RESUMEN

Understanding the mechanisms of soil organic carbon (SOC) sequestration in forests is vital to ecosystem carbon budgeting and helps gain insight in the functioning and sustainable management of world forests. An explicit knowledge of the mechanisms driving global SOC sequestration in forests is still lacking because of the complex interplays between climate, soil, and forest type in influencing SOC pool size and stability. Based on a synthesis of 1179 observations from 292 studies across global forests, we quantified the relative importance of climate, soil property, and forest type on total SOC content and the specific contents of physical (particulate vs. mineral-associated SOC) and chemical (labile vs. recalcitrant SOC) pools in upper 10 cm mineral soils, as well as SOC stock in the O horizons. The variability in the total SOC content of the mineral soils was better explained by climate (47%-60%) and soil factors (26%-50%) than by NPP (10%-20%). The total SOC content and contents of particulate (POC) and recalcitrant SOC (ROC) of the mineral soils all decreased with increasing mean annual temperature because SOC decomposition overrides the C replenishment under warmer climate. The content of mineral-associated organic carbon (MAOC) was influenced by temperature, which directly affected microbial activity. Additionally, the presence of clay and iron oxides physically protected SOC by forming MAOC. The SOC stock in the O horizons was larger in the temperate zone and Mediterranean regions than in the boreal and sub/tropical zones. Mixed forests had 64% larger SOC pools than either broadleaf or coniferous forests, because of (i) higher productivity and (ii) litter input from different tree species resulting in diversification of molecular composition of SOC and microbial community. While climate, soil, and forest type jointly determine the formation and stability of SOC, climate predominantly controls the global patterns of SOC pools in forest ecosystems.

Asunto(s)

RESUMEN

Body size (or mass) variations and their relationships with environmental variability have been well documented for many species at the local scale, while the effects of climate, combined with soil nutrients, on plant mass in large-scale gradient remain unclear. Herein, detailed surveys were conducted to investigate plant mass (PM, aboveground mass per plant) variations of Leymus chinensis and their relationship with environmental factors (e.g., climate, soil nutrient, and microbial diversity) at 18 wild sites along a large-scale gradient from 114 to 124° E in northeastern China. Based on site-by-site analyses, the plant mass of the species varied significantly from east to west along the gradient. It initially increased, peaking at middle sites, and then dropped with the increase of drought in both dry and rainy seasons. Plant mass at the eastern end was almost equal to that at the western end and was equivalent to 1/2 and 1/3 of middle sites. The average plant mass in the rainy season was about 50% greater than that in the dry season (F 1,1078 = 489.80, p < .001). The effects of environmental variables on plant mass differed in dry and rainy seasons. Mean annual temperature and temperature seasonality were the critical restrictions of plant mass in the dry season, while temperature and precipitation seasonality and soil resources (total C, Mn, Zn) had significant impacts in the rainy season (p < .05). In general, plant mass had not dropped linearly with the increase of drought along large-scale gradient, suggesting that precipitation decrease was not the critical restriction regulating the growth and settlement of the species.

RESUMEN

Temperature anomalies and changes in the diurnal temperature range (DTR) are expected to pose physiological challenges to biota; hence, both spatial and temporal variations in DTR provide important insights into temperature-induced stress in humans, animals, and vegetation. Furthermore, vegetation could dampen temperature variability. Here, we use the Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data of Land Surface Temperature (LST) to evaluate the global variation in DTR and its rate of change in spatial and temporal scales for the two decades spanning from 2001 to 2020. We show that North America, Africa, and Antarctica, as well as the global mean, experienced statistically significant DTR rates of change over the last 20 years in either summer, winter, or the annual mean. The rates were all negative, indicating the day-night temperature differences are decreasing in those regions because night temperatures are increasing at a faster rate than day temperatures. MODIS data of the Normalized Difference Vegetation Index (NDVI) revealed a strongly negative correlation with DTR, with a spatial correlation coefficient of -0.61. This correlation demonstrates a prominent dampening effect of vegetation on diurnal temperature oscillations. For future DTR projections, we used 19 models in the Coupled Model Intercomparison Project 6 (CMIP6) to predict global DTR trends from 2021 to 2050 with low and high CO2 concentration scenarios. The high CO2 emission scenario projects significant decreases in DTR in circumpolar regions, central Africa, and India compared to the low CO2 scenario. This difference in the two scenarios underscores the substantial influence of increased global temperatures and elevated CO2 concentration on DTR and, consequently, on the ecosystems in certain regions.

RESUMEN

Over the past few years, surface ozone (O3) pollution has dominated China's air pollution as particulate matter has decreased. In Beijing, the annual average concentrations of ground-level O3 from 2015 to 2020 regularly increased from 57.32 to 62.72 µg/m3, showing a change of almost 9.4%, with a 1.6% per year increase. The meteorological factors are the primary influencer of elevated O3 levels; however, their importance and heterogeneity of variables remain rarely understood. In this study, we used 13 meteorological factors and 6 air quality (AQ) parameters to estimate their influencing score using the random forest (RF) algorithm to explain and predict ambient O3. Among the meteorological variables and overall, both land surface temperature and temperature at 2 m from the surface emerged as the most influential factors, while NO2 stood out as the highest influencing factor from the AQ parameters. Indeed, it is crucial and imperative to reduce the temperature caused by climate change in order to effectively control ambient O3 levels in Beijing. Overall, meteorological factors alone exhibited a higher coefficient of determination (R2) value of 0.80, compared with AQ variables of 0.58, for the post-lockdown period. In addition, we calculated the number of days O3 concentration levels exceeded the WHO standard and newly proposed peak-season maximum daily 8-h average (MDA8) O3 guideline for Beijing. The exceedance number of days from the WHO standard of MDA8 ambient O3 was observed to be the highest in June, and each studied year crossed peak season guidelines by almost 2 times margin. This study demonstrates the contributions of meteorological variables and AQ parameters in surging ambient O3 and highlights the importance of future research toward devising an optimum strategy to combat growing O3 pollution in urban areas.

Asunto(s)

RESUMEN

Bermudagrass (Cynodon dactylon) is a widely used warm season lawn grass. Cuticular wax covering the surface of plant leaves plays an important role in helping plants resist biotic and abiotic stresses. We analyzed the changes of cuticle wax in 25 bermudagrass populations from different longitude and latitude gradients, in order to verify how environmental conditions affect the structure and chemical composition of cuticle wax. Five wax components were identified, including alkanes, esters, alkenes, aldehydes and primary alcohols. The wax characteristics were divided into two principal components, explaining 58.2 % and 66.7 % of the total variability in latitude and longitude, even some populations had a certain correlation with each other. Pearson correlation analysis further showed that the total wax coverage, wax component content and antioxidant enzyme activity of bermudagrass populations on the latitudinal gradient had different responses to environmental factors. Finally, nineteen key genes involved in wax biosynthesis, redox and photosynthesis were identified and verified by RT-qPCR. The results showed that the responses of bermudagrass in different populations to climate change were quite different, which was of great significance for the evolution of bermudagrass populations.

Asunto(s)

RESUMEN

Modernization and the global fashion market demand continuous improvements in upland cotton cultivars (Gossypium hirustum L.) to meet these improved fiber characteristics (fiber length, fiber strength, micronaire) requirements. Researchers have centered their efforts on improved fiber quality; however, the efforts are not immediately supporting the textile sector. The daily mean and temperature amplitude fluctuation affect cotton yield and fiber characteristics. This study analyzed four newly developed cotton varieties in two cotton regions for fiber characteristics' variations. It was observed that cotton fiber quality characteristics (fiber length, uniformity, strength, and micronaire) are impacted in diverse ways. Fiber quality is mainly affected by the genotype and environmental conditions, e.g., weather conditions, irrigation management, fertilization, and cultural practices. The Khanewal region had shown better fiber characteristics than the Multan region, whereas cotton variety CIM-785 had better fiber characteristics in both regions.

RESUMEN

Vessels are responsible for an efficient and safe water transport in angiosperm xylem. Whereas large vessels efficiently conduct the bulk of water, small vessels might be important under drought stress or after winter when large vessels are embolized. Wood anatomy can adjust to the environment by plastic adaptation, but is also modified by genetic selection, which can be driven by climate or other factors. To distinguish between plastic and genetic components on wood anatomy, we used a Quercus robur trial where trees from ten Central European provenances were planted in three locations in Austria along a rainfall gradient. Because wood anatomy also adjusts to tree size and in ring-porous species, the vessel size depends on the amount of latewood and thereby ring width, we included tree size and ring width in the analysis. We found that the trees' provenance had a significant effect on average vessel area (VA), theoretical specific hydraulic conductivity (Ks), and the vessel fraction (VF), but correlations with annual rainfall of provenances were at best weak. The trial site had a strong effect on growth (ring width, RW), which increased from the driest to the wettest site and wood density (WD), which increased from wet to dry sites. Significant site x provenance interactions were seen only for WD. Surprisingly, the drier site had higher VA, higher VF, and higher Ks. This, however, is mainly a result of greater RW and thus a greater proportion of latewood in the wetter forest. The average size of vessels > 70 µm diameter increased with rainfall. We argue that Ks, which is measured per cross-sectional area, is not an ideal parameter to compare the capacity of ring-porous trees to supply leaves with water. Small vessels (<70 µm) on average contributed only 1.4% to Ks, and we found no evidence that their number or size was adaptive to aridity. RW and tree size had strong effect on all vessel parameters, likely via the greater proportion of latewood in wide rings. This should be accounted for when searching for wood anatomical adaptations to the environment.

RESUMEN

Exogenous anomalies induced by contemporary climate change may severely impact dynamics of early life stages of fish. Here, we modelled how growth rate and abundance of postflexion larvae, and recruitment of Baltic spring-spawning herring (Clupea harengus membras) in the Pärnu Bay, Gulf of Riga (GoR) may respond to shifting climate variables. Higher larval growth rates were aligned with later seasonal emergence of yolk-sac larvae, while lower abundance of postflexion larvae occurred in years of earlier seasonal seawater warming. Cooler temperatures (<16 °C) in spring expanded the optimal thermal window for first-feeding herring larvae, attributable to the absence of early seasonal water temperature warming. Higher recruitment levels emerged in years of seasonally delayed warming and were associated with higher abundance of postflexion larvae. In recent decades, the trend towards earlier warming of the Baltic Sea in spring threatens to create a bottleneck to successful recruitment of herring. The existing paradigm that abundant Baltic herring year-classes occur only in the years following mild winters no longer stands as environmental conditions undergo rapid change. The relative contribution of Pärnu Bay larval nursery areas to recruitment has diminished as the suitable thermal window has been dramatically reduced in recent decades. Evolving thermal dynamics in the GoR have developed relatively recently and in future present a bottleneck for herring production.

Asunto(s)

RESUMEN

The COVID-19 pandemic has a close relationship with local environmental conditions. This study explores the effects of climate characteristics and air pollution on COVID-19 in Isfahan province, Iran. A number of COVID-19 positive cases, main air pollutants, air quality index (AQI), and climatic variables were received from March 1, 2020, to January 19, 2021. Moreover, CO, NO2, and O3 tropospheric levels were collected using Sentinel-5P satellite data. The spatial distribution of variables was estimated by the ordinary Kriging and inverse weighted distance (IDW) models. A generalized linear model (GLM) was used to analyze the relationship between environmental variables and COVID-19. The seasonal trend of nitrogen dioxide (NO2), wind speed, solar energy, and rainfall like COVID-19 was upward in spring and summer. The high and low temperatures increased from April to August. All variables had a spatial autocorrelation and clustered pattern except AQI. Furthermore, COVID-19 showed a significant association with month, climate, solar energy, and NO2. Suitable policy implications are recommended to be performed for improving people's healthcare and control of the COVID-19 pandemic. This study could survey the local spread of COVID-19, with consideration of the effect of environmental variables, and provides helpful information to health ministry decisions for mitigating harmful effects of environmental change. By means of the proposed approach, probably the COVID-19 spread can be recognized by knowing the regional climate in major cities. The present study also finds that COVID-19 may have an effect on climatic condition and air pollutants.

Asunto(s)

RESUMEN

The browntail moth (Euproctis chrysorrhoea (L.)) is a forest pest that was accidentally introduced in the late 1800's and spread throughout New England in the early part of the 20th Century. At its peak range expansion in 1915 it encompassed an area of 150,000 km2 after which populations declined. By the 1960s, its distribution had receded to relic populations on outer Cape Cod, MA, and islands in Casco Bay, ME. In 1989 browntail moth resurged in Maine, with periodic, moderate outbreaks before a dramatic increase of the population occurred in 2016. We examined the pattern of annual defoliation by browntail moth since its resurgence in the 1990s as well as variation in populations throughout infested areas in Maine during three years of the recent outbreak, 2016-2018, relative to differences in weather, parasitism and habitat characteristics. Levels of defoliation over 24 yr were predicted by the preceding spring precipitation (-, negative effect) and the year's previous late summer and early fall temperatures (+, positive effect) when first to third instar larvae feed and then construct winter hibernacula. Late summer temperatures predicted the abundance of hibernacula across outbreak areas (+). Early spring temperatures (+) and early and late spring precipitation (-) predicted early summer larval and pupal nest abundance. Warmer fall temperatures result in more mature populations coming out of winter hibernacula in the spring, whereas spring precipitation drives epizootic outbreaks of Entomophaga aulicae (Reichardt in Bail) Humber (Entomophthorales: Entomophthoraceae). with parasitoids playing a lesser role. Climate trends indicate continued increases in fall temperatures since browntail moth resurgence.

Asunto(s)

RESUMEN

This paper describes the global distribution and temporal trend of Varroa spp. during 13 years (2005-2018) using the information retrieved from the OIE World Animal Health Information Database (WAHIS). During the period of study 53.4% of the countries reported the presence of the mite at least once. Countries were classified in five categories: 22% as Enzootic, 18% as Epizootic, 9% as Free, 12% and 26% respectively as disease Present or Absent at least once since 2005. Twelve percent of the countries were not able to provide any information on the presence of the disease. The average percentage of countries reporting the disease present was stable along the study, but it was observed a statistically significant increasing trend in the number of outbreaks reported per year. The number of outbreaks were different among the climate regions. Based on the seasonality analysis, the second semester of each year was the period characterized by the highest number of outbreaks reported.

Asunto(s)

RESUMEN

Due to the close relationship between the incidence of infectious diseases by epidemics and environmental conditions, this research explores the temperature, evaporation, precipitation and regional climate effects on the local transmission of coronavirus SARS-CoV-2 inside 31 states and capital of Mexico since February 29 (national onset) to March 31, 2020. Statistical analysis was conducted to explore the association between the daily local COVID-19 confirmed positive cases (LCPC) and both climate characteristics and the daily weather reported by the regional meteorological stations. In this work, the local transmission ratio (LTR) was calculated with the regional LCPC divided by the number of the effective contagion days since regional onset in each state. The results showed a negative association between temperature (mean, max and min) and climate classification with both LCPC and LTR variables. The precipitation associated positively with LCPC and LTR. The associations between the climate classification with LCPC and LTR are statistically significant. The tropical climate (mean temperature around 25.95 °C and mean precipitation around 8.74 mm) delayed the regional onset. However, the regional onset in dry climates emerged earlier as consequence of the lower temperatures and higher precipitations (20.57 °C and 20.87 mm respectively) than the observed in the tropical climate. The fastest regional onsets were observed in tempered climates in states where the lowest temperatures and lowest precipitations were registered (19.65 °C and 8.48 mm respectively). Meteorological factors influenced the trend on the regional outbreaks in Mexican's states likely by the host predisposition and susceptibility during the cold winter season. In Mexico, the climate characteristics played a crucial role on the local infection during the phase 1 being the tempered regions (as Michoacán, Jalisco, Puebla, etc.) more vulnerable than the dry (as Chihuahua, Durango or Zacatecas, etc.) or tropical areas (as Colima, Campeche, Morelos etc.).

Asunto(s)

RESUMEN

Agricultural drought is one of the most frequent and widespread natural disasters occurring in China. Drought is associated with hydrological and meteorological conditions that lead to water-deficient vegetation, which has a negative effect on agricultural activities. The monitoring of droughts, as well as early-warning and timely information, is significant for crop production and food security. However, the spatial and temporal patterns of precipitation and temperature have rarely been reported when monitoring the agricultural drought loss rate on a national scale. In this study, we analyzed the spatial and temporal patterns of drought based on model simulation. An artificial neural network (ANN) model for drought warning was developed using monthly temperature and precipitation data from 1949 to 2015. Our results demonstrated that the agricultural drought loss rate can be simulated in most agricultural areas of China. Our ANN model simulation revealed that the areal percentages of precipitation and temperature are strongly correlated with agricultural drought, with the agricultural drought loss rate exhibiting greater sensitivity to precipitation than temperature. We suggest that the spatial and temporal patterns of precipitation are useful for capturing drought warning signals. The precipitation thresholds play an important role in detecting agricultural drought in critical months or seasons of crop growth in different regions. This study presents a framework and reference for drought monitoring in the regions and countries facing frequent agricultural drought.

RESUMEN

We compared greenhouse gas (GHG) fluxes and albedo of a pristine boreal bog and an adjacent abandoned peatland pasture in western Newfoundland, Canada to estimate the magnitude of radiative forcing (RF) created by agricultural drainage and abandonment. Our results indicated that these anthropogenic activities induced a climate cooling effect (negative RF), with the magnitude of the RF caused by the albedo change comparable to that induced by altered GHGs. Although the albedo-induced RF was positive in winter and negative in summer, the summer effect dominated because of greater solar radiation received. The climate cooling effect of GHGs change was due to an increase in the carbon dioxide sink capacity and a reduction in methane emissions under lower water table levels following agricultural drainage and abandonment. Calculation of sustained-flux global warming/cooling potentials also supported this finding. Our results show that the overall increase in albedo resulting from agricultural drainage and abandonment contributes significantly to the negative RF, strengthening the cooling effect due to the changing GHG fluxes. Therefore, changes in albedo due to altered vegetation coverage and hydrology and GHG fluxes should be considered when assessing the climatic impacts from land-use change in northern peatland.

Asunto(s)

RESUMEN

Afforestation in China provides carbon sequestration and prevents soil erosion, but its remote impacts on climate in other regions via the coupling of forest energy fluxes with atmospheric circulation are largely unknown. Here, we prescribe inventory-based forest cover change and satellite-observed leaf area index from 1982 to 2011 in a coupled land-atmosphere model to simulate their biophysical climate effects. Both local and global surface air temperatures show a seasonal contrast in response to past vegetation cover expansion over China: a phenomenon we primarily attribute to a variation of seasonality of vegetation greening. A large cooling in spring results in concurrent decreases in geopotential height over China and zonal wind over Mongolia, causing a dipole structure in the upper troposphere over the Arctic. This accounts for ∼58% of simulated spring warming over the Russian Arctic and ∼61% of simulated spring cooling over the Canadian Artic. Our results imply that spring vegetation dynamics in China may affect climate in northern high latitudes.

RESUMEN

To investigate the effect of climate and farm management practices on prevalence of bovine digital dermatitis (BDD) in spring-calving farms in Taranaki, New Zealand, whole herd assessments of BDD were made on 57 farms which had been previously identified as having cows with BDD. Assessments of BDD lesions were made on five occasions between early lactation (September 2015) and drying-off (May 2016; at approximately 6-week intervals). Along with the clinical assessment, data on farm management practices were collected using questionnaires. In addition, climate data including rainfall and soil/air temperature were obtained from a local weather station. The raw temporal pattern was analysed using a generalised estimating equation method, followed by a mixed effects negative binomial model which modelled the associations between prevalence and the covariates including management practices, rainfall and soil temperature. The highest farm and cow level prevalences were seen on the second visit (27/Oct/2015-11/Dec/2015) and were lowest on the fourth visit (29/Jan/2016-10/Mar/2016). Farms with a higher prevalence at the first visit tended to have a higher prevalence at later visits, even though the affected individuals were often different. There was thus a strong correlation (0.94) between prevalence (proportion of cows affected at each time point) and incidence (proportion of cows with new affections at each time point). Two climate measurements were found to have associations with BDD prevalence. Firstly, increased rainfall in the previous month was associated with decreased cow level prevalence; secondly, there was a quadratic relationship between prevalence and soil temperature, with prevalence increasing as soil temperature increased from 11.8 °C to approximately 18 °C and then decreasing as soil temperature increased from approximately 18 °C to 23.9 °C. In addition to the effect of climate, using outside staff to perform hoof trimming was found to increase the risk of BDD affection (risk ratio [RR]: 2.06, 95% confidence interval [CI]: 1.05-4.06).

Asunto(s)

RESUMEN

Plant-pollinator network structure is the outcome of ecological and evolutionary processes, and although the importance of environmental factors is beyond doubt, our knowledge of how abiotic factors (e.g. climate) shape plant-pollinator networks remains limited. This knowledge gap is critical, as climate change poses a major threat to ecosystems, especially in the Mediterranean. This study focuses on one of the hottest parts of the Mediterranean Basin, the Aegean Archipelago, Greece, and examines how climate affects species richness and network properties (e.g. nestedness, modularity and specialisation) - either directly or indirectly through species richness. We sampled systematically 39 local plant-pollinator networks on eight islands along a north-south climate gradient in the Aegean. All plant-pollinator material used in the analyses was collected in 2012 and identified to species level. Aspects of climate used in the models were expressed as average conditions (mean temperature and annual precipitation) or as seasonal variability (isothermality and temperature seasonality). Structural properties of plant-pollinator networks were found to be strongly associated with species richness, which was in turn affected by climate, implying that pollination network structure is driven indirectly by climate. In addition, climate had a direct effect on network structure, especially on modularity and specialisation. Different aspects of climate affected network properties in different ways. We highlight that even in a relatively narrow latitudinal gradient, such as within the Aegean Sea region, climate constitutes a significant driver of plant-pollinator interactions.

Asunto(s)

RESUMEN

Global patterns of biodiversity reflect both regional and local processes, but the relative importance of local ecological limits to species coexistence, as influenced by the physical environment, in contrast to regional processes including species production, dispersal, and extinction, is poorly understood. Failure to distinguish regional influences from local effects has been due, in part, to sampling limitations at small scales, environmental heterogeneity within local or regional samples, and incomplete geographic sampling of species. Here, we use a global dataset comprising 47 forest plots to demonstrate significant region effects on diversity, beyond the influence of local climate, which together explain more than 92% of the global variation in local forest tree species richness. Significant region effects imply that large-scale processes shaping the regional diversity of forest trees exert influence down to the local scale, where they interact with local processes to determine the number of coexisting species.

Asunto(s)