Raphanus is an important genus of Brassicaceae and has undergone a lengthy evolutionary process. However, the inter- and intraspecific phylogenetic relationships and genetic diversity are not well understood. To elucidate these issues, we SSR-sequenced 939 wild, semi-wild and cultivated accessions, and discovered that Europe was the origin center of radishes with diverse European wild radishes, and Europe, South Asia and East Asia might be three independent domestication centers. There was considerable genetic differentiation within European cultivated radishes. European primitive cultivated radish exhibited gene flow with black radish/oil radish and rat-tail radish. Among Asian cultivated radishes, rat-tail radish was a sister to the clade of Chines big radish (including Japanese wild radish), suggesting that they may share the most recent common ancestry. Japanese wild radish had strong gene exchange with Japanese/Korea big radish, oil radish and rat-tail radish. American wild radish developed from natural hybridization between European wild radish and European small radish. All these demonstrated that European primitive cultivated type, American wild radish and Japanese wild radish might have played indispensable roles in radish evolution. Our study provides new perspectives into the origin, evolution and genetic diversity of Raphanus and facilitates the conservation and exploitation of radish germplasm resources.Raphanus has undergone a lengthy evolutionary process and has rich diversity. However, the inter- and intraspecific phylogenetic relationships and genetic diversity of this genus are not well understood. Through SSR-sequencing and multi-analysis of 939 wild, semi-wild and cultivated accessions, we discovered that the European wild radish (EWR) population is separated from cultivated radishes and has a higher genetic diversity. Frequent intraspecific genetic exchanges occurred in the whole cultivated radish (WCR) population; there was considerable genetic differentiation within the European cultivated radish (ECR) population, which could drive radish diversity formation. Among the ECR subpopulations, European primitive cultivated radishes (EPCRs) with higher genetic diversity are most closely related to the EWR population and exhibit a gene flow with rat-tail radishes (RTRs) and black radishes (BRs)/oil radishes (ORs). Among Asian cultivated radishes (ACRs), Chinese big radishes (CBRs) with a relatively high diversity are furthest from the EWR population, and most Japanese/Korean big radishes (JKBRs) are close to CBR accessions, except for a few old Japanese landraces that are closer to the EPCR. The CBR and JKBR accessions are independent of RTR accessions; however, phylogenetic analysis indicates that the RTR is sister to the clade of CBR (including JWR), which suggests that the RTR may share the most recent common ancestry with CBRs and JWRs. In addition, Japanese wild radishes (JWRs),  are mainly scattered between CBRs and EPCRs in PCoA analysis. Moreover, JWRs have a strong gene exchange with the JKBR, OR and RTR subpopulations. American wild radishes (AWRs) are closely related to European wild and cultivated radishes, and have a gene flow with European small radishes (ESRs), suggesting that the AWR developed from natural hybridization between the EWR and the ESR. Overall, this demonstrates that Europe was the origin center of the radish, and that Europe, South Asia and East Asia appear to have been three independent domestication centers. The EPCR, AWR and JWR, as semi-wild populations, might have played indispensable transitional roles in radish evolution. Our study provides new perspectives into the origin, evolution and genetic diversity of Raphanus and facilitates the conservation and exploitation of radish germplasm resources. Raphanus, a member of the Brassicaceae family, consists of two species: Raphanus sativus L. and R. raphanistrum L. [R. raphanistrum L. is a wild relative species of R. sativus L., which is an important root vegetable crop species worldwide, comprising five different varieties; namely, R. sativus var. radicular  and R. sativus var. longipinnatus (East Asian big radish), var. niger Kerner (black radish), var. oleiformis (oil radish) and var. caudatus Hooler & Anderson (rat-tail radish) [R. raphanistrum, R. landra and R. maritimus [Raphanus species should be a single species with three subspecies: R. raphanistrum subsp. raphanistrum, R. raphanistrum subsp. landra and R. raphanistrum subsp. maritimus [R. raphanistrum L. is generally considered to comprise two subspecies (R. raphanistrum subsp. raphanistrum and R. raphanistrum subsp. landra) [strum L. . R. raph radish) ,3,4. Somaritimus ,6. Otheraritimus . However landra) . Compare landra) ,10,11.R. raphanistrum L. by some authors [R. landra and R. maritimus by other authors [R. raphanistrum) has also been recorded in the Flora of China [Raphanus. sativus forma raphanistroides [R. sativus var. raphanistroides is also widely distributed along the coast of China and Korea [R. sativus var. raphanistroides, rather than the wild R. raphanistrum [R. raphanistrum) less than 150 years ago [The wild ancestor of the cultivated radish was considered to be  authors ,12,13,14 authors . Althoug authors . The wilof China . The Midof China . A recenof China . In Japastroides . This hystroides ,20. R. snd Korea . Kim revanistrum . The Calears ago ,23. To dR. sativus var. raphanistroides Makino), 7 accessions of R. raphanistrum, with an average diversity of 4.88 alleles per locus and a polymorphism information content (PIC) value of 0.55. Other researchers used 221 amplified fragment-length polymorphism (AFLP) markers to assess the diversity of 65 cultivated radish accessions from 21 countries in Europe, North Africa, the Middle East, and South and East Asia, and found Nei genetic diversity values ranging from 0.267 to 0.279 [R. sativus, 13 accessions of R. raphanistrum, 3 accesions of R. maritimus, and 2 accessions unknown from East Asia, South and Southeast Asia, and the Occident and Near East [Genetic diversity is the basis of radish evolution and differentiation. Wang et al.  used 50 to 0.279 . Kong alto 0.279 . Japanesear East . UnfortuVitis vinifera L.) [Cucumis sativus L.) [Salmo salar, Quercus faginea, Quercus canariensis, Alosa alosa, Armillaria ostoyae, Melipona variegatipes [Camellia oleifera [SSRs are 2–5 bp sequences that are repeated nose-to-tail; the number of copies at each locus is what varies . Due to fera L.) , cucumbeivus L.) , Salmo segatipes , and hexoleifera .In this study, a total of 939 radish accessions were subjected to SSR-seq with 38 core SSR markers, which were designed based on the radish whole genome. Based on the diversity of the SSR markers, the genetic diversity and phylogenetic relationships among the radishes were further analyzed. The results provide valuable information on the genetic diversity distribution, origin and evolutionary trajectory of the radish and lay a solid foundation for effective germplasm collection and preservation, elite gene mining, and genetic improvement in the radish.R.raphanistrum but had characteristics of taproots, flowers, and siliques that were similar to those of the cultivated radish; the other forty-two accessions with the Latin name of R. sativus L. convar. sativus had characteristics of non-enlarged taproots, white or purple flowers, and hard siliques that were between those of cultivated radishes and European wild radishes (EWR). Among the accessions named wild radishes, the Japanese wild radish (JWR), the American wild radish  and the EWR, were included. Two subspecies of EWR, R. raphanistrum L. subsp. raphanistrum (72 accessions) and R. raphanistrum L. subsp. landra (Moretti ex DC.) Bonnier & Layens (118 accessions), as well as 11 accessions of wild radish with incomplete Latin names according to their original records, were included. All the seeds were planted in plastic greenhouses on Langfang Farm in the spring of 2017 and autumn of 2018 and cultivated normally, according to commercial production standards. We planted ten plants for each accession. A total of 939 cultivated and wild radish accessions were used in this study. These accessions were conserved in the National Mid-term Genebank of Vegetable Germplasm in China and collected from 31 provinces of China and from other countries, such as Japan, Korea, Thailand, India, Germany, Russia, Spain, France and the United States . The culRaphanus sativus L.) [To verify the botanical classification of all the accessions, their major phenotypic traits were observed and recorded during the vegetative growth and reproductive stages, according to the descriptors and data standards for the radish (ivus L.) . The vegWe collected the fresh and tender leaves from three normal and representative 2-week-old seedlings of each accession and pooled them together as a sample. Total genomic DNA was extracted for each accession using the modified cetyl-trimethylammonium bromide (CTAB) method . We addeBased on the XYB36–2 reference genome , MISA anThe SSR primers should satisfy the requirements of SSR-seq: the unit is repeated from 3 to 10 times, and the repeat unit cannot be composed of only GC or AT. For the screening of polymorphic primers, the PCR amplification reaction mixture consisted of the following: 0.3 μL of each primer; 2 μL of genomic DNA; 1.5 µL of 10X buffer; 0.3 µL of dNTPs (2.5 mmol/L); 0.2 µL of Taq polymerase (2.5 U/µL), and 10.4 µL of deionized water . The PCR amplification conditions were as follows: 1 cycle of 95 °C for 5 min; 30 to 35 cycles of 95 °C for 35 s, 55 °C for 30 s, and 72 °C for 1 min; and 1 cycle of 72 °C for a final extension of 7 min. The amplification products were separated by 8% polypropylene gel electrophoresis for 1 h at 200 V to assess the sample polymorphism. Polymorphic primers were used to amplify the DNAs of all materials and the amplified products were detected and genotyped on an Illumina NextSeq instrument .The genetic diversity among different populations and across all the populations was estimated based on SSR markers according to the Na , Ne, , Ho (observed heterozygosity), He (expected heterozygosity), I (Shannon’s information index) and Nei indexes. All these indexes were determined using normalized SSR genotyping data with POPGENE v1.32 software.K value ranging from 1 to 11, the STRUCTURE program was run 11 times with an admixture model and a Markov chain Monte Carlo (MCMC) burn-in length of 100,000, after which 50,000 burn-in runs and MCMC replicates were set up. Finally, the largest ΔK corresponding to the optimal K values was obtained based on the results of the ΔK analysis.Based on the microsatellite data and the Bayesian model, STRUCTURE v2.3.4 software was used to determine the optimum number of subpopulations for all the analyzed samples. For each The Nei genetic distance was calculated based on the allele frequencies of subpopulations, and the genetic similarity matrixes and genetic distance matrixes were obtained between subpopulations. Finally, the FastME method in the phangorn R package was used for the construction and rendering of an evolutionary tree. The polysat package was run in R 3.5 software and used to calculate the Bruvo distance between each pair of samples and to perform PCoA . Weir anraphanistrum accessions bloomed and produced seeds in the fall of the same planting year in Beijing. There were many thorns on the flower buds, leaves and stems. The silique surface was constricted between seeds. As the silique matured, it could automatically break at the constriction, and the seeds with hard shells were easily shattered. The taproot of these accessions was not enlarged and had highly branched lateral roots. With respect to subsp. landra, most of the accessions rarely bloomed in the autumn of the planting year in Beijing, but produced yellow flowers in the following spring. These accessions had a few thorns on their flower buds, leaves and stems. The silique surface of most accessions shrank between seeds; however, for some accessions it was smooth or wavy. Mature siliques either shattered later or did not shatter. Compared with those of subsp. raphanistrum, the unenlarged taproots of subsp. landra had fewer lateral roots.According to the observation of phenotypic characteristics and original records, the radish collection showed rich morphological diversity in shape, the size and color of the fleshy taproot, leaves, flowers and siliques . We diviR. raphanistrum from Europe had semi-enlarged and severely lignified taproots with an abundance of lateral roots, white or purple flowers and non-shattering siliques. We considered these to be members of the EPCR population because they resembled the weedy radish. At the same time, forty-two accessions with the Latin name of R. sativus L. convar. sativus, as primitive cultivated radishes, had the characteristics of non-enlarged or semi-enlarged and lignified taproots, white or purple flowers, and hard, lignified siliques. We also classified them into the EPCR population.In addition, eighteen accessions named Most of the OR accessions had semi-enlarged lignified taproots with many lateral roots and many leaves. However, the Chinese oil radish had non-enlarged taproots with many lateral roots. The BR accessions with black, long, cylindrical or round fleshy taproots were collected from Europe. ESR primarily had red, purple and white skin and round or flat-round taproots. The RTR accessions had non-enlarged or semi-enlarged taproots and easily bolted. Their tender siliques with seeds could be eaten as the main edible products, and the largest silique reached 32.89 cm.The AWR accessions had non-enlarged taproots, as well as red, purple or white flowers, with a few thorns on their stems, leaves and flower buds. The characteristics of the JWR accessions included: white, light red and purple flowers; few thorns on their stems, leaves and flower buds; non-enlarged or semi-enlarged taproots with many lateral roots; and highly hard, lignified mature siliques with wavy surfaces. Their seeds were not easy to burst or thresh. Most of the JKBR accessions had long, cylindrical, fleshy taproots with white, light green or red skin. However, Kosena daikon, Moriguchi daikon and Yamada daikon in the JKBR population had enlarged taproots with some lateral roots. CBR accounted for most of the materials and had enlarged taproots with a variety of colors, sizes and shapes. All of the above information provides the basis for further analysis of this collection at the molecular level.In total, 600 pairs of SSR primers distributed throughout the radish whole genome were preliminarily designed. Genotyping was ultimately conducted by amplifying the template of DNA using 38 pairs of highly stable polymorphic SSR primers , which wIn total, 424 alleles were detected in all the accessions by SSR-seq. We analyzed the genetic diversity of ten groups based on the allele variation profile . The EWRTo investigate the population structure of the collected radish genotypes, the Bayesian clustering program STRUCTURE based on SSR fragment length was used. ΔK analysis showed K = 2 to be optimal for all radish samples A, indicaraphanistrum; two accessions were named as subsp. landra, and one accession had an incomplete Latin name according to the original records. Similarly, the second subgroup included 135 radish accessions, among which 116 accessions are recorded as subsp. landra; 9 accessions were called subsp. raphanistrum, and the Latin names of 10 accessions were incomplete. Combined with the findings based on the phenotypic observations, 3 accessions in the first subgroup and 19 accessions in the second subgroup were corrected to subsp. raphanistrum and subsp. landra, respectively, which helped to verify the taxonomic status of these controversial radish genotypes.A neighbor-joining phylogenetic tree was constructed to show the phylogenetic relationships of all cultivated and wild radish genotypes . The EWRR. sativus L. convar. sativus had non-enlarged or semi-enlarged taproots with an abundance of lateral roots, white or purple flowers, hard, lignified siliques with a wavy surface, and non-shattering seeds. Most of these accessions were relatively closely related to the EWR accessions and seemed to be more primitive than the other cultivated radish accessions. A few of them were distributed among the RTR and EACR populations, implying that they may have been the transitional ancestors of RTR and EACR, respectively. The Latin names of the other eighteen radish accessions were recorded as R. raphanistrum subsp. raphanistrum and R. raphanistrum subsp. landra. However, their phenotypic traits were similar to those of the forty-two materials mentioned above, and they clustered closer to the EWR population. Therefore, the genotyping supported our classification of these accessions into the EPCR population.Notably, among the sixty accessions of EPCR from Europe, forty-two accessions of Three accessions of the AWR were scattered among those of the ECR, although they had more genetic components resembling the wild radish accessions. Among them were 247Y and 249Y, which had dark purple flowers and were clustered together, and another (248Y) had white flowers separated. Thirteen ESR accessions had white or light red flowers and most of them were clustered together, whereas the accession 602C was a unique ESR germplasm and had light yellow flowers, which were clustered into a separate branch. Five BR accessions had the same origin and were clustered together. Moreover, most of the OR accessions from Europe were clustered together, except for two accessions collected from Yunnan Province, China, which clustered far from the European OR. Almost all the RTR accessions introduced from Germany and India clustered together. The CBR accessions, accounting for 58.15% of all accessions, were collected from 31 provinces of China and clustered together into a large subgroup. Most of the JKBR accessions were closely related to the CBR population, and a few old Japanese landraces were close to the EPCR.The seventeen JWR accessions were spread among the EACR and South Asia cultivated radish (SACR) accessions, which showed that they were phenotypically diverse. Our results essentially agreed with the viewpoint of Yamagishi  and Kim The PCoA of the SSR data revealed that in terms of phylogenetic relationships, the EACR and EWR were also clearly separated far away in the horizontal direction . Most ofMost of the JWR accessions were distributed among or near the EACR accessions, although some were between the EACR and EWR accessions . These rPopulation differentiation within and among the different radish populations was evaluated through Wright’s (1965) F-statistics, the inbreeding index (Fis), and the Fit and fixation index (Fst) . The oveGene flow among different species/populations that typically occurs in ecosystems is helpful for understanding genetic exchange and species diversification. In terms of gene flow strength among different radish species, varieties or types , we founR. raphanistrum.Interestingly, no gene flow was detected between the OR population and the RTR population, although members of both populations are eaten as siliques or used as oil sources. This lack of gene flow may have occurred because of geographical or cultural isolation. In addition, the AWR accessions showed evidence of gene flow with the ESR accessions, suggesting that the AWR may be the offspring of natural hybridization between the ESR and By combining the data from the phylogenetic clustering and PCoA, we inferred that EPCR, AWR and JWR populations might have played a special transitional role during the course of radish evolution. In Europe, a possible evolutionary path might be from the EWR population to the EPCR, and then to cultivated radishes of the BR, ESR and OR populations. In South Asia, the path might have been from the EWR or EPCR, to the JWR or RTR populations. In East Asia, the RTR is the sister to the CBR/JWR clade, suggesting that they share the most recent common ancestor. This indicates the direction of evolution from the EPCR to an ancestor of the RTR and JWR/CBR, before the divergence of these two groups separated geographically: then, to the Chinese oil radish/Japanese traditional landraces and finally to the Asian cultivated big radish.The origin, evolution, and classification of the radish has been debated by many researchers ,14. NoneTraditional SSR markers, which are highly polymorphic and codominant, have been widely used in genetic diversity evaluations ,31,32,33R. raphanistrum originated in the Mediterranean region [During the process of plant evolution and crop domestication, a few agronomically desirable alleles were selected, and numerous genetic variations in wild progenitor species were lost due to natural/artificial selection and bottleneck effects , as has n region . Our sturaphanistrum and subsp. landra are recorded in our collection. Our phenotypic observations matched the characteristics [raphanistrum have yellow flowers and many thorns on their flower buds, leaves and stems. In addition, the plants flower easily, the surface of the siliques is shrunken between the seeds, and their lignified and hard siliques easily break between seeds, which then fall automatically. Self-shattering is an important diagnostic trait of domesticated crops and is beneficial for their rapid reproduction, high seed viability and ability to survive in different stressful environments. However, this phenomenon seems to have been lost during cultivation [raphanistrum is located farthest from the cultivated radish. Based on all the evidence, we infer that subsp. raphanistrum may be the most primitive wild ancestor of cultivated R. sativus.Previous findings on the evolution of cultivated radish accessions are controversial ,2,21,57,eristics  of the ttivation . Accordilandra have yellow flowers and few thorns on their flower buds, leaves, stems and silique surface. Additionally, they rarely flower in the autumn of the sowing season. In most cases, the surface of the lignified and hard siliques is shrunken between the seeds, and some are smooth or wavy. When they mature, the siliques usually do not fall off or shatter. Similar phenotypic traits were also observed in the EPCR. However, the flowers of the EPCR plants are white, red and purple, and they bolt late. Previous anatomical data has confirmed that the multilayered palisade tissue of subsp. landra is present only in cotyledonary leaves of cultivated radish plants [landra are closely related to the primitive cultivated radish accessions. Overall, we infer that subsp. landra may be the closest wild ancestor to R. sativus.Based on our observations, members of subsp. h plants . Our phyR. raphanistrum in the Mediterranean, the EPCR accessions evolved/domesticated first, after which the OR, ESR and BR accessions appeared successively across Europe. On the other hand, the EPCR might have been transferred to Asia and experienced independent domestication in South Asia (India) and East Asia . As a result, RTR, CBR and JKBR genotypes were domesticated following the domestication of the Japanese (Chinese) wild radish or oil radish accessions.Among the cultivated radish accessions, the degree of genetic differentiation is higher in the ECR accessions, whereas the evidence of gene flow is stronger in ACR accessions. The European and Asian cultivated radish accessions are relatively independent. The BR, ESR and OR accessions are closely related to the EWR accessions, whereas the RTR accessions are closely related to the East Asian radish accessions. EPCR accessions seem to play a bridging role connecting the ECR, SACR and EACR populations. Combining our evidence with previous findings ,14,60, worf138 is distributed within R. raphanistrum and JWR accessions; thus, the Ogura male-sterile cytoplasm originated from a wild species and was introduced into JWR [R. sativus forma raphanistroides, although this hypothesis has not been confirmed [JWR accessions are distributed mainly along the sandy coast and are found at numerous latitudes and longitudes in East Asia ,62. Howeinto JWR . Howeveronfirmed . In our From the perspective of gene flow, JKBR accessions have undergone the strongest degree of gene flow with JWR accessions, indicating that JWR accessions have undergone extensive genetic exchange with cultivated radish accessions in Asian regions, which may have resulted in the close relationship between these populations. Other research has also revealed that JWR plants can fully cross with other cultivars . The JWRRaphanus sativus L. and Raphanus raphanistrum L. [R. raphanistrum ssp. raphanistrum and R. sativus var. radicula for two generations, with R. sativus var. radicula as the recurrent parent through comparative genome analysis [Bidirectional gene flow between wild and cultivated species has become a frequent phenomenon, and plant evolution throughout domestication has contributed to plant diversification . If genestrum L. ,23. Threanalysis . Thus, tR. raphanistrum. From these discoveries, we inferred that EPCR, AWR and JWR accessions might have played a special transitional role in the course of radish evolution. In Europe, a possible evolutionary path might have been from the EWR to the EPCR, to the BR, ESR and ORs. In South Asia, the path might have been from the EWR to the EPCR, or the JWR to the RTR. In East Asia, the evolutionary path might have been from the EPCR to an ancestor of the RTR and JWR/CBR, to the Chinese oil radish/Japanese traditional landraces to the Asian cultivated big radish. Our study provides a comprehensive understanding of radish diversity, distribution, origin and domestication. The results will facilitate in-depth research and utilization of radish germplasm resources.In conclusion, SSR-seq of 939 radish accessions revealed that EWR accessions are the most diverse, indicating that Europe is the radish center of origin. The EPCR, CBR and JKBR genotypes are relatively highly genetically diverse, followed by the OR, RTR and ESR accessions, suggesting that Europe, South Asia and East Asia may have been independent domestication centers of radishes. The combination of phylogenetic analysis, genetic structural analysis and PCoA effectively distinguished the EWR and cultivated the radish populations. Each of the cultivated varieties cluster in a relatively concentrated group, with different distributions. The CBR is far from the EWR and close to the JKBR. The RTR is located between the ECR and EACRs. JWR accessions, as semi-wild radishes, are located between those of the EWR and CBR, but most of them are closer to EACR accessions. JWR accessions exhibit gene flow with the RTR, OR and JKBR accessions. EPCR accessions with high diversity are dispersed extensively throughout both EWR and ECR accessions, and some accessions are closely related to Asian accessions. There is evidence of gene flow between the EPCR and RTR accessions, and between the EPCR and BR/OR accessions. Gene flow analysis also indicated that the AWR might be the progeny of the ESR and


A.m. ligustica which is widely distributed along the entire Italian peninsula, (ii) quantify the introgression of A.m. carnica, Buckfast, and A.m. mellifera bees in the two autochthonous Italian subspecies A.m. ligustica and A.m. sicula, and to (iii) to propose conservation strategies for the two autochthonous subspecies. Whole-genome sequencing was performed by Illumina technology obtaining a total of 4,380,004 single nucleotide polymorphisms (SNPs). Results of the analysis of the patterns of genetic variation allowed us to identify and subgroup bees according to their type. Morphometric analysis of 5800 worker bees was in agreement with genomic data. The investigation revealed the genetic originality of the Sicula, and in A.m. ligustica limited genetic introgression from the other breeds.The purpose of this study was to (i) explore the population structure of the Apis mellifera was established in northern Europe. In Italy, Apis melliferaligustica adapted to the mild climate and to the rich floristic biodiversity. Today, with the spread of Varroa destructor and with the increasing use of pesticides in agriculture, the Ligustica subspecies is increasingly dependent on human action for its survival. In addition, the effects of globalization of bee keeping favored the spread in Italy of other honeybee stocks of A. mellifera, in particular the Buckfast bee. The purpose of this study was to characterize the Italian honeybee’s population by sequencing the whole genome of 124 honeybees. Whole genome sequencing was performed by Illumina technology, obtaining a total coverage of 3720.89X, with a mean sample coverage of 29.77X. A total of 4,380,004 SNP variants, mapping on Amel_HAv3.1 chromosomes, were detected. Results of the analysis of the patterns of genetic variation allowed us to identify and subgroup bees according to their type. The investigation revealed the genetic originality of the Sicula, and in A.m. ligustica limited genetic introgression from the other breeds. Morphometric analysis of 5800 worker bees was in agreement with genomic data. At the end of the last glaciation,  Apis mellifera (A.m.) was established in northern Europe spreading in numerous subspecies [At the end of the last glaciation, bspecies . The lonbspecies ,3.A. mellifera encompasses, in addition to Europe, Western Asia, Africa, and the Middle East. The different subspecies have been divided into 4 main branches: A (African subspecies), C (eastern European subspecies), M (western and northern European subspecies) and O (Middle Eastern subspecies) [The native distribution of species) . The higApis mellifera ligustica, adapted to the temperate climate and to the rich floristic biodiversity of the territory. Thanks to its favorable characteristics, this subspecies has spread since 1800 in many other regions of the world by human mediated action. Today, specimens of A.m. ligustica can be found in North America, in northern and central Europe [In Italy, the l Europe ,6, in Rel Europe , in Kangl Europe , in Maurl Europe  and in Bl Europe . A.m. sicula/siciliana, a variety close to the A.m. intermissa subspecies, endemic in the South side of the Mediterranean Sea [A. m. mellifera along the western Ligurian coast and A.m. carnica on the northeastern side of the Alps [Furthermore, another autochthonous subspecies is present in Italy, in Sicily, the nean Sea . Additiothe Alps . Before Varroa destructor in the 1980s, and with the increasingly dramatic use of pesticides in agriculture, the Italian bee is increasingly dependent on human action for its conservation, both for the control of parasites and for the threat posed by pesticides. In addition, the effects of globalization have favored the spread throughout Italy of other honeybee stocks of A. mellifera, commonly retained to be better performing in terms of productivity and resistance to pathogens, in particular the Buckfast bees. In fact, during the last 30 years, the importation of non-ligustica bees in Italy has significantly increased [With the spread of A.m. ligustica and A.m. mellifera subspecies on the Ligurian coast and along the western Alpine arch [A.m. ligustica and A.m. carnica were identified [A.m. ligustica population and suggests an absence of (specific ecotypes) regional genetic substructure within A.m. ligustica [To differentiate honeybee subspecies several tools are available and widely used in different countries. Some are based on the use of morphometric analyses on the wing venation . Concernine arch  by analyentified . A more igustica . More reigustica ,5,9,20. igustica  as well A.m. carnica, Buckfast, and A.m. mellifera bees in the two autochthonous Italian subspecies A.m. ligustica and A.m. sicula, and to explore the population structure of the A.m. ligustica which is widely distributed along the entire Italian peninsula, and finally to propose conservation strategies for the two autochthonous subspecies. The aim of this study was to characterize the Italian honeybee’s population, using next-generation sequencing (NGS) techniques. In particular, we wanted to quantify the introgression of During summer 2018 and spring 2019, 124 worker bees were sampled in 12 Italian regions . Some of-A.m. ligustica) from Piedmont (2), Lombardy (6), Emilia-Romagna (23), Tuscany (11), Umbria (2), Marche (6), Abruzzo (8) and Puglia (3). We will refer to them as Ligustica.61 Ligustica honeybees (-A. m. sicula). We will refer to them as Sicula.6 Sicilian bees (-A. m. carnica) from Lombardy (5), Piedmont, Trentino and Veneto (1 each). We will refer to them as Carnica.8 Carnica bees (-A.m. mellifera) along the western Riviera coast (Liguria). These samples actually represent a population located at the intersection of the Italian Ligustica and the French A.m. mellifera. Local beekeepers describe it as a typical stabilized hybrid well fitted to the local environment. We will refer to them as Mellifera.4 Mellifera bees (-2 hybrid specimens Carnica by Ligustica (one in Lombardy and one in Trentino). We will refer to them as Carnica x Ligustica.-43 Buckfast bees sampled in Lombardy (25), Veneto (2), Piedmont (15) and in Apulia (1). We will refer to them as Buckfast.According to genomic information the samples consisted of:For each of the 124 colonies, one newly hatched worker bee was sampled for DNA analysis. The bee was individually placed in a 1.5 mL Eppendorf tube containing 95% ethanol and kept at −8 °C until samples were processed for DNA analysis.Fifty worker bees from each of 116 colonies for a total of 5800 bees were enrolled for morphometric analysis. The 50 worker bees for each colony were stored in 50 mL tubes containing 95% ethanol and kept at −8 °C until processing.Morphometric analyses were performed at the CREA – Agriculture and Environment Research Centre laboratory according to Bouga et al. , based oTM Livestock kit following the manufacturer’s recommendations with few modifications. In detail, the lysis protocol D with lysis buffer P without PVP (polyvinylpyrrolidone) was used and DNA was eluted in 30 μL elution buffer AMP.Samples were processed by LCG genomics  from DNA extraction to NGS. Total DNA was extracted from 4 legs of each worker honeybee per colony. DNA isolation was performed with the sbeadexFragmentation of extracted DNA samples was performed using Covaris instrument  to obtain a desired fragment size of 300 bp. Sample purification was done using MiniElute Columns , eluted in 20 μL EB buffer. Illumina library construction was performed with the Ovation Rapid DR Multiplex System 1–96  according to the manual. Libraries were amplified for 10 cycles using MyTaq (Bioline) and standard Illumina primers. Illumina libraries were pooled and size selection was undertaken by gel electrophoresis selecting a range between 300 and 500 bp. Final library purification steps and quality control of DNA libraries was carried out via BioAnalyzer . Illumina Nextera libraries were prepared for all samples and sequenced with a 150 bp paired-end read module (Illumina NextSeq 500/550 V2) following manufacturer recommendations. In total, more than 2760 million quality-trimmed read pairs were produced.Demultiplexing of all libraries as well as clipping of sequencing adapter remnants and Nextera mate pair linkers were performed with the Illumina bcl2fastq 2.17.1.14 software. Sequence quality control was assessed with FastQC . ClippedVariant discovery was performed with Freebayes v1.0.2-16 , with stThe filtered dataset of 44,811 SNPs was used to perform principal component analysis (PCA) with plink, to build a phylogenetic tree, and to investigate population structure with the Admixture software . AdmixtuThe phylogenetic tree was built using a custom script, which builds a virtual sequence for each sample composed of variant positions. The sequences were aligned, and the alignment was input to the Phylip  programsIn total, 124 samples were sequenced with a total coverage of 3720.89X, obtaining a mean sample coverage of 29.77X (minimum coverage 15.55X and maximum coverage 56.27X). Mean number of raw, adapter and quality trimmed, and percentage of high quality trimmed reads are given in A.m. sicula exhibits the highest number of private SNPs (2287), followed by the A.m. mellifera (120) and A.m. ligustica × A.m. carnica (105). This confirms that A.m. mellifera and especially A.m. sicula differ from the other subspecies. This result is in agreement with the subsequent genomic analyses and the fact that they derive from two different evolutionary lineages.The distribution across subspecies of SNPs in the filtered dataset is shown in The principal component analysis (PCA) of the 124 sampled honeybees based on the selected 44,811 SNPs described above was performed to assess the Italian population structure and genetic relationship among the different genetic groups . The firAcarapis woodi. Furthermore, as foreseeable, the two Carnica × Ligustica (crosses of Carnica queens with Ligustica drones) are situated between the two groups of origin.The results show a clear separation among the sampled groups. The two dimensional PCA  displaysA limited number of samples had the breed declared by their beekeepers to be not coherent with their clustering position, such was the case of five colonies declared Ligustica, sampled in Apulia, Lombardy and Piedmont, in apiaries surrounded by Buckfast beekeepers. In reality, breeders were aware of a possible hybrid origin due to uncontrolled mating of the queen with males of Buckfast kept in nearby colonies, and in fact the five samples clustered in the Buckfast group.A.m. sicula and A.m. mellifera samples create two initial clearly separated branches. By contrast, the subspecies of group C are phylogenetically closer, and show a common root. Furthermore, a detailed analysis of the different branches of the tree that correspond to the Buckfast bees indicates that the Buckfast samples are split into four branches. The information provided by beekeepers allowed us to identify a possible explanation: the breeder of origin. Indeed, the samples forming the four branches correspond to four different breeders of origin. The first Buckfast group descended from a Luxemburg breeder. The second and the third groups have Danish and Austrian origins, respectively, whereas the fourth group is from a German breeder.A phylogenetic tree of all the samples based on the filtered dataset of 44,811 SNPs is shown in A.m. carnica samples and others nearer to A.m. ligustica, indicating the existence of different breeding strategies used by the different breeders. Finally, the A.m. ligustica samples are grouped in one branch, at the opposite side of the A.m. sicula samples, and next to the Buckfast. It is interesting to note that some Buckfast individuals are situated closer to the A.m. carnica and Buckfast) to 0.389 (A.m. carnica and A.m. mellifera), with A.m. mellifera showing the highest average value (0.357), followed by A.m. sicula (0.248).Population structure analyzed by Admixture software of the 124 individuals based on 44,811 SNPs, with K from 2 to 5, is shown in A comparison was made between the breed assessed by the genomic approach and the breed declared by the breeder. For the 124 specimens, the asserted subspecies was confirmed in 119 cases with a 96% agreement. Five cases were initially asserted as Ligustica, while the SNP panel assigned them to the Buckfast breed. Beekeepers, in these few cases, were aware of the possible hybrid situation of their bees, which was in fact verified by the genomic analyses.Among 116 samples that underwent morphometric analysis, inclusive of the tergite color test, 96 were in agreement with the SNP panel (82.8%).Excluding two cases where a Carnica and a Mellifera were incorrectly classified as a Ligustica and a Sicilian, respectively, and three Ligustica samples erroneously qualified as Buckfast, the major challenge for morphometric analysis was the detection of the Buckfast breed, which was identified correctly only 25 times out of 38 (65.8%). Indeed, Buckfast are frequently regarded as somehow intermediate, or hybrid forms, between Ligustica and Carnica. In this study, we analyzed the genetic diversity of honeybee populations in Italy, giving particular attention to detect and understand the hybridization with the Buckfast honeybees imported in the last few decades. The overall aim was to provide knowledge to support the implementation of genetic conservation and selection programs. The availability of the honeybee genome allowed us to use next-generation sequencing methods to better define the honeybee subspecies present in Italy. A. mellifera from all over the world, including samples from the A, O, C and M groups. In total, we obtained 4,380,004 SNPs on 124 samples belonging mainly to Ligustica (61) and Buckfast samples (43) and including individuals of other subspecies. Wallberg et al., [One hundred and twenty-four colonies were sampled in different regions of Italy and sequenced with a mean coverage of 29.77X, expanding and focusing in Italy the study conducted by Wallberg et al.  who sampThe Buckfast bees in our study exhibited a high level of variability compared to the Ligustica, with 3,055,491 SNPs, in accordance with the composite nature of the population and its breeding structure, and in agreement with previous studies that identified a higher level of genetic diversity in Buckfast samples compared to the ancestral populations .Despite the limited number of samples sequenced, the Sicula and Mellifera had a higher number of specific SNPs compared to the other subspecies included in the study. In the Sicula this is probably due to the contribution of the A lineage (African) already identified by microsatellite analysis in previous studies . In general, 9.23% of SNPs  were polymorphic in all samples compared to the Amel_Hav3.1 reference sequence .A.m. mellifera, carnica and Buckfast. In accordance with our clustering, the Buckfast were close to the Carnica samples [The Buckfast samples, known to have a highly introgressed genome represented by their Eastern and Western European progenitor populations , cluster samples .Based on our results, the Sicula bees can be considered a pure breed, despite the limited sample size. All the bees clustered closely in the PCA analysis and created a separate branch in the phylogenetic analysis. Furthermore the results of admixture confirmed at K = 5 the lack of recent hybridization events.A.m. ligustica bees did not reveal geographic specific ecotypes based on our analysis, confirming previous results [PCA analysis showed that despite Ligustica and Buckfast bees being present all over the country, their breeding management has not caused high levels of hybridization. The two populations create two distinct clusters on the PCA, which are further confirmed by the phylogenetic tree. The  results . These oLastly, referring to the 2 Ligustica × Carnica hybrid bees, results of Admixture analysis confirmed PCA and phylogenetic results, allowing us to clearly disentangle the samples as Carnica × Ligustica crosses. In general, all results of Admixture confirmed PCA and phylogenetic results. The morphometric analysis for bee subspecies detection was reasonably good especially when the color of tergites was included. Nevertheless, some improvement could be achieved for Buckfast detection with a wider or different reference sample of Buckfast honeybees necessary for statistical comparison. Interestingly, in only five cases was the subspecies declared by the beekeeper an unsuspected and perhaps undesired genetic type: a Buckfast. Since 2018, the Food and Agriculture Organization (FAO) has recognized the domesticated bee as a component of the animal genetic resources for food and agriculture, and the process to include the bee in DAD-IS, the FAO information System on breed-related information, has started . In thisFor the Sicula, all analyses underlined its genetic originality and absence of genetic introgression from the other analyzed breeds. Therefore, it is imperative to guarantee in the future the identity of the Sicula from hybridization risks associated to nomadism and commerce. A.m. ligustica samples did not show on average high levels of introgression from other breeds, however with the current development of bee breeding in Italy the picture could deteriorate. The widespread use by beekeepers of commercial queens purchased from trusted breeders, together with the practice of nomadism, poses the need to improve, for this species, a mating control strategy that is almost absent in the country today. The only way to achieve an efficient control of reproduction is through the identification of isolated areas for the reproduction of these two varieties in pureness. The identification of these areas is not easy given the high density of apiaries distributed throughout the national territory. Furthermore, the use of Italian islands is hampered by difficulties of connection and the short duration of the useful season, which changes quickly in arid summers of drought with a total disappearance of all flora. In addition, instrumental insemination cannot be seen as a solution due to the limited number of queens that this procedure could be applied to. A crucial element in the definition of the mating areas is that their location should be chosen in places not appealing to beekeepers looking for rich floristic pastures. Furthermore, specific municipal ordinances should be defined to limit these areas to the sole presence of apiaries intended for the production of specific drones. From the genetic point of view, the colonies that should produce the drones present in these areas must guarantee the widest genetic variability of the variety they intend to protect and must also represent the best lines of selection of beekeepers who will make them available. The assessment of whether these colonies belong to the required variety can be based on traditional morphometric evaluations, which we have shown here deserve a more precise definition, or on more advanced molecular tools such as the SNPs presented in this paper. With this approach, the control of mating will ensure a pure fertilization of the virgins that will also merge with the commitment of achieving genetic improvement that sometimes makes non-native varieties more competitive than native ones. Then, conservation and selection must flow together under the mandatory conditions to increase the mating control through artificial insemination and/or the creation of well-ordered mating stations. We believe that even a limited increase of mating control could help in creating a wider perception among beekeepers of the meaning of terms like pure breed, hybrid, and biodiversity conservation. A.m sicula, all analyses underlined its genetic originality and absence of genetic introgression from the other analyzed breeds. A.m. ligustica samples did not show on average high levels of introgression from other breeds. However with the current development of bee breeding in Italy the picture could deteriorate. One possibility that could be applied to improve genetic conservation of local breeds in Italy is the creation of isolated mating sites for the reproduction of these two varieties in pureness.In conclusion, the results of the analysis based on whole genome sequencing of 124 Italian honeybees allowed us to identify and subgroup bees according to their type. For


Based on the panel data of 285 prefecture-level cities and above in China from 2005 to 2019, this paper takes the “Broadband China” pilot policy as a quasi-natural experiment and evaluates the impact of Internet development on urban eco-efficiency (symbolized by the “Broadband China” policy) by constructing multi-period difference-in-difference (DID) and spatial DID models. Results show that: the “Broadband China” pilot policy significantly improves the urban eco-efficiency: the eco-efficiency in pilot cities is about 16.8% higher than that in other cities. The results remain consistent after testing for robustness, including using estimation methods, excluding the sample of key cities, changing core explanatory variables, and introducing instrumental variables. Next, the influence of the “Broadband China” pilot policy on eco-efficiency is characterized by significant regional heterogeneity: Internet development significantly improves the eco-efficiency in the central, eastern and northeastern regions that are economically more developed and not resource-dependent. In contrast, this effect is not obvious in the western region that is economically less developed and resource-dependent. Moreover, the influencing mechanism of Internet development on eco-efficiency suggests that the “Broadband China” strategy boosts urban eco-efficiency by increasing the Internet penetration rate, improving technological innovation capacity, and upgrading the industrial structure. In addition, results from the spatial DID models indicate that the “Broadband China” pilot policy improves the eco-efficiency in local cities and significantly enhances that in neighboring cities. Based on this, this paper puts forward some suggestions regarding promoting new network infrastructure construction and differentiating development policies to fit local conditions. Humankind has created more material wealth in the 21st century than in the entire previous history. The same applies to the development of China. With its abundant natural resources and inexpensive labor, China has created a series of growth miracles since its economic reform and opening-up 40 years ago . On the China has entered a “new normal” . Current studies, both at home and abroad, have focused on economic growth effects ,6,7, resThe idea of eco-efficiency was first introduced by German scholars Schaltegger and Sturm . The defWith the rise and advancement of the Internet, scholars at home and abroad have paid increasing attention to the role of the Internet in environmental governance, but relevant literature is limited. However, it is clear that Internet development has a complex effect on the ecological environment. On the one hand, by virtue of the technology itself, the Internet can promote information disclosure and facilitate information sharing, ultimately reducing environmental pollution and serving as a tool to save energy and reduce carbon emission . FurtherPrevious studies have mostly been limited to the impact of Internet development (or information technology) on environmental pollution (or carbon emissions). Few studies have investigated the effect of Internet development on urban eco-efficiency and its mechanism. In addition, when measuring the level of Internet development, previous studies mainly used indicators such as the number of web pages, domains and websites, or built an evaluation index system. These measures are deemed subjective. Some studies also treated innovative cities  or smartCompared with existing research, this paper provides innovative insights in the following aspects: first, it makes up for the inadequacy of research on analyzing the impact of Internet development on urban eco-efficiency from the perspective of new infrastructure. In contrast to previous research on carbon emissions and environmental pollution, this paper takes eco-efficiency as the starting point, which would better reflect the comprehensive influence of the Internet on green, low-carbon, high-quality development. Second, using the exogenous policy of “Broadband China” in its identification strategy, this paper examines the impact of pilot policies on eco-efficiency by constructing multi-period DID methods. This method could be more objective than the existing literature methods . At the same time, this paper further analyzes the spatial spillover effects of the policy by adopting spatial DID models. Third, using technological innovation and industrial structure upgrading as mediators and constructing a mediating effect model, this paper investigates the influencing mechanism of the “Broadband China” pilot policy on eco-efficiency.As the Industrial Revolution advances, computer and information technology have developed rapidly. Science and technology have gradually become essential indicators to assess a country’s economic progress. In particular, network infrastructure, the basis for science and technology, has gradually attracted wide attention. However, China’s netizen population and the Internet penetration rate still lagged behind developed countries such as European countries and the United States. To effectively address this issue, China introduced the “Broadband China” strategy at the National Industry and Information Work Conference 2011, aiming to boost Internet speed and cut prices in a phased, effective approach. A total of 120 cities was selected as “Broadband China” pilot cities (clusters) in three patches in 2014, 2015 and 2016. After being selected as a pilot city (cluster), the city strives to boost broadband network speed, expand network coverage and increase the scale of broadband users with a goal to achieve full coverage for broadband access in urban and rural areas by 2020. It is foreseeable that the “Broadband China” pilot policy would improve Internet development in cities directly and facilitate local information transmission and knowledge diffusion. Meanwhile, the selection of “Broadband China” pilot cities is not logically influenced by the conditions of the local ecological environment. This would address reverse causality issues in these policies, it also provides a foundation for this paper to analyze the political effects of the Internet.Compared with traditional infrastructure, the Internet, as an essential foundation for technological development and innovation infrastructure, plays a significant role in increasing resource efficiency, reducing energy consumption and improving pollution control measures . From a Based on the above analysis, this paper proposes:Hypothesis 1 (H1).The “Broadband China” pilot policy enhances urban eco-efficiency.“Broadband China” pilot policy affects eco-efficiency by increasing Internet penetration rateThe “Broadband China” pilot policy puts forward several specific goals in the field of the Internet. For example, China strives to achieve fiber-to-the-home broadband networks in cities and fiber-to-the-village coverage in rural areas by 2015, thus enhancing broadband access capability in cities and rural areas. The selected cities should be in a leading position regarding broadband access capability and broadband penetration rate. It can be expected that areas where the “Broadband China” strategy has been implemented would see significant improvements in the network infrastructure. These goals would force governments to invest more in infrastructure in a short time, which would directly drive the Internet penetration rate up. The rise of the Internet, along with its rising penetration, continues to increase the eco-efficiency of cities through many ways, such as technology, economic structure, production methods, environmental governance and resource allocation.2.“Broadband China” pilot policy affects eco-efficiency by promoting industrial structure upgradingThe boosting effect of the “Broadband China” pilot policy on industrial structure upgrading is mainly reflected in two aspects: promoting new industries and new forms of business and transforming traditional industries. On the one hand, the “Broadband China” pilot policy accelerates industrial structure upgrading. The “Broadband China” pilot policy promotes the construction of network infrastructure that primarily supports the Internet. First, with sound network infrastructure in place, new economic growth models such as new forms of business, new types and new models have emerged. This would assist the progress of emerging industries such as information technology, cloud computing, mobile Internet and the Internet of Things, drive industrial upgrading and contribute to the optimization of industrial structure. Next, technological innovation helps to upgrade traditional production equipment. Hence, traditional industries would be immersed with new technology and knowledge, which would accelerate their integration with information technology, forcing them to transform into high-tech, high-efficiency and low-polluting industries and letting go of businesses and modules that are harmful to the environment. In addition, the development of network infrastructure has also enabled and triggered the evolution of sharing economy, which offers exact matching between supply and demand for traditional industries , driving3.“Broadband China” pilot policy affects eco-efficiency by improving technological innovation capacityThe “Broadband China” pilot policy is beneficial to improve urban technological innovation capacity. This is mainly reflected in the following two aspects: first, the network infrastructure has the ability to disseminate information across time and space, and the Internet is capable of accelerating cross-regional integration of innovative elements such as funds, talents and technology. This would lead to knowledge spillover effects and encourage the diffusion of the technological innovation systems characterized by manufacturing, learning, research and using. It also stimulates technological progress in manufacturing, energy-saving and environmental protection for enterprises. Second, the application of Internet information technology covers all aspects of business productions and operations. As network infrastructure improves, enterprises have gradually strengthened their broadband networking capability and their network-based process reengineering and business innovation capabilities. This would also help enterprises enhance the technological innovation capabilities of their research and development (R&D) and production departments . On the Hypothesis 2 (H2).The “Broadband China” pilot policy enhances urban eco-efficiency by increasing the Internet penetration rate in cities, upgrading industrial structure and improving technological innovation capacity.Therefore, this paper proposes:While the “Broadband China” pilot policy improves the Internet in local areas, it also radiates outwards, creating an “urban integration effect.” New technology has reduced time and space constraints through the efficient transmission of data and accelerated inter-regional information sharing, knowledge accumulation and technology diffusion. It also enhances the breadth and depth of linkages in inter-regional economic activities and produces positive spillover effects . Yilmaz Hypothesis 3 (H3).“Broadband China” pilot policy enhances the urban eco-efficiency in neighboring cities through spatial spillover effects.Thus, this paper proposes:A stands for affluence, and According to the classic IPAT model that measures human impact on the environment proposed by Holdren and Ehrlich , factoriand Rosa  have extConsidering that eco-efficiency aims to find a balance between environmental protection and economic development, this paper reformulates Equation (3) and uses d Levkov , with ciIn this formula, The predicted variable2 emissions and industrial smoke (dust) emissions as undesirable outputs. The software used is MaxDEA 7.0 Pro. As for the dataset, this paper analyzes 285 prefecture-level cities in China, except six cities , Bijie, Tongren and Lhasa) because these cities have relatively more missing data.Andersen and Petersen  have int2.The core explanatory variableThe paper treats the “Broadband China” pilot policy as a quasi-natural experiment and uses it to measure Internet development. It takes on a value of 1 for pilot cities and 0 for non-pilot cities and is set to 1 in the year of implementation and each subsequent year and 0 before the implementation. The paper obtains the list of “Broadband China” pilot cities from the website of the Ministry of Industry and Information Technology of China. The pilot list includes certain autonomous regions , certain districts in municipalities , certain cities at the county-level  and cities with serious data deficiencies (Linzhi City in Tibet Autonomous Region). After dropping these areas, the final research sample contains 108 cities in the experimental group and 177 cities in the control group.3.The controlled variable2 emissions per unit of GDP; industrial agglomeration (LQ), expressed as the location entropy of the secondary industry, the formula is specified as According to existing literature, given the heterogeneity among cities and the prevention of omitted variables, the paper also controls for other variables that might influence eco-efficiency. Other variables include economic development level (GDP), measured by the logarithm of the gross domestic product ; population density (PEO), defined as the logarithm of the total population per square kilometer; energy intensity (EI), measured as the industrial SOThe sample includes data of 285 cities at the prefecture-level and above in mainland China, except Hong Kong, Macao and Taiwan, from 2005 to 2019, given the availability of data. The relevant data are taken from various sources, such as the China City Statistical Yearbook, the Provincial Statistical Yearbooks and the China Statistical Yearbook for Regional Economy. In addition, there is a small portion of data missing and has been supplemented by using the mean substitution method and multiple imputation method. To smooth the data, this paper takes the logarithm of some of the explanatory variables.The final sample contains data from 285 prefecture-level cities in China from 2005 to 2019. k means that the city has become a pilot city for The premise of using the DID method to conduct policy evaluation is that the parallel trend assumption is met; that is, before the implementation of the pilot policy, the urban eco-efficiency should remain steady in both the experimental and the control group. Therefore, the paper employs the method proposed by ,75,76. IThe paper employs a two-way fixed effects model to evaluate the impact of Internet development, which is driven by the “Broadband China” pilot policy, on urban eco-efficiency. 2 emissions per unit of GDP, is significantly negative at 1%, with a coefficient of −0.67. SO2 is a typical air pollutant and can reflect the effect of inter-regional pollution transmission [2 are considered of all harms but no benefit. Government spending also has a negative impact on eco-efficiency, with an estimated value of −0.62 and is significant at the 5%. This indicates that an increased proportion of fiscal expenditures is detrimental to improving eco-efficiency.With regard to the controlled variables, results show that the sample tends to give more stable estimation results with more controlled variables added, and the impact of GDP on urban eco-efficiency remains significantly positive. Generally speaking, people are inclined to have higher requirements for environmental quality as the economy grows. Thus more funds will be spent on environmental governance. Urban eco-efficiency and economic growth are complementary and mutually supportive. Energy intensity, measured as the industrial SOsmission . IncreasMoreover, the impacts of population density, industrial agglomeration and FID on the eco-efficiency are all positive, but none passes the significance test. Industrial agglomeration facilitates infrastructure sharing, and Internet development promotes the digital transformation of business, both of which help reduce carbon emissions, achieve carbon neutrality and improve the urban eco-efficiency. International trade has long been believed to affect pollution. The effects of trade on the environment have long been interpreted as follows: in the past, China was considered the world’s “pollution refuge” or “pollution haven” due to its policy of opening up to the outside world. However, as reform and opening up deepen, this situation has changed: China used to be the primary destination for the developed countries’ high-polluting, high-energy-consuming manufacturing sectors, whereas now, more and more high-value-added service sectors are making their ways to China. While China remains an integral part of the global value chain, the phenomenon of “pollution refuge” has eased.The above results indicate that the “Broadband China” pilot policy contributes significantly to the urban eco-efficiency. To further verify the reliability and stability of these regression results, this paper conducts a series of robustness tests, including using different estimation methods, excluding samples of key cities and replacing core explanatory variables. By re-estimating the results with additional tests, it is suggested that the regression results of the multi-period DID models are robust.Using different estimation methodsIn addition to using two-way fixed effects regression methods for estimating, this paper also uses reg, areg and reghdfe ,79,80, t2.Excluding samples of key citiesSample data used in the paper is panel data of cities at the prefecture-level; however, there are four municipalities directly under the administration of the central government, namely Beijing, Tianjin, Shanghai and Chongqing. With large sizes and huge populations, these four cities play a leading role in China’s economic growth and are the regional economic and social development growth poles. Given the significant disparities in supporting policies and economic growth between these four cities and others, data of these four cities can be considered more of provincial-level. To ensure the robustness of the regression results, this paper, therefore, excludes the data of these four municipalities from the full sample and applies the two-way fixed effects model to re-examine the impact of the “Broadband China” pilot policy on the eco-efficiency. The results are shown in columns 1–2 of 3.Replacing a core explanatory variableThe Internet penetration rate is more representative in measuring the level of Internet development than traditional measures such as the number of webpages, domain names and websites. Based on the approach applied by Ye Chusheng et al. (2018) , this paEndogeneity may exist between pilot policies and urban eco-efficiency. On the one hand, Internet development may improve the urban eco-efficiency by enhancing network penetration, upgrading industrial structure and improving technological innovation capability. On the other hand, cities with higher levels of eco-efficiency tend to have strong overall strength. With a better endowment of resources and a more robust economy, these cities attract the continuous inflows of external resources and become more capable of building network infrastructure, which would accelerate Internet development. Meanwhile, there are many factors that influence urban eco-efficiency. Hence, the controlled variables selected in this paper cannot avoid the omitted variable problem. Scientifically appropriate instrumental variables are among the most common methods to address the endogenous problem caused by reverse causality in regressions. A good instrumental variable usually has two important characteristics: first, it is highly correlated with the endogenous variable (which is the Internet development); second, this variable does not directly affect the predicted variable (which is the eco-efficiency); that is, the choice of instrumental variable needs to meet two criteria: relevance and exogeneity.Given these considerations, this paper studies existing literature and adopts the idea of Kolko (2012)  by usingHeterogeneity of urban locationsFrom the perspective of urban locations, China’s economy presents strong spatial differences. There is a noticeable development gap among the eastern, central, western and northeastern regions. The construction of network infrastructure may have a different impact on eco-efficiency due to the city’s geographic location. Therefore, this paper further divides the 285 sample cities into four major regions  namely Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong and Hainan; the central region includes 6 provinces of Shanxi, Anhui, Jiangxi, Henan, Hubei and Hunan; the western region includes 12 provinces , namely Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, Guangxi, Chongqing and Inner Mongolia; the northeast region mainly includes 3 provinces of Liaoning, Jilin and Heilongjiang.) eastern, central, western and northeastern regions—to analyze the impact of Internet development on eco-efficiency. As a result, there are 87 cities in the eastern region, 80 in the central region, 84 in the western region and 34 in the northeastern region. Regression analysis is performed for each region, with results shown in The results indicate that the coefficients of variables representing the “Broadband China” pilot policy are significant at 5%, suggesting that this pilot policy promotes eco-efficiency in the eastern, central and northeast regions. After controlling for other factors, the coefficients for these three regions are 0.260, 0.283, and 0.287. The coefficient in the western region is insignificant, standing at −0.086, suggesting that the “Broadband China” pilot policy has a negative but insignificant impact on the eco-efficiency in the western region. Based on the above results, it can be concluded that Internet development, driven by the “Broadband China” pilot policy, improves the ecological environment nationwide but has a greater impact in central and eastern regions. The reason could be that the central and eastern regions are endowed with natural resources and geographical advantages and have been equipped with a higher level of network infrastructure, whereas the environment in the western region is relatively more unpleasant. Its undulating terrain means a long infrastructure construction period. As a result, network infrastructure development is lagging and tends to be harmful to the ecological environment.2.Heterogeneity of city scaleThe heterogeneity of city scale means that there are big differences between larger cities and smaller cities in industrial structure, energy consumption and technological development, causing variations in the impact of the “Broadband China” pilot policy on the ecological environment. Thus, this paper conducts additional regression analysis by dividing the sample into economically developed and underdeveloped cities by whether the per capita GDP of each city in 2018 is higher than the national per capita GDP of the same year. The results are shown in 3.Heterogeneity of resource dependenceResource-based cities are the types of cities that exploit and process natural resources, such as minerals and forests in the region. The production and development of cities are closely related to resource exploitation and processing, which greatly influences eco-efficiency. This paper refers to the Sustainable Development Plan for National Resource-Based Cities (2013–2020) issued by the State Council and divides samples into two types: resource-based cities and non-resource-based cities. The number of cities in each type is 112 and 173. Regression results are shown in To verify whether Internet development can promote eco-efficiency through other mechanisms, this paper further tests the influencing mechanism of the two by constructing mediation models. The steps to test the mediating effect are as follows:The first step: take eco-efficiency as the predicted variable and perform regression with the “Broadband China” pilot policy as the explanatory variable.The second step: take mediators such as Internet penetration rate, industrial structure upgrading and technological innovation as the predicted variables and perform regression with the “Broadband China” pilot policy as the explanatory variable.The third step: incorporate both the “Broadband China” pilot policy and mediators into the regression model and observe the impact of these two on total factor productivity growth.In the regression results of the baseline model  implies that the “Broadband China” pilot city program should have a strong demonstration effect and leading role in similar regions across the country. Based on the previous theoretical analysis, the construction of information infrastructure has strong scale effects and network effects, generating a significant spatial spillover effect on “local-neighboring” economic activities. This would cause the causal effect identified by the traditional DID model to become invalid , and thuIn choosing the spatial matrix, this paper mainly uses two spatial weight matrices to examine the spatial spillover effects of the “Broadband China” pilot policy on the eco-efficiency of neighboring and economically similar regions. The first matrix used is the geographical distance spatial weight matrix. This paper uses g (2005) , this paBefore employing the spatial DID model, this paper examines the spatial correlation of urban eco-efficiency. All the values of Moran’s I test for the sample cities are positive and significant at 1%, suggesting a significant spatial correlation between the eco-efficiencies of cities. Therefore, it is reasonable to consider spatial correlation based on the baseline model. The results of the Hausman test show that the fixed-effects model is more efficient than the random-effects model. Hence, when conducting spatial econometric analysis, this paper uses two-way fixed effects models.To promote the comprehensive green transformation of social and economic development, China pledges to implement the new development philosophy and achieve “carbon peak” and “carbon neutral” with the help of Internet technology. Based on the panel data of 285 prefecture-level cities in China from 2005 to 2019, this paper evaluates the impact of Internet development on urban eco-efficiency (symbolized by the “Broadband China” policy) and its underlying mechanisms by constructing multi-period and spatial DID models via a quasi-natural experiment of the “broadband China” pilot policy. The conclusions are as follows: First, the results of the fixed-effects baseline model show that the “Broadband China” pilot policy significantly improves urban eco-efficiency. The results remain consistent after testing for robustness, including changing estimation methods, excluding the sample of key cities, replacing core explanatory variables and introducing instrumental variables. Next, the impact of the “broadband China” pilot policy on eco-efficiency has significant regional heterogeneity. Internet development significantly improves the eco-efficiency in the central, eastern and northeastern regions that are economically more developed and not resource-dependent. In contrast, the influence is not obvious in the western region that is economically less developed and resource-dependent. Furthermore, the analysis of the influencing mechanism of Internet development on eco-efficiency suggests that the “broadband China” strategy boosts urban eco-efficiency by increasing the urban Internet penetration rate, improving technological innovation capacity and upgrading the industrial structure. Finally, the spatial DID model results indicate that the “broadband China” pilot policy has a positive spillover effect on urban eco-efficiency and can improve the eco-efficiency in neighboring regions. Based on these findings, this paper proposes the following recommendations:The new infrastructure initiative (symbolized by network infrastructure construction) plays an essential role in improving urban eco-efficiency. This provides a theoretical foundation and empirical evidence for a positive effect of Internet technology on high-quality and green economic development in the new era. Therefore, it is necessary to further implement the “Broadband China” strategy and advance the construction of digital facilities, strengthening the positive spillover effects of network infrastructure and unleashing the dividends of the digital economy. This would facilitate the internalization of new information technology, injecting new high-quality development momentum into cities and unleashing the benefits of boosting eco-efficiency and promoting green growth.The results of heterogeneity analysis could serve as a useful reference for the direction of promoting network development. Regions should design their infrastructure policies according to their local conditions, resource endowments and economic development levels, give full play to key cities’ radiating and leading role, and improve flexibility and tolerance in implementing the “Broadband China” strategy. For underdeveloped and resource-dependent cities in the western region, it is crucial to accelerate the construction of local infrastructure, increase the support for technological innovation and form comparative advantages by utilizing their resources and introducing talents and technology. This would help these cities exploit the latecomer advantages and enable them to catch up with the developed cities, thanks to the increased eco-efficiency driven by Internet development.Explore multiple ways for the “Broadband China” strategy to promote eco-efficiency, and thus maximize the impact of the “Broadband China” pilot policy. The first is to increase government spending on science and technology, use network infrastructure as a starting point and promote the co-construction and sharing of innovation platforms, thus enhancing the innovation capabilities of cities. The second is to strengthen the transformation and upgrading of the industrial structure by making full use of the Internet technology, further enhancing the driving effect of the Internet on industrial structure upgrading by transforming traditional sectors and promoting the emergence of large, new sectors. This would promote the coordinated development of ecology and economy and achieve “economy ecologization” and “ecological economicalization”, thus enhancing urban eco-efficiency.There is still room for improvement in existing research. This paper evaluates the impact of Internet development on urban eco-efficiency by building a quasi-natural experiment using the “Broadband China” pilot policy. Although this paper’s conclusions are supported by rigorous analysis methods, more in-depth discussion is needed to examine whether the selection of policies can cover all aspects of Internet development and whether there are more appropriate policies. In addition, as countries, regions and city clusters are experiencing different levels of development, further research is also needed to determine whether this paper’s findings can be generalized. With the world entering the era of a digital economy where the growth of the digital economy is closely connected to the Internet, building high-tech smart cities has become one crucial path to solve urban problems such as resource scarcity and environmental pollution. More in-depth research can be carried out to determine the impact of the digital economy and smart cities on eco-efficiency.


Clupea harengus) and the Northeast Arctic (NEA) cod (Gadus morhua) are examples of strong stock reduction and decline of the associated fisheries due to overfishing followed by a recovery. Cod and herring are both part of the Barents Sea ecosystem, which has experienced major warming events in the early (1920–1940) and late 20th century. While the collapse or near collapse of these stocks seems to be linked to an instability created by overfishing and climate, the difference of population dynamics before and after is not fully understood. In particular, it is unclear how the changes in population dynamics before and after the collapses are associated with biotic interactions. The combination of the availability of unique long‐term time series for herring and cod makes it a well‐suited study system to investigate the effects of collapse. We examine how species interactions may differently affect the herring and cod population dynamic before and after a collapse. Particularly we explore, using a GAM modeling approach, how herring could affect cod and vice versa. We found that the effect of cod biomass on herring that was generally positive  but the effect became negative after the collapse . Likewise a change occurred for the cod, the juvenile herring biomass that had no effect before the collapse had a negative effect after. Our results indicate that the population collapses may alter the inter‐specific interactions and response to abiotic environmental changes. While the stocks are at similar abundance levels before and after the collapses, the system is potentially different in its functioning and may require different management action.Both the Norwegian Spring Spawning herring ( Stock collapses not only change abundance and the relationship with environment conditions but also the long‐term interaction with other species. We illustrated this with two iconic stocks the Norwegian Spring Spawning herring and the Northeast Arctic cod. Due to overexploitation, the NSS herring stock collapsed in the 1960s from a biomass of more than 14 million tonnes in 1956 to less than 0.1 million tonnes in 1972  is a prime example for the overexploitation of marine fish populations  herring  and late (1975‐ongoing) 20th century  to demographic variables such as fishing mortality and mean age of the spawning stock, as well as to environmental variables  and potential interacting species  biomass; Table To understand how stock collapse may affect the population dynamic, we modeled the change of the log‐transformed dominant eigenvalue 2.1The data are model‐based estimates derived from a form of Virtual Population Analysis (VPAs). These analyses are based on data from commercial catches, calibrated with fisheries' independent survey data and combined with estimates of natural mortality. Table Gadus morhua) were obtained from the long‐term VPA performed by Hylen (Data for NEA cod (by Hylen  over theby Hylen .Clupea harengus) were obtained from the VPA performed by Toresen and Østvedt .Since annual values on the proportion of maturity at age was only available from 1950 onward; we extended the ICES matrix of maturity at age for the period 1907–1949 by replicating the year 1950  for each time series separately ). We then located the year when ln(λ1) passed the 50% quantile at the end of the time series for the data covering the period before the collapse and at the beginning of the time series for the data covering the period after the collapse. Using this method, the collapse period for the herring was 1965–1973 and for the cod 1974–1980. We analyzed the data outside the collapse periods: in 1921–1964 and 1974–2011 for the herring and 1921–1973 and 1981–2013 for the cod.To define the period of collapse, we calculated the 50% quantile of ln(2.2tA (matrix A at time t). By definition, the population size in the following year (tn+1) is the product of the matrix tA and the current year's population size (tn), where the “n” are vectors representing the number of individuals for each age class. For each year t, the transition matrix tA is defined as follows:aR,t the contribution of each age‐class a to the recruitment at year t and with aS−(a−1),t the survival of age a − 1 at year t to age a at year t + 1, computed as the ratio of the abundance of age a at year t and age a − 1 at year t − 1. The age index a varies between 1 and amax, the older age‐class in the population (respectively amax = 12 years and amax = 14 years for cod and herring). Note that for both stocks, the last age classes (15+ for herring and 13+ for cod) were ignored in order not to get an unrealistic survival aSmax–(amax−1) > 1. S been directly calculated through abundance estimates, aS−(a−1) can be approximated to exp(−(aM−(a−1) + aF−(a−1))) with M the natural mortality and F the fishing mortality for age a.To allow for a direct comparison between the two studied stocks while integrating the maximum information, that is, spawning biomass, recruitment, abundance, and maturity, from the complex age‐structured dynamics of NEA cod and NSS herring, we summarized the vital rates  in an annual transition matrix aR,t the contribution of each age‐class a to the recruitment at year t was defined as follows:t is the recruitment at year t, MATa,t−1 the proportion of mature at age a and time t − 1 and aN,t−1 the abundance for age a at time t − 1. Note that our model does not take into account the difference of egg productivity between age classes but only the maturity in percent.tA independently for two sets of data for NEA cod (1913–1999 and 1946–2016) and the two sets for NSS herring (1907–1998 and 1950–2015).We built annual transition matrices λ1). We interpret the dominant eigenvalue as a proxy for population growth for the given year. This interpretation is supported by a positive correlation between the eigenvalue and per capita growth rate  fluctuating around 0). Since no data on recruitment at age 1 was available for NEA cod, we used as a recruitment proxy the age 3 data with a lag of 3 years and we set the survival between the first and second year and between the second and third year  to 1. It has previously been shown that the choice of this value does not substantially affect the estimate of λ1  reported by ICES ,As species potentially interacting with the cod, we used the immature herring biomass (Bcod) as potential competitor/predator , that was shown to affect population dynamic for both stocks  is given for age groups 5−10 (F5–10) and age groups 5−12 (F5−12) for cod and herring, respectively ). The Kola meridian transect intersecting the Murman Current in the south‐central Barents Sea, covers the inflow of Atlantic and Coastal water masses from the Norwegian Sea to the south‐eastern Barents Sea. This time series of temperature is representative of the Atlantic water masses in the south‐central Barents Sea  for the Barents Sea from 1921 until 2015 was obtained from the Kola meridian transect  collected by the Polar branch of the Russian Federal Institute of Fisheries and Oceanography  calculated for the months of December, January, February, and March for the period 1921–2015 . We wanted a parsimonious model which described the response well but was as simple as possible. We used thin plate regression splines as smoothers.Population structure, fishing, climate, and predation/competition effects on population change were investigated for both stocks for the two periods delimited by a population collapse  at time t for the herring models or of the juvenile herring (Bherrt) at time t for the cod models, and tε an error term. The spline function is given as is(·).All models started with a similar formulation:2.5We entered all candidate explanatory variables in the GAM model and conducted model selection using shrinkage. In the shrinkage approach to model selection, the smoother is modified so it allows insignificant variables to be shrunk to zero  as part of the smoothness selection Wood, . Thus, aacf in R). For the other three models, we did not detect any significant autocorrelation. To account for the autocorrelation in the residuals of the cod model before the collapse, we used an AR(1) model ).For one model (model for cod before the collapse), we found a temporal autocorrelation in the residuals of one‐year lag   and the NEA cod (Gadus morhua) are shown in the Figure Time series of the dominant eigenvalue λ1) are displayed on the Figure λ1) for the NSS herring and the NEA cod before the collapse give us an insight of the change in interaction with other species and effects of environment and harvesting  on fishing mortality (F) and the validity of our modeling approach we have run the four GAM models without including s2(tF). These four new models displayed similar effects (direction and strength) of the explanatory variables MAt, STt, wNAOt, and Bt than the full models  was independent of the effect of F.The best stock‐specific GAM models of the dominant eigenvalue ln shows a positive effect (p < .001), mean age of the spawning stock (MA) a positive but not significant effect (p = .08), and Kola sea temperature (ST) a positive but not significant effect (p = .08) on the herring ln(λ1). The positive effect of Bcod may indicate a covariation.Before the collapse , MA a positive but not significant (p = .11), fishing mortality (F) a negative effect (p < .01) and ST a positive but not significant (p = .14) on the herring ln(λ1).After the collapse  on the cod ln(λ1).Before the collapse  shows a negative effect (p < .01), MA a positive then a negative effect after MA = 6.7 years (p < .01), F a not significant effect (p = .08), and ST a not significant positive effect (p = .13) on the cod ln(λ1).After the collapse  before the collapse is the cod SSB (Bcod) replaced after the collapse by the fishing mortality (F). For the cod models, the variable explaining the most variation before the collapse is the fishing mortality (F) replaced after the collapse by the mean age of the spawning stock (MA).The relative importance of regressors for each model in percentage is given in Figure 4Climate forcing  (a proxy of the changes occurring in the population between the two years), before and after a population collapse, in NSS herring (Clupea harengus) and NEA cod (Gadus morhua), we were able to explore the effect of such collapse on the population dynamics. There is no long time continuous and consistent time series survey data readily available that could be used to compare the dynamics before or after the collapse for these stocks (particularly before the collapses). Our study then relies on outputs from four virtual population analysis (VPA) models  before the collapse indicating a covariation. The absence of a negative effect of cod on herring before the collapse may also be explained by the very high abundance of herring relatively to the cod. However, note that the covariation was reduced at high cod abundance  indicating that they are reasonably good for the type of analyze conducted Figure  that maye Figure . Since te Figure .Atlantic cod is considered a major predator of herring Hamre, , particuOn the other hand, the herring is also a major predator of capelin larvae in the Barents Sea ; data curation (lead); formal analysis (lead); funding acquisition ; investigation (lead); methodology (lead); project administration ; validation (lead); visualization (lead); writing–original draft (lead). Leana Aarvold: Formal analysis (supporting); investigation (supporting); methodology (supporting); validation (supporting); visualization (supporting); writing–original draft (supporting). Øystein Langangen: Conceptualization (supporting); formal analysis (supporting); funding acquisition ; investigation (supporting); methodology (supporting); project administration ; writing–original draft (supporting).Supplementary MaterialClick here for additional data file.