged cod residency in the northern Barents Sea is, therefore, not a certainty.