Phytophthora sojae, and a large number of Pythium species, is an economically important disease across the Midwest United States that negatively impacts soybean yields. Research on biocontrol strategies for crop pathogens has focused on compounds produced by microbes from soil, however, recent studies suggest that aquatic bacteria express distinct compounds that efficiently inhibit a wide range of pathogens. Based on these observations, we hypothesized that freshwater strains of pseudomonads might be producing novel antagonistic compounds that inhibit the growth of oomycetes. To test this prediction, we utilized a collection of 330 Pseudomonas strains isolated from soil and freshwater habitats, and determined their activity against a panel of five oomycetes: Phytophthora sojae, Pythium heterothalicum, Pythium irregulare, Pythium sylvaticum, and Pythium ultimum, all of which are pathogenic on soybeans. Among the bacterial strains, 118 exhibited antagonistic activity against at least one oomycete species, and 16 strains were inhibitory to all pathogens. Antagonistic activity toward oomycetes was significantly more common for aquatic isolates than for soil isolates. One water-derived strain, 06C 126, was predicted to express a siderophore and exhibited diverse antagonistic profiles when tested on nutrient rich and iron depleted media suggesting that more than one compound was produced that effectively inhibited oomycetes. These results support the concept that aquatic strains are an efficient source of compounds that inhibit pathogens. We outline a strategy to identify other strains that express unique compounds that may be useful biocontrol agents.Seedling root rot of soybeans caused by the host-specific pathogen  Pythium spp., three Phytophthora spp., three Phytopythium spp., and one Aphanomyces sp. In the 2nd year of the survey, 54 Pythium spp., seven Phytophthora spp., six Phytopythium spp., and one Phytigeton sp. were recovered using a modified medium to enhance the recovery of slower growing Phytophthora strains. The most common isolates recovered from diseased plants were Pythium sylvaticum (16%) and Pythium oopapillum (13%) in 2011, and Pythium sylvaticum (14%) and Pythium heterothallicum (12%) in 2012. Some of these Pythium species such as P. irregulare, P. sylvaticum, P. torulosum, and P. macrosporum were cold adapted and most aggressive at soil temperatures below 20°C. Other species such as P. ultimum infect different hosts at temperatures ranging from 12 to 25°C  and on NB solid media (BD Difco) with 1.5% agar (BD Difco) and incubated at 23°C. P. sojae and Pythium species were cultured on V8 agar media  and incubated at 23°C. P. sojae strain P6497  in February 2012 and from soil in Bowling Green, OH on April 5th, 2012 . Water sin P6497  was obtain P6497  and PythgyrB gene have been previously described . Pythium strains were cultured and maintained on V8 plates, as described above, and 3 mm plugs containing isolates were transferred to GCA plates. One microliter aliquots from overnight cultures of wildtype 0C6 126 or the qbs mutant were transferred between the plugs. Inhibition of hyphal growth around the bacterial colony was assessed after 3 days at 23°C.Antagonistic assays with SAMN05727803 . Most groupings consisted of pseudomonads from soil or aquatic habitats. Isolates from phylogenetic groups 2, 3, 10, and 13 were soil-derived while phylogenetic groups 1, 4, 6, 7, and 11 consisted of isolates almost exclusively from water. Interestingly, Phylogenetic groups 5, 8, 9, and 12, contained isolates from both soil and aquatic environments. Phylogenetic diversity, based on the gyrB gene, was sufficient to distinguish most isolates.Water samples were collected from the photic zone at a depth of one meter and a temperature of 1.5°C; soil samples were obtained from topsoil at a depth of one inch and a temperature of 17.0°C . We deteequences . All strFigures 2A,B). Microscopic examination of the clearing zone revealed that hyphae were largely excluded, and that some of the isolates were capable of swarming. Results showed that 118 out of 330 environmental isolates (36%) effectively inhibited at least one pathogen . Antagonistic isolates showed consistent levels of inhibition against oomycetes in replicate assays.All 330 strains were tested through interspecific competition against the five different plant pathogens resulting in 1,650 individual interactions. To assay for bacterial inhibition, of hyphal growth, environmental isolates were positioned adjacent to rapidly growing hyphae of oomycetes on V8 agar plates. After 2 days when the plates were scored, all of the environmental isolates formed robust colonies on this media which is typically used to maintain oomycete cultures . A zone Table 1). Out of 118 antagonistic strains, 88 and 30 were water and soil-derived, respectively. Sixty-four strains exhibited specific interactions and inhibited only one pathogen, while 54 were more general in their activity and antagonized more than one oomycete . For instance, strains from phylogenetic groups 1, 4, and 9 all exhibit specific activity against one pathogen, while isolates in other phylogenetic groups exhibit both specific and a broader range of activity. In all, 253 antagonistic events were observed, and activity from water-derived strains was significant, 205 out of the 253 , compared to soil isolates. Inhibitory events were observed most frequently in phylogenetic groups 5 and 7 which is composed of more isolates compared to other phylogenetic groups and are mostly water-derived. Although population 13 had the most number of strains and were almost entirely from soil, only 15 antagonistic events were observed; 13 out of 15 occurred by soil-derived isolates (Table 1). Of particular interest among the 330 pseudomonads were 16 genetically diverse isolates that were able to inhibit all pathogens  meaning that the Phytophthora and four Pythium isolates were susceptible to the produced antagonistic compounds. All 16 strains were isolated from Lake Erie and 14 grouped within phylogenetic groups 5 and 7. Overall, P. sojae was the most susceptible and was inhibited by 103 bacterial strains (Table 1). All Pythium species were inhibited by less than half the antagonistic events compared to P. sojae; P. sylvaticum was the least susceptible, and was antagonized by only 31 strains. Taken together, significantly more pseudomonads from a freshwater habitat inhibit oomycetes compared to soil isolates. Moreover, their phylogenetic diversity and dissimilar antagonistic profiles suggest the production of unique compounds. These results support the concept that water-derived bacteria produce effective compounds that inhibit pathogens.Antagonistic activity was observed from both water and soil strains and among all phylogenetic groups except 2 and 3 which consisted almost entirely of strains from soil . This locus is predicted to encode a siderophore in P. fluorescens and was found to inhibit the growth of Pythium debaryanum . Under iron limiting conditions, the mutant lost the ability to inhibit Pythium spp. Conversely, antagonism was observed against only P. sojae and P. sylvaticum on nutrient rich medium  suggesting dissimilar inhibitory compounds are produced under different nutritional conditions . P sojae did not grow well enough on GCA media to enable testing for inhibition under iron limiting conditions.Transposon mutagenesis was first implemented in one of these environmental isolates to identify the molecular basis of antagonism against pathogenic isolates taken from the lungs of cystic fibrosis patients . Sequencbaryanum . Becauseqbs locus, we utilized the JGI Atlas of Biosynthetic Gene Cluster (ABC) (qbs locus within a BGC (ID #161755954) comprised of 20 open reading frames (ORFs), one of which the transposon disrupted . To determine if this gene cluster is frequent among genomes within the JGI ABC database, we generated a heatmap of the 30 most similar hits of the predicted protein families (Pfam) to the qbs BGC . Three clades were generated in the analysis . C1 consists entirely of BGCs from nine Pseudomonas aeruginosa strains which are most dissimilar from the BGC in strain 06C126; C2 consist of 11 strains from six genera, and C1 comprises of the most similar BGCs and consists 11 strains from four genera. The 06C 126 BGC consists of 27 Pfams. Results validated the NCBI BLAST search showing that the locus is most similar to P. fluorescens ATCC 17400, and the other closely related BGC was also from a P. fluorescens strain; however, the predicted Pfams were not all identical to the ones in the 06C 126 BGC. These three strains were similar in Pfams 1–7 in the cluster , 9–14 , 20 and 21 (00587 and 00155), 28 (03301), and 39 (13372). The remaining 10 Pfams were either unique to strain 06C 126 or shared with one other P. fluorescens strain. No other BGCs were as similar in Pfam content. Results from the NCBI nucleotide BLAST analysis and a search for homologous regions in JGI ABC, suggest the qbs BGC is rare in these databases.To identify if other bacteria, besides 06C 126 and ATCC 17400, encode the er (ABC)  to searcFigures 2C,D), the genome of 06C 126 was analyzed for other BGCs that may encode secondary metabolites. Twenty-one other BGCs were identified (Table 3). Of these, five BGCs were predicted to encode a non-ribosomal peptide synthetase (NRPS) and two to encode a bacteriocin. Both types of operons are diverse in nature and are known to produce metabolites that are inhibitory to pathogens  composed mostly of water-derived strains, had 14 isolates capable of antagonizing all five oomycete pathogens. Twenty-five freshwater strains inhibited P. sylvaticum which was shown to be the cause of most soybean oomycete infections in the survey of 2011–2012 . Although P. fluorescens ATCC 17400 exhibits 99% homology with ORFs 4–15 . Although two P. fluorescens strains show close similarity in Pfam content, more than 1.1 million BGCs were searched in the analysis. A bi-directional ORF search was also performed to identify additional similar genes surrounding this locus; results showed that surrounding gene regions of 14 ORFs are most closely related to loci in other non-Pseudomonas strains (Table 2) suggesting genomic variability. It is notable that this BGC encodes a unique siderophore that provides a fitness advantage in a freshwater ecosystem, such as Lake Erie where iron can be a limited resource  would be produced under identical conditions. Not only are these complex metabolites costly to produce, but it is unlikely that metabolites with different functions are expressed under the similar conditions. In strain 06C 126, we identified 21 additional BGCs with potential for antagonistic activity, suggesting this strain may produce distinct antagonistic compounds under certain environmental conditions.The observed differential activity of wildtype strain 06C 126 and the nditions , nitrogesubtilis , and met strains . Thus, iPseudomonads, and combined with high throughput screening to identify the molecular basis of antagonism (We have already shown that transposon mutagenesis can be applied to some environmental strains of tagonism . Once thPseudomonas isolates and analyzed the data. PM and HW designed the experiments, and wrote the manuscript with contributions from AW, SN, and PC.AW and SN helped to design experiments and performed the antagonistic assays. PC characterized the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Ehrlichia ruminantium, is the causal agent of heartwater, a fatal disease in ruminants transmitted by Amblyomma ticks. So far, three strains have been attenuated by successive passages in mammalian cells. The attenuated strains have improved capacity for growth in vitro, whereas they induced limited clinical signs in vivo and conferred strong protection against homologous challenge. However, the mechanisms of pathogenesis and attenuation remain unknown. In order to improve knowledge of E. ruminantium pathogenesis, we performed a comparative transcriptomic analysis of two distant strains of E. ruminantium, Gardel and Senegal, and their corresponding attenuated strains. Overall, our results showed an upregulation of gene expression encoding for the metabolism pathway in the attenuated strains compared to the virulent strains, which can probably be associated with higher in vitro replicative activity and a better fitness to the host cells. We also observed a significant differential expression of membrane protein-encoding genes between the virulent and attenuated strains. A major downregulation of map1-related genes was observed for the two attenuated strains, whereas upregulation of genes encoding for hypothetical membrane proteins was observed for the four strains. Moreover, CDS_05140, which encodes for a putative porin, displays the highest gene expression in both attenuated strains. For the attenuated strains, the significant downregulation of map1-related gene expression and upregulation of genes encoding other membrane proteins could be important in the implementation of efficient immune responses after vaccination with attenuated vaccines. Moreover, this study revealed an upregulation of gene expression for 8 genes encoding components of Type IV secretion system and 3 potential effectors, mainly in the virulent Gardel strain. Our transcriptomic study, supported by previous proteomic studies, provides and also confirms new information regarding the characterization of genes involved in E. ruminantium virulence and attenuation mechanisms.The obligate intracellular pathogenic bacterium,  Ehrlichia ruminantium is the causal agent of heartwater, a fatal disease in wild and domestic ruminants  was compared during its developmental cycle. There are two main stages: the extracellular and infectious form  and the vegetative intracellular non-infectious form   family proteins, a family of OMPs. Previously, a study on the Map1 cluster showed that it was differentially expressed depending on the host and tick cell lines and E. ruminantium strains  and at passage 238, 243 and 251  respectively. For virulent Senegal, the replicates were Senegal passage 7 (Sp7) and two passage 8 replicates (Sp8a and Sp8b). For attenuated Senegal, biological samples were Senegal passage 70, 75, and 77 . All the biological samples were produced in bovine aorta endothelial cells as previously described by Emboulé et al. .E. ruminantium growth was observed daily by light microscopy with detection of morula in each cell. E. ruminantium cell cultures used to produce biological samples were thus synchronized. When complete cell lysis was confirmed by light microscopy, samples containing supernatant and cellular debris were harvested and then ultra-centrifuged at 20,000 × g for 15 min at 4°C to collect EBs. The pellets were placed in sterile eppendorfs and homogenized in 2.5 mL of TRIzol reagent (Invitrogen). The samples were immediately stored at −80°C before RNA extraction.After infection with an appropriate inoculum, all cells were infected and the development of It is noteworthy that the duration between cell infection and lysis was 4 days for the Gardel and Senegal attenuated strains and 5 and 6 days for the Gardel and Senegal virulent strains respectively (data not shown). The duration of lysis remained the same within biological replicates.The total RNA extraction procedure was carried out as described in Emboulé et al. . Total RE. ruminantium genomic DNA (gDNA) contaminant was evaluated in each RNA sample by performing the pCS20 PCR using AB128-AB129 primers as described previously with a limited number of cycles (25 cycles) , indicating limited E. ruminantium gDNA contaminant. Afterward, the RNA samples were reverse transcribed by random priming with Superscript II (Invitrogen) according to the manufacturer's instructions. Reverse transcription and PCR amplification of corresponding cDNA were done using KpnI-primers as previously described . The PCR program was 10 min at 95°C and 45 cycles with 30 s at 95°C, 30 s at 60°C and 1 min at 72°C. The difference of Ct between the RNA and cDNA samples was always higher than 5 cycles, indicating low contamination by gDNA in the RNA samples (data not shown).Moreover, the efficiency of reverse transcription was checked using real-time PCR (qPCR) targeting the E. ruminantium microarrays (8 x 60 k) used in this study were manufactured by Agilent, France. The probes were designed with a modified version of the Oligoarray program  . There were probes common to the six strains and probes specific to one or more strains. Specific probes were designed for virulent and attenuated strains due to differences observed between genome sequences of virulent and attenuated strains (unpublished data). For data analyses, only probes that are specific for Senegal and Gardel strains were used.E. ruminantium probes gave 14,747 specific probes (91%), with Tm between 80 and 92°C containing 30 to 50% GC. These rules were progressively relaxed to get the additional 964 probes for a subset of missing sequences (Tm between 70 and 92°C and a GC % between 20 and 60). Analysis of specificity indicated that 46,696 oligos had 100% identity on 60 bases, 73,513 had 95% identity on 60 bases and 84,767 had 95% identity on at least 50 bases. Cross-reactivity of probes between the strains was assessed using this latter criterion (95% identity on at least 50 bases).The microarrays contained a total of 16,199 probes (60-mer), with three replicates per probe, including 83 bovine genes as negative controls. The selection of http://www.ncbi.nlm.nih.gov/geo/ under series GSE55726 and platforms GPL18397.Forty-eight percent of ORF were covered by 10 or more probes, and 90% were covered by 3 or more probes. Experimental data and associated microarray design have been deposited in the NCBI Gene Expression Omnibus (GEO) Two hundreds nanograms of cDNA were randomly amplified and labeled with Cy3-dUTP using the SureTag DNA Complete Labeling Kit . Following purification with reaction purification columns , quantification of Cy3-dUTP incorporation was performed by absorbance measurement at 550 nm. The yield of cDNA labeling ranged between 3 and 5 μg, and the specific activity ranged between 20 and 25 pmol per μg of cDNA, according to the manufacturer's instructions . Microarrays were incubated for 24 h at 65°C, with a rotation of 20 rpm, in a hybridization chamber. After hybridization, stringent washings were performed according to the manufacturer's instructions . Arrays were scanned using an Agilent C microarray scanner and extracted with the Agilent Feature Extraction program (version 10.10). The obtained images were saved in TIFF format and data with the signal intensities of all spots on each image were saved as “.txt” files for further analysis.http://www.bioconductor.org). Inter-slide normalization was performed using the quantile method. Mean log2 fold change (FC) between the virulent and attenuated strains was calculated for each probe and a B test was performed. Probes that had low or no signals were excluded from the analysis. For each probe, the expression values of the biological replicates for the virulent and attenuated strains were compiled. The average FC per probe was calculated by taking the average of the log2 values of the virulent strain from the average of the log2 values from the attenuated strain. The statistical significance of differential expression for each probe was calculated using a t-test in R 3.2.3  ≥ 1 and a p-value < 0.1. A mean FC per CDS was then calculated.For genes covered by multiple probes, transcripts were considered differentially expressed between the virulent and attenuated strains for Gardel and Senegal when more than 50% of probes mapping the transcripts had an absolute value of loghttp://blast.ncbi.nlm.nih.gov/) in order to identify potential functional domains.The annotations of genes differentially expressed were checked on NCBI. For genes encoding for hypothetical functions, protein patterns were searched in the InterProt database  were done targeting 7 map1-related genes on Gp43 vs. Gp243 and Sp7 vs. Sp77. Briefly for each sample, 1.5 μg of RNA were reverse transcribed with the Superscript VILO cDNA synthesis kit (Invitrogen) according to manufacturer's instructions. The quantity of resulting cDNA was determined by qPCR as previously described  between virulent and attenuated strains was measured as follows:R = (number of cDNA for virulent strain) / (number of cDNA for attenuated strain).2 FC between virulent and attenuated strains: comparing Gp43 vs. Gp243 and Sp7 vs. Sp77.The results were expressed in logE. ruminantium CDS. The mean normalized signal intensities obtained were compared between the different biological replicates for each strain and indicated a good technical reproducibility with the linear correlation coefficients included between 0.6 and 0.94   and for a hypothetical membrane protein (hmp) (CDS_04750: hmp10) (Tables fdxB and atpG), nucleotide transport and metabolism (ndk), replication, recombination and DNA repair (ssb), hypothetical membrane proteins (CDS_03690: hmp9 and CDS_05140: hmp12) and hypothetical proteins (hp)  (Tables There were 114 and 133 out of 950 genes (12 and 14% of ORFs) differentially expressed between the virulent and attenuated Gardel and between the virulent and attenuated Senegal strains respectively. Fifty genes were found upregulated for the Gardel virulent strain compared to the attenuated strain, and conversely 64 genes were found upregulated for the attenuated Gardel strain compared to the virulent strain (Table The upregulated genes were classified according to their COG (clusters of orthologous groups of proteins) function. The proportion of upregulated genes in each COG for the virulent and attenuated Gardel and for the virulent and attenuated Senegal strains is shown in Figure There was upregulation of genes belonging to nucleotide transport and metabolism and cell wall/membrane/envelope biogenesis in both virulent and attenuated Senegal and in the attenuated Gardel strain only Figure .Genes involved in metabolic functions such as energy production and conversion; translation, ribosomal structure and biogenesis; and posttranslational modification, protein turnover, chaperones were upregulated for both virulent and attenuated strains of Gardel and Senegal, but with more genes upregulated for the attenuated strains overall. Similarly, there was an upregulation for the Gardel and Senegal strains for genes involved in carbohydrate/Amino acid/Inorganic ion transport and metabolism, coenzyme transport and metabolism, but with more genes upregulated in the virulent Senegal strain Figure .map1-related gene family was higher and more specific for the virulent strains than for the attenuated strains: 16 and 12% for the virulent Gardel and Senegal strains respectively  but we confirmed the upregulation of map1-10 exclusively for virulent Senegal strain with a FC = 4.1 obtained by qRTPCR and 2.47 obtained by microarray . There were 11 upregulated genes in common between the Gardel and Senegal strains. For hypothetical membrane proteins, CDS_03690 (hmp9) and CDS_05140 (hmp12) were upregulated in the attenuated strains of both Gardel and Senegal, whereas CDS_04750 (hmp10) was upregulated in the virulent strains. CDS_07940 (hmp13) and CDS_04760 (hmp11) were upregulated in attenuated Gardel and conversely upregulated in virulent Senegal  are also upregulated in attenuated Gardel , including hypothetical membrane proteins (hmp), were found to be upregulated for both virulent and attenuated strains of Gardel and Senegal Tables , 2. TherE. ruminantium, genes encoding for T4SS are organized into five clusters comprising two major operons. Eight vir genes were upregulated only in virulent Gardel with a higher log2-FC ranging from 3.72 to 1.31 ; virB10 and virB11 localized on a second operon (operon virB8-11/D4); and virB2b and virB2c localized on a third operon (operon virB4b/B2a-d), as shown in Figure ankA) have been identified by S4TE software as potential effectors of T4SS and were also upregulated in virulent Gardel  differentially expressed between the virulent and attenuated strains, but contrary to Gardel, they were upregulated in the attenuated strain , for NADH dehydrogenase subunit E (nuoE) and for a putative Na+/H+ antiporter subunit (CDS_01720) were upregulated for the virulent strain  were upregulated for the attenuated strain  and CDS_07190 (2.30) encoding for BolA-like protein were upregulated in attenuated Senegal , thus strengthening our microarray data.In the Anaplasmataceae family, most studies have been conducted on virulent strains and have identified a small number of key components of pathogenicity  and 2 genes encoding proteins related to virulence (virB10 and ankA)  Table . The travir genes encoding components of T4SS. Vir genes upregulated in virulent Gardel encode for two major T4SS clusters , whereas no upregulation of vir genes was observed in the virulent Senegal strain. Moreover, ERGA_CDS_03830 (homolog of ankA) and ERGA_CDS_06440 were predicted as potential T4SS effectors for E. ruminantium using S4TE software , with intensive DNA replication beginning quickly after infection of new host cells . This result reflects the progressive adaptation of E. ruminantium to the in vitro culture.Interestingly, we observed a higher proportion of upregulated genes involved in coenzymes, carbohydrate, amino acid and inorganic ion transport and metabolism for the virulent Senegal strain. For this strain, lysis of host cells was observed at 6 days post-infection, whereas the virulent Gardel strain with a higher number of passages displays a lysis of host cells at 5 days post-infection. Replicates of virulent Senegal used in this study had a small number of passages E. ruminantium seems to be able to fight efficiently against osmotic and oxidative stresses generated by host cells. Osmotic and oxidative stresses are key methods by which mammalian infected cells kill bacteria. Thioredoxin and Glutaredoxin are the key proteins that fight oxidative stress  encoding for proteins of NADH-quinone oxidoreductase complex, were upregulated. This complex is usually involved in energy production, but it can help to maintain homeostasis as observed in R. conorii . The modulation of gene expression is probably due to mutations within unknown map1 regulatory regions. These proteins are major antigenic proteins and in the case of Map1 induce a strong humoral response, which is not protective. Previous studies shown that map1-family genes were differentially expressed in host or vector cells suggesting that they are involved in the adaptation of E. ruminantium to its host or vector , which was upregulated for both attenuated strains, and CDS_04750 (hmp10), which was upregulated for both virulent strains.For example, CDS_05140 (hmp12) was one of the most upregulated genes in both attenuated strains. This gene encodes for a proteoform porin located in the outer membrane of E. ruminantium. The upregulated membrane proteins expressed in the attenuated strains could be vaccine candidates against heartwater, and their function will be further studied.In conclusion, the comparison of global transcriptomes of virulent and attenuated strains suggested a reorganization of the membrane of E. ruminantium pathogenesis. For both the virulent and attenuated strains, most of the upregulated genes encoding hypothetical membrane proteins were different between Gardel and Senegal, indicating the possible modification of membrane structures. These gene expression modifications could induce either unprotective or protective immune responses, highlighting the importance of studying these proteins.In fact, genes encoding for Map1 proteins were found to be downregulated in both attenuated strains, suggesting that these proteins have a specific role in BM, DM, NV, and TL: conceived and designed the experiments; LP and KL: performed the experiments; LP, BM, KL, DM, and NV: analyzed the data; LP and NV: wrote the paper. All authors reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Aegolius funereus) males during the breeding season in a mountain area of Central Europe  between years 2006–2010, determined their average hunting home range size and explored what factors affected the size of home range utilised. The mean breeding home range size calculated according to 95% fixed kernel density estimator was 190.7 ± 65.7 ha (± SD) with a median value of 187.1 ha. Home range size was affected by prey abundance, presence or absence of polygyny, the number of fledglings, and weather conditions. Home range size increased with decreasing prey abundance. Polygynously mated males had overall larger home range than those mated monogamously, and individuals with more fledged young possessed larger home range compared to those with fewer raised fledglings. Finally, we found that home ranges recorded during harsh weather (nights with strong wind speed and/or heavy rain) were smaller in size than those registered during better weather. Overall, the results provide novel insights into what factors may influence home range size and emphasize the prey abundance as a key factor for breeding dynamics in Tengmalm’s owl.Animal home ranges typically characterized by their size, shape and a given time interval can be affected by many different biotic and abiotic factors. However, despite the fact that many studies have addressed home ranges, our knowledge of the factors influencing the size of area occupied by different animals is, in many cases, still quite poor, especially among raptors. Using radio-telemetry  we studied movements of 20 Tengmalm’s owl ( As early as Darwin  it was ninter alia): body size, climate, abundance and distribution of food, social organisation, population density and risk of predation.Different biotic and abiotic factors (intrinsic and/or extrinsic) are likely to affect the size, use, and spatial configuration of individuals’ HR, and all these factors interact along a hierarchical pattern according to different spatial and temporal scale –12. UsinAt the species level, positive correlations between size of HR and body mass/size were found in mammals, birds and lizards e.g., –16), wit, wit16])Meles meles) the dispersion of pasture patches with high earthworm availability positively correlated with territory size, however, the group size depended on the quality of particular foraging patches within the territory )Aegolius funereus) is a small, nocturnal, cavity-nesting owl , living in coniferous forests in the boreal zone and in alpine forests further south in Eurasia )d LSCV; ,67); HRs; HRsh esd , we used  in the study area was assessed by using snap-traps at the beginning of June during all study years; snap-traps were set up in three 1 ha squares (with 10 m spacing). The traps were left out for 3 nights and checked daily in the morning. The total trapping effort was 1089 trap nights (n = 3 locations). The number of mammals captured per 100 traps-nights was calculated as an index of prey abundance. All trapped individuals  were identified to the species level. For details of prey abundance in different study years see Owls were trapped, handled and tagged under permit No. 530/758 R/08-Abt/UL from the Ministry of the Environment of the Czech Republic, and were ringed under the Ringing Centre of the National Museum in Prague permit No. 329; all efforts were made to minimize suffering.All data were analysed with the aid of SAS System version 9.4 (SAS Institute Inc.). The analysis was made in two steps. In order to check for possible multicollinearity we first calculated correlations between the individual variables involved  using a multivariate General Linear Mixed Model . To account for the use of repeated measures on the same individuals, all analyses were performed using mixed model analysis with individual male as a random factor. We constructed the GLMM entering first the factor and/or factors expected to have the most significant effect, subsequently checking the model with addition of other factors which might contribute. The significance of each fixed effect in the mixed GLMM was assessed by the F-test. Non-significant factors (P > 0.05) were dropped from the model. Where appropriate we tested interaction terms. Associations between the dependent variable and fixed effects were estimated by fitting a random coefficient model using PROC MIXED as described by Tao et al. . We calcIn the analyses the size of individual male hunting HRs during breeding season established by (I) KDE and (II) MCP method were taken as the dependent variable. The following factors were considered as fixed effects in both models: number of fledglings, mean age of nestlings/fledgling from hatching (days), presence or absence of polygyny, age of male , number of radio-tracking nights, number of locations/fixes used for HR calculation, duration of whole radio-tracking period for individual males (days), male’s weight (g) and wing length (mm), mean wind speed (m/s) and prey abundance see . All relDependent variables and fixed effects entered into both models were log-transformed in order to achieve normal distribution of residuals. Interactions tested  were not significant, and thus excluded from both models (I and II).The mean size of hunting HRs during breeding season for Tengmalm’s owl males (n = 20) calculated according to 90% kernel density estimator was 153.8 ± 53.7 ha (± SD) with a median value of 152.9 ha, and according to 95% KDE: 190.7 ± 65.7 ha with median 187.1 ha; MCP method offered a range estimate of 94.2 ± 53.3 ha (80% MCP) with median 83.1 ha, 152.1 ± 79.8 ha (95% MCP) with median 131.8 ha, and according to 100% MCP: 179.4 ± 87.4 ha with median 156.7 ha. These ranges were based on 99 ± 45 (± SD) locations/fixes on average with median value 121 locations.Results of the GLMM I  revealedHome range sizes increased with decreasing prey abundance . PolygynResults of the GLMM II (where size of hunting range was defined from 95% or 100% MCP) were virtually identical regarding every single fixed effect ; graphicThe size of hunting HRs of male Tengmalm’s owls during the breeding season reported in this study is consistent with results from previous studies by other authors ,55–57 whWe found the HR size was dependent on different prey abundance as expected (prediction i). This is in accordance with other studies on birds of prey which reported larger HRs during poor food years and vice versa ,36,75, aWe have reported a similar relationship also for Tengmalm’s owl fledglings during the PFDP in the same study area that in the season with low prey abundance young owls occupied larger HRs than in the year with higher prey abundance . HoweverWe also found the HR size was dependent on presence or absence of polygyny (prediction ii). Although data for only two polygynous males were available, these males have significantly larger HRs compared to those mated monogamously most as a result of having to move between their two nestboxes (being 410 and 1035 m apart). Large size of HRs of these two polygynous males could further be exaggerated by the fact that they were supporting a large number of offspring, since hunting HR size was also positively associated with the number of fledged individuals (prediction iii).2  that the HR size should vary positively with the actual age of nestlings/fledglings, despite the fact that Tengmalm’s owl males increased feeding rates throughout the nestling period . The reaFinally, our results suggested that the HR size decreased with increasing wind speed and/or amount of precipitation during the radio-tracking nights when the HRs were recorded (prediction v). This reflects the hunting strategy of Tengmalm’s owl. The owl searches for prey by the pause-travel mode and depends heavily on sound to localize ground-dwelling prey –53. ThusTo conclude: we stress the importance of the time interval during which the HRs are recorded as shown for instance by studies regarding temporal changes in range use within years and/or between different parts of breeding season e.g., ,80,81). ,81. 80,8S1 TableRelevant data used in the analyses (GLMM I and II).(XLS)Click here for additional data file.


Despite the availability of a safe and effective vaccine since 1982, overall coverage of hepatitis B vaccination among healthcare workers (HCWs) has not reached a satisfactory level in many countries worldwide. The aim of this study was to estimate the prevalence of hepatitis B vaccination, and to assess the predictors of hepatitis B vaccination status among HCWs in Serbia. Of 380 randomly selected HCWs, 352 (92.6%) were included in the study. The prevalence of hepatitis B vaccination acceptance was 66.2%. The exploratory factor analyses using the vaccination-refusal scale showed that items clustered under ‘threat of disease’ explained the highest proportion (30.4%) of variance among those declining vaccination. The factor analyses model of the potential reasons for receiving the hepatitis B vaccine showed that ‘social influence’ had the highest contribution (47.5%) in explaining variance among those vaccinated. In the multivariate adjusted model the following variables were independent predictors of hepatitis B vaccination status: occupation, duration of work experience, exposure to blood in the previous year, and total hepatitis B-related knowledge score. Our results highlight the need for well-planned national policies, possibly including mandatory hepatitis B immunisation, in the Serbian healthcare environment. Hepatitis B infection is a major cause of occupational disease among healthcare workers (HCWs) worldwide. It has been estimated that every year between 600,000 and 800,000 cut and puncture injures occur in this professional group ,2. FurthDespite the availability of a safe and effective vaccine since 1982, the overall prevalence of hepatitis B vaccination in this cohort at risk has not reached a satisfactory level -7. StudiIn Serbia, there are very few data available on the hepatitis B vaccination status of HCWs, although this vaccine is mandatory for occupationally exposed HCWs . MoreoveA cross-sectional study design was applied in order to explore predictors of hepatitis B vaccination status among HCWs in the largest clinical centre in Serbia.The Clinical Centre of Serbia, with 41 organisational units (of which 23 are clinics) and 3,500 beds, is Serbia’s national referral hospital, located in the capital city, Belgrade, which has ca 1.6 million inhabitants. It is affiliated with the Faculty of Medicine of the University of Belgrade, the state university with ca 1,200 faculty staff.The HBV vaccine has been provided free of charge to occupationally exposed employees in Clinical Centre of Serbia since 1989. However, despite legal rules, the vaccine has been offered sporadically (depending on socioeconomic situation and availability of vaccine) at the time of employment and on request, but it is also mandatory after evaluation of high-risk occupational injury. However, organised public health efforts to increase the hepatitis B vaccination compliance throughout the Clinical Centre of Serbia have not yet been realised.A random sample of HCWs stratified by occupation was selected from the list of employees in December 2015, with the sample structure reflecting occupational distribution within the Clinical Centre of Serbia. The sample comprised 7.1% of the employees at the Clinical Centre of Serbia.All participants provided signed informed consent. The study was approved by the Ethical Committee of the Faculty of Medicine, University of Belgrade.The relevant data in this study were collected by questionnaire that was derived and adapted from other surveys ,15. AfteEach correct answer in this set of items was awarded 1 point. Therefore, the total HBV-related knowledge score represented a range between a minimum of 0 and maximum of 30 points. The third part contained the questions related to hepatitis B vaccination status of respondents, as well as a number of issues related to hazardous contact with blood and blood products in the workplace.The general estimate of voluntary vaccination acceptance in our sample was assessed using the frequency of participant’s influenza immunisation as an indicator. Furthermore, in order to control for a possible confounding effect of general acceptance of a legally mandated preventive health measure, HCWs were also asked to categorise their frequency of seat belt use when driving the car, which is required by law in the Republic of Serbia.The last part of the questionnaire consisted of both 13-item vaccination-acceptance and 15-item vaccination-refusal scales. The respondents completed the scale that was relevant to their hepatitis B vaccination status. Items in the scales were designed to explain HCWs’ hepatitis B vaccination status and their potential reasons for compliance or non-compliance. Therefore, workers were asked to assess the relative contribution of each item on a seven-point Likert scale, with response options ranging from ‘not important’ (one point) to ‘very important’ (seven points). The total score in each domain was calculated as the mean Likert point with corresponding standard deviation.Normality of distribution was tested by using the Kolmogorov-Smirnov test. Data were presented as mean ± standard deviation for continuous variables and as absolute numbers and percentage for discrete variables. Differences between groups were assessed by t-test and chi-squared test. A p value of less than 0.05 was considered as statistically significant.Internal reliabilities of the vaccination-refusal and vaccination-acceptance scales were assessed using Cronbach’s alpha coefficient for multiple item scales, which ranges from 0 to 1, with 1 representing perfect reliability.In order to assess the allocation of items into domains  of the vaccination-refusal and acceptance scales, exploratory factor analyses  were conducted. A factor was considered important if its eigenvalue exceeded 1.0.Independent predictors of hepatitis B vaccine status among HCWs were identified using a series of logistic regression models based on heterogeneous factors with potential confounding effects. All potential covariates were first analysed in a univariate unadjusted regression model with hepatitis B vaccination status as dependent variable. Subsequently, a multivariate logistic regression analysis was performed to test whether possible predictors remained statistically significant. This adjusted analysis included all covariates that appeared to be associated (p < 0.05) with the outcome following the univariate unadjusted analysis.Of 380 randomly selected HCWs, 367 (96.6%) were enrolled in the study, but only 356 (93.7%) provided all relevant information. Of these 356, four potential participants reported a history of hepatitis B and were excluded from all subsequent analyses. Thus, the total sample size in our survey comprised 352 HCWs, which corresponded to a statistical power of 0.843, with 95% confidence interval and probability level of α = 0.05.Overall, the prevalence of HCW vaccinated against hepatitis B was 66.2%. Additionally, among workers who had been vaccinated, 189 (81.1%) had completed the three-dose course, while 27 (11.6%) had received two doses, and seven (3.0%) one dose. Ten (4.3%) HCWs in our study did not know the number of doses they had received. Comparison of participants’ demographic and professional characteristics by hepatitis B vaccination status is presented in Employees who had either initiated or completed vaccination were significantly younger (37.8 ± 8.8 years old) than those who were unvaccinated (41.5 ± 9.5 years old). Slightly more men (73.3%) than women (63.9%) reported vaccination against hepatitis B (p = 0.118). Vaccination uptake varied significantly by occupation and work site, with predominantly higher proportions vaccinated among physicians and those working in surgical and intensive care units. Overall, 58.5% (206/352) of workers reported sharps injury, and 73.6% (259/352) reported unprotected blood mucocutaneous exposure in the past year. Statistically significantly higher rates of hepatitis B vaccination were observed in HCW sub-cohorts who had at least one episode of sharps injury and/or exposure of skin/mucous membranes to blood in the past year.The overall reliabilities of the vaccination-refusal and vaccination-acceptance scales, as estimated by Cronbach’s alpha coefficients, were 0.812 and 0.881, respectively .The loading weights obtained in the exploratory factor analyses of these scales are shown in The model of potential reasons for not receiving the hepatitis B vaccine revealed five factors with an eigenvalue greater than 1, explaining 73.9% of cumulative variance .Items clustered under ‘threat of disease’ explained the highest proportion of variance (30.4%) among those declining the vaccination, followed by ‘knowledge of disease’ and ‘social influence’ domains, explaining 16.4% and 11.7% of variance, respectively. Two other factors derived from this exploratory factor analysis model labelled as ‘access to care’ and ‘risk denial’ explained an additional 8.4% and 6.9% of variance of the reasons for not receiving the hepatitis B vaccine. The highest ranked reasons for hepatitis B vaccine refusal included ‘not at increased risk’ (4.0 ± 2.2), ‘concern about side-effects of vaccine’ (3.9 ± 2.1), ‘too busy/never enough time’ (3.9 ± 1.9) and ‘unconvinced of efficacy of vaccine’ (3.8 ± 1.9) .The exploratory factor analysis of the reasons for receiving the hepatitis B vaccine yielded three factors that explained 65.8% of variance among those accepting the vaccination . Items cHepatitis B-related knowledge in our cohort of HCWs was assessed through 30 questions. The mean score in this questionnaire was 22.9 ± 4.8 (range: 8 to 30). The items and the proportion of correct answers are shown in The predictors of hepatitis B vaccination status among HCWs that were identified using logistic regression models are illustrated in The unadjusted models revealed that significant predictive value for vaccination acceptance had the following variables: age, occupation, work site, duration of work experience, blood exposure in the last year, influenza vaccination, seat belt use frequency and total hepatitis B-related knowledge score. Furthermore, after testing for variables interaction and controlling the effect of potential confounders, the multivariate adjusted model has demonstrated that independent predictive value of hepatitis B vaccination status among HCWs remained significant for occupation, duration of work experience, blood exposure in the last year, seat belt use frequency and total hepatitis B-related knowledge score. Namely, this analysis showed that physicians had a more than three times greater likelihood of being vaccinated against hepatitis B compared with the occupational group consisting of administrative staff, sanitary workers and others (odds ratio (OR) = 3.41, p = 0.026). Additionally, this predictive model also demonstrated that with each year of work experience, the likelihood for vaccination acceptance declined by ca 5% . Furthermore, participants who experienced unprotected blood exposure between six and 10 times in the last year had an almost four times greater likelihood of being vaccinated compared with those who did not report any accident in the previous year . The HCWs who reported using seat belts frequently or always had an eight and five (respectively) times greater likelihood of hepatitis B vaccination acceptance compared with those who reported never using seat belts . Finally, after controlling for all of these potential confounders, the total hepatitis B-related knowledge score showed independent prognostic value in determining the HCWs vaccination status. Namely, adjusted logistic regression model revealed that with each one-unit increase in knowledge score, the likelihood of hepatitis B vaccination acceptance increased by 10% .Vaccination against HBV should be a moral imperative and responsibility for every health professional. Namely, successfully immunised HCWs not only protect themselves, but also prevent the spread of infection to patients and colleagues, and thus deliver safe healthcare. Despite over three decades of accumulated knowledge regarding the effectiveness and safety of hepatitis B vaccine, there is still a sizeable proportion of HCWs at a global level who never get vaccinated for various reasons.According to the World Health Organization estimates, HBV vaccination coverage among HCWs shows remarkable discrepancy worldwide . Namely,On the other hand, when we consider potential reasons for receiving the hepatitis B vaccine, we observed that factors related to ‘social influence’ played the most important role in decision-making behaviour. In addition, results from other studies revealed that recommendations of a superior/supervisor, spouse or friend strongly influenced HCWs’ positive attitude towards hepatitis B vaccination .In an attempt to elucidate independent predictors of hepatitis B vaccination status, physicians in our HCWs sample had more than three times greater likelihood of being vaccinated against HBV compared with the occupational group consisting of administrative staff, sanitary workers and others. This finding could be explained by the physicians’ greater educational and awareness status about hepatitis B and importance of its prevention, which is also supported by other authors ,13,19. FThe most common route of transmission of HBV in healthcare settings is needlestick injuries, especially those involving hollow needles. Approximately 70% of HCWs have reported needlestick injuries, with an average of two needle punctures per year. However, only ca 10–30% of needlestick injuries are reported to the authorities . It is tFinally, after controlling for general acceptance of other preventive measures (frequency of influenza vaccination and seat belt use), in the last two steps of the multivariate analysis, the total hepatitis B-related knowledge score showed independent prognostic value in exploring the vaccination status in our sample of HCWs. Namely, adjusted logistic regression model revealed that with each one-unit increase in knowledge score, the likelihood of hepatitis B vaccination acceptance increased by 10%. The results from studies in various setting also indicated that greater knowledge of both HBV infection and vaccination resulted in positive attitudes among healthcare providers, and sustained their beliefs in the safety and efficacy of the vaccine ,19,23,24Some limitations of the present study need to be kept in mind when interpreting the results. Firstly, this investigation was performed at one national clinical centre, and thus selection bias cannot be excluded. Secondly, cross-sectional design captures association but does not allow for determination of causality or temporal sequence. Thirdly, an information bias should be acknowledged, because this study relies on self-reported data, which may be subject to over- or underestimation, potentially distorting results. Another drawback of this study is the anonymous nature of data collection, as we were not able to track subjects who were not vaccinated and offer them HBV vaccine. Despite limitations, there are several advantages to our study, including the fact that such a study was conducted for the first time in Serbia. We recruited a representative sample of the HCWs from a large referral healthcare facility. Because of this, we hypothesise that the results of our study could be generalised to the total HCW population of the country.In conclusion, the findings of our study showed that a knowledge gap exists around Serbian HCWs’ awareness of hepatitis B vaccination, leading to suboptimal coverage. Further vaccination implementation efforts should emphasise the comprehensive involvement of HCWs in continuing education about occupational risk, liability, safety and effectiveness of hepatitis B vaccination. Therefore, there is a need for clear, well-planned national policies and guidelines, including the possibility of mandatory HBV immunisation within the Serbian healthcare environment.


We show that 50–60% of China’s air pollutant emissions in 2007 were associated with goods and services consumed outside of the provinces where they were produced. Of an estimated 1.10 million premature deaths caused by PM2.5 pollution throughout China, nearly 19%  are attributable to international exports. In contrast, interprovincial trade leads to improved air quality in developed coastal provinces with a net effect of 78,500 avoided deaths nationwide. However, both international export and interprovincial trade exacerbate the health burdens of air pollution in China’s less developed interior provinces. Our results reveal trade to be a critical but largely overlooked consideration in effective regional air quality planning for China.Recent studies show that international trade affects global distributions of air pollution and public health. Domestic interprovincial trade has similar effects within countries, but has not been comprehensively investigated previously. Here we link four models to evaluate the effects of both international exports and interprovincial trade on PM International and domestic interprovincial trade of China are entangled, but their health impacts have been treated separately in earlier studies. Here Wang. quantify the complex impacts of trade on public health across China within an integrative framework. As the world’s largest exporter, China accounted for over 10% of world merchandise export value in 20092. Although global trade in principle benefits both trading nations in terms of GDP, it tends to outsource pollution to less developed nations by taking advantage of low-cost labor and energy as well as lax environmental enforcement to increase returns on capital3. Because China’s economic boom has been fueled primarily by coal using less advanced technologies for production and emission control4, international exports have become an increasingly important factor driving China’s air pollutant emissions in recent decades5.The Chinese economy has experienced rapid growth since the open door reform policy was adopted in 1978. A significant portion of the growth has been driven by exports, particularly after China became a member of the World Trade Organization in 2001. In 2010, China became the world’s second largest economy and the gross domestic product (GDP) reached US$5.88 trillion, of which 27% was contributed by merchandise exports6, partly because interior provinces export emission-intensive products  to support production and consumption of finished goods in coastal regions8. At the same time, emissions in interior provinces can contribute to air pollution in coastal provinces through transport of both primary and secondary pollutants, the latter formed by chemical reactions of precursor gases in the air9. Provinces often cite this quandary in disputes about respective responsibilities in regional air quality planning in China. Note that the health effects of air pollution exposures are dominated by those due to fine particles (PM2.5), which take many chemical forms and occur both as primary pollutants and secondary products of SO2, NOX, NH3, and other gases.China is a vast country with substantial disparities across provinces in terms of resource and energy endowments, economic development, population densities, and lifestyles, resulting in trade between provinces of goods with embodied pollution. In recent years, emissions grew rapidly in some interior provinces but stabilized or even decreased in many coastal regions2 emissions embodied in international and Chinese interprovincial trade11. Application of these methods to study trade-related air pollution in China is an emerging field with important implications. Zhao et al.8 estimated that 15–23% of China’s air pollutant emissions were related to exports for foreign consumption. Lin et al.12 investigated air pollution embodied in China’s international trade and found its exports responsible for 23–34% of the concentrations of sulfate, 10–23% of black carbon, and 12–23% of CO over East China in 2006. Jiang et al.13 estimated that international exports caused 12% of the total mortality attributable to PM2.5 across China in 2007. Zhang et al.14 proposed a comprehensive framework to differentiate the total mortality of ambient PM2.5 according to the source emissions generated in local production, international exports, and international imports for various regions in the world. They indicated that consumption-based premature deaths due to PM2.5 in China  are much lower than production-based ones . However, existing studies of trade-related air pollution in Chinese provinces are not linked with a global multi-regional input−output (MRIO) model, thus are less accurate in quantifying the impact of international trade, both generally and with regard to specific countries, on China’s air pollution. Study of the impact of interprovincial trade on air pollution, moreover, is critical for designing regional air quality improvement plans in China, but has not yet been addressed in the literature. For a thorough quantitative understanding of the effects of trade on regional air pollution and public health across China, it is essential to integrate interprovincial and international trade into one MRIO model.A number of studies have applied input−output models to analyze CO2.5 pollution throughout China are attributable to international exports. Interprovincial trade has mixed environmental impacts across China. It led to improved air quality in developed coastal provinces and avoided an estimated 78,500 deaths nationwide in 2007. However, both international trade and interprovincial trade exacerbate the health burdens of air pollution in China’s less developed interior provinces, where large quantities of emission-intensive goods are manufactured for direct consumption in the coastal provinces or exported indirectly in the form of raw materials used in the supply chain of exported finished goods.In this study, we calculate the extent to which international and interprovincial trade resulted in relocation of air pollutant emissions across 30 Chinese provinces  and 40 other countries/regions in 2007, and we evaluate the subsequent effects on air quality and public health across China. We accomplish this by linking a global integrated MRIO model, an air pollutant emissions inventory, an atmospheric chemical transport model, and an exposure-response model. We show that nearly 208,500 premature deaths resulting from PM2.5 concentration (PWM-PM2.5) by nearly 20%, from 45.5 to 57.6 μg/m3 in 2007. The estimated mortality associated with pollution embodied in international exports was 208,500 throughout China, with a 95% confidence interval (CI95) of 158,800–255,900  , North America (21%), and East Asia (12%)  drives the health impacts attributable to pollution embodied in China’s international exports. While in value terms China’s imports (US$955 billion) in 2007 were ~ 80% of its exports (US$1.22 trillion) and had similar sector composition  Fig. . This im15, the coastal provinces, including Shanghai and Guangdong, were responsible for 40% of export values in 2007 but only 11% of China’s total mortality associated with emissions embodied in international exports . In contrast, exports from China’s interior regions include primarily energy-intensive and emission-intensive products with lesser monetary values. Furthermore, the production of export goods often requires inputs of raw materials and energy forms produced by heavy industry , which are geographically concentrated in China’s interior provinces7. These sources increased indirect export-related emissions  from the interior provinces. Despite contributing only 19.0% of China’s total export value, the interior provinces suffered much higher air pollution burdens from exports, e.g., 57.9% of related SO2 emissions. For interior regions with large populations , the health burden associated with international exports can be quite high in some provinces including Henan , Hebei , and Anhui .Our results further demonstrate that the impacts of international exports of Chinese goods on air pollution and public health are unevenly distributed in China Fig. . Thanks While the above emphasizes trade-derived air pollution and related health impacts in China, it is important to acknowledge that other countries suffer health impacts of air pollution from emissions embodied in exports to China. As reflected in the disparities of embodied emission intensities of exports vs. imports, however, the total environmental impacts resulting from imports to China will be considerably less than those resulting from its exports. It should also be noted that because international exports have at least partially replaced domestic consumption, our counterfactual scenarios excluding emissions embodied in exports might overestimate the health impact on China of its international exports. On the other hand, production for international export may also prompt diffusion of improved technologies to or within China, in which case its effect on the health impact within China might be underestimated.2 emissions in Beijing−Tianjin, the Yangtze River Delta, and the Pearl River Delta were generated outside of their boundaries, in other provinces. Interior provinces, where per capita GDP averages less than $3000 compared to $4400−$8700 in coastal regions, exhibit the largest difference in the emission intensity of exports and imports, resulting in nearly 75% of the interprovincial trade-related emissions. For example, in Guizhou, where the per capita GDP was only $969 in 2007, the SO2 emission intensity of interprovincial exports was 6.6 times that of imports from other provinces. Ratios over 2 exist in other less developed provinces, including Shanxi, Ningxia, and Inner Mongolia. Even for production of the same products, emission intensities of the interior provinces are usually higher than their coastal counterparts because of different energy structures and technology levels. The coal-fired electric power industry generates 58.4 g SO2 per US$ of electricity in Inner Mongolia, nearly twice that in Shanghai.Compared to air pollutant emissions from international trade, those embodied in trade between China’s provinces were even greater in 2007 Fig. . These e2.5 concentrations , avoiding 78,500  deaths. This means that current interprovincial trade resulting from specialization and relocation of industries has potentially improved the resource utilization efficiency16, and therefore mitigated the adverse health impact attributable to ambient air pollution for China as a whole. The most developed, coastal regions and provinces gain the greatest air pollution health benefits from interprovincial trade, including Beijing (−43.2 μg m−3 in PWM-PM2.5 and 8600 avoided deaths), the Yangtze River Delta , and the Pearl River Delta . Exacerbation of air pollution and health burdens, on the other hand, was suffered by interior provinces, such as Hebei , Henan (+9.3 and +9700), Guizhou (+6.2 and +3700).In order to evaluate the effects of interprovincial trade on ambient PMEffects of interprovincial trade on mortality risks associated with air pollution are inversely related to provincial per capita wealth Fig. , reveali2 and NOX are less harmful but can be transformed into sulfate and nitrate PM2.5 through secondary chemical processing noted above17, yielding longer atmospheric lifetimes and transport distances than those for primary PM2.5. To the extent that prevailing winds transport pollution from China’s interior provinces to coastal regions18, a function of seasonal meteorology, the latter can be affected by elevated PM2.5 from the upwind pollutant sources. These complex effects are captured in our results by nested-grid GEOS-Chem modeling of atmospheric transport and chemistry.Note that mitigation of air pollution in coastal regions achieved by relocating emissions to interior provinces through interprovincial trade can be partially canceled by long-range atmospheric transport and chemistry. For instance, gaseous SO2 emissions embodied in China’s interprovincial trade would have been reduced by 20.0% in 2007, an amount equivalent to the emissions of Canada (2.16 Mt). But existing environmental controls, including the Action Plan for Air Pollution Prevention and Control launched in 2013 to combat increasingly serious haze events in China, still focuses primarily on the developed coastal regions where the emission intensities are relatively low. In contrast, environmental regulations are looser for interior provinces , where the emission intensities and health burdens of air pollution are relatively high. Even as the central government is seeking to reduce national inequities through economic development of China’s interior provinces, air pollution control policies may encourage further relocation of heavy industries to those same provinces, aggravating local health burdens at the same time they improve them on a net national basis.Both international and interprovincial trade have exacerbated air pollution and associated health burdens in China’s interior provinces. Relatively high emission intensities of some industries in a number of less developed interior provinces of China may be a key factor driving the large emissions embodied in both international exports and interprovincial trade in China. Targeted shifts to cleaner energy sources and modernization of technology used by related industries of those interior provinces might alleviate the air pollution associated with Chinese trade. If the emission intensities of interprovincial exports from five interior provinces  were equal to levels of Shanghai, the total SO2 and domestic air pollutants, in many cases low-cost carbon reductions in China’s interior provinces effectively sold to developed nations would also help to improve the regional air quality in China.Our results show the complexity of regional air pollution issues, which need to be addressed by comprehensive consideration of entire production chains, atmospheric transport and chemistry, and population distributions. Since interprovincial trade between provinces generally improves the air quality in coastal provinces but degrades it in interior regions, policies should be designed to favor transfer of advanced technologies for production and emissions control from the coastal regions to the interior regions. Similarly, as Chinese industries generally emit more pollutants per unit output than their counterparts in developed countries, such domestic efforts are likely insufficient to mitigate total air pollutant emissions from a global perspective. In contrast to the global impact of greenhouse gas emissions, the health impacts of air pollution are mainly local or regional. International cooperation is critical to accelerate the diffusion of advanced technologies in manufacturing, non-fossil energy, and pollution control to and within China. Programs undertaken by multilateral development agencies  might provide one institutional mechanism for such technology transfer. If a global market in carbon allowances eventually emerges under the United Nations Framework Convention on Climate Change, it might also serve such aims as a co-benefit. Because fossil fuel combustion generally emits both CO2.5 across China. Our analytical approach includes three major components . Second, we apply the nested-grid GEOS-Chem model (http://geos-chem.org/) to estimate the spatial change ratios of ambient PM2.5 concentrations induced by trade, which we then calibrate using satellite-derived PM2.5 concentrations to estimate trade-related PM2.5 exposures. Third, an integrated exposure-response (IER) model ; I is the identity matrix; and (I − A∗)−1 is the Leontief inverse matrix.We developed a linked MRIO model 20 to estimate the sector-specific emissions for Chinese provinces and other countries/regions, respectively. Due to the different classification of sectors between the emission inventories and the linked MRIO model, some of the sectors are combined or divided through a mapping process as shown in Supplementary Fig. E∗ is the air pollutant emissions  embodied in the trade flow; F is a row vector of per unit output of emissions  for each sector in the 70 regions; F; d represents the 21 sectors in the linked MRIO.Sector-specific emission intensities of air pollutants are calculated as total production-based emissions divided by total monetized outputs from the respective sectors. We employed the multi-resolution emission inventory for China (MEIC)s1 and s2 represent the 30 Chinese provinces and 40 other countries/regions, respectively; r; r but consumed in other Chinese provinces or other countries/regions, respectively; r but produced in other Chinese provinces or other countries/regions, respectively.Then, the emissions generated in one region  can be quantitatively decomposed into the components related to consumption activities in that region as well as in other regions Eq. . The emi21 associated with international trade. CO2 emissions have also been calculated based on our linked MRIO model, and the resulting emissions embodied in trade are generally consistent with Feng et al.7  across China at a resolution of 0.5° latitude × 0.667° longitude . The spatial change ratios between baseline PM2.5 concentrations and the five alternative simulated results are considered as the impacts of various types of trade activities on PM2.5 concentrations  to simulate the spatial change ratios of PM0-01 to s22. These data have already been extensively applied in previous studies including the global burden of disease (GBD) project24. In order to reduce errors due to insufficient samples of satellite data, the average satellite-retrieved PM2.5 concentrations over 3 years (2006–2008) were used to represent the annual mean concentrations for 2007. This approach helps to correct the potential model bias if the GEOS-Chem-calculated PM2.5 concentrations are directly used for the baseline case, and improves the spatial resolution of our final model results. More descriptions of the GEOS-Chem simulation process and evaluation against observations are provided in The employed satellite-retrieved data have a high spatial resolution (10 × 10 km) and have been transformed into estimates of ground-level concentrationsM is the premature deaths from a given disease attributable to ambient air pollution; AF is the attributable fraction of trade-driven PM2.5 pollution; B is the incidence of the given health effect due to specific disease , reported at the national level due to data limitations in China1; P is the exposed population; pi is the proportion of population in grid cell i, %; and RR(C)i is the relative risk of grid cell i.We quantified the premature deaths attributable to trade-induced air pollution from four major causes of mortality, i.e., ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), stroke and lung cancer (LC), according to the GBD project:2.5 has been conducted in China, the IER functions developed by Burnett et al.25 were employed to calculate RR(C) for each grid cell in this study. The IER functions describe the C−R relationship throughout a wide range of ambient PM2.5 concentrations (including the high levels observed in China) by integrating data from cohort studies of ambient air pollution, secondhand tobacco smoke, indoor burning of solid fuels, and active smoking. The four major causes of mortality share the same health impact function with different parameters, and can be expressed as:C) is the relative risk of a given PM2.5 concentration C; C0 is the counterfactual PM2.5 concentration below which there is no additional risk; and α, γ, and δ are parameters describing the overall shape of the exposure-response curve resulting from a stochastic fitting process25. For each health endpoint, we implemented the RR function as in Eq. C0, α, γ, and δ derived from Monte Carlo simulations, leading to 1000 sets of exposure-response functions. Supplementary Fig. As very limited epidemiologic research on the effects of long-term exposure to PM2.5 concentration (CTRE) occurs, we assumed an equal probability of CTRE throughout the distribution of concentrations, and the RR(CTRE) is calculated using Eq. CTRE) of each grid cell can be calculated and then applied to quantify the impact of trade on premature deaths attributable to PM2.5 exposures:N is the sampling number, set as 1000; i = 0, 1, 2,…, 998, 999; and α is the constant increment (Eq. CnoTRE (Eq. Since we are unable to specify where on the nonlinear IER curve a given trade-induced PMmentclasspt{minimaoTRE Eq.  into equ6 were re-gridded to match the 10 × 10 km resolution of the current study. It is worth noting that this research of the impact of trade on premature death attributable to ambient PM2.5 across China is inherently multidisciplinary. The results should be interpreted with full consideration of the uncertainties associated with different parts of the framework.Premature deaths are calculated for each grid cell at a resolution of 10 × 10 km and are aggregated for each province. The population densities of China in 2007 at 1 × 1 km resolution developed and applied in our previous studiesThe data sets generated and/or analyzed during this study are available upon request from the corresponding authors.Supplementary Information


Projections of future landscape change illustrated potential impacts of anthropogenic development on areas lynx and bobcat may use, and indicated where connectivity for bobcats and lynx may be lost. These projections provided a guide for conservation of landscape permeability for lynx, bobcat, and species relying on similar habitats in the region.Landscape connectivity is integral to the persistence of metapopulations of wide ranging carnivores and other terrestrial species. The objectives of this research were to investigate the landscape characteristics essential to use of areas by lynx and bobcats in northern New England, map a habitat availability model for each species, and explore connectivity across areas of the region likely to experience future development pressure. A Mahalanobis distance analysis was conducted on location data collected between 2005 and 2010 from 16 bobcats in western Vermont and 31 lynx in northern Maine to determine which variables were most consistent across all locations for each species using three scales based on average 1) local (15 minute) movement, 2) linear distance between daily locations, and 3) female home range size. The bobcat model providing the widest separation between used locations and random study area locations suggests that they cue into landscape features such as edge, availability of cover, and development density at different scales. The lynx model with the widest separation between random and used locations contained five variables including natural habitat, cover, and elevation—all at different scales. Shrub scrub habitat—where lynx’s preferred prey is most abundant—was represented at the daily distance moved scale. Cross validation indicated that outliers had little effect on models for either species. A habitat suitability value was calculated for each 30 m Lynx canadensis) was absent from the region for decades but became reestablished naturally in Maine in 1999 [Lynx rufus) and lynx (Lynx canadensis) rely on connective habitat to facilitate seasonal range-shifts between heavily used core areas, as well as longer–distance movements such as dispersal that link subpopulations and permit gene flow [Forest cover across the Northeastern United States has increased since the early nineteenth century as agricultural land has been abandoned. Populations of native carnivores have recovered in response to increased habitat. For example, a breeding population of lynx  [Setting such strategies presents three major challenges. First, species have differing habitat requirements that may require unique conservation solutions. Bobcats use broader landscape characteristics including natural habitats, riparian areas, edge, and natural cover in areas of moderate human use –14, but ricanus) . Second,ricanus) –22. The ricanus) –25. Thusricanus) –29. And ricanus) .As change to the Northeastern landscape intensifies in order to accommodate a greater human population, maintaining ecosystem processes such as dispersal of wide ranging mammals depends on identifying networks of connective habitat linking high quality core areas. Efforts to create connectivity maps have been achieved for bobcats in New Hampshire and lynx in the Rocky Mountains, and sub home-range scales have been investigated for pumas, but corridor models using resource selection methods may not best predict landscape use –35. RegiD2) to derive a habitat suitability model for lynx and bobcat and map suitability across the Northeastern U.S. based on GPS location data and the spatial covariates that are associated with each location. The D2 approach is a Principal Components Analysis (PCA), but rather than focusing on components that explain the variation among locations, it reveals the habitat components that are most similar across all locations; these represent the minimum habitat requirements for each species and can be scored on a pixel-by-pixel basis [D2 approach [2 pixel across Vermont, New Hampshire and Maine; 2) use the D2 model for each species to identify current connectivity (linked areas conducive to movement) across subportions of the region by developing cost-distance based landscape conductivity maps—including an area recently recolonized by unstudied lynx, and 3) estimate the persistence of connectivity into the future in areas most likely to experience increased anthropogenic pressure.Here, we used a partitioned Mahalanobis Distance Squared analysis , New Hampshire (NH) and Maine (ME), an area of 132,313 km2 . Empiriced areas . Lowlanded areas . Road de km/ km2 , while h/ km2 [2 .2 area, primarily in the Musquacook lakes region of northwestern Maine (2), these dirt roads were used primarily for wood extraction and most were not maintained. Human density was 0 in the majority of the lynx study area, as activity was limited to seasonal camps and logging operations [2.Empirical lynx data were collected from a 19,875 kmrn Maine . Averageerations . One lynBobcat GPS radio–collar locations were provided by the Vermont Cooperative Fish and Wildlife Research Unit from a study conducted between 2005 and 2008  S1 Tabl. Lynx GP®  collars used was absorbed within the 30 m pixels and the buffers around each location used in this analysis  [GPS radio–collar locations were taken at regular intervals 24 hours a day. The full range of locations were used to incorporate less frequently used habitats such as those used by individuals moving across longer distances. Locations from each cat were edited to 4 hours apart. We balanced available data per cat with activity patterns to maximize independence, time between locations and available data. There may be autocorrelation of some resting locations, though both species move throughout the day depending on climate and daylight hours, and consistency of use of certain habitats for both species underscores the importance of specific landscape variables. A maximum of 200 points were taken from each collar to minimize weighting of data  Tables. s. com.) , 45.Lynx were found to be recolonizing New Hampshire after modeling but during the mapping phase of this study, and we took the opportunity to explore how the lynx population may be recolonizing parts of its historic range. A connectivity map was produced using, instead of core habitat blocks, 142 uncollared lynx locations from 2006 through 2011, verified by the US Fish and Wildlife Service and state wildlife departments using photos, tracks and observations.The association of bobcat and lynx occurrences with 39 variables was evaluated across three scales, each described by a map layer . Variabl2 and 25.7 km2 respectively) [2 (2790 m radius), under the premise that male ranges encompass female ranges [The density of habitat variables was examined at three scales  , 43. Thee ranges –56.Topographic features are localized in many areas, including the Champlain Valley, and would not have been as informative over larger neighborhoods. To provide greater definition of topography, smaller scales with 90 m, 150 m and 270 m radii were arbitrarily chosen to evaluate slope, sin aspect, and cosine aspect. Elevation data were taken at location points only.Values for each variable (map layer) were extracted from under radio-telemetry locations. The most consistent variables within each species dataset  were preselected and sets of uncorrelated variables were analyzed. Preselection reduced the total variables to 31 for bobcat and 35 for lynx Mahalanobis distance analyses .least amount of variation  among known locations [For each species, sets of the selected variables were analyzed using principal components analysis (PCA), which describes increasing amounts of variation within the dataset with a set of linear equations. For each PCA analysis, we were interested in the component that described the ocations , as it docations , 57.D2 analysis of each location using the equation,D2 was the squared distance, standardized by Σ [D2 value quantified the dissimilarity of a location from ideal (minimum) habitat with a standardized squared distance between each variable’s value at any given location (y) and the mean of each variable from known used habitat locations (μ). Low values described favorable habitat more similar to the means of the predictor variables.For each PCA analysis, the component that described the least variation among locations provided the foundation for a partitioned ariables . Deviatized by Σ . Thus, tP–values [P–values for each location using:k = 1), plus the number of variables in the model (p) plus 1 [D2 values, which have no upper limit, to P–values rescaled values between 0 and 1, with high P–values describing areas closer to ideal habitat. As habitat variables often do not meet the assumption of normality, P–values do not indicate probabilities [Distance values describing movement habitat suitability for each location were transformed to P–values  for ease) plus 1 , 58, 59.bilities , 59, 60.P–value was generated for each location for each candidate model, as previously described [P–values were averaged in bins of 0.01 increments  to produce a random cumulative frequency set of P–values for each candidate model. Cumulative frequencies of random and species telemetry location P–values were evaluated by plotting distribution curves  were selected as core areas. To explore how unstudied lynx may have recently recolonized an area west of the radio-collared lynx study area, an additional connectivity map was generated using the validated lynx model and 142 buffered confirmed uncollared lynx locations from outside the study area in VT, NH and ME instead of habitat blocks.We assessed the current connectivity of portions each species’ pper v.6 , a progrpper v.6 , or coreP from the D2 analysis. The Linkage Mapper tool (now integrated into Circuitscape), used the resistance map to compute multiple pathways between each polygon (core areas of conserved habitat) and others, and then mosaicked the results into a single composite map. The resulting map of each focal area provided an additive estimate of the relative accessibility of each cell to the nearest core area [The goal of the connectivity analysis was to identify, map, and evaluate connective habitat between polygons (core areas of conserved land) using a circuit-based least-cost corridor method to depict conductivity across the landscape e.g., , 64, 66), 6664, 6ore area , 64.We then defined “connective habitat” for each species by overlaying GPS points on the Linkage Mapper connectivity map and identifying the highest cost distance value used by each species. This maximum, rounded up by 1%, was used to set a connective habitat threshold for each species. Cost-distance pixels below this threshold were identified as “connective habitat”, while pixels exceeding this value were deemed “non-connective habitat”.2 pixel resolution based on projected human settlement, road, and amenities over a 20 year horizon.The projected change in the human footprint in the Northeast , 67  was also calculated. Each cost-distance pixel in the future map was dichotomized as being connected or not based on the threshold identified in Objective 2. We compared the change in connective habitat between the current and projected landscape for each species.A total of 2,427 independent radio–collar GPS locations from 16 bobcats  and 3,639 GPS collar locations from 31 adult lynx  were used in these analyses . Two youP–value of 0.57  component of the PCA, which explained 13.5% of the variation in the dataset .Cross validation revealed that the bobcat model  adequateP = 0.78 threshold  component, which explained 4.95% of variation in the data  and a validation set of 3 females  had average P–values significantly lower than validation thresholds .Cross validation revealed that the lynx model  adequate2 (4%) of the 4,879 km2 Champlain Valley biophysical region (CVBR), 547.81 km2 (8%) of the Northern Piedmont of VT, and 992.63 km2 (6%) of the Route 2 corridor (2 (96.5%) of the CVBR region, 6,450.67 km2 of the Northern Piedmont of VT (96.6%), and 11,776.93 km2 (69.3%) of the Route 2 corridor (Conserved (core) areas for bobcat comprised 202 kmcorridor . Twenty corridor , Fig 3.2 (23%) and 2,668.54 km2 (12%) of the northeastern and southeastern Maine areas respectively (2 (98.3%) and 22,618.31 km2 (98.2%) of northeastern and southeastern Maine areas, respectively  in the CVBR, by 796.72 km2 (11.9%) across the Northern Piedmont area, and by 1,139.57 km2 (6.7%) across the Route 2 corridor  over the next 30 years, and across the area of uncollared lynx locations (west of the Musquacook lakes study area to Vermont) by 81.35 km2 (0.3%), though connective habitat was predicted to increase by 197.79 km2, or 0.7%, in northeastern Maine  than lynx  [In contrast to bobcats, which used undeveloped habitat including agricultural lands, lynx were closely associated only with natural habitats. Natural habitat and proximity to cover were essentially consistent among locations . Lynx rees < 0.8  suggestslatrans) , 87. Clilatrans)  and expaAnthropogenic development is expected to have different impacts on connectivity for lynx and bobcats in the areas we studied. Mapping connective areas using circuit-based least-cost path analysis and examining how anthropogenic changes are likely to impact the landscape at a 30 m x 30 m resolution identified areas of this multiuse landscape where connectivity could decline substantially Figs , Table 5In contrast to bobcats, lynx connectivity is expected to remain stable in most areas examined. Connective habitat in southeastern Maine is predicted to undergo contraction in some areas and localized expansion in others , such thOur approach provides a conservative illustration of future connectivity, especially for bobcats, because: 1) models for each species are based on data largely from adults, who are less likely to disperse, so connectivity mapping is conservative. Only two of the animals, bobcats B11 and B44, were subadults and these cats have relatively few data points (33 and 102 respectively). Thus, the models largely reflect habitat use of individuals settled into home ranges; 2) bobcats are flexible in their habitat use, which allows them to occupy such a wide variety of habitats lower 48 United States and Mexico , 80. BecSeveral caveats in terms of modeling species’ distribution are worth highlighting. First, depending on species, analysis by sex and age, and analyses of habitat use by season and time of day could be informative if the data were robust enough. Information on temporal use of habitats by species could allow schedule adjustments of landscape use by humans to also allow wildlife use. Second, although there is evidence that snow depth affects distribution of lynx and bobcats, it was not possible to correlate locations with snowdepth due to the lack of localized detail in the snowdepth data that were available. Elevation was suggested to provide some proxy for this. Third, it should be noted that connectivity is not always a gain for populations; depending on configuration, it can also facilitate the spread of emerging diseases and invasive species , 90.Only areas with variable values similar to those of the study areas for each species were selected for connectivity modeling, as we assumed the models applied best to these landscapes. Though there is cohesion of individuals to the models , there a2 pixel maps Click here for additional data file.S2 Methods(DOCX)Click here for additional data file.S1 Table(XLS)Click here for additional data file.S2 Table~ for B4 and B11 indicates that these were young adults at the time data were gathered, and possibly dispersing.Data for four bobcats with large datasets was selected to even out distribution of data through the year. A star* in the Used location dates column indicates that locations from these cats were selected for months that were lacking elsewhere in the dataset. A(TIF)Click here for additional data file.S3 TableSix lynx were recaptured and recollared and data from multiple collars used (i.e. L140 has 35+11 locations). Data was taken from the full range of dates for all lynx. All lynx providing data were adults.(TIF)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 FigDashed lines indicate that not all locations from that month were used, and that locations were selected to even out locations over the year.(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.


Toxoplasma gondii are pathogenic to mice and exhibit great genetic variability.In Brazil, studies on animals and humans in mainland areas have shown that most strains of T. gondii strains from one cat and three rats on Fernando de Noronha Island. The cat had antibodies to T. gondii, which were revealed using a modified agglutination test  and the seroprevalence among the 46 rodents was 15.2%. Viable T. gondii was isolated from one cat (TgCatBrFN1), two brown rats (TgRatnoBrFN1 and TgRatnoBrFN2) and one black rat (TgRatraBrFN1). Unlike the strains from mainland Brazil, these isolates were not pathogenic to outbred mice. The genotypes of these strains were compared with strains previously isolated on the island and in mainland Brazil. The analysis based on microsatellite data showed a limited genetic diversity of T. gondii on Fernando de Noronha Island with the majority of strains clustered into the following three groups: type II, III, and Caribbean 1.In this study, using a set of 11 PCR-RFLP and 15 microsatellite markers, we isolated and genetically characterised via mainland Brazil.There was little variation among strains within the same group, suggesting that the majority of strains circulating on Fernando de Noronha are derived from only a few strains that were recently introduced to the island, likely from imported cats. Except for the strain belonging to the Caribbean 1 group that originates from northeast Brazil, there was little evidence that strains from the other groups were introduced to Fernando de Noronha The online version of this article (doi:10.1186/s13071-017-2150-4) contains supplementary material, which is available to authorized users. Toxoplasma gondii infections are prevalent in animals and humans on a global level [T. gondii because sexual reproduction in their intestines leads to the production of millions of highly resistant oocysts [T. gondii among humans is high in Brazil, reaching 90% in some regions, and may be related to high environmental contamination by oocysts [T. gondii isolates has been studied extensively over the last two decades, showing that the hotspot of diversity is located in South America, particularly in Brazil [al level . Felids  oocysts . The ser oocysts . The worn Brazil . Severe n Brazil .Fernando de Noronha  is an archipelago of 21 islands and islets in the Atlantic Ocean and is located approximately 354 km east of the Brazilian coast. The main island has a population of approximately 3,000 inhabitants . There aT. gondii seroprevalence in different animal species in Fernando de Noronha, including cats, suggesting that transmission of this zoonotic parasite is active among the animal fauna of this Brazilian archipelago [Toxoplasma gondii strains isolated from chickens, cats, and cattle egrets on Fernando de Noronha showed unexpected genotyping results. These results showed the presence of atypical genotypes that seemed endemic to the island as well as clonal type II strains that are common in Europe and North America but are virtually absent in mainland Brazil [T. gondii strains from one cat and several rodents on Fernando de Noronha with PCR-FLP and microsatellite markers and examine their genetic relationships with other strains previously isolated on the island and in mainland Brazil.Previous studies reported high rates of hipelago –9. Toxopd Brazil , 9, 10. g for 10 min; the serum sample was stored at -20 °C.On October 5, 2013, an adult male cat with a terminal condition was admitted by its owner to the Animal Surveillance Centre (NVA) of the State District Administration of Fernando de Noronha in the village of Vila do Sueste. The cat was necropsied soon after death, and the heart, brain and thigh muscle samples were collected. A blood sample was obtained from the cardiac cavity and was centrifuged at 1,500× Rattus rattus) and 18 brown rats (Rattus norvegicus) were captured with Tomahawk live traps at different locations on the island. The rodents were anaesthetised using ketamine hydrochloride (40–90 mg/kg) and xylazine hydrochloride (2–5 mg/kg) and blood samples (3 ml) were collected by means of cardiac puncture. The rodents were individually sacrificed in a hermetically sealed box containing cotton wool soaked with isoflurane. Necropsies were performed to collect brain, heart, and skeletal muscle samples from each rodent.Between October 2013 and April 2014, as part of a synanthropic rodent control programme on the Island of Fernando de Noronha, 28 black rats (All cat and rodent samples were transported under refrigeration by air to the Faculty of Veterinary Medicine of University of São Paulo (FMVZ-USP) for laboratory analyses.The serum samples from the cat and black and brown rats were tested using the modified agglutination test (MAT) , with a T. gondii antibodies with MAT. Mice were euthanised (using the same protocol as above) two months p.i., and their brains were examined for T. gondii tissue cysts [To conduct the bioassay, brain, heart and skeletal muscle samples from each rodent were homogenised together in a blender with 0.85% NaCl, whereas each cat tissue sample was homogenised separately. The homogenates from each animal were digested with an acidic pepsin solution  and subcue cysts .T. gondii strains collected in this study were extracted from mouse brains with the Qiagen® Dneasy® Blood & Tissue kit and genotyped using 11 PCR-RFLP and 15 microsatellite markers distributed on the 14 chromosomes and plastid of T. gondii, as described previously [T. gondii type I, II, and III strains, respectively [DNA samples from eviously . As showeviously , 10 and eviously –20 and 2eviously ). The ENectively .http://bioinformatics.org/populations/) based on the chord-distance Dc evaluation of Cavalli-Sforza and Edwards [http://www.megasoftware.net/history.php).Because microsatellite markers are better markers than PCR-RFLP for discriminating related isolates at a limited geographic scale such as an island , the nei Edwards  and gene Edwards  , and in two out of 18 brown rats (11%). The MAT titres were as follows: < 25 (39 rodents), 25 (one black rat), 100 (cat), 800 (two black rats), 1,600 (two black rats and one brown rat), and 6,400 (one brown rat)  from Fernando de Noronha Island were highly structured in three groups: three strains (including TgCatBrFN1 and TgRatnoBrFN1 from this study) were clustered with the ME49 strain in the type II group, six strains (including TgRatnoBrFN2 from this study) were clustered with the NED strain in the type III group, and the TgRatRaBrFN1 strain was grouped in the Caribbean 1 group  in Fernando de Noronha: of the estimated 848 domestic animals living on the island, 470 are domestic cats [T. gondii infection in these intermediate hosts. All the rats were bioassayed, irrespective of serological findings, because congenitally infected rats may develop immune tolerance without antibody production [Toxoplasma gondii antibodies were found in 15% of the 46 rats collected in our study, which is lower than the 38% [T. gondii and contribute to the cycle of this zoonosis on the island.The Island of Fernando de Noronha provides a unique opportunity to study the epidemiology of toxoplasmosis because of restricted animal and human populations. There is a high density of cats  has a programme to promote public health and control synanthropic animals. Our results support the implementation of a toxoplasmosis prevention and control programme based on the guidelines of One Health and Ecological Health (conservation medicine) in the archipelago of Fernando de Noronha.