Microbial communities are critical to ecosystem dynamics and biogeochemical cycling in the open oceans. Viruses are essential elements of these communities, influencing the productivity, diversity, and evolution of cellular hosts. To further explore the natural history and ecology of open-ocean viruses, we surveyed the spatiotemporal dynamics of double-stranded DNA (dsDNA) viruses in both virioplankton and bacterioplankton size fractions in the North Pacific Subtropical Gyre, one of the largest biomes on the planet. Assembly and clustering of viral genomes revealed a peak in virioplankton diversity at the base of the euphotic zone, where virus populations and host species richness both reached their maxima. Simultaneous characterization of both extracellular and intracellular viruses suggested depth-specific reproductive strategies. In particular, analyses indicated elevated lytic interactions in the mixed layer, more temporally variable temperate phage interactions at the base of the euphotic zone, and increased lysogeny in the mesopelagic ocean. Furthermore, the depth variability of auxiliary metabolic genes suggested habitat-specific strategies for viral influence on light-energy, nitrogen, and phosphorus acquisition during host infection. Most virus populations were temporally persistent over several years in this environment at the 95% nucleic acid identity level. In total, our analyses revealed variable distributional patterns and diverse reproductive and metabolic strategies of virus populations in the open-ocean water column. Viru. Viru7/ms .Recent developments in high-throughput DNA sequencing have allowed for exploration of viral diversity at unprecedented scales. The continuing description of viral genetic diversity highlights the importance of further cultivation-independent in situ characterization of environmental viral populations. Metagenomic virus surveys have focused on characterizing geographic variability across surface oceans –17, tempTo further explore viral diversity, environmental distributions, and dynamics in the open ocean, we characterized virus genomes from seawater in virus-enriched (0.02–0.2 μm) and cell-enriched (>0.2 μm) size fractions over time and depth in the North Pacific Subtropical Gyre (NPSG). The approach facilitated the exploration of both extracellular virioplankton particles as well as cell-associated phages, to better characterize reproductive and metabolic strategies of viruses in the open ocean. We use the term “reproductive strategies” here to refer life history differences between strictly lytic viruses with a singular strategy of host lysis, versus temperate phages that in addition to the lytic cycle, have the potential to either integrate into their host’s genome or reside as an extrachromosomal element. In this study, we analyzed samples collected over 1.5 years over 12 depths (5–500 m) to characterize dsDNA viruses in both virioplankton and bacterioplankton size fractions. This virus genome dataset  provides new perspectives on the diversity, reproductive strategies, gene content, and ecology of viruses in the open ocean.A schematic overview of our workflow is presented in Fig. http://hahana.soest.hawaii.edu/hot/hot-dogs).Station ALOHA , a relatively seasonally stable environment located in the NPSG, is a well-characterized sampling site of the Hawaii Ocean Time-series (HOT) program. The ALOHA 2.0 dataset contains 374 metagenomic samples collected at 12 depths  at approximately monthly intervals of 16 timepoints spanning 1.5 years from 2014 to 2016 Fig. . These cAll samples were collected using the following procedure. 2–4 L of seawater  were collected using CTD-attached Niskin bottles and filtered, using peristaltic pumps at a flow rate of about 6 L/h, onto a 0.2 μm 25 mm Supor filter (VWR 28147-956) housed in polypropylene filter holder . These >0.2 μm cell-enriched samples were removed from filter holder and stored in 300 μL of RNALater  at −80 °C. 1–2 L  of the < 0.2 μm filtrate were collected and filtered, using peristaltic pumps at a flow rate of about 1 L/h, onto a 0.02 μm Whatman Anotop filter . These corresponding 0.2–0.02 μm virus-enriched samples were stored sealed in filter housing at −80 °C. DNA extraction, sequencing, and read quality-control are described in the Quality-controlled reads, on average 9–10 million per sample Table , were asAll >3 kb contigs were filtered using VIRSorter v1.03  using thPelagibacter phage, S33 found enriched in aquatic viruses, and L7/12 found in assembled viral contigs [Viral contigs across the 13 reassemblies, along with viral contigs from two previous smaller datasets near Station ALOHA , 32, wer contigs . One pop contigs .The high proportion of novel viral diversity in our samples precludes using reference genomes for the detection of chimeras, which are expected to occur at a frequency of ~0.5% using metaSPAdes . As a reWe used terminal repeats (apparent circularity) to identify a nonredundant set of complete genomes , using aViral contribution was calculated for each sample as the proportion of reads mapping to the ALOHA 2.0 viral database (>95% across >45 bp). Prokaryotic contribution was calculated for each sample as the proportion of reads classified as bacterial or archaeal with Kaiju v1.6.2 .Reads from each sample were mapped using BWA-MEM to virus populations and filtered using msamtools at >95% across >45 bp. Anvi’o v3 [To examine temporal persistence, reads from a previous 2010–2011 dataset from Station ALOHA  were mapCrocosphaera mOTU not previously included was curated, and relative abundances were calculated using relative coverages of reads mapping to these 2569 mOTUs . Proteins with functional domains not found in previously reported datasets , 26 werePutative temperate phages were identified using i. functional annotations to identify phages with the genomic potential for lysogeny and ii. VIRSorter to identify integrated prophages. i. Functional annotations identified 922 populations with temperate phage markers . ii. VIRSorter identified prophages from original assemblies, of which 413 temperate phage populations shared significant homology (a minimum of 150 bp at 95% ANI); VIRSorter identified 73 final viral populations as prophages.Putative archaeal viruses were identified in unannotated populations using archaeal protein markers and sequence similarity to Archaea or archaeal viruses in RefSeq84 using archaeal markers (PFAM bit score >30). Populations carrying protein markers included one with AmoC , 16 withPutative eukaryotic viruses were identified using the nucleocytoplasmic large DNA virus capsid marker (PFAM bit score >30) and ≥2 proteins with top hits to eukaryotic viruses in RefSeq84 Table . All taxCrocosphaera phages were identified through a combination of methods. First, alignments to RefSeq84 revealed one putative Crocosphaera phage . 170 other potential Crocosphaera phages that displayed similar spatiotemporal distributions  near Station ALOHA around the same time [Prochlorococcus/Synechococcus cyanobacterial proteins than top hits to Prochlorococcus or Synechococcus proteins, for a final set of one “putative” and six “potential” Crocosphaera phages  here as the log-ratio of a population’s relative abundance (nucleotides mapped) in the virus-enriched versus cell-enriched size fractions. To calculate VC ratios, samtools bedcov  was usedPelagibacter and Puniceispirillum phages were identified, along with 12 complete archaeal virus genomes, 25 genomic fragments of eukaryotic viruses, and a putative Crocosphaera phage-like element . These samples were used to prepare DNA from cell-enriched >0.2 μm size fractions , and virus-enriched 0.2–0.02 μm size fractions . After metagenome assembly, curation, and classification Fig. , the 4.2ent Fig. , S5. Theent Fig.  not prevent Fig. , and CRIOn average across all depths, the ALOHA 2.0 viral dataset recruited 42% of reads from the virus-enriched fraction and 8% of reads from the cell-enriched fraction Fig. . AssuminWithin-sample α-diversity and richness revealed hotspots for virioplankton diversity, and confirmed it for prokaryotic diversity , at the The community-wide abundances of 1352 putative temperate phages displayed depth-specific patterns Fig. . In cellIn virus-enriched samples, we postulate that temperate phage signal represents temperate virus particles, which peaked at 150–250 m Fig. . This peGiven the low abundance of temperate phages in the upper 75 m Fig. , we infet test, p = 0.02). This trend provided further support for our temperate phage identifications using genomic markers. Nevertheless, intracellular temperate phage counts may reflect a variety of life history states. Intracellular temperate phage counts could represent prophage DNA still integrated in the host genome, replicating temperate phage that have have excised from the host genome, or temperate phage that entered directly into the lytic cycle immediately post-infection (in eclipse phase). Presuming that the temperate phage signal in the virus-enriched fraction represents packaged phage particles, ~98% of putative temperate phages appeared to have the ability to produce viral particles in situ . We shoSynechococcus phage genome, were thought to prevent photoinhibition by supplementing declining host photosynthesis during infection [Prochlorococcus hosts [Virus-encoded copies of photosystem reaction center genes were first observed in a nfection , and werus hosts , 75. Phous hosts , yet theus hosts .Fig. 6DiViral-encoded ammonium transporter genes, which shared highest similarity to bacterial homologs Table , increasPhoH genes are used during phosphorus starvation , upregulMany virioplankton populations displayed temporal persistence through the 1.5-year time series Figs. , S9, conViral assemblages displayed stratified depth structure, with shifting depth ranges along the transition zone between surface and mesopelagic waters Figs. , S9. ThiSeveral different archaeal lineages, including Euryarchaeota and Thaumarchaeota (formerly Group I marine Crenarchaeota ) are comCrocosphaera can fix both nitrogen and carbon, and plays an important role in fueling primary production in nutrient-poor open ocean environments [Prochlorococcus and Synechococcus [Crocosphaera phage sequences have yet been identified in current databases. We identified the genome of a putative Crocosphaera phage or phage parasite based on multiple lines of evidence: sequence similarity to Crocosphaera in 11 of 15 proteins, similar spatiotemporal abundance profiles to that expected from Crocosphaera (summer in the upper ocean), and presence during a confirmed Crocosphaera “bloom” near Station ALOHA around the same time [Crocosphaera at ~37.4% [Prochlorococcus at ~32% [Crocosphaera phages (Table Crocosphaera, their presence during a Crocosphaera “bloom” in one set of samples, and their dissimilarity from Prochlorococcus or Synechococcus gene homologs.The unicellular cyanobacterium ronments . Althoughococcus , no Crocame time . This get ~37.4% , compare at ~32% . Account at ~32% , 94. Thees Table  based onCrocosphaera phages or phage parasites that have not been previously identified. Taken together, these new data and analyses provide new insight on the spatiotemporal patterns of planktonic viral diversity, reproductive strategies and metabolic repertoires in the open ocean. Furthermore, simultaneous ennumeration of extracellular and intracellular viruses and their hosts sets the stage for delineating more specific host-virus interactions.Viruses impact the ecology and biogeochemistry of microbial communities across the oceans. Our study recovered a large fraction of dsDNA viruses found at Station ALOHA, revealing a hotspot for microbial diversity at the base of the euphotic zone, where the majority of viruses were distinct from those previously reported. The concurrent characterization of both intracellular and extracellular viruses provided independent support of temperate phage identification using marker genes, and revealed community-wide shifts in viral reproductive strategies. In this open-ocean environment, lytic interactions dominated the upper photic layer above the DCM, and temperate phages were most abundant in the mesopelagic ocean. Temporal variability in reproductive strategies appeared most prevalent in transitional depths at the base of the euphotic zone, marked by a peak in prophage integration and induction. Environmental distributions of viral AMGs also displayed depth-specific patterns in energy and nutrient acquisition. For example, photosystem genes were most abundant at light-limited depths around the DCM; bacteriophage-encoded ammonium transporter genes increased along with potential ammonia-oxidizing thaumarchaeal competitors; phosphorus starvation genes increased in tandem with N:P ratio. Although most viruses were temporally persistent over several years, some displayed temporal variability that appeared to reflect the seasonal distributions of specific hosts. These temporal patterns, in conjunction with other lines of evidence, led to the identification of putative Supplementary methodsSupplementary legendsFigure S1Figure S2Figure S3Figure S4Figure S5Figure S6Figure S7Figure S8Figure S9Figure S10Table S1Table S2Table S3Table S4Table S5Table S6Table S7Table S8Table S9Table S10


Several oncolytic viruses (OVs) including various human and canine adenoviruses, canine distemper virus, herpes-simplex virus, reovirus, and members of the poxvirus family, such as vaccinia virus and myxoma virus, have been successfully tested for canine cancer therapy in preclinical and clinical settings. The success of the cancer virotherapy is dependent on the ability of oncolytic viruses to overcome the attacks of the host immune system, to preferentially infect and lyse cancer cells, and to initiate tumor-specific immunity. To date, several different strategies have been developed to overcome the antiviral host defense barriers. In our study, we used canine adipose-derived mesenchymal stem cells (cAdMSCs) as a “Trojan horse” for the delivery of oncolytic vaccinia virus Copenhagen strain to achieve maximum oncolysis against canine soft tissue sarcoma (CSTS) tumors. A single systemic administration of vaccinia virus-loaded cAdMSCs was found to be safe and led to the significant reduction and substantial inhibition of tumor growth in a CSTS xenograft mouse model. This is the first example that vaccinia virus-loaded cAdMSCs could serve as a therapeutic agent against CSTS tumors. The use of oncolytic virus strains is a novel approach for the treatment of canine cancer patients. Several different oncolytic viruses (OVs) have successfully been tested in the treatment of canine tumors ,2,3,4. OIn general, carrier-mediated deliveries of OVs may protect the virus against the components of the host innate or acquired immune system and may increase the efficacy of viral tumor colonization. In our study, we examined canine adipose-derived mesenchymal stem cells (cAdMSCs) as a carrier for delivery of oncolytic vaccinia virus strains. These cells are relatively easy to isolate from canine adipose tissue and have similar immunomodulatory potency compared to canine bone marrow-derived mesenchymal stem cells ,15. In aOur data showed that vaccinia virus-loaded cAdMSCs have abilities to home to sites of tumor growth and to substantially inhibit the tumor growth in canine soft tissue sarcoma xenograft mouse model.All mouse animal experiments were carried out in accordance with protocol approved by the government of Unterfranken, Germany, according to the German Animal Welfare Act (TierSchG) (permit numbers: RUF-55.2-DMS-2532-2-610). The canine soft tissue sarcoma (STSA-1) cell line was obtained from Dr. A. MacNeill  and was derived from a canine patient with a low-grade II soft-tissue sarcoma . The proSucrose gradient purified C1-opt1, W1-opt1 or L3-opt1 (thymidine kinase (TK)-inserted Turbo-FP635 engineered Copenhagen (C1), Wyeth (W1) or LIVP (L3) strains) vaccinia viruses were provided by Tanja Auth, StemVac GmbH, Bernried, Germany.2.Cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with antibiotic-solution  and 10% fetal bovine serum  for African green monkey kidney fibroblasts (CV-1) cell line  and 20% FBS for canine prostate carcinoma cell line CT1258 at 37 °C under 5% COSTSA-1 cells were cultivated in minimum essential medium (MEM) with Earle’s salts supplemented with 2 mM of glutamine, 50 U/mL of penicillin G, 50 µg/mL of streptomycin, 1 mM of sodium pyruvate, 0.1 mM of nonessential amino acids (MEM-C), and 10% FBS.The virus-infected cells were examined using an Axiovert 200M microscope  with Axiovision 4.5 software . Digital images were processed with Photoshop 7.0 .Adipose tissues from dogs were obtained by surgical intervention and were isolated and cultured as described before . In brieAfter isolation and culture, cAdMSCs were characterized by trilineage differentiation as described elsewhere . FACS anFor the viral replication assay, STSA-1, CT1258, or cAdMSC cells were infected with C1-opt1, W1-opt1, or L3-opt1 vaccinia virus strains at a MOI of 0.5. After one hour of incubation at 37 °C, the infection medium was removed and replaced by fresh growth medium. After 3 h, 24 h, 48 h, 72 h, and 96 h, the cells and supernatants were harvested. Following three freeze-thaw cycles and three times sonication (three times at 30 s), serial dilutions of the supernatants and lysates were tittered by standard plaque assay on CV-1 cells. All samples were measured in triplicate.n = 3.The viral cytotoxicity in cAdMSCs was quantitatively assessed by LDH viability  which is based on detecting lactate dehydrogenase released from damaged cells. For this purpose, cAdMSCs seeded in 24–well plates were infected with C1-opt1, W1-opt1, or L3-opt1 vaccinia virus strains at a MOI of 0.5. After one hour of incubation at 37 °C, the infection medium was removed and replaced by fresh growth medium. After 3 h, 24 h, 48 h, 72 h, and 96 h, cell-free supernatant aliquots were collected from each experimental sample and LDH in the culture supernatants was measured using the Pierce LDH Cytotoxicity Assay Kit, following the manufacturer’s instructions. These measurements were performed with Tecan Sunrise Remote microplate reader  at wavelengths of 490 nm and 680 nm. The results were shown as fractions of LDH release. Data were presented as mean standard deviation (SD), For detection of the virus-encoded proteins, STSA-1 or CT1258 cells were harvested and resuspended in SDS sample buffer at 24 h, 48 h, 72 h, or 96 h post virus infection (hpvi). Samples were separated by 10% SDS-Polyacrylamide gel electrophoresis and subsequently transferred onto a nitrocellulose membrane . After blocking in 5% skim milk in PBS, the membrane was incubated with rabbit polyclonal antibody against red turboFP635 protein  or polyclonal rabbit anti-vaccinia virus antibody . The primary antibodies were detected using horseradish peroxidase-conjugated anti-rabbit  secondary antibody, followed by enhanced chemiluminescence detection.6 canine soft tissue sarcoma (STSA-1) cells subcutaneously into the right hind leg of six- to eight-week-old female nude mice (Athymic Nude-Crl:NU(NCr)-Foxn1nu, Charles River, Sulzfeld, Germany). Tumor growth was monitored at least once a week in two dimensions using a digital caliper. Tumor volume was calculated as [(length × width2)/2]. When tumors reached 300–500 mm3, STSA-1 mice were randomized, distributed into three groups (n = at least 3), and injected with a single intravenous dose of either C1-opt1 alone (2.5 × 106 pfu), cAdMSCs alone (2.5 × 105 cells), or a combination of C1-opt1/cAdMSCs , previously co-incubated for 2 h at 37 °C. Mice were monitored for changes in body weight and signs of toxicity. The significance of the results was calculated by two-way ANOVA at 0.05 level of significance. Results are displayed as means ± SD.The STSA-1 xenograft tumors were generated by implanting 4 × 10For histological studies of the xenograft model, tumors were excised and snap-frozen in liquid nitrogen. Tissue samples were sectioned (7-mm thickness) with the cryostat CM3050 S . The VACVs were labeled using CODEX tag-conjugated polyclonal rabbit anti-vaccinia virus (anti-VACV) antibody  and ATTO 550 tag-conjugated fluorescent dye . The fluorescence-labeled preparations were examined using a BZ-X800 fluorescence microscope  equipped with the BZ-X800 Analyzer software .The presence of the C1-opt1 in the sera of virus-injected mice was determined by PCR analysis with specific primers for turboFP635 (Forward 5’ATGGTGGGTGAGGATAGCGTGCT3′ and Reverse 5′TCAGCTGTGCCCCAGTTTGCTAGG3′) and for hemagglutinin gene A56R (Forward 5′-ACGGCCGACAATATAATTAATGC-3′ and Reverse 5′-CATCATCTGGAATTGTCACTACTAAA-3). Sucrose gradient-purified C1-opt1 virus (Copenhagen strain) was used as PCR-positive control (detection LIMIT < 100 pfu/50 µL serum).7 pfu/mL) (The three new recombinant oncolytic vaccinia virus (VACV) strains used in this study, expressing the red turboFP635 fluorescent protein (FP635), were kindly provided by StemVAC GmbH, Bernried, Germany. The construction details of these strains will be published elsewhere. The oncolytic effects of VACVs were studied in a panel of two different canine cancer cell lines, including soft tissue sarcoma (STSA-1)  and pros pfu/mL) B.In order to confirm the virus replication in canine cancer cell lines CT1258 and STSA-1, we followed virus-mediated expression of FP635 by Western blot analysis . In thesCanine AdMSCs were obtained from the adipose tissue of healthy donors as described in the Material and Methods section. The cAdMSCs were characterized for their capability to differentiate into three main mesodermal lineages. This could be shown by formed lipid droplets (adipogenic), calcium deposits (osteogenic) and build glycosaminoglycans (chondrogenic) , and theFACS analysis was performed from passage 3 (p3) of cAdMSCs with antibodies for stemness markers CD44, CD90, and non-stemness markers CD45 and MHCII . CD44 an6 pfu/mL, five-fold increase compared to loaded virus at 0 hpi) and for C1-opt1 at 72 hpvi   .In these experimental settings, all viruses efficiently infected cAdMSCs, as demonstrated by the virus-mediated expression of the turboFP635 protein determined by fluorescence microscopy at 96 hpvi .Finally, we also tested the cytolytic effects of the three viruses on the canine stem cells after infection using the Pierce LDH cytotoxicity assay kit . Surprisingly, we found that under these experimental conditions (MOI of 0.5) only about 30% to 50% of the infected stem cells were lysed at 96 hpvi .In summary, our studies demonstrated that the used vaccinia virus strains infected und replicated in canine AdMSCs without a significant lysis (less than 15%) of the stem cells at least in the first two days of infection. Therefore, cAdMSCs could be useful as a “Trojan horse” for the delivery of VACVs. For animal experiments, we chose C1-opt1 (Copenhagen strain), since the strain was optimal concerning tumor cell lysis and replication in cAdMSCs.6 canine soft tissue sarcoma (STSA-1) cells subcutaneously into the right hind leg of seven-week-old female nude mice (Athymic Nude-Crl:NU(NCr)-Foxn1nu, Charles River Germany). Four weeks post implantation, all mice developed tumors with volumes of 200 mm3 to 500 mm3. Animals were separated into three groups (n = at least 3) and injected intravenously (i.v.) with a single dose of either C1-opt1, cAdMSCs, or a combination of both into the lateral tail vein. The cAdMSCs-injected mice were used as a control.The STSA-1 xenograft tumors were generated by implanting 4 × 103), all animals in the control cAdMSCs group were euthanized after 13 days post injection (dpi). At this timepoint, there was no significant difference between the two virus-treated groups (C1-opt1 vs. cAdMSCs/C1-opt1).As shown in The toxicity of the combination therapy was determined by monitoring the weight change of mice over time B. All vi3–105-fold higher when compared to PFUs in the lungs of corresponding animals at the same timepoint (In order to analyze the oncolytic effects of C1-opt1 virus alone and in combination with cAdMSCs in STSA-1 xenografts, we compared the virus colonization in different organs and tumor tissues. imepoint . Taken tIn addition, the presence of virus was analyzed by immunohistochemistry. For this purpose, tissue sections of primary tumors of STSA-1 tumor-bearing mice injected with C1-opt1, cAdMSCs/C1-opt1 at 24 dpvi and with cAdMSCs alone at 13 dpi were prepared as described in the Materials and Methods section. The histological data revealed a massive viral distribution in the tumor tissues of the C1-opt1- and C1-opt1/cAdMSCs-infected groups at the last stage of infection B,C. In bIn the current study, we investigated the oncolytic efficacy of three new VACVs, namely C1-opt1, W1-opt1, and L3-opt1, expressing the red turboFP635 protein, in STSA-1 and CT1258 canine cancer cell lines. The results showed that all vaccinia virus strains were able to effectively infect, replicate in, and lyse the tested canine tumor cells. The virus infection led to efficient expression of FP635 under cell culture conditions. In addition, we showed, for the first time, that vaccinia virus strains can efficiently infect cAdMSCs at a lower MOI of 0.5. Interestingly, the virus replication in cAdMSCs was about 40–60-fold lower than in canine cancer cells at the same MOI . The reaThe lysis of the virus-infected cAdMSCs seemed to be relatively delayed under the applied cell culture conditions. At a MOI of 0.5, only about 15% of the cells were lysed in the first two days of virus infection . For aniThe oncolytic effects of C1-opt1-loaded cAdMSCs and the C1-opt1 alone were tested in mice with STSA-1 tumor xenografts. The results demonstrated that both C1-opt1 alone and when loaded into the stem cells achieved a significant inhibition of tumor growth in the STSA-1 canine xenograft models. In the both cases, the STSA-1 tumor xenografts demonstrated a typical three-phase growth curve, and the tumor regression was observed as early as 14 days after virus injection, as described in previous studies ,22. HoweThe analysis of virus distribution in STSA-1 tumor-bearing nude mice at 24 dpvi revealed that C1-opt1 preferentially replicated in cancerous tissue B,C. We aGenerally, the C1-opt1 virus seems to be highly tumor-specific, since C1-opt1 was mainly detected in the tumor tissue of all treated animals . ConcernFinally, the application of cAdMSCs in mice was not toxic and led to a moderate effect on the body weight of the injected animals B. TherefHowever, the therapeutic efficacy of combination of cAdMSCs and the C1-opt1 vaccinia virus strain should be confirmed in clinical trials with canine cancer patients.


Pteropus medius roosts, and patterns of land-use change in Bangladesh over the last 300 years. We found that 53% of annual variation in winter spillovers is explained by winter temperature, which may affect bat behavior, physiology, and human risk behaviors. We infer from changes in forest cover that a progressive shift in bat roosting behavior occurred over hundreds of years, producing the current system where a majority of P. medius populations are small (median of 150 bats), occupy roost sites for 10 years or more, live in areas of high human population density, and opportunistically feed on cultivated food resources—conditions that promote viral spillover. Without interventions, continuing anthropogenic pressure on bat populations similar to what has occurred in Bangladesh could result in more regular spillovers of other bat viruses, including Hendra and Ebola viruses.Nipah virus is a bat-borne paramyxovirus that produces yearly outbreaks of fatal encephalitis in Bangladesh. Understanding the ecological conditions that lead to spillover from bats to humans can assist in designing effective interventions. To investigate the current and historical processes that drive Nipah spillover in Bangladesh, we analyzed the relationship among spillover events and climatic conditions, the spatial distribution and size of  Despite successes in decreasing the burden of infectious diseases during the 20th century ,2,3,4, eHenipavirus) is hosted by various Pteropus fruit bat species with partially overlapping ranges across countries of South and Southeast Asia [Nipah virus  from silver date palm trees (Phoenix sylvestris) [Distinct outbreaks of Nipah virus infection have highlighted that the same pathogen may use multiple routes to spillover. Nipah virus was first discovered following an outbreak of febrile illness in pigs, pig farmers, and abattoir workers in Malaysia and neighboring Singapore between September 1998 and May 1999 ,37,38,39vestris) ,46,47. Gvestris)  and the vestris) . The indvestris) . Lastly,vestris) ,51 with vestris) . Human-tvestris) ,43,52,53vestris) ,55. ThusPteropus medius (formerly P. giganteus) frequently visit date palm trees to consume sap, potentially contaminating sap by licking the shaved area of the tree, urinating or defecating in the collection pots, or, in some cases, becoming trapped and dying in the pot [P. medius are highest during winter months  when date palm sap is primarily harvested to drink fresh (October to March or April) [Phoenix sylvestris is a native species in Bangladesh [P. medius is found throughout Bangladesh and bats shed Nipah virus in their urine in all seasons [P. medius is generally low [One striking similarity between Nipah virus ecology in Bangladesh and Malaysia is that spillovers were facilitated by human resource supplementation in modified landscapes . In Mala the pot ,59,60. Vr April) ,60,61 anr April) . While Pngladesh ,64,65,66 seasons . Nipah v seasons ,69; most seasons ,47,59. Wally low , presentally low . These pP. medius in Bangladesh. Like other Pteropus spp. bats, P. medius populations appear to be in decline due to hunting and habitat loss [P. medius also appears to thrive in the human-dominated landscapes of Bangladesh. This adaptability derives from the opportunistic feeding habits of Pteropus species and their ability to forage over large areas [P. medius roosts in Bangladesh are found in areas with higher human population density, forest fragmentation, and supplemental food resources from residential fruit trees [P. medius roosts or total bats in the village or within 5 km of the village boundary than villages where spillovers have not been detected [P. medius roost sites and population trends, including mapping of food resources used by bats, would provide a better understanding of P. medius interactions with humans. Lastly, we lack a historical perspective on how land-use changes in Bangladesh may have influenced P. medius populations and behavior, thereby setting the stage for the emergence of Nipah virus. Analysis of these aspects of Nipah virus ecology will provide clearer insights into the potential drivers of Nipah virus spillover from bats.However, there are still aspects of Nipah virus ecology in bats and their interface with human populations that are unclear. First, there is substantial year-to-year variation in the number of Nipah virus spillover events in Bangladesh  that maytat loss ,71,72, bge areas ,73,74,75ge areas , more P.it trees ,78. Howedetected . NationaP. medius roosting sites, we hypothesized that spatial variables related to climate, human population density, land-use, and anthropogenic food resources such as fruit trees and date palm trees could explain variation in the occupancy and size of roosting bat populations. Lastly, we hypothesized that land-use change, specifically the loss of primary forests, has been a continuous process throughout human occupation of the region that was accelerated during British occupation. This progressive loss of forests likely led to a shift in roosting sites toward more urban areas closer to anthropogenic food resources, a condition that facilitates spillover but predates the first recognized outbreaks of Nipah virus infection by many years. By assessing these patterns, we develop a more comprehensive view of Nipah virus ecology in Bangladesh and provide a path forward for research and management of this system.The objective of this study was to describe the ecological factors that contribute to a higher likelihood of Nipah virus spillover, including climate effects on bat behavior or physiology, the geography of bat roosting sites in Bangladesh, and the relationship between historical land-use change and bat roosting behavior. Following the results of Cortes et al. , we hypoTo investigate the spatial and temporal patterns of Nipah virus spillover in Bangladesh, we compiled data on the number of spillover events and affected administrative districts during 2001–2018. Cases prior to 2007 were detected through community investigations following reports of clusters of encephalitis. Cases from 2007 onward reflect those identified through systematic surveillance for Nipah virus infection at three tertiary care hospitals combined with investigations of all cases detected to look for clusters, as well as any reports of possible outbreaks through media or other information sources . IndepenExpanding on the results from Cortes et al.  showing Pteropus medius in Bangladesh was inferred from a countrywide survey of villages as part of investigations regarding risk factors for Nipah spillover performed over the winters of 2011–2012 and 2012–2013 [Phoenix sylvestris) and known feeding sites that bats were reported to visit within 500 m of the villages. Feeding sites included fruit trees planted in orchards or in residential areas: jujube (Ziziphus mauritiana), banana, mango, guava, lychee, star fruit, jackfruit, papaya, sapodilla (Manilkara zapota), mulberry, hog plum (Spondias mombin), Indian olive (Elaeocarpus serratus), and other species.The spatial distribution of 012–2013 . BrieflyP. medius in two colonies in Bangladesh were estimated to be 10.8 km and 18.7 km; thus, 15 km was chosen to represent the distance a bat might expect to travel to reach a suitable feeding site [To evaluate spatial covariates that could explain the occupancy (presence/absence of bats) and abundance (estimated population size) of bats living in mapped roost sites, we extracted data from available raster surfaces describing human population density, land-use, bioclimatic variables , elevation, slope, and forest cover. Spatial covariate raster files were downloaded from WorldPop ,83, the ing site . The numP. medius on tall trees for roosting and various native and cultivated fruit trees for food, we gathered data on historical changes in land-use, particularly forested lands, across Bangladesh from data sources covering separate but overlapping time periods. Reconstructed natural biomes and anthropogenic biomes from 1700–2000 were extracted from rasters produced by Ellis et al. [2 for settlements, >2500 persons/km2 for urban areas), rice villages and other croplands or rangelands, and forested areas, including populated woodlands and remote forests. Land-use data for the years 1992, 2004, 2015, and 2018 were downloaded from the Organization for Economic Cooperation and Development (OECD) land-cover database [gfcanalysis [2 [Given the reliance of s et al.  using ths et al.  and avaidatabase , deriveddatabase . Data fodatabase . Land codatabase  using thanalysis ,94. For MASS [MuMIn [Separate Nipah virus spillover events were clustered geographically by the latitude and longitude of affected administrative districts and temporally by the date of illness of each index case using a bivariate normal kernel via the R package MASS . To examMASS  using thS [MuMIn .caret, glmnet, and ranger [The importance of spatial covariates in explaining variation in the occupancy and abundance of bats at roost sites was assessed through a combination of linear modeling and machine learning. The covariates were standardized, and data were split into two sets: an occupancy dataset of 488 mapped roost sites with a binary variable describing whether bats were currently present or not and an abundance dataset of 323 mapped roost sites with the estimated count of bats at each currently occupied roost at the time of the interview. Both datasets were split into training (80%) and testing (20%) sets for validation of models . Generald ranger ,102,103.p < 0.001; p > 0.05; On the basis of 183 spillover events from 2001–2018, we confirmed previous analyses ,44,48 shInterviewers mapped a total of 474 roost sites in and around 204 villages, 315 that were occupied at the time of the interview and 159 that were unoccupied. According to interviewees, most occupied roosts  were reported as being at least occasionally occupied for more than 10 years, with an average occupancy duration of 8.5 years A. The maP. medius demonstrate that this distribution of individual roost sizes is similar to those reported in Pakistan, India, Nepal, and Sri Lanka [P. lylei in Cambodia and Thailand [P. alecto and P. poliocephalus in Australia estimated in the tens of thousands [The size of occupied roosts varied widely, from only one bat to an estimated 8000 bats at one roost in west–central Bangladesh, with a median size of 150 bats A,B. Studri Lanka ,109,110.Thailand ,111, andhousands ,113,114.2R of 15% or less for testing and training sets , interviewees report that, with respect to their own memory, most roosts are decreasing in size A. These rhunting ,67. Locarhunting . In suppAccording to the collated data, the majority of forest loss in Bangladesh occurred prior to the 20th century but has steadily continued to the present . Prior tFollowing the Battle of Plassey in 1757, the British East India Company took control of the country and established Permanent Settlement, a system of land taxation that set a fixed tax burden for landholders (zamindars). While the intention was that the fixed tax rates would allow zamindars to invest more in agricultural development of the land through better seeds, irrigation, and tools, this never materialized. Since the British would auction the zamindars’ land if they fell behind on their tax obligation, land became a valuable commodity that was bought and sold by wealthy bureaucrats and zamindars. This fostered a hierarchical system where the peasantry working the land paid rent but had no property rights, while landowners were only attached to the land through a series of intermediary managers. To meet their tax obligation and collect rent from tenant farmers, landowners encouraged cultivation of cash crops  meant for export in the global market. Agrarian production increased not through agricultural intensification of already cultivated land, but through clearing of native forest. Forest cover declined dramatically during the 1700s and 1800s  and the Phoenix sylvestris. While, historically, date palm sugar was used locally for the preparation of sweetened foods, it became integrated into the global sugar trade starting in 1813, and the value of date palm sap increased. The number of date palms in Bangladesh increased rapidly from the 1830s and remained high until at least the early 1900s, propelled by British encouragement of landowners and the development of mills by the British to produce sugar from date palm sap [gur) was produced from date palm sap on average during 1792–1813 in Bangladesh, which increased to 38,000 t of gur in 1848 and 162,858 t by 1905, and then decreased to 66,930 t by 1911 [2 with a production of 169,056 mt of palm sap (perhaps 10% of which might be converted to gur) [2 under sugarcane producing 3,862,775 t of sugarcane juice during the same year [Production of sugar for export and local consumption came predominantly from sugarcane during the colonial period, but a minor proportion (perhaps 10–15%) was produced from date palm sap from cultivated palm sap . Roughly by 1911 . The mos to gur) ,118. Thiame year .2 in 2010 [Today, Bangladesh has less than 14% of its forest remaining , and the in 2010 .P. medius relies on tall tree species such as banyan  to form large roosts [Recent deforestation in Bangladesh has continued at a steady pace, with a net rate of 0.75% or less per year during 1930–2014 , and is e roosts , the losPteropus medius bats now live in mostly small, resident roosts in close proximity to humans and opportunistically feed on cultivated food resources. These gradual but dramatic changes have produced a system that facilitates spillover of a bat-borne virus. The consequence is almost annual spillover of Nipah virus in winter months following consumption of raw or fermented date palm sap that has been contaminated with bat excreta containing Nipah virus.Given the nearly two decades of research on Nipah virus in Bangladesh, there are facets of its ecology that are now clear. Historical patterns of forest loss have drastically diminished native habitat for fruit bats. P. medius, the majority of the land-use change from forest to cultivated areas occurred at least a century ago  [We propose that the systems of Nipah virus in Bangladesh and Hendra virus in Australia represent distinct points on a continuum describing patterns of bat aggregation and feeding behavior in a landscape of available roosting sites and food resources . One end review) . Similar review) .P. medius roosting behavior may have modulated the frequency of spillovers into human populations in multiple ways. The frequency of spillovers depends on a cascade of events including viral shedding by reservoir hosts, survival of the virus in the environment, and human behavior that leads to exposure to the virus [P. medius in India that larger colonies occupy more roost trees [P. medius roosts in villages with reported Nipah virus spillovers, and both smaller roosts and the occurrence of human Nipah virus cases were associated with greater forest fragmentation [Pteropus populations in Australia indicate that the landscape density of bat roosts, not the population density of bats, is associated with Hendra virus spillover [The proposed shift in he virus . Decreashe virus . It is ast trees . Such beentation . Multiplpillover . This asP. medius shed Nipah virus at low levels throughout the year but with no consistent periodicity or seasonality across years [tari production, but harvesting increases during winter months to meet increased demand for tari and fresh sap [P. medius to date palm trees are more frequent in winter [tari production . Therefore, the risk of viral spillover is always present, but may increase during winter because bats are capitalizing on a resource when it is most available, thereby increasing the probability that sap is contaminated during the winter harvest. While infection dynamics in bats could theoretically result in higher levels of shedding during winter, aligning with peak human consumption of date palm sap, there is no evidence that this is a consistent annual pattern [Beyond the broad ecological forces that facilitate henipavirus spillover from bats, there are epidemiological patterns that will require further research to explain. Perhaps the most complex are the causes of winter seasonality in Nipah virus spillovers. Recent evidence suggests that ss years . There wss years . Periodsss years  but weress years . Date paresh sap ,47. Visin winter , even wh pattern .Phoenix sylvestris to seasonal weather conditions , yet no data are available on variation in sap flow or sugar content for this species outside of winter months [P. medius feeding behavior and the fruits they consume at different times of the year would be necessary to assess this hypothesis [The observation that more Nipah virus spillovers occur during years with colder winters indicates that climate is affecting one or more factors in the system: date palm physiology, bat and human behavior, bat physiology and immunology that affect viral replication, or some combination of these factors. Date palm sap collectors report that date palm sap is sweeter and flows more freely during cooler weather ,60,65. Tr months ; hence, pothesis . Complempothesis .P. medius are shedding more Nipah virus when they are experiencing physiological or nutritional stress in winter is an open question. We need more documentation of body condition, biomarkers of stress and immune function, or abortion rates among female bats to understand any relationships among Nipah virus shedding, stress, and climate [Another hypothesis, derived from research on Hendra virus in Australian bats, posits that bats shed viruses more frequently during periods of nutritional stress that compromise bat immune function ,129. Inc climate ,131,132.P. medius roost populations vary seasonally, with larger populations in fall and winter than in summer [P. medius home ranges contract during the dry season (including winter) in comparison to the wet season [P. medius and Nipah virus in Bangladesh indicate that bat movements are common enough to promote genetic admixture and spread distinct Nipah virus genotypes among geographically distant P. medius populations [We also lack information on how seasonal bat movements might influence Nipah virus spillover dynamics. Although our data suggest that most roost sites are continuously occupied , there mn summer ,134. Thit season . Neverthulations . To bettP. medius populations. While historical patterns of deforestation and land-use change have undoubtedly reduced available habitat for pteropodid bats  [Lastly, there is a need to explore possible interventions to prevent Nipah virus spillover. Without a vaccine for Nipah virus, much of the research has focused on mitigating the risk of spillovers. Several studies in Bangladesh have centered on educating the public about the risks of drinking raw date palm sap and methods for preventing bat access to date palm sap during collection ,136,137.st sites ,138,139.st sites ,140, thist sites . A 2009  of pigs . Animalsellifer) . Therefotari) and had numerous bats living in trees around their home [Similar risks may apply in neighboring India where Nipah virus outbreaks have been linked to fruit bats ,142. Theeir home . Researceir home ,48. The eir home . Silver eir home . The nareir home  but migheir home ,135. SucP. medius, such as cotton silk , Indian mast tree , and Singapore cherry . Trees that produce fruit year-round or specifically during winter could provide bats with the required nutrition that would have been acquired from date palm sap or other cultivated fruits. In combination with methods to prevent bat access to date palm sap, ecological interventions that would allow P. medius populations to persist in Bangladesh and other areas while lowering the risk of Nipah virus spillover should be explored.At a higher level, methods that limit human–bat contact through ecological interventions may be beneficial. Plantations of fruit- and nectar-producing tree species could provide alternative food for P. medius has allowed populations to adapt to these modified landscapes, persisting in small, resident colonies feeding on cultivated fruits. Shared use of date palm sap by bats and humans is a key route for Nipah virus spillover during winter months. Continued research on this system could reveal how bat behavior and physiology influence the seasonality of Nipah spillovers and explore potential ecological interventions to prevent spillover.The ecological conditions that produce yearly spillovers of Nipah virus in Bangladesh are not a new phenomenon, but rather a culmination of centuries of anthropogenic change. The opportunistic feeding behavior of


We consider alternative history scenarios in which explicit climate mitigation begins before the present day, estimating the total costs to date of delayed action. Considering a 2(1.5) degree Celsius stabilization target, peak costs are greater and reached sooner with a later start to mitigation, reaching 15(17)% of global GDP in 2085(2070) for a 1990 start and 18(35)% in 2080(2035) for a 2020 start. Further mitigation delay costs a best estimate of an additional 0.5(5) trillion dollars per year. Additional simulations show how optimal mitigation pathways evolve without imposing a warming limit, finding that median abatement levels and costs are not strongly dependent on start date. However, whereas 18(5) percent of optimal solutions starting in 1980 meet the 2(or 1.5) degree target, 5(or 0)% of 2020 simulations meet the goals. Discounted damages due to delayed mitigation action rise by 0.6 trillion US dollars per year in 2020. Such a framework is required to justify actions or in-actions in the present informed by potential costs of mitigation, adaptation, or impacts which might be incurred in the future. Such a process also allows the potential costs arising from greenhouse gas emissions to be incorporated into an established economic system, by defining a “social cost of carbon” quantifying future damages (costs of impacts) from present day emissions3, are the primary type of research tool used to evaluate multiple costs and benefits of climate change policies4. Their representation of economic damages from climate change impacts, however, is usually defined as aggregate relationships between global average warming levels and damages whose parameters are defined by meta-analysis5. These “damage functions” are uncertain: there is physical model disagreement on how some key future economic damages such as extreme rainfall will scale with temperature6, and Earth System Models generally lack the complexity to fully resolve the dynamic ice-sheet processes necessary to capture the range of possible sea level rise7. From a socio-economic perspective, there is wide uncertainty in how changes in the climate system translate to impacts on the economy, and how that translation will depend on the changing vulnerability of society over time9. Damage functions can be estimated either on the basis of “bottom up” sectoral impact projections14 or by “top-down” methods based on statistical analysis of historical temperature-GDP relationships16. Representing damages at the process level is done in some “detailed process” IAMs for specific sectors . Fuller incorporation would require coupled consideration of human and physical systems which influence factors such as agricultural productivity and habitability of environments18 and such capacity, where it exists at all, only describes a subset of human-climate interactions19. As a result, a wide range of climate damage functions can be justified in economic models20, and damages for a given level of warming can vary by an order of magnitude depending on the assumptions made21. The damage function in the DICE (Dynamic Integrated Climate-Economy) 2013R model used in this study22 can be modulated to span the range of damages observed in the literature , so-called benefit-cost IAMssee Fig. .Figure 123 and economic pathways24 and baseline characteristics25 - which can result in a wide range of possible costs for achieving a given abatement level. In DICE 2013R, mitigation costs are represented in an aggregate sense by a set of exogenous and endogenous variables. The former include a marginal abatement cost function describing the cost of each additional unit reduction of emissions relative to a baseline case in which no mitigation occurs, including the cost of a backstop technology, defined as the cost of a generic zero-carbon technology assumed to be available in the future in unlimited supply if abatement costs become high enough. The level of abatement, including use of the backstop technology, as a function of time is then determined in the process of optimizing the scenario pathway. By sampling the marginal abatement cost function parameters in DICE, a range of costs can be simulated consistent with the uncertainties in the IAM literature 27, but for the climate problem, century scale changes raise questions of inter-generational fairness28 which some have attempted to resolve through an ‘inter-generational discounting’ rate which explicitly resolves benefits and costs for those not yet born30.A wider conceptual question also exists whether existing economic principles are appropriate for climate change. A traditional exponential discount rate might be appropriate for representing present and future costs for a single person24. For example, the major IAMs used to produce emissions and land use scenarios to drive global climate models in big international coordinated efforts, as for producing CMIP (Coupled Model Inter-comparison Project) ensembles, which in turn inform the IPCC  process, are generally initialized in a present-day, or near present-day, state.Most IAM applications simulate current and future policies which represent a possible joint evolution of climate and society31, and to inform issues related to accountability and responsibility for damages. For example, hindcasts of how stratospheric ozone concentrations (and their climate implications) might have evolved with alternative CFC policies have improved understanding of policy approaches to that issue32. Similarly33, investigated the relevance of the timing of the start of negative emissions as an approach to returning CO2 to pre-industrial levels by simulating the effect of a delay in such measures from 2013 to 2021.There are some questions, however, for which a retrospective approach might be useful. Hindcasts, by which we mean model projections that begin in a historical year and are then compared to actual experience since then, can be used to evaluate model performance, to improve understanding of the effectiveness of alternative policy options including those related to the timing of actions34, requiring the joint consideration of past and future emissions, compensation for potentially uncertain impacts and an assessment of what is fair. Although a discussion of the ethical considerations is not the subject of this paper, establishing responsibility for damages which have arisen as a result of the action or inaction of an individual, nation state or company will require (amongst other things) a practical assessment of what impacts might have occurred in a counter-factual world where other choices had been made35.Regarding the historical responsibility for damages, the ethical framework for such issues is a subject of research and debateIn the following paper, we attempt a more general discussion of this concept by developing a set of alternative histories where significant global climate mitigation had begun at various points in the past. Using this approach, we seek to address a number of key questions: first, within a cost-effectiveness framework, how might the costs of mitigation to reach the temperature goals of the Paris Climate Accord have differed, had a least-cost emissions pathway been enacted beginning at alternative points in the past, and what is the ongoing annual cost of delay in adopting a least-cost decarbonization pathway. Secondly, within a cost-benefit framework without a pre-defined temperature target, but with a joint assessment of mitigation costs and climate damages, how would the optimal pathway have evolved given an initialization of climate policy in a past year.20. The model structure, parameter choices, and implementation of cost-effectiveness and cost-benefit simulations are described in section 4. Briefly, the model is simple and globally aggregated, but nonetheless represents in an integrated fashion the key elements necessary to illustrate the type of analysis that can be brought to bear on these questions, including a representation of the drivers of future emissions growth, the climate response to emissions, mitigation costs and options, the costs of impact-related damages to the economy, and discounting and intergenerational issues.This study uses DICE 2013R as implemented in MATLAB by38. We partially address the former by perturbing key parameters controlling the social rate of time preference, climate sensitivity, mitigation costs39 and, in the latter section of the paper, climate damage costs20  is based on that used for the 2010 US Department of Energy assessment of the social cost of carbonAll the simulations considered here start in the year 1970. Delayed mitigation simulations are implemented by fixing the DICE emissions control rate (MIU) at zero until a given date, after which the model can freely choose that control rate for each year of the simulation. Optimal solutions are found by maximizing the 1970 present value of welfare over the entire simulation period . Welfare is negatively impacted by both emissions reduction costs and by climate damages.Although we address some of the model’s parameter uncertainty, we do not in this study address the structural assumptions or functional forms of the default DICE model or aspects of the baseline scenario such as population growth, labor productivity, or rates of technological change. We recognize that any comprehensive assessment of costs would need to consider a super-set of available, plausible economic and physical representations of the system.C (see Methods section 4.3). Climate damage costs are not considered in this section, given the model’s damage function is zero by construction at temperatures below the target. The results are presented in Fig. The first set of calculations use the model to find (if possible) a solution meeting (and not exceeding) each of the Paris global average temperature goals of 1.5 and 2.0 °2 emissions of 6% per decade from 1980–2020, compared with the real world average increase of 24% per decade  in Fig. Costs for the 1.5C target are significantly greater. For a 2020 initialization, costs by 2025 reach 20% of GWP, with an 10–90 percentile uncertainty range of 15–30% of GWP), peaking in 2050 at 25% (8–35%) of GWP. By contrast, a least-cost 1980 abatement start would have had a median abatement path that never reached 20%, but rather slowly increased to a peak cost of 18% by 2080.Figure 31, who estimated a cost of order 0.5 trillion dollars per year for a 2 degree target (measured from 2005).There are large parameter uncertainties associated with these results, but the sign of the cost of delay is unambiguous: for a 1980 start, total discounted post-1980 costs for meeting 2C would range from 40 to 150 trillion 2015 dollars (10th and 90th percentiles). The median rates of change of costs in meeting the targets are rising: costs for meeting the 2C target rose by 0.3 trillion dollars per year in 2010, with the annual cost increase rising to nearly 0.6 trillion dollars per year in 2020. The cost of meeting 1.5 degrees rises dramatically - from 1.3 trillion dollars per year of inaction in 2010 to over 5 trillion dollars per year in 2020. These numbers are broadly comparable with the findings ofA second set of simulations uses DICE in its unconstrained configuration without a temperature target imposed, using a quadratic damage function which smoothly increases as a function of global mean temperature, representing economic damages which would be experienced due to climate change. We discuss the methodology of these simulations in section 4.4, where we sample a wide range of possible coefficients for the default DICE damage function.The results are shown in Fig. An optimal solution in which action was taken beginning in 1980 would have involved reducing the rate of growth in global emissions until a peak was reached around mid-century. With mitigation starting in 2020, emission growth essentially stops now; emissions immediately stabilize and remain constant before declining beyond mid-century. The delay in mitigation from 1980 to 2020 implies optimal future pathways with somewhat higher global temperature and climate, translating into an increase in likely 2100 damages of about 15%.However, without strict temperature constraints, the median and upper bounds of the distributions are not strongly affected by the delayed start in adoption of the least cost pathway. The default model version does not show a large dependency of the temperature trajectory as a function of the time at which abatement is enabled, increasing by only a small amount with a later adoption of the optimal pathway Fig. .The evolving discounted costs of the optimal solution are shown in Fig. We can explore the conditions necessary for a 2 degree target to be met from 1980 and 2020 conditions in the optimal, unconstrained solutions with quadratic damage functions by considering the regions of the ensemble parameter space which support a sub 2 degree maximum warming (before 2150). Figure S) exerts a strong control on the feasibility of the target. The 90th percentile of the prior ensemble distribution on S is 5.6 K, but 90 percent of simulations meeting the 2 degree target for abatement starting in 1980 have S < 4 K, and 2.9 K for an abatement start in 2020. Simulations with a larger damage exponent, lower abatement costs and lower social rate of time preference are more likely to meet the target.Climate sensitivity  to meet them. A least cost 2C scenario initiated in the 1980s would have involved several decades of gradual decarbonization, followed by a commitment to net zero emissions late in the 21st century. In contrast, a scenario starting from present day conditions requires a halving of global emissions in little more than 15 years, and net zero emissions by 2060. Mitigation costs for achieving the 2 degree target have risen as a result of the delay. While the expected total (discounted) costs over time have increased modestly (10% or so), the later start necessitates very large near term costs (up to 3–5% of GWP by 2025). Such costs continue to climb rapidly with any further delay.Uncertainties in the costs are high, but the annual increase in cost is relatively well constrained - with each additional year of delay in implementing mitigation costing an additional 0.3–0.9 trillion dollars in total discounted future mitigation costs, if the 2C target is to be ultimately met.The simulations constrained to meet the 1.5C goal suggest that, with the assumptions and model used here, the goal requires near-term spending which may not be feasible: a 2020 start to abatement would require 15–30 percent of GWP by 2025. In contrast, had abatement started in 1980, costs could have risen gradually over more than 80 years and peaked at less than 20% of GDP.Another perspective on the implications of delay is provided by simulations that are not constrained by temperature targets but that identify optimal pathways balancing mitigation costs with damages from climate change impacts. Optimal simulations with abatement starting in the present day show a much more rapid rate of change in emissions than simulations starting in 1980, and the optimal solution results in higher long term climate damages. In the optimal solutions, the majority of the costs of mitigation delay come in the form of additional climate damages.42 is incompatible with the 2 degree target. 90 percent of solutions require mitigation costs low enough to be consistent with a backstop price of 70 USD/tonne, significantly less than the value assumed in the US SCC calculation40 of 344 USD/tonne of CO2. Mitigation costs of this magnitude are not, however, out of the range of published IAMs, a selection of which achieve comparably low mitigation costs , partly because that learning may work in either direction, leading to unexpectedly low (and not only higher) costs. However, asymmetric effects of learning in either direction could change such conclusions.In most parameter configurations, mitigation costs are pushed to the future when backstop prices are lower. This occurs partly due to discounting, which decreases the weight given to future costs. In addition, given the model’s assumption of perfect foresight, when it is known that mitigation costs in the future will decline, the optimal solution delays mitigation to take advantage of that knowledge. The perfect foresight assumption may also affect optimal near term emission policy by not accounting for the possibility that future learning may lead to damages or mitigation costs that turn out to be unexpectedly high. Existing work on the effect of learning has not generally demonstrated a large effect on optimal policies in the near term . As such, the uncertainties explored here  are a subset of a potentially wider set of uncertainties relating to humanity’s ability to predict the physical and economic evolution of the planet.Finally, we acknowledge some sociological assumptions - firstly, that society would have known at past times that the Paris targets might be desirable. This is clearly debatable, from the societal standpoint, for 1980, when there was little consensus on global climate sensitivity or impacts. Recent analysis of publicly available documents, however, have shown that the potential gravity of human-caused climate change was known by many companies as early as that dateDespite uncertainties associated with the absolute costs, the results of this study highlight some general aspects of the decision-making framework which are likely robust. The difficulty and cost associated with delayed action towards meeting a temperature target are likely to increase over time, and that rate of increase has the potential to be strongly nonlinear. In the framework considered here, the 1.5 degree temperature target is already in this regime and total costs of meeting the target are considerably greater (and less certain) than they would have been if stronger past mitigation action had occurred.This paper, therefore, represents an attempt to apply a retrospective lens to global integrated assessment modeling. We acknowledge that the model and analysis are relatively simple, but we believe there is value in this endeavour; looking back can help us build models which better reflect reality, allow us to frame decisions which lie in the future, and to detangle how we consider responsibilities for past actions.20 of the DICE 2013R global coupled climate and economy model22 . The model has been used extensively since its introduction in the early 1990s, and recently in assessments of emissions pathways necessary to achieve the Paris temperature goals50.We use a MATLAB implementationThe model solves iteratively for a pathway that maximizes inter-temporal social welfare (itself a function of consumption), given assumptions about population and labor productivity which drives economic growth, discounting, costs of emissions reductions and a function relating global mean temperature to climate damages on the economy. Optimal solutions are calculated by identifying pathways of savings rates and emissions reduction rates that maximize the discounted sum of social welfare over time. This solution produces an emissions pathway that effectively minimizes combined damages and mitigation costs. DICE has perfect foresight, so decisions about savings and emissions reductions are made in the full knowledge of how the price of mitigation will evolve in the future, and how costly different levels of climate change will be. This is clearly a simplification  of much more complicated types of knowledge and uncertainty about the future, and we discuss its implications in the main text.40, and is illustrated in Supplemental Fig. 22), which we fix at zero until the time at which mitigation begins. After the mitigation start date, MIU is allowed to increase such that emissions can be reduced compared with the baseline . DICE has an exogenous representation of carbon emissions per unit economic output, and the economy can pay for additional emissions reductions by means of a mitigation module in which the cost of emissions reduction is a function of the control rate. Costs are also influenced by the assumed price of a backstop clean technology which starts from an initial cost α and decays over time at a fixed rate (in this study) of 2.5% for each 5 year period36.Baseline emissions are those that result from the optimal solution to the model when it is assumed that there are no climate damages and no emissions mitigation. The baseline scenario for our default model parameters follows2 forcing agents are represented in a bulk form, and their emissions are scaled by the same abatement factor as CO2. The climate response is simulated by a global energy balance model with a two-layer diffusive ocean as per the default configuration in22 . All model simulations begin in 1970 and are run through 2150.Land use emissions are exogenously defined in the model, non-CO51 is used for Equilibrium Climate Sensitivity. We use this ensemble to produce a diverse range of baseline and counterfactual simulations, conditional on the parametric PDFs used. Each parameter configuration is used for a set of simulations, all initialized on the same date (1970) - but differing in the date at which abatement is allowed to have a non-zero value, and in the cost function (described below). A wide range of social time preference (from 0 to 0.02) modulates the amount of weight given to the welfare of future generations relative to that of the current generation.In each section of the study, we perform a 1000 member perturbed ensemble using a Latin hypercube sampling strategy over the parameter space defined in Table 52  is consistent with the range of mitigation costs observed in the IPCC AR5 emissions databasesee Fig. .20 - with all exogenous inputs identical to the baseline simulation in that paper. Additional data are used to initialize the model to 1970 conditions. Exogenous global population from53. Initial GDP data is taken from the World Bank54, global mean surface temperature from55 and global fossil fuel and land use emissions from52. Key variables from the resulting baseline simulation with default parameters are plotted in Supplemental Fig. The baseline simulations are largely implemented as inT is the global mean temperature above pre-industrial levels, Tt is the desired temperature target (1.5 or 2 degrees C in this case), and r is the ramping range in Celsius (where r = 0.5C is used in this case). The damage functions are illustrated in the Supplementary Material, Fig. Temperature constraints for the 1.5 and 2C scenarios are implemented by a semi-linear temperature damage function, such that the cost of exceeding the climate target increases from 0 to 100% of GWP above the desired target:The damage estimate is therefore not useful in itself, but forces the model to produce an optimal pathway (if possible) that does not exceed the desired temperature target and does not account for climate damages. Using a ramp function rather than a step function was found  to create stability for the solver by allowing the model to solve with short overshoots of the temperature target, however, with the chosen damage function the damage costs associated with the least cost solution are in practise negligible with respect to the abatement costs.15 - allowing for damages to be significantly greater than the current range used in the IAMs which contributed to the 5th Assessment Report of the IPCC.In the second set of experiments, the semi-linear climate damage function is replaced with the quadratic damage function used in the default model configuration. The quadratic coefficient is allowed to vary in the ensemble sufficiently to span the range of global damage estimates from a number of sourcesThe model is then solved for the optimal growth and emissions pathway for each parameter configuration, with no exogenous constraint on temperature change.Supplementary information