Climatic Variations Research Articles

Enhancing reliability in climate projections: A novel approach for selecting global climate models

Reliable climate projections are essential for informed decision-making in the context of climate change. However, selecting suitable Global Climate Models (GCMs) for such projections remains challenging, especially when computational resources are limited. This study introduced an innovative approach to GCM selection, emphasizing the identification of models that exhibit consistency in projecting future climate changes and skill in representing current climate conditions, including average climate, seasonal patterns, and climatic variations. GCM performance in simulating these critical properties was evaluated for three major climatic variables: rainfall, maximum temperature, and minimum temperature. This assessment results in a structured 3 × 3 performance matrix for each GCM, encapsulating its ability to capture these essential climate features. The matrix distances, quantifying the disparities between each GCM's performance matrix and the ideal reference matrix, were used to collectively represent the overall model performance. Finally, GCMs were ranked based on these differences using the Jenks natural break classification method, a robust statistical technique, to aid in identifying the top-performing GCMs, making them ideal candidates for ensemble model construction. The newly developed method was tested by applying it to select GCMs for Nigeria from a pool of 19 CMIP6 GCMs. The results indicate that 15 of 19 GCMs consistently projected future climate within a 95% confidence interval. Further evaluation of matrix distances and natural classification reveals a subset of GCMs, ACCESS.ESM1.5, BCC.CSM2.MR, CMCC.ESM2 and MRI.ESM2.0 are the most suitable choice for simulating Nigeria's climate. The multimodel ensemble mean of the selected GCMs projected a notable increase in rainfall by 10–40% over most of the country and the maximum and minimum temperatures by 1.0–3.5 °C and 0.5–4.0 °C across the country. The method introduced in this study can be an effective tool for GCM selection to enhance climate projection reliability.

Effect of Foliar Nutrition on Growth and Yield of Pigeonpea [Cajanus cajan. (L.) Mill sp.

Pigeonpea is most important rainfed pulse crop of Karnataka. Yield of pigeonpea is fluctuating due to variation in climate causing flower drop and poor pod set. The field experiment was conducted to study growth and yield of pigeonpea as influenced by foliar nutrition. The experiment consisted of foliar application of two types of nutrients (19:19:19 and Pulse magic), two growth promoters (NAA, and N - Triacontanol) and their combinations at flowering and pod formation stages. The growth and yield attributes varied significantly and RDF + foliar application of 1% pulse magic at flowering and pod formation stage recorded significantly higher plant height (144.6 cm), number of branches (16.8 plant‑1), leaf area (3218 cm2 plant-1), total dry matter accumulation (135.5 g plant-1), absolute growth rate (0.812 g plant-1 day-1,), crop growth rate (5.19 g m-2 day-1) and relative growth rate (0.01 g g-1 day-1) as compared to control (122.2 cm, 12.9, 2421 cm2 plant-1, 89.4 g plant-1, 0.633 g plant-1 day-1, 4.24 g m-2 day-1 and 0.007 g g-1 day-1, respectively) at harvest. Higher seed yield (1590 kg ha-1), stalk yield (4308 kg ha-1) and harvest index (0.26) recorded with the application of RDF + foliar application of 1% pulse magic at flowering and pod formation stage and lower seed yield, stalk yield and harvest index (1104 kg ha-1, 3416 kg ha-1 and 0.23, respectively) was recorded with control treatment.

Growth responses of Persian walnut (Juglans regia L.) to climate variation along its full elevational range in Kyrgyzstan

Kyrgyzstan features the largest naturally occurring walnut forests in the world. Their high plant biodiversity, including wild relatives to modern-day fruit species such as apple and pear, make them a valuable guardian of genetic diversity. Further, walnut forests have a high economic importance for the country. Climate change, however, poses a major threat to these ecosystems, in particular since rises in temperature are projected that are well above global average. As studies on effects of changing environmental conditions on the growth of walnut are missing, we investigate the climate sensitivity and temporal stability thereof as well as extreme growth responses of walnut along its full elevational gradient in Kyrgyzstan. Whereas we expected to find a shift from water- to temperature-limitation over the elevational gradient, which may move upwards with recent warming, we found walnut growth to be temperature-limited along the entire elevational gradient. In recent decades, negative correlations between the drought index SPEI and tree growth, however, weakened. An up until now low importance of drought stress for walnut growth is also substantiated by a pointer-year analysis. Overall, our results show that walnut growth is already affected by climate change, though imminent risks of drought-induced vitality loss seem still low. With ongoing climate change, this may, however, rapidly change.

Multivariate analysis of long-term climate data in connection with yield, earliness and the problem of global warming.

Climate change is the key challenge to agriculture in the XXI century. Future agricultural techniques in the Russian Federation should involve the optimization of land utilization. This optimization should apply algorithms for smart farming and take into consideration possible climate variations. Due to timely risk assessment, this approach would increase profitability and production sustainability of agricultural products without extra expenditures. Also, we should ground farming optimization not on available empirical data encompassing limited time intervals (month, year) or human personal evaluations but on the integral analysis of long-term information bodies using artificial intelligence. This article presents the results of a multivariate analysis of meteorological extremes which caused crop failures in Eastern and Western Europe in last 2600 years according to chronicle data and paleoreconstructions as well as reconstructions of heliophysical data for the last 9000 years. This information leads us to the conclusion that the current global warming will last for some time. However, subsequent climate changes may go in any direction. And cooling is more likely than warming; thus, we should be prepared to any scenario. Plant breeding can play a key role in solving food security problems connected with climate changes. Possible measures to adapt plant industry to the ongoing and expected climate changes are discussed. It is concluded that future breeding should be based on the use of highly adapted crops that have already been produced in pre-breeding programs, ready to meet future challenges caused by potential climate change.

Upper Ocean variations at IODP Hole U1505C in the northern South China Sea and their response to the East Asian Monsoon during the middle Miocene

We used the samples from International Ocean Discovery Program (IODP) Hole U1505C in the northern South China Sea (SCS) to reconstruct the upper ocean profiles and discussed the East Asian Monsoon (EAM) variations during 15.0–12.5 Ma. 15 genera and 41 species were identified, and 7 planktonic foraminifer datums were recognized, then a reliable chronostratigraphic framework was updated. A principal component analysis (PCA) was used to identify the suitable assemblages for reconstructing upper water profiles, based on planktonic foraminifera relative abundance and isotope records. The sea surface temperature (SST), paleo-productivity, and the depth of thermocline (DOT) were reconstructed by the content of warm water species, high productivity species, and the ratio of mixed layer to thermocline species, respectively. Three main phases were identified: (1) during 15.0–14.7 Ma, the SST and paleo-productivity were high, while the thermocline was shallow, indicating a warm and rainy climate influenced by East Asian Summer Monsoon (EASM); (2) during 14.7–13.8 Ma, the SST was lower, the paleo-productivity increased significantly, and the thermocline deepened, indicating an enhanced East Asian Winter Monsoon (EAWM); (3) during 13.8–12.5 Ma, the SST increased slightly, the paleo-productivity deceased, while the DOT showed neglectable change, indicating a stable EAWM and a waning EASM. The results of the Morlet wavelet spectrum revealed that EAM and the upper ocean profiles in the northern SCS were predominantly regulated by the eccentricity cycles, emphasizing the significant impact of low-latitude processes on climate variations.

Assessing climate impacts on slow-moving landslides in the western Alps of Piemonte: integration of monitoring techniques for detecting displacements

The influence of climatic factors on landslides triggers and displacement rates is a crucial research topic, especially due to the growing need to understand the evolution of climate change in historical periods of intense precipitation and anomalous temperature increases. Italy, highly prone to hydrogeological instability, extremely its mountainous regions such as the Alps, stands as a pertinent subject area for instability scenarios. However, the interpretation of climate effects on landslides is still an open issue. This work proposed a simplified methodology for investigating the displacements of three slow-moving landslides located in the Western Alps of Piemonte region, in response to significant meteorological events evaluated from reference normal of precipitation and temperature trends over the reference period 1991–2020. Another purpose is to emphasize the advantages of using different monitoring techniques by comparing displacement time series measured with in situ and remote sensing instruments, to detect ground deformation processes of these gravitational phenomena. The existence of a robust monitoring network, coupled with InSAR dataset support, has allowed detecting climatic factors’ impact on displacement rates for the outlined case studies. The results have demonstrated the relationships between the identified climatic events and variations in displacement time series, as well as the potential of integrating field observations and InSAR techniques to improve the interpretation of landslide dynamics. Although this study has laid the basis for understanding the influence of climatic factors on landslide displacements, there is still much to investigate and refine. The proposed preliminary analysis will further improve the ability to predict, monitor and mitigate landslide risk under changing climate conditions.

Reconstruction of warm-season temperatures in central Europe during the past 60 000 years from lacustrine branched glycerol dialkyl glycerol tetraethers (brGDGTs)

Abstract. Millennial-scale climate variations during the last glacial period, such as Dansgaard–Oeschger (DO) cycles and Heinrich events, have been extensively studied using ice core and marine proxy records. However, there is a limited understanding of the magnitude of these temperature fluctuations in continental regions, and questions remain about the seasonal signal of these climate events. This study presents a 60 000-year-long temperature reconstruction based on branched glycerol dialkyl glycerol tetraethers (brGDGTs) extracted from lake sediments from the Eifel Volcanic Field, Germany. brGDGTs are bacterial membrane-spanning lipids that are known to have a strong relationship with temperature, making them suitable for temperature reconstructions. We test several temperature calibration models on modern samples taken from soils and multiple maar lakes. We find a negative bias in brGDGT-based temperature estimates associated with water depth and anoxic conditions that can be corrected for by accounting for a brGDGT isomer that is only produced in anoxic conditions. The corrected temperature reconstruction correlates with proxy and climate model estimates of temperature spanning the same time period, validating the calibration approach we selected. However, millennial-scale variability is significantly dampened in the brGDGT record, and in contrast to other Northern Hemisphere climate records, during several Heinrich stadials, temperatures actually increase. We demonstrate that these apparent discrepancies can be explained by the unique seasonal response of the brGDGT paleothermometer to temperatures of months above freezing (TMAF). Our data support the view that warm-season temperatures in Europe varied minimally during the last glacial period and that abrupt millennial-scale events were defined by colder, longer winters. Our continuous high-resolution temperature reconstruction provides important information about the magnitude of seasonal climate variability during the last glacial period that can be used to test climate models and inform studies of paleoecological change.

A multi-model assessment of the early last deglaciation (PMIP4 LDv1): a meltwater perspective

Abstract. The last deglaciation (∼20–11 ka BP) is a period of a major, long-term climate transition from a glacial to interglacial state that features multiple centennial- to decadal-scale abrupt climate variations whose root cause is still not fully understood. To better understand this time period, the Paleoclimate Modelling Intercomparison Project (PMIP) has provided a framework for an internationally coordinated endeavour in simulating the last deglaciation whilst encompassing a broad range of models. Here, we present a multi-model intercomparison of 17 transient simulations of the early part of the last deglaciation (∼20–15 ka BP) from nine different climate models spanning a range of model complexities and uncertain boundary conditions and forcings. The numerous simulations available provide the opportunity to better understand the chain of events and mechanisms of climate changes between 20 and 15 ka BP and our collective ability to simulate them. We conclude that the amount of freshwater forcing and whether it follows the ice sheet reconstruction or induces an inferred Atlantic meridional overturning circulation (AMOC) history, heavily impacts the deglacial climate evolution for each simulation rather than differences in the model physics. The course of the deglaciation is consistent between simulations except when the freshwater forcing is above 0.1 Sv – at least 70 % of the simulations agree that there is warming by 15 ka BP in most places excluding the location of meltwater input. For simulations with freshwater forcings that exceed 0.1 Sv from 18 ka BP, warming is delayed in the North Atlantic and surface air temperature correlations with AMOC strength are much higher. However, we find that the state of the AMOC coming out of the Last Glacial Maximum (LGM) also plays a key role in the AMOC sensitivity to model forcings. In addition, we show that the response of each model to the chosen meltwater scenario depends largely on the sensitivity of the model to the freshwater forcing and other aspects of the experimental design (e.g. CO2 forcing or ice sheet reconstruction). The results provide insight into the ability of our models to simulate the first part of the deglaciation and how choices between uncertain boundary conditions and forcings, with a focus on freshwater fluxes, can impact model outputs. We can use these findings as helpful insight in the design of future simulations of this time period.

Utility of in situ ion‐exchange membranes to assess nutrient availability, productivity, and fertilizer response of coastal Douglas‐fir of the Pacific Northwest

AbstractDouglas‐fir [Pseudotsuga menziesii (Mirb.) Franco] is the predominant forest plantation species in the Pacific Northwest (PNW), with site productivity and fertilizer response influenced by climate and soil variations. This study investigates the utility of in situ 12‐week supply measurements of nitrogen (N), calcium (Ca), and phosphorus (P) to ion‐exchange resins (specifically Plant Root Simulator [PRS] probes) to estimate carbon (C):N ratios, soil nutrient contents (0–1 m), foliar nutrient concentrations, Douglas‐fir productivity (site index and basal area mean annual increment), and fertilizer volume response. PRS nutrient supply rates were correlated with N, Ca, and P soil nutrient contents (0–1 m), C:N ratios, and foliar nutrient concentrations. Low PRS NO3 supply rates (<25 mg N·m−2·burial period−1) were correlated with lower Douglas‐fir productivity and greater fertilizer volume response. PRS NO3 supply rates performed as well as total soil N contents and foliar N concentrations at estimating volume growth response to fertilizer. Twelve weeks after fertilization, PRS NO3, NH4, and Ca supply rates were significantly elevated compared to the unfertilized treatment. This research found that PRS probes were an effective in situ tool and are recommended for understanding N, Ca, and P nutrient availabilities, site productivity, and fertilizer response in Douglas‐fir plantations and for developing fertilizer prescriptions.

Impact of Climate Change on Tourism Sector in Nepal

Climatic variations might have a negative impact on the activities and services provided by the tourism industry. However, this idea has not yet been investigated in the context of Nepal. This study examines the monetary impact that climate change has had and will continue to have on Nepal's tourism industry and makes projections on such impacts. The economic impact assessment of climate change on Nepal's tourism sector is the first study of its sort to be conducted anywhere in the nation. This research is predicated on a conceptual model that was established on the theoretical foundation, a mathematical model that generated the tourism demand function, and an economic effect analysis that was performed on the tourism sector using secondary data. The findings of the study's analysis have been broken down into three distinct sections: a trend analysis of tourism and its contribution; regression results based on the models that have been established; and a projection of GDP for the years 2020-2030 and 2100. It is abundantly clear from the trend analysis, the analysis of loss and damage from climate-induced hazards, the econometric modeling for tourism function analysis and correlation on tourism GDP, and other research that the tourism sector is extremely vulnerable to the effects of climate change and that it will have significant repercussions. The projection of tourism's contribution to the national GDP shows that this sector has the potential to make a larger contribution, provided that the conditions that could prevent this from happening do not change. On the other hand, the rising trend of climatic factors and climate-induced dangers could potentially lead to a greater overall loss and damage in the tourism industry. As a result, it will have an immediate bearing on the contribution made to the national economy.

IoT Based Crop Prediction using Machine Learning

To enhance agricultural productivity and resource allocation. Leveraging historical data encompassing various agricultural factors such as soil composition, weather conditions, and crop types, a predictive model is developed to forecast crop yields. Machine learning techniques, including regression and classification algorithms, are employed to analyze the intricate relationships within the dataset and predict the most likely outcomes for specific crops in different regions. The model is trained on a diverse dataset, considering variations in climate and soil characteristics, ensuring robustness and adaptability across different agricultural environments . The proposed crop prediction system not only provides accurate yield forecasts but also assists farmers in making informed decisions regarding crop selection and resource optimization. By harnessing the power of machine learning, this research contributes to sustainable agriculture by promoting precision farming practices. The integration of technology in crop prediction not only improves yield predictions but also supports the overall resilience of agricultural systems, fostering a data-driven approach that aligns with the evolving needs of the agricultural sector in a rapidly changing world.

Reframing the wicked problem of pre-harvest burning: A case study of Thailand's sugarcane

Pre-harvest sugarcane burning persists in many countries though there are policies prohibiting the practice. As problems related to sugarcane harvesting are complex, a thorough understanding of the problems for policy formulation is required. The objective of this study was to reanalyze or reframe problems of sugarcane harvesting and pre-harvest sugarcane burning. Concepts of wicked problems, practical reasoning and policy reframing were applied. The study used a participatory modeling approach to illustrate the case of Thailand. Wickedness was shown by complexity and uncertainties of factors intertwining with values related to adoption of harvesting methods; green mechanical, green manual and burnt manual. As timeliness of harvest was the top priority, the burnt method was considered more efficient. It was easier, faster, cheaper and more suitable under unfavorable circumstances for the green methods. The policy to reduce burnt-harvested sugarcane was not so effective and also led to the undesired ‘green but unclean’ method. To frame harvesting problems based on emissions of fine particulates (PM2.5) from sugarcane burning was not a good choice. Incomplete problem sense-making and poor problem frame were indicated. Most farmers were unable to associate sugarcane burning with environmental problems of PM2.5 (and also global warming/climate change) and livelihood impacts. Nevertheless, a larger concern over climate variations was perceived by a majority of farmers. Farmers who adapted relied primarily on green harvesting and the use of residues as trash blankets. Through policy reframing, inefficient green harvesting was seen as a better frame. The new frame enabled farmers linking agricultural practices to sustainability of environment, productivity and livelihoods in the context of climate change. Using participatory modeling for reframing policy problems in general and wicked problems in particular was shown to be powerful and contributing to originality.

Habitat alteration or climate: What drives the densities of an invading ungulate?

Anthropogenic habitat alteration and climate change are two well-known contributors to biodiversity loss through changes to species distribution and abundance; yet, disentangling the effects of these two factors is often hindered by their inherent confound across both space and time. We leveraged a contrast in habitat alteration associated with the jurisdictional boundary between two Canadian provinces to evaluate the relative effects of spatial variation in habitat alteration and climate on white-tailed deer (Odocoileus virginianus) densities. White-tailed deer are an invading ungulate across much of North America, whose expansion into Canada's boreal forest is implicated in the decline of boreal caribou (Rangifer tarandus caribou), a species listed as Threatened in Canada. We estimated white-tailed deer densities using 300 remote cameras across 12 replicated 50 km2 landscapes over 5 years. White-tailed deer densities were significantly lower in areas where winter severity was higher. For example, predicted deer densities declined from 1.83 to 0.35 deer/km2 when winter severity increased from the lowest value to the median value. There was a tendency for densities to increase with increasing habitat alteration; however, the magnitude of this effect was approximately half that of climate. Our findings suggest that climate is the primary driver of white-tailed deer populations; however, understanding the mechanisms underpinning this relationship requires further study of over-winter survival and fecundity. Long-term monitoring at the invasion front is needed to evaluate the drivers of abundance over time, particularly given the unpredictability of climate change and increasing prevalence of extreme weather events.

Constraints on hopanes and brGDGTs as pH proxies in peat

pH is one of the major parameters governing peat functioning, and pH variations in modern peatlands affect carbon and methane production and consumption. Paleo-pH reconstructions have been limited thus far, but they could help to better understand peat functioning in variety of settings and also serve as an indirect proxy for climatic and environmental variations such as precipitation. Bacterial hopanes and branched Glycerol Dialkyl Glycerol Tetraethers (brGDGTs) were investigated in a 10-ka peat record from North-East Cameroon (NGaoundaba, Western Central Africa). Recently developed pH proxies using the hopane ββ/(αβ + ββ) ratio and the brGDGT cyclization ratio (CBTpeat) were applied and compared with previously published bulk organic data from the same core. Different hypotheses are usually proposed to explain the high abundance of the “thermally mature” C31 αβ hopane in peats: acid-catalyzed isomerization of ββ to αβ isomers with or without biological mediation or the direct input of C31 αβ hopanes by bacteria. In the NGaoundaba peat deposit, the opposite variation in the ββ/(αβ + ββ) ratio of C30 and C31 hopanes and the carbon isotopic composition of C31 ββ and αβ hopanes suggest that an eventual transformation of C31 ββ to αβ isomers is not possible without biological mediation. A linear correlation between hopane- and brGDGT-reconstructed pH is observed, suggesting a similar response to environmental changes for these two independent proxies. A large increase in reconstructed pH values coincides with changes in vegetation and precipitation at the end of the African Humid Period (AHP). Lower pH values are observed during the AHP, coinciding with a period of increased precipitation and consistent with bulk organic data and slightly higher C31 ββ hopane δ13C values compared to middle and late Holocene. Bulk organic data indicate an interruption of the AHP by a drier intermission that coincides with a decrease in reconstructed pH values, probably reflecting a decrease in evapotranspiration. Variations in pH values could be interpreted in terms of preservation of peat organic matter and might reflect past changes in methane cycling in the investigated peatland. The present study reinforces the idea that reconstruction of pH in peat deposits represents a promising proxy of environmental change, enabling a better understanding of changes in peat functioning over large timescales and various locations.

Depositional Facies and Sequence Stratigraphy of Kodiak Butte, Western Delta of Jezero Crater, Mars

AbstractHigh‐resolution 2D and 3D data remotely acquired by SuperCam's Remote Micro‐Imager and Mastcam‐Z aboard the Perseverance rover enabled us to characterize the stratigraphic architecture and sedimentary record of the Kodiak butte, an isolated remnant of the western delta fan of Jezero crater. Using these data, we build up on previous interpretations of the butte interpreted as a prograding Gilbert‐type deltaic series. We characterize three individual stratigraphic Units 0 to 2 on the eastern and northern faces of the butte. Each Unit displays the same vertical succession of prodeltaic/lacustrine bottomsets, delta slope toesets and foresets, and fluvially influenced topsets of a deltaic plain with a braided river pattern, shown by 11 individual sedimentary facies. We infer that these individual Units record the formation of three distinct deltaic mouth bars successively across time and space. For the first time on another planet than Earth, we are able to construct a precise sequence stratigraphic framework to highlight lake‐level fluctuations at the time the Kodiak butte was emplaced, during the latest stages of deltaic activity. We identify four hydrogeological cycles indicated by alternating rises and falls of the lake‐level on the order of 5–10 m. These were most probably linked to climatic events and variations controlling lake water inputs in probable relation to an astronomical control.

Climate and habitat type interact to influence contemporary dispersal potential in Prairie Smoke (Geum triflorum).

Understanding dispersal potential, or the probability a species will move a given distance, under different environmental conditions is essential to predicting species' ability to move across the landscape and track shifting ecological niches. Two important drivers of dispersal ability are climatic differences and variations in local habitat type. Despite the likelihood these global drivers act simultaneously on plant populations, and thus dispersal potential is likely to change as a result, their combined effects on dispersal are rarely examined. To understand the effect of climate and varying habitat types on dispersal potential, we studied Geum triflorum-a perennial grassland species that spans a wide range of environments, including both prairie and alvar habitats. We explored how the climate of the growing season and habitat type (prairie vs. alvar) interact to alter dispersal potential. We found a consistent interactive effect of climate and habitat type on dispersal potential. Across prairie populations, an increased number of growing degree days favored traits that increase dispersal potential or the probability of dispersing farther distances. However, for alvar populations, dispersal potential tended to decrease as the number of growing degree days increased. Our findings suggest that under continued warming, populations in prairie habitats will benefit from increased gene flow, while alvar populations will become increasingly segregated, with reduced potential to track shifting fitness optima.

Stage-Specific Demographic Effects of Hydrologic Variation in a Stream Salamander.

AbstractWe lack a strong understanding of how organisms with complex life histories respond to climate variation. Many stream-associated species have multistage life histories that are likely to influence the demographic consequences of floods and droughts. However, tracking stage-specific demographic responses requires high-resolution, long-term data that are rare. We used 8 years of capture-recapture data for the headwater stream salamander Gyrinophilus porphyriticus to quantify the effects of flooding and drying magnitude on stage-specific vital rates and population growth. Drying reduced larval recruitment but increased the probability of metamorphosis (i.e., adult recruitment). Flooding reduced adult recruitment but had no effect on larval recruitment. Larval and adult survival declined with flooding but were unaffected by drying. Annual population growth rates (λ) declined with flooding and drying. Lambda also declined over the study period (2012-2021), although mean λ was 1.0 over this period. Our results indicate that G. porphyriticus populations are resilient to hydrologic variation because of compensatory effects on recruitment of larvae versus adults (i.e., reproduction vs. metamorphosis). Complex life cycles may enable this resilience to climate variation by creating opportunities for compensatory demographic responses across stages. However, more frequent and intense hydrologic variation in the latter half of this study contributed to a decline in λ over time, suggesting that increasing environmental variability poses a threat even when demographic compensation occurs.

Spatially Weighted Multinomial Modelling of Comorbidity of Anaemia and Malaria among Under-Five Children in Nigeria

Children in sub-Saharan African countries, especially Nigeria, continue to suffer increased mortality owing to comorbidity of infections such as anaemia and malaria, which are known to epidemiologically overlap. In order to examine the risk factors and spatial patterns of comorbidity of anaemia and malaria using the 2021 Nigeria Malaria Indicator Survey (NMIS), a multinomial logit model was extended by incorporating a spatially weighted random effect. The impact of climatic variation on the childhood disease comorbidity was explored by weighting the spatial structured component based on the 2021 NMIS average cluster temperature of each state in Nigeria. A number of spatially weighted geo-additive models were fitted and compared using deviance information criterion. Inference was fully Bayesian, and an Intrinsic Conditional Autoregressive prior was used for structured random effects. Based on the map generated from the best-fitted model, which unveiled states that are more susceptible to the risk of disease comorbidity, the average temperature used as a weighting factor, however, has a strong relationship with the spatial pattern of disease comorbidity. States with low temperatures have a higher risk of comorbidity of anaemia and malaria compared to states with higher average temperatures. Area of residence, level of education of the mother, economic status of the mother, and owning mosquito-treated nets were identified as the significant risk factors associated with the disease comorbidity. Findings from this study will be helpful to policymakers and health authorities in their effort to combat the comorbidity of childhood anaemia and malaria, thereby reducing child mortality in Nigeria.

The carryover effects of embryonic incubation temperature on subsequent growth and thermal tolerance in white sturgeon

Environmental variation experienced during early periods of development can lead to persistent phenotypic alteration, known as carryover effects. Such effects increase concern for threatened or endangered species such as the white sturgeon (Acipenser transmontanus), particularly considering expected thermal changes due to climate change. We evaluated how temperature during embryonic development affects physiological parameters such as larval and early juvenile growth and thermal tolerance. Nechako River white sturgeon embryos were incubated at different environmental temperatures (Te) of 12 °C (the natural spawning temperature of this population), 15 °C (the hatchery incubation temperature), and 18 °C (representing potential increases in river temperatures given global climate change). After hatch, fish were reared at a common 15 °C for 80 days post-hatch (dph). Individuals from each temperature treatment were tested for thermal tolerance using the critical thermal maximum method (CTmax), euthanized, and measured. Fish were examined at regular intervals from 13 to 80 dph, which bridged the time from the start of exogenous feeding through the transition into early juveniles. We found carryover effects of high embryonic Te in the short term for both thermal tolerance and growth. Fish that developed at 18 °C had the lowest thermal tolerance during the start of exogenous feeding. However, differences in thermal tolerance were small for early juveniles and were unlikely to be ecologically relevant in the longer term. Fish that developed at 18 °C were smallest over the observation period, indicating a possible cost for survival from increasing environmental temperatures during embryonic development. This research represents a window into a critical period of development during which fish are particularly vulnerable to climatic variation, and shows that cooler temperatures (12 °C) during incubation are optimal for this population. The results can inform environmental managers on the best strategies to help conserve current white sturgeon populations across their range.

Optimizing the key parameter to accelerate the recovery of AMOC under a rapid increase of greenhouse gas forcing

Atlantic Meridional Overturning Circulation (AMOC) plays a central role in long-term climate variations through its heat and freshwater transports, which can collapse under a rapid increase of greenhouse gas forcing in climate models. Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations. In this work, with a low-resolution earth system model, the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse. Through a new optimization strategy, the extra freshwater flux (FWF) parameter is determined to be the dominant one affecting the AMOC's variability. The traditional ensemble optimal interpolation (EnOI) data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO2 forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC. The results show that, under an abrupt 4×CO2 forcing in millennial simulations, the AMOC will first collapse and then re-establish by the default FWF parameter slowly. However, during the parameter adjustment process, the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC, according to their physical relationship with FWF on the interdecadal timescale.