Exploring Relationships between Boltzmann Entropy of Images and Building Classification Accuracy in Land Cover Mapping.

Remote sensing images are important data sources for land cover mapping. As one of the most important artificial features in remote sensing images, buildings play a critical role in many applications, such as population estimation and urban planning. Classifying buildings quickly and accurately ensures the reliability of the above applications. It is known that the classification accuracy of buildings (usually indicated by a comprehensive index called F1) is greatly affected by image quality. However, how image quality affects building classification accuracy is still unclear. In this study, Boltzmann entropy (an index considering both compositional and configurational information, simply called BE) is employed to describe image quality, and the potential relationships between BE and F1 are explored based on images from two open-source building datasets (i.e., the WHU and Inria datasets) in three cities (i.e., Christchurch, Chicago and Austin). Experimental results show that (1) F1 fluctuates greatly in images where building proportions are small (especially in images with building proportions smaller than 1%) and (2) BE has a negative relationship with F1 (i.e., when BE becomes larger, F1 tends to become smaller). The negative relationships are confirmed using Spearman correlation coefficients (SCCs) and various confidence intervals via bootstrapping (i.e., a nonparametric statistical method). Such discoveries are helpful in deepening our understanding of how image quality affects building classification accuracy.

Antagonistic effect of selenium on mercuric chloride in the central immune organs of chickens: The role of microRNA-183/135b-FOXO1/TXNIP/NLRP3 inflammasome axis.

Mercury (Hg) is a persistent environmental and industrial pollutant that accumulated in the body and induces oxidative stress and inflammation damage. Selenium (Se) has been reported to antagonize immune organs damage caused by heavy metals. Here, we aimed to investigate the prevent effect of Se on mercuric chloride (HgCl2 )-induced thymus and bursa of Fabricius (BF) damage in chickens. The results showed that HgCl2 caused immunosuppression by reducing the relative weight, cortical area of the thymus and BF, and the number of peripheral blood lymphocytes. Meanwhile, HgCl2 induced oxidative stress and imbalance in cytokines expression in the thymus and BF. Further, we found that thioredoxin-interacting protein (TXNIP) and the NOD-like receptor pyrin domain containing 3 (NLRP3) inflammasome mediated HgCl2 -induced oxidative stress and inflammation. Mechanically, the targeting and inhibitory effect of microRNA (miR)-135b/183 on forkhead box O1 (FOXO1) were an upstream event for HgCl2 -activated TXNIP/NLRP3 inflammasome pathway. Most importantly, Se effectively attenuated the aforementioned damage in the thymus and BF caused by HgCl2 and inhibited the TXNIP/NLRP3 inflammasome pathway by reversing the expression of FOXO1 through inhibiting miR-135b/183. In conclusion, the miR-135b/183-FOXO1/TXNIP/NLRP3 inflammasome axis might be a novel mechanism for Se to antagonize HgCl2 -induced oxidative stress and inflammation in the central immune organs of chickens.

Selenium alleviates mercury chloride-induced liver injury by regulating mitochondrial dynamics to inhibit the crosstalk between energy metabolism disorder and NF-κB/NLRP3 inflammasome-mediated inflammation.

Mercury (Hg) is a persistent heavy metal contaminant with definite hepatotoxicity. Selenium (Se) has been shown to alleviate liver damage induced by heavy metals. Therefore, the present study aimed to explore the mechanism of the antagonistic effect of Se on mercury chloride (HgCl2)-induced hepatotoxicity in chickens. Firstly, we confirmed that Se alleviated HgCl2-induced liver injury through histopathological observation and liver function analyzation. The results also showed that Se prevented HgCl2-induced liver lipid accumulation and dyslipidemia by regulating the gene expression related to lipid as well as glucose metabolism. Moreover, Se blocked the nuclear factor kappa B (NF-κB)/NLR family pyrin domain containing 3 (NLRP3) inflammasome signaling pathway, which was the key to alleviate the inflammation caused by HgCl2. Mechanically, Se inhibited immoderate mitochondrial division, fusion, and biogenesis caused by HgCl2, and also improved mitochondrial respiration, which were essential for preventing energy metabolism disorder and inflammation. In conclusion, our results suggested that Se inhibited energy metabolism disorder and inflammation by regulating mitochondrial dynamics, thereby alleviating HgCl2-induced liver injury in chickens. These results are expected to provide potential intervention and therapeutic targets for diseases caused by inorganic mercury poisoning.

belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients.

Entropy is a fundamental concept in thermodynamics that is important in many fields, including image processing, neurobiology, urban planning, and sustainability. As of recently, the application of Boltzmann entropy for landscape patterns was mostly limited to the conceptual discussion. However, in the last several years, a number of methods for calculating Boltzmann entropy for landscape mosaics and gradients were proposed. We developed an R package belg as an open source tool for calculating Boltzmann entropy of landscape gradients. The package contains functions to calculate relative and absolute Boltzmann entropy using the hierarchy-based and the aggregation-based methods. It also supports input raster with missing (NA) values, allowing for calculations on real data. In this study, we explain ideas behind implemented methods, describe the core functionality of the software, and present three examples of its use. The examples show the basic functions in this package, how to adjust Boltzmann entropy values for data with missing values, and how to use the belg package in larger workflows. We expect that the belg package will be a useful tool in the discussion of using entropy for a description of landscape patterns and facilitate a thermodynamic understanding of landscape dynamics.

Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic.

Shannon entropy is currently the most popular method for quantifying the disorder or information of a spatial data set such as a landscape pattern and a cartographic map. However, its drawback when applied to spatial data is also well documented; it is incapable of capturing configurational disorder. In addition, it has been recently criticized to be thermodynamically irrelevant. Therefore, Boltzmann entropy was revisited, and methods have been developed for its calculation with landscape patterns. The latest method was developed based on the Wasserstein metric. This method incorporates spatial repetitiveness, leading to a Wasserstein metric-based Boltzmann entropy that is capable of capturing the configurational disorder of a landscape mosaic. However, the numerical work required to calculate this entropy is beyond what can be practically achieved through hand calculation. This study developed a new software tool for conveniently calculating the Wasserstein metric-based Boltzmann entropy. The tool provides a user-friendly human-computer interface and many functions. These functions include multi-format data file import function, calculation function, and data clear or copy function. This study outlines several essential technical implementations of the tool and reports the evaluation of the software tool and a case study. Experimental results demonstrate that the software tool is both efficient and convenient.

Use of Entropy in Developing SDG-based Indices for Assessing Regional Sustainable Development: A Provincial Case Study of China.

Sustainable development appears to be the theme of our time. To assess the progress of sustainable development, a simple but comprehensive index is of great use. To this end, a multivariate index of sustainable development was developed in this study based on indicators of the United Nations Sustainable Development Goals (SDGs). To demonstrate the usability of this developed index, we applied it to Fujian Province, China. According to the China SDGs indicators and the Fujian situation, we divided the SDGs into three dimensions and selected indicators based on these dimensions. We calculated the weights and two indices with the entropy weight coefficient method based on collecting and processing of data from 2007 to 2017. We assessed and analyzed the sustainable development of Fujian with two indices and we drew three main conclusions. From 2007 to 2017, the development index of Fujian showed an increasing trend and the coordination index of Fujian showed a fluctuating trend. It is difficult to smoothly improve the coordination index of Fujian because the development speeds of Goal 3 (Good Health and Well-being) and Goal 16 (Peace, Justice, and Strong Institutions) were low. The coordination index of Fujian changed from strong coordination to medium coordination from 2011 to 2012 because the development speed of the environmental dimension suddenly improved. It changed from strong coordination to medium coordination from 2015 to 2016 because the values of the development index of the social dimension were decreasing. To the best of our knowledge, these are the first SDGs-based multivariate indices of sustainable development for a region of China. These indices are applicable to different regions.

An Urban Scaling Estimation Method in a Heterogeneity Variance Perspective.

Urban scaling laws describe powerful universalities of the scaling relationships between urban attributes and the city size across different countries and times. There are still challenges in precise statistical estimation of the scaling exponent; the properties of variance require further study. In this paper, a statistical regression method based on the maximum likelihood estimation considering the lower bound constraints and the heterogeneous variance of error structure, termed as CHVR, is proposed for urban scaling estimation. In the CHVR method, the heterogeneous properties of variance are explored and modeled in the form of a power-of-the-mean variance model. The maximum likelihood fitting method is supplemented to satisfy the lower bound constraints in empirical data. The CHVR method has been applied to estimating the scaling exponents of six urban attributes covering three scaling regimes in China and compared with two traditional methods. Method evaluations based on three different criteria validate that compared with both classical methods, the CHVR method is more effective and robust. Moreover, a statistical test and long-term variations of the parameter in the variance function demonstrate that the proposed heterogeneous variance function can not only describe the heterogeneity in empirical data adequately but also provide more meaningful urban information. Therefore, the CHVR method shows great potential to provide a valuable tool for effective urban scaling studies across the world and be applied to scaling law estimation in other complex systems in the future.

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images.

The quality of an image affects its utility and image quality assessment has been a hot research topic for many years. One widely used measure for image quality assessment is Shannon entropy, which has a well-established information-theoretic basis. The value of this entropy can be interpreted as the amount of information. However, Shannon entropy is badly adapted to information measurement in images, because it captures only the compositional information of an image and ignores the configurational aspect. To fix this problem, improved Shannon entropies have been actively proposed in the last few decades, but a thorough evaluation of their performance is still lacking. This study presents such an evaluation, involving twenty-three improved Shannon entropies based on various tools such as gray-level co-occurrence matrices and local binary patterns. For the evaluation, we proposed: (a) a strategy to generate testing (gray-level) images by simulating the mixing of ideal gases in thermodynamics; (b) three criteria consisting of validity, reliability, and ability to capture configurational disorder; and (c) three measures to assess the fulfillment of each criterion. The evaluation results show only the improved entropies based on local binary patterns are invalid for use in quantifying the configurational information of images, and the best variant of Shannon entropy in terms of reliability and ability is the one based on the average distance between same/different-value pixels. These conclusions are theoretically important in setting a direction for the future research on improving entropy and are practically useful in selecting an effective entropy for various image processing applications.

GIS-based analysis of population exposure to PM2.5 air pollution-A case study of Beijing.

PM2.5, formally defined as particulate matter with diameter less than 2.5µm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and long-term exposures to PM2.5 are strongly linked with respiratory diseases. In this study, various types of spatio-temporal data were collected and used to estimate the spatio-temporal variation of PM2.5 exposure in Beijing in 2014. The seasonal and daily variation of the population-weighted exposure level (PWEL) in 2014 was estimated and compared. The results show that the population exposure to ambient air pollution differs significantly in the four seasons, and the exposure levels in winter and spring are notably higher than the other seasons; the exposure level changes greatly from North to South, and each sub-district maintains similarity to neighboring sub-districts.

A raster-based spatial clustering method with robustness to spatial outliers.

Spatial clustering is an essential method for the comprehensive understanding of a region. Spatial clustering divides all spatial units into different clusters. The attributes of each cluster of the spatial units are similar, and simultaneously, they are as continuous as spatially possible. In spatial clustering, the handling of spatial outliers is important. It is necessary to improve spatial integration so that each cluster is connected as much as possible, while protecting spatial outliers can help avoid the excessive masking of attribute differences This paper proposes a new spatial clustering method for raster data robust to spatial outliers. The method employs a sliding window to scan the entire region to determine spatial outliers. Additionally, a mechanism based on the range and standard deviation of the spatial units in each window is designed to judge whether the spatial integration should be further improved or the spatial outliers should be protected. To demonstrate the usefulness of the proposed method, we applied it in two case study areas, namely, Changping District and Pinggu District in Beijing. The results show that the proposed method can retain the spatial outliers while ensuring that the clusters are roughly contiguous. This method can be used as a simple but powerful and easy-to-interpret alternative to existing geographical spatial clustering methods.

Coupled analysis of arable land input intensity and output intensity based on sliding windows.

Sustainable intensification (SI) of agriculture can produce more food to meet the demand of a growing population while considering ecosystem health. The current SI estimation framework ignores the complex coupling between input and output intensity of arable land. A method for coupled analysis of arable land input intensity and output intensity based on sliding windows is proposed. By calculating the correlation coefficient and partial correlation coefficient between input intensity and output intensity in different value ranges as the order parameter, the phase transition and the influence process of input intensity on output intensity can be explained. Meanwhile, a python-based framework is developed. An application of the method was made to reveal the interaction process between annual provincial input intensity and output intensity in mainland China. Researchers in many fields may benefit from the method by obtaining a fast way to analysis the coupling relationship between driving and dependent variables in complex systems.•New method for SI estimation is presented.•The order parameter of the coupling relationship between input and output intensity is calculated based on sliding windows.•Analysis of coupling relationships between driving and dependent variables in complex systems.

Analyzing spatial patterns and driving factors of cropland change in China's National Protected Areas for sustainable management.

Farming in protected areas frequently challenges ecological conservation goals while supporting local livelihoods. To balance protection and agriculture, a comprehensive understanding of cropland dynamics in protected areas is of paramount importance. However, studies addressing this trade-off are relatively scarce, especially considering explicit Chinese government regulations on population relocation and cropland retirement in National Protected Areas (NPAs). Our study examined the spatial and temporal pattern of cropland in NPAs and explored the covariance between cropland density and species richness. Concurrently, the driving factors of cropland development in NPAs were analyzed using Multiple Linear Regression. The results indicate that the cropland area in NPAs continued to expand, growing from 1.93 to 2.34 million hectares in 2000-2020, with a cropland density of approximately 0.4. Cropland expansion in the northern NPAs, particularly in the resource-rich Northeast (28.12 %) and the Northwest with high marginal agricultural returns (38.26 %), have encroached upon species habitats and aggravated biodiversity loss. Moreover, cities with higher cropland densities in NPAs are usually located at borders, possibly due to decentralized management. The Multiple Linear Regression results show that high cropland density is usually associated with a high population density (ß = 0.156) and lower levels of rural education (ß = -0.101) and income (ß = -0.122). To mitigate the issue of cropland development in NPAs, it is crucial to avoid one-size-fits-all management strategies, strengthen regional legal supervision, adjust fiscal incentives, and promote eco-friendly agriculture. In the north regions, the expansion of cropland in NPAs should be strictly controlled. For the southwest, the positive role of preserving cropland in NPAs for alleviating human-nature conflict and maintaining social stability should be emphasized. This study provides research support for China's exploration of geographically suitable strategies for controlling cropland in NPAs. Moreover, the findings could serve as a reference for the governance of NPAs in other countries.

CLUMondo-BNU for simulating land system changes based on many-to-many demand-supply relationships with adaptive conversion orders.

Land resources are fundamentally important to human society, and their transition from one macroscopic state to another is a vital driving force of environment and climate change locally and globally. Thus, many efforts have been devoted to the simulations of land changes. Among all spatially explicit simulation models, CLUMondo is the only one that simulates land changes by incorporating the multifunctionality of a land system and allows the establishment of many-to-many demand-supply relationships. In this study, we first investigated the source code of CLUMondo, providing a complete, detailed mechanism of this model. We found that the featured function of CLUMondo-balancing demands and supplies in a many-to-many mode-relies on a parameter called conversion order. The setting of this parameter is a manual process and requires expert knowledge, which is not feasible for users without an understanding of the whole, detailed mechanism. Therefore, the second contribution of this study is the development of an automatic method for adaptively determining conversion orders. Comparative experiments demonstrated the validity and effectiveness of the proposed automated method. We revised the source code of CLUMondo to incorporate the proposed automated method, resulting in CLUMondo-BNU v1.0. This study facilitates the application of CLUMondo and helps to exploit its full potential.

Selenium alleviates endoplasmic reticulum calcium depletion-induced endoplasmic reticulum stress and apoptosis in chicken myocardium after mercuric chloride exposure.

Mercury is a highly toxic heavy metal with definite cardiotoxic properties and can affect the health of humans and animals through diet. Selenium (Se) is a heart-healthy trace element and dietary Se has the potential to attenuate heavy metal-induced myocardial damage in humans and animals. This study was designed to explore antagonistic effect of Se on the cardiotoxicity of mercuric chloride (HgCl2) in chickens. Hyline brown hens received a normal diet, a diet containing 250 mg/L HgCl2, or a diet containing 250 mg/L HgCl2 and 10 mg/kg Na2SeO3 for 7 weeks, respectively. Histopathological observations demonstrated that Se attenuated HgCl2-induced myocardial injury, which was further confirmed by the results of serum creatine kinase and lactate dehydrogenase levels assay and myocardial tissues oxidative stress indexes assessment. The results showed that Se prevented HgCl2-induced cytoplasmic calcium ion (Ca2+) overload and endoplasmic reticulum (ER) Ca2+ depletion mediated by Ca2+-regulatory dysfunction of ER. Importantly, ER Ca2+ depletion led to unfolded protein response and endoplasmic reticulum stress (ERS), resulting in apoptosis of cardiomyocytes via PERK/ATF4/CHOP pathway. In addition, heat shock protein expression was activated by HgCl2 through these stress responses, which was reversed by Se. Moreover, Se supplementation partially eliminated the effects of HgCl2 on the expression of several ER-settled selenoproteins, including selenoprotein K (SELENOK), SELENOM, SELENON, and SELENOS. In conclusion, these results suggested that Se alleviated ER Ca2+ depletion and oxidative stress-induced ERS-dependent apoptosis in chicken myocardium after HgCl2 exposure.

Fulfilling global climate pledges can lead to major increase in forest land on Tibetan Plateau.

The UN Climate Change Conference in Glasgow spawned the enhancement and updating of many nations' climate pledges. Previous research has investigated the effects of these pledges on limiting planetary warming, but their spatially explicit effects on land use/cover are unknown. Here, we linked the Glasgow pledges and the spatially explicit responses of the Tibetan Plateau's land systems. We found that while fulfilling global climate pledges may not significantly affect the global shares of forestland, grassland/pasture, shrubland, and cropland, it needs a 9.4% increase in the forest area of the Tibetan Plateau. This need is an area 11.4 times the increase of the plateau's forest in the 2010s, or greater than the size of Belgium. The new forest comes mainly from the medium-density grassland in the Yangtze River basin, calling for more proactive environmental management for the headwaters area of this longest river in Asia.

The COVID-19 lockdown: a unique perspective into heterogeneous impacts of transboundary pollution on snow and ice darkening across the Himalayas.

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFSLAPs) substantially contributes to glacier retreat. Yet how anthropogenic pollutant emissions affect Himalayan RFSLAPs through transboundary transport is currently not well known. The COVID-19 lockdown, resulting in a dramatic decline in human activities, offers a unique test to understand the transboundary mechanisms of RFSLAPs. This study employs multiple satellite data from the moderate resolution imaging spectroradiometer and ozone monitoring instrument, as well as a coupled atmosphere-chemistry-snow model, to reveal the high spatial heterogeneities in anthropogenic emissions-induced RFSLAPs across the Himalaya during the Indian lockdown in 2020. Our results show that the reduced anthropogenic pollutant emissions during the Indian lockdown were responsible for 71.6% of the reduction in RFSLAPs on the Himalaya in April 2020 compared to the same period in 2019. The contributions of the Indian lockdown-induced human emission reduction to the RFSLAPs decrease in the western, central, and eastern Himalayas were 46.8%, 81.1%, and 110.5%, respectively. The reduced RFSLAPs might have led to 27 Mt reduction in ice and snow melt over the Himalaya in April 2020. Our findings allude to the potential for mitigating rapid glacial threats by reducing anthropogenic pollutant emissions from economic activities.

The spatiotemporal variation in heavy metals in China's farmland soil over the past 20 years: A meta-analysis.

Accurate information on farmland soil heavy metal elements is needed for pollution management and strategic decision making at the national level. In this paper, we review the Chinese literature on soil heavy metal elements (i.e., arsenic, cadmium, chromium, copper, lead, mercury, and zinc) over the past 20 years using meta-analysis. The overall pollution status, spatiotemporal distribution patterns and driving factors of heavy metals in China's farmland soil are explored by using the geoaccumulation index, the standard deviation ellipse method and the PCA/APCS model, respectively. The results show that most heavy metals in farmland soil from the study cases are similar to the world average. Seven types of elements have increased compared with background values. Cd and Hg have become the top polluting elements in China and industrial and agricultural activities are the main sources of current heavy metal element enrichment. Regional natural-social-economic differences have led to significant spatial heterogeneity of heavy metal pollution, showing an intensity pattern unfavourable to national food security. In the time period, the overall distribution range gradually increased with the accelerated growth of regional industrial output, and there was a tendency for the gravity centre of the pollution studies to migrate inland to the northwest and southwest. Regionally differentiated environmental regulation and pollution remediation measures should be developed for pollution prevention and control in the future.

Selenium ameliorates mercuric chloride-induced brain damage through activating BDNF/TrKB/PI3K/AKT and inhibiting NF-κB signaling pathways.

Mercuric chloride (HgCl2), a heavy metal compound, causes neurotoxicity of animals and humans. Selenium (Se) antagonizes heavy metal-induced organ damage with the properties of anti-oxidation and anti-inflammation. Nevertheless, the molecular mechanism underlying the protective effects of sodium selenite (Na2SeO3) against HgCl2-induced neurotoxicity remains obscure. Therefore, the present study aimed to explore the protective mechanism of Na2SeO3 on HgCl2-induced brain damage in chickens. Morphological observations showed that Na2SeO3 alleviated HgCl2-induced brain tissues damage. The results also showed that Na2SeO3 decreased the protein expression of S100 calcium binding protein B (S100B), and increased the levels of nerve growth factors (NGF), doublecortin domain containing 2 (DCDC2), as well as neurotransmitter to reverse HgCl2-induced brain dysfunction. Further, Na2SeO3 attenuated HgCl2-induced oxidative stress by decreasing the level of malondialdehyde (MDA) and increasing the activities of total superoxide dismutase (T-SOD), glutathione peroxidase (GSH-Px), and total antioxidant capacity (T-AOC). Mechanistically, Na2SeO3 activated the brain-derived neurotrophic factor (BDNF)/tropomyosin-related kinase receptor type B (TrKB)/phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway and suppressed the nuclear factor kappa B (NF-κB) signaling pathway to inhibit apoptosis and inflammation caused by HgCl2 exposure. In summary, Na2SeO3 ameliorated HgCl2-induced brain injury via inhibiting apoptosis and inflammation through activating BDNF/TrKB/PI3K/AKT and suppressing NF-κB pathways.

Mercuric chloride induces sequential activation of ferroptosis and necroptosis in chicken embryo kidney cells by triggering ferritinophagy.

Mercuric chloride (HgCl2) is an environmental pollutant with serious nephrotoxic effects, but the underlying mechanism of HgCl2 nephrotoxicity is not well understood. Ferroptosis and necroptosis are two programmed cell death (PCD) modalities that have been reported singly in heavy metal-induced kidney injury. However, the interaction between ferroptosis and necroptosis in HgCl2-induced kidney injury is unclear. Here, we established a model of HgCl2-exposed chicken embryo kidney (CEK) cells to dissect the progresses and mechanisms of these two PCDs. We found that ferroptosis was initially activated in CEK cells after HgCl2 exposure for 12 h, and necroptosis was activated subsequently at 24 h. Importantly, further study indicated that the shift from ferroptosis to necroptosis was driven by ROS, which was produced by iron-dependent Fenton reaction, and the iron chelation by DFO prevented the sequential activation of both ferroptosis and necroptosis. To investigate the source of intracellular iron, the regulation of iron homeostasis was first explored and demonstrated a tendency for intracellular iron overload in CEK cells. Interestingly, the cellular ferritin, a free iron depository, decreased in a time-dependent manner. Further studies revealed that the degradation of ferritin was attributed to the activation of selective cargo receptor nuclear receptor coactivator 4 (NCOA4)-mediated ferritinophagy, and the inhibition of ferritinophagy by CQ prevented the HgCl2-induced cell death. In conclusion, our study demonstrated that HgCl2 released excess free iron via ferritinophagy, led to a sustained accumulation of ROS and ultimately activated ferroptosis and necroptosis sequentially. These findings provide a new understanding for the nephrotoxic mechanism of HgCl2.

Protective mechanism of selenium on mercuric chloride-induced testis injury in chicken via p38 MAPK/ATF2/iNOS signaling pathway.

Mercuric chloride (HgCl2) is a well-known toxic heavy metal contaminant, which causes male reproductive function defects. Selenium (Se) has been recognized as an effective antioxidant against heavy metals-induced male reproductive toxicity. The aim of present study was to explore the potentially protective mechanism of Se on HgCl2-induced testis injury in chicken. Firstly, the results showed that Se mitigated HgCl2-induced testicular injury through increasing the blood-testis barrier (BTB) cell-junction proteins expression of occludin, zonula occludens-1 (ZO-1), connexin 43 (Cx43), and N-cadherin. Secondly, Se alleviated HgCl2-induced oxidative stress through decreasing the malondialdehyde (MDA) content and increasing the superoxidase dismutase (SOD), glutathione peroxidase (GSH-Px) activities as well as the total antioxidant capacity (T-AOC) level. Thirdly, Se inhibited the activation of p38 MAPK signaling through decreasing the proteins expression of phosphorylated-p38 (p-p38) and phosphorylated-ATF2 (p-ATF2), and alleviated inflammation response through decreasing the proteins expression of inducible nitric oxide synthase (iNOS), nuclear factor kappa B (NF-κB), tissue necrosis factor-alpha (TNF-α), and cyclooxygenase 2 (COX2). Collectively, these results demonstrated that Se effectively alleviated HgCl2-induced testes injury via improving antioxidant capacity to reduce inflammation mediated by p38 MAPK/ATF2/iNOS signaling pathway in chicken. Our data shed a new light on potential mechanisms of Se antagonized HgCl2-induced male reproductive toxicity.