Ecology

Identification of two Zn/Co responsive proteins in diatomsZn and Co growth rate experiments in which Zn or Co (omitting the other) were added to the growth media were conducted and harvested for proteomic analysis. Growth rates of the marine diatom species Thalassiosira pseudonana CCMP1335, Phaeodactylum tricornutum CCMP632, Pseudo-nitzschia delicatissima UNC1205 and Chaetoceros sp. RS19 (Chaetoceros RS19 herein) were conducted in a consistent media composition to allow for intercomparison among species (see “Methods”). The onset of growth limitation by Zn and Co was evident by decreased growth rates under low [Zn2+] and [Co2+], and the ability to use Co to restore Zn-limited growth was species-specific and consistent with prior results for the diatoms T. pseudonana, P. tricornutum and P. delicatissima (Fig. 1a, b)9 and for other eukaryotic algae2,8,10. Growth rates of Chaetoceros RS19 were not stimulated by increasing [Co2+] up to 23.5 pM in the absence of added Zn. This inability to substitute Co for Zn in Chaetoceros RS19 was clearly distinct from that of other diatoms, but was consistent with previous observations in Chaetoceros calcitrans10, implying a genus-wide attribute.Fig. 1: Growth responses of diatoms to varying [Zn2+] and [Co2+] and initial detection of ZCRPs in T. pseudonana.Growth rates of four diatoms over a range of a [Zn2+] and b [Co2+]. Data are presented as mean values of biological duplicate cultures. Data is available in Supplementary Table 1. Global proteomic analyses comparing the proteomes of pooled biological duplicate cultures (n = 2) of T. pseudonana in c high vs. low added Zn and d high vs. low added Co. Each point is an identified protein with the mean of technical triplicate abundance scores in one treatment plotted against the mean of abundance scores in another treatment. The solid line denotes 1:1 abundance. Error bars in c are the standard deviation of technical triplicate measurements.Full size imageThe proteome as a function of Zn2+ and Co2+ was explored in the marine diatom T. pseudonana harvested during log phase growth. Global proteomic analysis comparing low (1.1 pM) versus high (10.2 pM) added [Zn2+] and low (2.3 pM) versus high (23.4 pM) added [Co2+] revealed two uncharacterized diatom proteins that greatly increased in abundance at low [Zn2+] or [Co2+] (Fig. 1c, d). These proteins were annotated as a CobW/HypB/UreG, nucleotide binding domain and a bacterial extra-cellular solute binding domain, respectively, within the manually curated JGI Thaps3 T. pseudonana genome17 and were identified in T. pseudonana cultures with high confidence (≥9 exclusive unique peptides, 100% protein probability; Supplementary Fig. 1). BLAST sequence alignments showed these proteins to be homologous with CobW-like proteins (with 31.69% identity relative to Pseudomonas denitrificans CobW) and with the bacterial nickel transport protein NikA (with 30.5% identity relative to E. coli NikA), respectively. Based on their clear response to Zn and Co in the proteomes of multiple diatom species (Fig. 2a–d), the lack of definitive annotations in diatoms, and their genetic distance from bacterial homologs, these proteins are referred to as ZCRP-A and ZCRP-B (Zn/Co Responsive Protein A and B) in this study. Abundance patterns of these proteins were also investigated in P. tricornutum, P. delicatissima and Chaetoceros RS19. ZCRP-A spectral abundance counts were significantly (Kendall correlation, p  10 times. j Topology predictions from five sub-methods (OCTOPUS, Philius, PolyPhobius, SCAMPI, and SPOCTOPUS), consensus prediction (TOPCONS), and predicted ΔG values for P. tricornutum ZCRP-B generated using the TOPCONS webserver (https://topcons.cbr.su.se/)27,28. k Extent of Co uptake after 24 h for wild-type (WT), ZCRPA-knockout (KO), and ZCRPA-overexpression (OE) lines of P. tricornutum normalized to fluorescence units (fsu). Data are presented as mean values ± the standard deviation of biological triplicate cultures (n = 3). Individual data points are overlaid as white circles. The extent of Co uptake was found to be significantly larger in the ZCRPA-OE line compared to the wild-type via one-way ANOVA (f(3) = 23.16, p = 0.000268) and post hoc Dunnett test (p = 0.00048).Full size imageTo date, connections between COG0523 proteins and utilization of Zn and Co have been explored primarily in prokaryotic organisms. For example, the COG0523 protein CobW has a role in vitamin B12 biosynthesis and thus Co use19,21. In contrast, a subgroup of other COG0523 proteins (YjiA, YeiR, ZigA, and ZagA) have been implicated in Zn2+ metabolism8,13,14,15,16, and a client protein to the metallochaperone ZagA in Bacillus subtilis has been identified22.Compared to bacteria, less is known about the function of COG0523 proteins in marine phytoplankton, though COG0523 protein family members are known to occur in all kingdoms8,23. A recent study described the presence of COG0523 domain proteins upregulated under low Zn in the coccolithophore Emiliania huxleyi, but without further functional characterization24, implying a potential Zn-related function of a COG0523 protein in a marine alga distinct from the marine diatoms included in this study.Although various proteins belonging to the COG0523 subgroup share similar conserved domains, they possess different metal binding abilities and thus likely have different functions among the diverse organisms in which they are found. For example, recent work has established that CobW preferentially binds Co2+ as the cognate metal and acts as a Co2+ chaperone ultimately supplying vitamin B12 in bacteria, whereas the closely related putative metal chaperones YeiR and YjiA (homologs of CobW) bind Zn2+19. We can infer from homology and the response to low Zn and low Co in the present study that Zn2+ and Co2+ are likely both cognate metals for diatom ZCRP-A. Further metal binding and affinity assays can confirm and characterize metal binding in this protein.Frustule morphologyPhenotypic plasticity in P. tricornutum is well documented. Two basic cell morphotypes, fusiform and triradiate, are found in natural liquid environments. It is thought that by adopting the triradiate form, a cell increases its surface area and thus the area of membrane available for enzymatic activity or molecular diffusion of dissolved inorganic carbon (DIC) into the cell. The triradiate form is known to be more common under DIC limiting conditions, which supports this hypothesis25. Distinct morphological differences resulted from the knockout (KO) of the ZCRP-A gene. In P. tricornutum, ZCRP-A knockout cells consistently adopted a triradiate shape while wild-type cells were fusiform (Fig. 4i). Normally, triradiate cells of P. tricornutum spontaneously revert to fusiform across generations26, thus it is notable that ZCRP-A knockout cells have consistently maintained their triradiate shape for 4+ years in culture irrespective of media [Zn2+]. As Zn2+ is the predominant metal cofactor used in diatom CAs, the adoption of the triradiate form in knockout P. tricornutum cells may be a response to a disruption of the carbon concentrating mechanism caused by a reduction in Zn acquisition capability due to ZCRP-A knockout. This is consistent with the observed relative increase in Mn2+-utilizing CA (ι-CA) in the knockout line compared to the wild-type (Supplementary Fig. 5).ZCRP-B sequence analysis and cellular localizationUnlike COG0523 proteins, the relationship of ZCRP-B abundance to environmental Zn and Co concentrations does not appear to have been previously described. Topology predictions of P. tricornutum ZCRP-B using TOPCONS27,28 revealed a single predicted transmembrane domain near the N-terminus, with the majority of the protein predicted to be oriented outside the membrane (Fig. 4j). Overexpression and fluorescent tagging of ZCRP-B confirmed localization to the cell membrane (Fig. 4e–h; Supplementary Fig. 3b). A single predicted transmembrane domain contrasts with the Zrt/Irt-like divalent metal transporters (ZIPs) in eukaryotic algae, which have 7+ transmembrane domains and are key Zn transporters in many organisms29,30. It is therefore most likely that ZCRP-B is not a transporter itself, but one part of a multi-protein membrane complex and potentially interacts with the ZIP system. A sequence database similarity search (BLASTp, NCBI) found the ZCRP-B protein to be homologous with NikA, a protein subunit of the bacterial ATP-binding cassette (ABC) type Ni transport system protein Nik (30.5% identity with E. coli NikA, E = 7e−49, Supplementary Fig. 6). This transporter is well characterized in bacteria and is comprised of five subunits NikA-E. NikB and NikC are two pore-forming integral inner membrane proteins, NikD and NikE are two inner membrane-associated proteins with ATPase activity, and NikA is the periplasmic component that functions as the initial metal receptor31. No proteins with homology to NikB nor NikC were detected in the P. tricornutum proteomes generated in this study. Two uncharacterized P. tricornutum proteins were homologous with NikD (28.8% identity, E = 1e−14) and NikE (34.9% identity, E = 1.33e−8), though neither had abundance trends similar to ZCRP-B, implying that their function and regulation are independent of ZCRP-B.The sequence of a functionally similar bacterial ABC transport complex, CntABCDF (cobalt nickel transporter, also known as Opp1) from Staphylococcus aureus was also compared to NikA and ZCRP-B (Supplementary Fig. 6). CntA shares 25.6% identity with ZCRP-B (E = 3e−28), and similar to NikA, is an extra-cytoplasmic solute-binding protein that transports Ni, Zn and Co. CntA functions as a Ni/Co acquisition system in Zn-limited S. aureus32. Although the Nik and Cnt systems serve Ni and Co transport in bacteria, ZCRP-B responds to Zn and Co in marine diatoms, which have a significant Zn demand. This may imply a recruitment and repurposing of this bacterial Ni transporter component as part of the Zn acquisition systems during the evolution of marine diatoms.ZCRP-B as a putative high-affinity ligandSequence similarity to the extracellular transport components NikA and CntA (Supplementary Fig. 6), localization to the plasma membrane (Fig. 4b; Supplementary Fig. 3b), and increased abundance under low Zn and Co conditions (Fig. 2b) of P. tricornutum ZCRP-B suggests a metal-binding role as part of a high-affinity transport complex. The induction of ZCRP-B expression at low [Zn2+] (Fig. 2a–c) fits the description of a high-affinity Zn uptake system observed in marine algae that is known to be induced at low free [Zn2+]33,34, suggesting that this protein is involved in an adaptive response to extremely scarce Zn availability. Furthermore, ZCRP-B could contribute to the pool of high-affinity organic ligands that complex dissolved Zn, either by dissociation from living cells or upon cell death by viral lysis and grazing, in the upper water column12,35.The identification of a membrane-associated Zn-Co responsive protein-containing putative metal-binding sites allows us to reconsider the mechanisms of cellular metal uptake in diatoms. Prior physiological experiments observed Zn uptake in marine diatoms to approach the limits of diffusion33, and predicted kinetic control with fast cell surface metal binding and uptake relative to dissociation and release back to the seawater environment36. To enable this transport capability, it was postulated that transporters might be so abundant that the membrane becomes crowded37. Here, the observation of a putative Zn-binding, membrane-associated protein with only 1 predicted transmembrane domain instead implies a separation of the Zn concentrating function at the cell surface relative to its transport into the cell. In this scenario when Zn is scarce, biosynthesis of ZCRP-B increases and is tethered to the cell surface to compete Zn away from natural dissolved Zn ligands35 and/or chelate Zn atoms that make it through the diffusive boundary layer to the membrane. In this manner, ZCRP-B would increase the surface Zn concentration in the vicinity of Zn transporters, and multiple ZCRP-B proteins could supply nearby surface ZIP transporters or be endocytosed, avoiding the predicted membrane crowding of transporters problem. Aristilde and colleagues have previously demonstrated that weak natural Zn-binding ligands containing cysteine do indeed enhance cellular Zn uptake within the diatom Thalassiosira weissflogii, with heightened effects in Zn-limited compared to Zn-replete cells38. They proposed the formation of a transient tertiary complex between the Zn-bound ligand and Zn transporters (ZIPs and heavy metal P-type ATPases) at the cell surface, which could be mediated by a surface-tethered Zn binding ligand such as ZCRP-B. Future studies could examine the mechanism of Zn exchange between ZCRP-B and Zn/Co transporters such as the ZIPs in eukaryotic algae, which were also detected at lower Zn and Co abundances in P. tricornutum but with relatively lower spectral counts (Supplementary Fig. 7a, b), consistent with this model. Furthermore, the proposed mechanism of ZCRP-B binding is similar to that of the high-affinity Fe3+ binding protein ISIP2a, previously characterized in marine algae as an iron starvation-induced protein39. ISIP2a has been characterized as a phytotransferrin involved in endocytosis-mediated high-affinity Fe uptake in P. tricornutum that acts to concentrate Fe at the cell surface and is an extracellular protein anchored to the membrane with one transmembrane domain39. As the protein sequences of P. tricornutum ZCRP-B and ISIP2a share no significant similarity, it is possible that the uptake mechanism of ZCRP-B is similar to that of ISIP2a, but specific to high-affinity Zn and Co uptake rather than Fe. This suggests a common strategy of using extracellular membrane-anchored metal acquisition proteins in marine algae faced with metal limitation.Co uptake in wild-type and mutant diatom strainsAs ZCRP-A and ZCRP-B abundance is related to media [Co2+] (Fig. 2a–d), we investigated differences in the extent of Co uptake after 24 h among Zn/Co-limited wild-type, ZCRP-A knockout, ZCRP-A overexpression, and ZCRP-B overexpression lines of P. tricornutum via addition of the radiotracer 57Co (see methods). The extent of Co uptake among genetically modified P. tricornutum lines was observed to be significantly different via one-way ANOVA (f(3) = 23.16, p = 0.000268). A Dunnet post hoc test revealed that uptake was significantly greater (2.6× larger) in the ZCRP-A overexpression line compared to wild-type (p = 0.00048, Fig. 4k). We interpret this result as the overexpression of ZCRP-A creating a larger intracellular binding capacity for Co, thus protecting it from intracellular sensor or regulatory systems and/or efflux pumps. In contrast, no significant difference in Co uptake rates was observed when comparing ZCRP-A knockout, ZCRP-B overexpression, and wild-type lines, suggesting that P. tricornutum ZCRP-A knockout cells are capable of compensating for knockout to maintain Co metabolism, perhaps through the use of low-affinity transporters33. This is consistent with these uptake experiments being conducted using seawater media with a relatively abundant concentration of Zn (background of 7.7 pM Co and 4.0 nM Zn in the absence of EDTA), thus the use of low-affinity transporters was likely sufficient to acquire Zn and Co for growth, and neither ZCRP-A knockout nor ZCRP-B overexpression would be expected to add any metabolic benefit (Fig. 4k). Moreover, if ZCRP-B is only one part of a multi-protein acquisition and transport complex as hypothesized, overexpression of the single protein may not result in enhanced functionality.Abundance patterns of CAs in two diatomsCarbonic anhydrase enzymes constitute a major reservoir of Zn and Co within marine diatoms7. Within the stroma, intracellular chloroplastic CAs are essential in supplying CO2 to RUBISCO as they convert HCO3−, the predominant species of inorganic carbon in the pyrenoid, into CO240,41. Seven subclasses of CAs have been identified in marine diatoms to date and are designated as alpha, beta, gamma, delta, zeta, theta, and iota (α, β, γ, δ, ζ, θ, and ι). While Zn2+ is the cofactor most commonly used in algal CAs, utilization of both cadmium (Cd2+) and cobalt (Co2+) in place of Zn2+ at the active site of ζ-CA (CDCA) and a δ-CA, respectively, has been previously documented2,5,42. Overall, Zn-utilizing CAs increased in abundance with increasing Zn, consistent with the need for rapid HCO3− conversion at faster growth rates (Fig. 5; Supplementary Fig. 7). Specifically, spectral abundance counts of two β-type CAs, PtCA1 and PtCA2, became abundant in high [Co2+] (23.4 pM) and [Zn2+] ( > 1.1 pM) and were inversely related to ZCRP-A abundance (Supplementary Fig. 7). Both PtCA1 and PtCA2 are known to localize to the chloroplast pyrenoid41,43. Moreover, the increasing abundance trends of the Zn-utilizing α-CAs (CA-II and CA-VI) and the θ-CA Pt43233, which localize to the periplastidial compartment, chloroplast endoplasmic reticulum, and thylakoid lumen, respectively, at higher and Zn/Co provide further evidence for this strategy of increasing CA use under Zn-replete and higher growth rate conditions (Fig. 5; Supplementary Fig. 7)43,44.Fig. 5: Comparison of α-CA, ι-CA, and ZCRP abundances.Spectral counting abundance scores of a alpha CA, iota CA, and b ZCRP-A and ZCRP-B detected in Zn and Co treatments of P. tricornutum measured by global proteomic analysis. Data are plotted as means ± the standard deviation of technical triplicate measurements of pooled biological duplicate cultures (n = 2). Protein names are shown with their corresponding JGI protein ID.Full size imageIn contrast, abundance trends of the recently discovered ι-CA were inversely related to Zn2+ (Fig. 5). Originally identified in T. pseudonana, ι-CA was found to localize to the inner chloroplast membrane surrounding the stroma and is unusual in that it prefers Mn2+ to Zn2+ as a cofactor45. In the present study, spectral counts of P. tricornutum ι-CA decreased as metal concentrations increased, similar to that observed for ZCRP-A and ZCRP-B (Fig. 5). This ι-CA response was consistent with a Zn sparing strategy under low [Zn2+] and [Co2+] used to prioritize the use of Zn2+ for other metalloenzyme functions.Due to the inverse relationship between the abundances of ZCRP-A and chloroplastic Zn2+-requiring CAs in P. tricornutum (that is, all CAs detected with the exception of ι-CA) and the various types of CAs in T. pseudonana (Supplementary Fig. 7), it seems unlikely ZCRP-A directly interacts with CAs. These results are instead consistent with the hypothesis that ZCRP-A functions as a Zn2+ allocation and prioritization mechanism during Zn limitation. The role of Zn2+ in key transcriptional and translational proteins such as RNA polymerase and ribosomal proteins is well known, and major reservoirs of Zn are associated with these transcription and translation systems in the fast-growing copiotrophic bacterium Pseudoalteromonas6. The availability of Zn in ribosomes and the ER is therefore likely also a cellular priority in diatoms, and could benefit from utilizing the putative chaperone and trafficking capability of ZCRP-A when Zn is scarce. We, therefore, posit that ZCRP-A may serve as a Zn2+ trafficking or storage protein that contributes to the prioritization and movement of Zn2+ to the ER or CER, while the Mn-utilizing Mn ι-CA compensates for the lowered Zn availability in the chloroplast. The increased biosynthesis of ZCRP-A may be an important function to shift Zn homeostasis, competing for intracellular Zn and trafficking it towards the ER or CER.Distribution of putative ZCRP homologs among oceanic taxaPutative ZCRP homologs among eukaryotic oceanic taxa were identified by BLAST searching the P. tricornutum ZCRP-A and ZCRP-B protein sequences against all available transcriptomes in the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP) database, which includes over 650 assembled and annotated transcriptomes of oceanic microbial eukaryotes46. Phylogenetic analysis revealed the presence of putative ZCRP-A and ZCRP-B homologs in a wide variety of organisms belonging to the Chromista kingdom that could be further categorized into Bacillariophyceae, Dinophyceae, and Prymnesiophyceae classes (Supplementary Figs. 8 and  9). Notably, the Chaetoceros RS-19 ZCRP-A homolog did not phylogenetically cluster with the other diatoms (Bacillariophyceae), but instead appears to be more closely related to E. coli YjiA (Supplementary Fig. 8). Furthermore, the lack of the conserved G2/Switch I region in the Chaetoceros RS-19 homolog (Fig. 3) is anomalous in comparison to other putative homologs identified within the MMETSP database. Overall, ZCRPs are not exclusive to oceanic diatoms, but rather are widely distributed amongst oceanic taxa.Metaproteomic detection of ZCRP-A and ZCRP-BTo investigate the use of ZCRP-A and ZCRP-B in the natural environment, we searched metaproteomic data collected during the KM1128 METZYME (Metals and Enzymes in the Pacific) research expedition on the R/V Kilo Moana October 1–25, 2011 from Oʻahu, Hawaiʻi, to Apia, Samoa (Fig. 6a). dZn followed a nutrient-like distribution as described previously, with an average surface (40 m) dZn concentration of 1.21 nM and average deep water (3000 m) concentration of 10.37 nM47 (Fig. 6b). dCo was highly depleted in the upper photic zone as the result of biological uptake48,49 (Fig. 6c). Eukaryotic homologs of ZCRP-A and ZCRP-B were detected at multiple stations at surface ( More

To estimate the potential increase in biodiversity decline and the national level of conservation investment needed to counteract it in post-conflict Colombia, we used a model developed by Waldron et al.19. This quantitative model predicts national biodiversity status change, the biodiversity decline score (BDS), based on investment in conservation actions in relation to human development pressures. The model uses seven predictors related to the economy of each country, its biodiversity status or dynamics, and its conservation spending19.ScenariosWe used the Waldron et al.19 model to predict (1) the expected increase in biodiversity decline immediately after the peace agreement (the post-conflict period), (2) the conservation funding needed to prevent this additional decline and (3) the investment necessary to avoid biodiversity decline. We used four scenarios to examine our questions.The baseline scenario was the War BDS scenario, which estimated the BDS of the last 12 years of the conflict, before the peace agreement in 2016. Predictor variables related to human pressures were from 4–5 years before to appropriately represent the lag in the modelled effect19. We used the most recent available value of ‘strict-sense’ conservation investment19. The following three scenarios examined post-conflict options and were compared with this War BDS scenario.The Peace BDS scenario predicted the BDS for a 12-year period post-conflict. The predictor variables related to human pressures were from the 11-year period immediately after the peace agreement. We assumed the same conservation spending as for the War BDS. The Lower BDS scenario estimated the necessary investment to achieve the War BDS. This represented a situation where the biodiversity loss during the conflict did not change post-conflict. For this scenario, we held the human pressure variables the same as in the Peace BDS scenario. The Prevented BDS scenario was exactly the same as the Lower BDS scenario, but we set a target of no biodiversity decline (BDS = 0).We used the War and Peace BDS estimates to calculate the expected additional biodiversity decline post-conflict. Then, we used the model with data from the Lower BDS scenario to calculate the investment needed to prevent any additional biodiversity decline post-conflict. Finally, we used data from the Prevented BDS scenario to estimate the conservation investment necessary to halt biodiversity decline in the post-conflict period.Data for predictor variablesWe modified the predictors related to agriculture and economic growth to examine anticipated changes in human pressures. This revision allowed us to consider the expected agricultural expansion, in the form of percentage of agricultural land and growth, and economic growth, as the gross domestic product (GDP) and GDP growth. We also modified the function so that we could use it to estimate funding needs given a target BDS.For the War BDS scenario, data on GDP, GDP growth, agricultural land area and agricultural land area growth were either available or easily computed. The data for GDP and the percentage of agricultural land from 2001–2012 were obtained from The World Bank28. The agricultural land growth was calculated as the difference between the percentage of agricultural land of consecutive years, and GDP growth was calculated from the GDP per capita data from The World Bank28.For the Peace, Lower and Prevented BDS scenarios, we made projections about the predictors. For the GDP we used projections for 2017–2019, and for the GDP growth projections for 2019–2022 (ref. 33), and then selected an annual increase in the GDP growth of 0.3 percentage points for the remaining 5 years, corresponding to the most conservative estimate found in ref. 34. We then used our estimates of GDP growth for the whole time period to calculate the GDP per capita for the last 10 years, and used population projection to compute the GDP for the next 10 years.To estimate the agricultural land and growth for the Peace, Lower and Prevented BDS scenarios, we used projections on deforestation. We developed our model to reflect the immediate consequences in agricultural expansion and deforestation post-conflict. Thus, we estimated the percentage agricultural land area using projected values of deforestation35. We support this approach based on two observations. First, at least 90% of deforested land was transformed to agriculture during past years36. Second, forest transformation to agriculture has been more aggressive since the peace agreement7,10,11. Thus, the processes that fuel agricultural conversion are stronger. For each year we added the deforested area to the previous agricultural land area. We then calculated the yearly percentage agricultural land area and computed the agricultural growth as the percentage difference between the agricultural land area of consecutive years. We took the minimum and maximum values of deforestation projections to create best- and worst-case scenarios.We acknowledge that our use of the Waldron et al.19 model has limitations because we did not update all the predictors. Specifically, two ‘inertia’ terms that account for the effect of biodiversity decline occurring immediately before the time period of interest19. The coefficients associated with these terms have a positive effect on the BDS, which means that a more intense decline in the past will increase the predicted biodiversity decline. Given the increase in human pressures, the actual inertia terms are probably larger than the ones we used. Thus, the Peace BDS and the actual increase in biodiversity decline post-FARC may be larger.The ModelTo create a broad proxy for the expected cost of potential conservation interventions across Colombia, we estimated the OCC for agriculture at the 1 km2 scale. We estimated the OCC by building a spatially explicit probability model of forest conversion to agriculture and then paired it with the net present value of the expected return of different agricultural activities.We calculated the OCC following the methodology proposed by Naidoo and Adamowicz24. Their approach models the expected net present value of potential net rents resulting from agricultural uses of a forested parcel, while accounting for the probability of conversion to agriculture. Provided that each agricultural use k has its own annual expected return per area of land Rk, and that each parcel i has a probability of conversion Pik from forest to agricultural use k, the expected value for a given discount rate δ is$${{{mathrm{OCC}}}} = mathop {sum}limits_{i = 1}^{{I}} {mathop {sum}limits_{k = 1}^{{K}} {{{P}}_{i,k}} } frac{{{{R}}_k}}{{delta }}$$
(1)
Thus, the OCC of an area composed of several parcels is equal to the sum of the expected returns of the probable agricultural uses, weighted according to their probability of conversion, in each of the parcels, summed across all of the parcels.We calculated the OCC for forested areas in three steps. First, we built a probability model to obtain the general risk of forest conversion (Pdef). Next, we built a second model that, given that a parcel had been transformed, predicted the probability of forest conversion to different types of agricultural activities (({{P}}_{{{{mathrm{ag}}}}_k})). We used both models to compute the total probability of conversion to each type of agricultural activity k in a parcel i (({{P}}_{ik} = {{P}}_{{{{mathrm{def}}}}_i} times {{P}}_{{{{mathrm{ag}}}}_{i,k}})). We then estimated the net present value of the expected return of each agricultural activity (Rk/δ) using literature and commercial prices and the costs of agricultural products.Types of agricultural land use modelledOur OCC model needed to represent relevant agricultural activities. Below, we justify our selection of three types of agricultural land uses: cattle ranching, coca crops and other crops.Cattle ranching is expected to be a major driver of post-conflict deforestation11. This activity has accounted for 50% of deforestation, in the form of forest conversion to pasture, in past years36, and has considerably expanded post-conflict7.Illegal coca crops are expected to be, and have been observed to be, an important driver of post-conflict deforestation12. This activity is at risk of increase where the withdrawal of FARC and the absence of state presence left a ‘power vacuum’ that facilitated other illegal groups gaining control of such crops in the territory7,11,12. Indeed, evidence shows that deforestation associated with coca cultivation increased as the conflict became less intense37.Other crops were grouped into a single category with cattle ranching due to their small percentage contribution to forest conversion in our time frame (3%) compared with cattle ranching and coca crops (47 and 50%, respectively). We proxy for the extent of all other crops by using data on the distribution of three relevant agricultural products in the post-conflict period: cacao, oil palm and coffee. The cacao crop has high potential in most of the key post-conflict areas in Colombia, so it could have a major role in the peace transition38. Oil palm is important owing to its steep increase in cultivation during the last few years12, to the point that Colombia is now the largest producer in South America39. The relevance of coffee resides in its impact on the rural population, given that coffee crops are the only source of income for approximately 563,000 families and generates over 726,000 rural jobs40.Landscape features dataWe selected ten factors relevant to deforestation in Colombia to model the probability of forest conversion: proximity to roads, presence of FARC (binary: presence or no presence), population density, slope23, elevation, proximity to deforested areas, to rivers, to mining areas and to oil wells, and belonging to national and regional PAs10. National PAs restrict economic activities and are managed by the System of National Natural Parks, while regional PAs allow multiple-use activities and are managed by regional environmental authorities8,41. We did not include indigenous reserves or Afro-Colombian lands.We used deforested areas from 1990 to 2000 from the Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM)42, the water bodies map from the Department of Environment and Sustainable Development43 and maps from the Instituto Geográfico Agustín Codazzi (IGAC)44 to calculate the distance to already deforested areas, rivers, roads, mining areas and oil wells. The elevation map was obtained from NASA’s (National Aeronautics and Space Administration’s) Land Topography digital images45, and we calculated the slope using the elevation map. We computed population density as the mean value of the 32 mainland administrative departments from 2000 to 2012 using data from the Departamento Administrativo Nacional de Estadística46 (DANE; see Supplementary Table 3 for dataset details). We obtained a map showing the presence of FARC from the Fundación Paz y Reconciliación (PARES)47. All spatial data calculations were performed using software QGIS (https://www.qgis.org/en/site/, version 3.12.2) and R (https://www.r-project.org/, version 3.6.2).Forest conversion and agricultural use modelWe used a two-stage modelling process. First, we modelled the probability of an area being deforested by any driver (not exclusively due to agricultural expansion), using the total deforested area in the country in a 12-year period to parametrize our model (forest conversion model). Second, we modelled the probability that the deforestation was due to a particular agricultural activity (agricultural use model). To parametrize this second model, we used patches of land that were indeed transformed to an agricultural use in this same 12-year period. We combined these two models to obtain the probability that a patch of land was deforested to a particular agricultural activity.We used a binomial logistic regression model to build our forest conversion model, which estimates the probability of forest conversion (Pdef). We used the land cover change from 2000 to 2012 across the country, available from IDEAM42, and reclassified each pixel cell as forested or transformed. We used the bayesglm function from the R arm package48.For our agricultural use model, we built a second binomial logistic regression model to estimate ({{P}}_{{{{mathrm{ag}}}}_k}), the probability of conversion to each type of agricultural activity (cattle and other crops or coca crops) for a parcel that had been transformed. We employed data on forested areas in 2000 that had been converted by 2012. The coca crops cover map was obtained from the Sistema Integrado de Control de Cultivos Ilícitos (BIESIMCI)49. For the cattle ranching map, we used forested areas converted to pasture. Our other crop data contained temporary and permanent crops obtained from a land cover map43.It should be noted that in logistic regression models, the probability of conversion does not change in a linear fashion, but the ratio of probabilities (odds) does. For the agricultural model, the odds describe the probability of conversion to coca crops over the joint probability of conversion to cattle and other crops. This implies that the variation between the probabilities, not the probability itself, changes constantly.To check for spatial autocorrelation, we plotted spatial correlograms of the models’ residuals with Moran’s I. Because spatial patterns were present, we subsampled for pixel cells at a minimum distance of 20 km between points, which reduced the spatial effects adequately for our purposes, although it was most effective for the forest conversion model (Extended Data Fig. 1). We checked for collinearity in the predictor variables using variance inflation factor scores and removed the variables with a value >3 (distance to mines and oil wells; Supplementary Tables 4 and 5). We performed tenfold cross-validation to test the prediction accuracy of the models. This process splits the data into ten subsets and repeatedly fits the model with the data of nine of the subsets to compare its predictions with the remaining subset. We calculated the percentage of correct predictions (overall accuracy) each time and computed the mean as the final forecasting accuracy indicator.Estimation of annual net rentWe estimated the net present values of the expected return of each agricultural activity to estimate the OCC of forested areas in Colombia. For cattle, we used annual net rent from a beef company50. The total annual net rent for other crops was calculated as the weighted average of the net rents for oil palm, cacao and coffee proportional to their land area in 2016 and 2017 (refs. 51,52,53). For coca crops, we used the average net profit for farmers who sell coca leaves54. We selected three discount rate values: 5, 10 and 20% (Supplementary Tables 6 and 7).Predicting forest conversion and OCCTo predict the probability of forest conversion, we updated our spatial information on roads, deforested areas from 2007 to 2017 (ref. 42), FARC presence as the presence of FARC dissidents and deserters in 2017 (ref. 47), and population density as the mean population density by department from 2017 to 2023 (ref. 55). Together with the annual net rent for each agricultural activity, we used the probabilities of conversion of the two models to compute the OCC, or expected land value, of each forested pixel cell for the three discount rates using Eq. (1).We recognize that the simplified national context of social violence when predicting the probability of forest conversion can limit the application of our results. Our models included FARC presence, and we used the presence of dissidents and deserters in this forecasting stage. However, this ignores other criminal groups that might influence the risk of forest conversion, particularly to coca crops, due to the ‘power vacuum’ left by the withdrawal of FARC and lack of state presence11. Because we overlooked the potential impact of other criminal groups, the probability of forest conversion, particularly to coca crops, could have been underestimated. This would imply an underestimation of the OCC in the areas with presence of these other criminal groups.We used the rural cadastral values56 to validate our OCC results by comparing our predicted mean land values by administrative department in the country. Although rural cadastral values might not reflect the value of illegal coca crops, they were, to the best of our knowledge, the best available data for our purposes.The STAR metricThe STAR metric is a measurement of the potential benefit to threatened and near-threatened species of actions aimed at reducing threats and restoring habitat20. The metric can be disaggregated spatially using the area of habitat for each species, showing the proportional potential contributions of conservation actions in particular regions. We focused on the STAR threat-abatement score (START) only. The START score can be further disaggregated by threat according to the contribution of each threat to the species’ risk of extinction, which allows analysis of potential abatement of species extinction risk by particular activities at particular locations. We took advantage of this trait and used the START metric in a specialized way, focusing on the threats posed by agriculture only on all the species with an area of habitat in Colombia. This resulted in 475 species considered (246 amphibians, 172 birds and 57 mammals), of which 169 are vulnerable, 124 near-threatened, 130 endangered and 52 critically endangered. Agriculture accounted for 52% of the total START. This focus on agriculture includes annual and perennial non-timber crops, wood and pulp plantations, and livestock farming and ranching, so we treated land converted to cattle and crops in the same way even though each land-use type has different impacts on species.The use of the STAR metric has some limitations associated with the spatial distribution of the threat due to agriculture. First, the STAR metric is based on documented ongoing and expected future threats to the species according to the International Union for Conservation of Nature Red List. The majority of documented threats are ongoing, thus the majority of species threatened by agriculture are already being negatively impacted. This causes uncertainty in the assumption that avoiding further agricultural conversion will reduce species extinction risk, as additional activities to mitigate the impact of current agricultural activities on the species may also be required. Nevertheless, species assessed as threatened by agriculture are known to be vulnerable to this pressure, meaning that they would almost certainly suffer negative impacts under future agricultural expansion.Second, there is uncertainty in the potential spatial distribution of agricultural expansion. Therefore, the STAR metric as we used it helped us identify sites with urgent potential benefits of avoiding agriculture. This could under-represent territories of great biodiversity value that are not currently impacted by agriculture, like the Amazon region.Prioritization mapsWe wanted to achieve a coarse methodology that could help decision-makers direct national conservation funding to the territories with the most potential benefits of halting forest conversion to agriculture. To pair the STAR scores with our modelled OCC, we divided the total range of STAR scores and OCC into high, medium and low values. Given the distribution of STAR scores, we divided the total range in the logarithmic scale. We classified each forested pixel cell into one of nine combinations of STAR scores and OCC. This analysis was later translated to the municipality resolution by calculating the mean STAR score and mean OCC of all forested pixel cells in each municipality, and applying the same classification system used at the pixel resolution. The distributions of aggregated STAR scores and OCC at the municipality resolution follow a similar pattern to the distribution by pixel cell, with small differences due to the grouping of the values in means (Extended Data Fig. 2b,c).Reporting SummaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Canadell, J. G. et al. Multi-decadal increase of forest burned area in Australia is linked to climate change. Nat. Commun. 12, 6921 (2021).Nolan, R. H. et al. What do the Australian Black Summer fires signify for the global fire crisis? Fire 4, 97 (2021).Article 

Google Scholar 
Levin, N., Yebra, M. & Phinn, S. Unveiling the factors responsible for Australia’s Black Summer fires of 2019/2020. Fire 4, 58 (2021).Article 

Google Scholar 
Abram, N. J. et al. Connections of climate change and variability to large and extreme forest fires in southeast Australia. Commun. Earth Environ. 2, 8 (2021).Keenan, R. et al. No evidence that timber harvesting increased the scale or severity of the 2019/20 bushfires in south-eastern Australia. Aust. For. 84, 133–138 (2021).Article 

Google Scholar 
Fire Severity in Harvested Areas (New South Wales Department of Primary Industry, 2020); https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0020/1222391/fire-severity-in-harvested-areas.pdfLindenmayer, D. B., Kooyman, R. M., Taylor, C., Ward, M. & Watson, J. E. Recent Australian wildfires made worse by logging and associated forest management. Nat. Ecol. Evol. 4, 898–900 (2020).Bowman, D. M., Williamson, G. J., Gibson, R. K., Bradstock, R. A. & Keenan, R. J. The severity and extent of the Australia 2019–20 Eucalyptus forest fires are not the legacy of forest management. Nat. Ecol. Evol. 5, 1003–1010 (2021).Poulos, H. M., Barton, A. M., Slingsby, J. A. & Bowman, D. M. Do mixed fire regimes shape plant flammability and post-fire recovery strategies? Fire 1, 39 (2018).Article 

Google Scholar 
Lindenmayer, D. B. et al. Logging elevated the probability of high-severity fire in the 2019–20 Australian forest fires. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-022-01716-z (2022).Peterson, D. A. et al. Australia’s Black Summer pyrocumulonimbus super outbreak reveals potential for increasingly extreme stratospheric smoke events. NPJ Clim. Atmos. Sci. 4, 38 (2021).Gibson, R., Danaher, T., Hehir, W. & Collins, L. A remote sensing approach to mapping fire severity in south-eastern Australia using sentinel 2 and random forest. Remote Sens. Environ. 240, 111702 (2020).Article 

Google Scholar 
Taylor, C., McCarthy, M. A. & Lindenmayer, D. B. Nonlinear effects of stand age on fire severity. Conserv. Lett. 7, 355–370 (2014).Article 

Google Scholar 
Price, O. F. & Bradstock, R. A. The efficacy of fuel treatment in mitigating property loss during wildfires: insights from analysis of the severity of the catastrophic fires in 2009 in Victoria, Australia. J. Environ. Manag. 113, 146–157 (2012).Article 

Google Scholar 
Lindenmayer, D., Taylor, C. & Blanchard, W. Empirical analyses of the factors influencing fire severity in southeastern Australia. Ecosphere 12, e03721 (2021).Article 

Google Scholar 
Bowman, D. M., Williamson, G. J., Prior, L. D. & Murphy, B. P. The relative importance of intrinsic and extrinsic factors in the decline of obligate seeder forests. Global Ecol. Biogeogr. 25, 1166–1172 (2016).Article 

Google Scholar 
Taylor, C., Blanchard, W. & Lindenmayer, D. B. Does forest thinning reduce fire severity in Australian eucalypt forests? Conserv. Lett. 14, e12766 (2021).Article 

Google Scholar 
Lindenmayer, D. B. & Taylor, C. New spatial analyses of Australian wildfires highlight the need for new fire, resource, and conservation policies. Proc. Natl Acad. Sci. USA 117, 12481–12485 (2020).CAS 
Article 

Google Scholar 
Cruz, M., Alexander, M. & Plucinski, M. The effect of silvicultural treatments on fire behaviour potential in radiata pine plantations of South Australia. For. Ecol. Manag. 397, 27–38 (2017).Article 

Google Scholar 
Lindenmayer, D. B., Hobbs, R. J., Likens, G. E., Krebs, C. J. & Banks, S. C. Newly discovered landscape traps produce regime shifts in wet forests. Proc. Natl Acad. Sci. USA 108, 15887–15891 (2011).CAS 
Article 

Google Scholar  More

Oppel, S. et al. Spatial scales of marine conservation management for breeding seabirds. Mar. Policy 98, 37–46 (2018).Article 

Google Scholar 
Lewison, R. et al. Research priorities for seabirds: improving conservation and management in the 21st century. Endanger. Species Res 17, 93–121 (2012).Article 

Google Scholar 
Hasegawa, H. & DeGange, A. R. The Short-tailed Albatross, Diomedea albatrus, its status, distribution and natural history. Am. Birds 36, 806–814 (1982).
Google Scholar 
Tickell, W. L. N. Albatrosses (Pica Press, 2000).BirdLife International. Phoebastria albatrus. The IUCN Red List of Threatened Species, e.T22698335A132642113 https://doi.org/10.2305/IUCN.UK.2018-2.RLTS.T22698335A132642113.en (2018).Japan Ministry of the Environment. Ministry of the Environment Red List (Government of Japan, 2020).COSEWIC. COSEWIC Assessment and Status Report on the Short-tailed Albatross Phoebastria albatrus in Canada (Committee on the Status of Endangered Wildlife in Canada, 2013).Environment Canada. Recovery Strategy for the Short-tailed Albatross (Phoebastria albatrus) and the Pink-footed Shearwater (Puffinus creatopus) in Canada (Environment Canada, 2008).United States of America Fish and Wildlife Service. Endangered and Threatened Wildlife and Plants; Final Rule to List the Short-tailed Albatross as Endangered in the United States. 65 FR 46643, 46643–4654, Document Number 00–19123 (2000).United States of America Fish and Wildlife Service. Short-tailed Albatross (Phoebastria albatrus) 5-Year Review: Summary and Evaluation (United States of America Fish and Wildlife Service, 2020).United States of America Fish and Wildlife Service. Short-tailed Albaross Recovery Plan (United States of America Fish and Wildlife Service, 2008).Orben, R. A. et al. Ontogenetic changes in at-sea distributions of immature short-tailed albatrosses Phoebastria albatrus. Endanger. Species Res 35, 23–37 (2018).Article 

Google Scholar 
Orben, R. A. et al. Across borders: external factors and prior behaviour influence North Pacific albatross associations with fishing vessels. J. Appl. Ecol. 58, 1272–1283 (2021).Article 

Google Scholar 
Fox, C. H., Robertson, C., O’Hara, P. D., Tadey, R. & Morgan, K. H. Spatial assessment of albatrosses, commercial fisheries, and bycatch incidents on Canada’s Pacific coast. Mar. Ecol. Prog. Ser. 672, 205–222 (2021).Article 

Google Scholar 
Piatt, J. F. et al. Predictable hotspots and foraging habitat of the endangered short-tailed albatross (Phoebastria albatrus) in the North Pacific: implications for conservation. Deep Sea Res. Part II 53, 387–398 (2006).Article 

Google Scholar 
Suryan, R. M. et al. Migratory routes of short-tailed albatrosses: use of exclusive economic zones of North Pacific Rim countries and spatial overlap with commercial fisheries in Alaska. Biol. Conserv. 137, 450–460 (2007).Article 

Google Scholar 
Suryan, R. M. & Fischer, K. N. Stable isotope analysis and satellite tracking reveal interspecific resource partitioning of nonbreeding albatrosses off Alaska. Can. J. Zool. 88, 299–305 (2010).CAS 
Article 

Google Scholar 
Zador, S. G., Punt, A. E. & Parrish, J. K. Population impacts of endangered short-tailed albatross bycatch in the Alaskan trawl fishery. Biol. Conserv. 141, 872–882 (2008).Article 

Google Scholar 
Geernaert, T. O., Gilroy, H. L., Kaimmer, S. M., Williams, G. H. & Trumble, R. J. A Feasibility Study that Investigates Options for Monitoring Bycatch of the Short-tailed Albatross in the Pacific Halibut Fishery off Alaska (International Pacific Halibut Commission, 2001).Guy, T. J. et al. Overlap of North Pacific albatrosses with the U.S. west coast groundfish and shrimp fisheries. Fish. Res. 147, 222–234 (2013).Article 

Google Scholar 
Bolnick, D. I. et al. The ecology of individuals: incidence and implications of individual specialization. Am. Natural 161, 1–28 (2003).Article 

Google Scholar 
Votier, S. C. et al. Individual responses of seabirds to commercial fisheries revealed using GPS tracking, stable isotopes and vessel monitoring systems. J. Appl. Ecol. 47, 487–497 (2010).Article 

Google Scholar 
Wakefield, E. D. et al. Long-term individual foraging site fidelity—why some gannets don’t change their spots. Ecology 96, 3058–3074 (2015).PubMed 
Article 
PubMed Central 

Google Scholar 
Votier, S. C. et al. Effects of age and reproductive status on individual foraging site fidelity in a long-lived marine predator. Proc. R. Soc. B 284, 20171068 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Sztukowski, L. A. et al. Sex differences in individual foraging site fidelity of Campbell albatross. Mar. Ecol. Prog. Ser. 601, 227–238 (2018).Article 

Google Scholar 
Gutowsky, S. E. et al. Divergent post-breeding distribution and habitat associations of fledgling and adult Black-footed Albatrosses Phoebastria nigripes in the North Pacific. Ibis 156, 60–72 (2014).Article 

Google Scholar 
Weimerskirch, H., Åkesson, S. & Pinaud, D. Postnatal dispersal of wandering albatrosses Diomedea exulans: implications for the conservation of the species. J. Avian Biol. 37, 23–28 (2006).
Google Scholar 
Olson, S. L. & Hearty, P. J. Probable extirpation of a breeding colony of Short-tailed Albatross (Phoebastria albatrus) on Bermuda by Pleistocene sea-level rise. Proc. Natl Acad. Sci. 100, 12825–12829 (2003).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Dall, W. H. Notes on pre-historic remains in the Aleutian islands. Proc. Calif. Acad. Sci. 4, 283–287 (1872).
Google Scholar 
Eda, M. et al. Inferring the ancient population structure of the vulnerable albatross Phoebastria albatrus, combining ancient DNA, stable isotope, and morphometric analyses of archaeological samples. Conserv. Genet. 13, 143–151 (2012).Article 

Google Scholar 
Cousins, K. L., Dalzell, P. & Gilman, E. Managing pelagic longline-albatross interactions in the North Pacific Ocean. Mar. Ornithol 28, 159–174 (2000).
Google Scholar 
Hobson, K. A. & Montevecchi, W. A. Stable isotopic determinations of trophic relationships of great auks. Oecologia 87, 528–531 (1991).PubMed 
Article 
PubMed Central 

Google Scholar 
Fuller, B. T. et al. Pleistocene paleoecology and feeding behavior of terrestrial vertebrates recorded in a pre-LGM asphaltic deposit at Rancho La Brea, California. Palaeogeogr. Palaeoclimatol. Palaeoecol. 537, 109383 (2020).Article 

Google Scholar 
Hobson, K. A. & Clark, R. G. Assessing avian diets using stable isotopes I: turnover of 13C in tissues. Condor 94, 181–188 (1992).Article 

Google Scholar 
Hyland, C., Scott, M. B., Routledge, J. & Szpak, P. Stable carbon and nitrogen isotope variability of bone collagen to determine the number of isotopically distinct specimens. J. Archaeol. Method Theory https://doi.org/10.1007/s10816-021-09533-7 (2021).Article 

Google Scholar 
Hedges, R. E. M., Clement, J. G., Thomas, D. L. & O’Connell, T. C. Collagen turnover in the adult femoral mid‐shaft: modeled from anthropogenic radiocarbon tracer measurements. Am. J. Phys. Anthropol. 133, 808–816 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
Guiry, E. J., Orchard, T. J., Royle, T. C. A., Cheung, C. & Yang, D. Y. Dietary plasticity and the extinction of the passenger pigeon (Ectopistes migratorius). Quat. Sci. Rev. 233, 106225 (2020).Article 

Google Scholar 
Minagawa, M. & Wada, E. Stepwise enrichment of 15N along food chains: further evidence and the relation between δ15N and animal age. Geochim. Cosmochim. Acta 48, 1135–1140 (1984).CAS 
Article 

Google Scholar 
DeNiro, M. J. & Epstein, S. Influence of diet on the distribution of carbon isotopes in animals. Geochim. Cosmochim. Acta 42, 495–506 (1978).CAS 
Article 

Google Scholar 
Hobson, K. A., Ambrose, W. G. Jr & Renaud, P. E. Sources of primary production, benthic-pelagic coupling, and trophic relationships within the Northeast Water Polynya: insights from δ13C and δ15N analysis. Mar. Ecol. Prog. Ser. 128, 1–10 (1995).Article 

Google Scholar 
Sigman, D., Karsh, K. & Casciotti, K. Ocean process tracers: nitrogen isotopes in the ocean in Encyclopedia of Ocean Science (eds Steele, J. H. et al.) 4139–4152 (Academic Press, 2009).Guiry, E. Complexities of stable carbon and nitrogen isotope biogeochemistry in ancient freshwater ecosystems: implications for the study of past subsistence and environmental change. Front. Ecol. Evol 7, 313 (2019).Article 

Google Scholar 
Rau, G. H., Takahashi, T. & Des Marais, D. J. Latitudinal variations in plankton δ13C: implications for CO2 and productivity in past oceans. Nature 341, 516–518 (1989).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Popp, B. N. et al. Effect of phytoplankton cell geometry on carbon isotopic fractionation. Geochim. Cosmochim. Acta 62, 69–77 (1998).CAS 
Article 

Google Scholar 
Laws, E. A., Popp, B. N., Bidigare, R. R., Kennicutt, M. C. & Macko, S. A. Dependence of phytoplankton carbon isotopic composition on growth rate and (CO2) aq: theoretical considerations and experimental results. Geochim. Cosmochim. Acta 59, 1131–1138 (1995).CAS 
Article 

Google Scholar 
Vokhshoori, N. L. et al. Broader foraging range of ancient short-tailed albatross populations into California coastal waters based on bulk tissue and amino acid isotope analysis. Mar. Ecol. Prog. Ser. 610, 1–13 (2019).CAS 
Article 

Google Scholar 
Sherwood, O. A., Lehmann, M. F., Schubert, C. J., Scott, D. B. & McCarthy, M. D. Nutrient regime shift in the western North Atlantic indicated by compound-specific δ15N of deep-sea gorgonian corals. Proc. Natl Acad. Sci. 108, 1011–1015 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Szpak, P., Savelle, J. M., Conolly, J. & Richards, M. P. Variation in late holocene marine environments in the Canadian Arctic Archipelago: evidence from ringed seal bone collagen stable isotope compositions. Quat. Sci. Rev. 211, 136–155 (2019).Article 

Google Scholar 
Guiry, E. J. et al. Deforestation caused abrupt shift in Great Lakes nitrogen cycle. Limnol. Oceanogr. 65, 1921–1935 (2020).CAS 
Article 

Google Scholar 
Wiley, A. E. et al. Millennial-scale isotope records from a wide-ranging predator show evidence of recent human impact to oceanic food webs. Proc. Natl Acad. Sci. 110, 8972–8977 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Keeling, C. D. The Suess effect: 13Carbon-14Carbon interrelations. Environ. Int. 2, 229–300 (1979).CAS 
Article 

Google Scholar 
McMahon, K. W., Thorrold, S. R., Elsdon, T. S. & McCarthy, M. D. Trophic discrimination of nitrogen stable isotopes in amino acids varies with diet quality in a marine fish. Limnol. Oceanogr. 60, 1076–1087 (2015).CAS 
Article 

Google Scholar 
Chikaraishi, Y. et al. Determination of aquatic food‐web structure based on compound‐specific nitrogen isotopic composition of amino acids. Limnol. Oceanogr. Methods 7, 740–750 (2009).CAS 
Article 

Google Scholar 
Jackson, A. L., Inger, R., Parnell, A. C. & Bearhop, S. Comparing isotopic niche widths among and within communities: SIBER–stable isotope Bayesian ellipses in R. J. Anim. Ecol. 80, 595–602 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
Ambrose, S. H. Preparation and characterization of bone and tooth collagen for isotopic analysis. J. Archaeol. Sci. 17, 431–451 (1990).Article 

Google Scholar 
Guiry, E. J. & Szpak, P. Improved quality control criteria for stable carbon and nitrogen isotope measurements of ancient bone collagen. J. Archaeol. Sci. 132, 105416 (2021).CAS 
Article 

Google Scholar 
Thompson, D. R. & Furness, R. W. Stable-isotope ratios of carbon and nitrogen in feathers indicate seasonal dietary shifts in Northern Fulmars. Auk 112, 493–498 (1995).Article 

Google Scholar 
Carter, H. R. & Sealy, S. G. Historical occurrence of the short-tailed Albatross in British Columbia and Washington. 1841–1958. Wildl. Afield 11, 24–38 (2014).
Google Scholar 
Crockford, S. The Archaeological History of Short-tailed Albatross in British Columbia: A Review and Summary of STAL Skeletal Remains, as Compared to Other Avian Species, Identified from Historic and Prehistoric Midden Deposits. Report on file, Canadian Wildlife Service (2003).Borrmann, R. M., Phillips, R. A., Clay, T. A. & Garthe, S. High foraging site fidelity and spatial segregation among individual great black-backed gulls. J. Avian Biol. 50, e02156 (2019).Article 

Google Scholar 
Wilkinson, B. P., Haynes-Sutton, A. M., Meggs, L. & Jodice, P. G. High spatial fidelity among foraging trips of Masked Boobies from Pedro Cays, Jamaica. PLoS ONE 15, e0231654 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Araújo, M. S., Bolnick, D. I. & Layman, C. A. The ecological causes of individual specialisation. Ecol. Lett. 14, 948–958 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
Grémillet, D. et al. Offshore diplomacy, or how seabirds mitigate intra-specific competition: a case study based on GPS tracking of Cape gannets from neighbouring colonies. Mar. Ecol. Prog. Ser. 268, 265–279 (2004).Article 

Google Scholar 
Irons, D. B. Foraging area fidelity of individual seabirds in relation to tidal cycles and flock feeding. Ecology 79, 647–655 (1998).Article 

Google Scholar 
Piper, W. H. Making habitat selection more “familiar”: a review. Behav. Ecol. Sociobiol. 65, 1329–1351 (2011).Article 

Google Scholar 
Davoren, G. K., Montevecchi, W. A. & Anderson, J. T. Search strategies of a pursuit‐diving marine bird and the persistence of prey patches. Ecol. Monogr. 73, 463–481 (2003).Article 

Google Scholar 
Hazen, E. L. et al. Marine top predators as climate and ecosystem sentinels. Front. Ecol. Environ. 17, 565–574 (2019).Article 

Google Scholar 
Dall, S. R. X., Bell, A. M., Bolnick, D. I. & Ratnieks, F. L. An evolutionary ecology of individual differences. Ecol. Lett. 15, 1189–1198 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
McAllister, N. M. Avian fauna from the Yuquot excavation in The Yuquot Project, Volume 2 (eds. Folan, W. J. & Dewhirst, J.) 103–174 (National Historic Parks and Sites Branch, 1980).Drucker, P. I. The Northern and Central Nootkan tribes. Bureau of American Ethnology Bulletin 144, 1–480 (1951).
Google Scholar 
Lepofsky, D. & Caldwell, M. Indigenous marine resource management on the Northwest Coast of North America. Ecol. Process 2, 12 (2013).Article 

Google Scholar 
Dewhirst, J. The Indigenous Archaeology of Yuquout, a Nootkan Outside Village (National Historic Parks and Sites Branch, 1980).Longin, R. New method of collagen extraction for radiocarbon dating. Nature 230, 241–242 (1971).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Guiry, E. J. & Hunt, B. P. V. Integrating fish scale and bone isotopic compositions for ‘deep time’ retrospective studies. Mar. Environ. Res. 160, 104982 (2020).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Hobson, K. A., Atwell, L. & Wassenaar, L. I. Influence of drinking water and diet on the stable-hydrogen isotope ratios of animal tissues. Proc. Natl Acad. Sci. 96, 8003–8006 (1999).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Qi, H., Coplen, T. B., Geilmann, H., Brand, W. A. & Böhlke, J. K. Two new organic reference materials for δ13C and δ15N measurements and a new value for the δ13C of NBS 22 oil. Rapid Commun. Mass Spectrom 17, 2483–2487 (2003).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Qi, H. et al. A new organic reference material, l-glutamic acid, USGS41a, for δ13C and δ15N measurements − a replacement for USGS41. Rapid Commun. Mass Spectrom 30, 859–866 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Szpak, P., Metcalfe, J. Z. & Macdonald, R. A. Best practices for calibrating and reporting stable isotope measurements in archaeology. J. Archaeol. Sci. Rep 13, 609–616 (2017).
Google Scholar 
Hammer, Ø., Haper, A. T. & Ryan, P. D. PAST: paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4, 4 (2001).
Google Scholar 
R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).RStudio Team. RStudio: Integrated Development for R (RStudio, PBC, 2019). More

Obtaining bacterial strains with varied resistance levelsWe experimentally evolved 24 replicate lineages of E. coli to tolerate increasing concentrations of chloramphenicol. By serially passaging bacterial cultures through 14 increasing chloramphenicol levels, we obtained 336 (24 lineages × 14 concentrations) populations of E. coli across a gradient of resistance levels (Fig. 2). The 24 replicate lineages enabled us to study the variability arising from the stochastic nature of mutation acquisition. We refer to these populations as “cultures” rather than “strains” due to the possible coexistence of multiple genotypes.Resistance incurs costs in both thermal tolerance and maximum growth rateWe measured growth rates of experimentally evolved E. coli cultures at three different temperatures: their historic temperature of 37 °C, and the novel temperatures of 32 °C and 42 °C. We hypothesized that growth rate costs of resistance would be larger in the novel temperatures, consistent with reduced thermal niche breadth.Overall, we found the growth rates decreased strongly with increasing antibiotic resistance (Fig. 3A). We then calculated relative growth rates for each lineage by dividing the growth rate at each timepoint by the growth rate of the culture at timepoint 1 (T1) at the appropriate temperature (e.g., all cultures at 32 °C were standardized by the ancestral growth rate at 32 °C). Analysis of these relative growth rates showed that there was both a fitness cost in maximum growth rate and a fitness cost in thermal niche breadth; the linear model showed a strong negative effect of increasing resistance on growth rate at 37 °C (F1, 974 = 988.2, p  More

Boyle, T. H. & Anderson, E. in Cacti: Biology and Uses (ed. Nobel, P. S.) 125–141 (Univ. California Press, 2002).Gibson, A. C. & Nobel, P. S. The Cactus Primer (Harvard Univ. Press, 1986).Bravo Hollis, H. & Sánchez Mejorada, H. Las Cactáceas de México (Univ. Nacional Autónoma de México, 1978).Goettsch, B. et al. High proportion of cactus species threatened with extinction. Nat. Plants 1, 15142 (2015).CAS 
PubMed 

Google Scholar 
Benavides, E., Breceda, A. & Anadón, J. D. Winners and losers in the predicted impact of climate change on cacti species in Baja California. Plant Ecol. 222, 29–44 (2021).
Google Scholar 
Nobel, P. S. Responses of some North American CAM plants to freezing temperatures and doubled CO2 concentrations: implications of global climate change for extending cultivation. J. Arid. Environ. 34, 187–196 (1996).
Google Scholar 
Reyes-García, C. & Andrade, J. L. Crassulacean acid metabolism under global climate change. N. Phytol. 181, 754–757 (2009).
Google Scholar 
Smith, S. D., Didden-Zopfy, B. & Nobel, P. S. High-temperature responses of North American cacti. Ecology 65, 643–651 (1984).
Google Scholar 
Larios, E., González, E. J., Rosen, P. C., Pate, A. & Holm, P. Population projections of an endangered cactus suggest little impact of climate change. Oecologia 192, 439–448 (2020).PubMed 

Google Scholar 
Esparza-Olguı́n, L., Valverde, T. & Vilchis-Anaya, E. Demographic analysis of a rare columnar cactus (Neobuxbaumia macrocephala) in the Tehuacan Valley, Mexico. Biol. Conserv. 103, 349–359 (2002).
Google Scholar 
Seal, C. E. et al. Thermal buffering capacity of the germination phenotype across the environmental envelope of the Cactaceae. Glob. Change Biol. 23, 5309–5317 (2017).
Google Scholar 
Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion under climate change. Nat. Clim. Change 6, 166–171 (2016).
Google Scholar 
Gurvich, D. E. et al. Combined effect of water potential and temperature on seed germination and seedling development of cacti from a mesic Argentine ecosystem. Flora 227, 18–24 (2017).
Google Scholar 
Nuzhyna, N., Baglay, K., Golubenko, A. & Lushchak, O. Anatomically distinct representatives of Cactaceae Juss. family have different response to acute heat shock stress. Flora 242, 137–145 (2018).
Google Scholar 
Andrade, J. L. & Nobel, P. S. Microhabitats and water relations of epiphytic cacti and ferns in a lowland neotropical forest. Biotropica 29, 261–270 (1997).
Google Scholar 
Williams, D. G., Hultine, K. R. & Dettman, D. L. Functional trade-offs in succulent stems predict responses to climate change in columnar cacti. J. Exp. Bot. 65, 3405–3413 (2014).PubMed 

Google Scholar 
Aragón-Gastélum, J. L. et al. Induced climate change impairs photosynthetic performance in Echinocactus platyacanthus, an especially protected Mexican cactus species. Flora Morphol. Distrib. Funct. Ecol. Plants 209, 499–503 (2014).
Google Scholar 
Martorell, C., Montañana, D. M., Ureta, C. & Mandujano, M. C. Assessing the importance of multiple threats to an endangered globose cactus in Mexico: cattle grazing, looting and climate change. Biol. Conserv. 181, 73–81 (2015).
Google Scholar 
Dávila, P., Téllez, O. & Lira, R. Impact of climate change on the distribution of populations of an endemic Mexican columnar cactus in the Tehuacán-Cuicatlán Valley, Mexico. Plant Biosyst. 147, 376–386 (2013).
Google Scholar 
Conver, J. L., Foley, T., Winkler, D. E. & Swann, D. E. Demographic changes over >70 yr in a population of saguaro cacti (Carnegiea gigantea) in the northern Sonoran Desert. J. Arid. Environ. 139, 41–48 (2017).
Google Scholar 
Carrillo-Angeles, I. G., Suzán-Azpiri, H., Mandujano, M. C., Golubov, J. & Martínez-Ávalos, J. G. Niche breadth and the implications of climate change in the conservation of the genus Astrophytum (Cactaceae). J. Arid. Environ. 124, 310–317 (2016).
Google Scholar 
de Cavalcante, A. M. B. & de Duarte, A. S. Modeling the distribution of three cactus species of the Caatinga biome in future climate scenarios. Int. J. Ecol. Environ. Sci. 45, 191–203 (2019).
Google Scholar 
de Cavalcante, A. M. B., de Duarte, A. S. & Ometto, J. P. H. B. Modeling the potential distribution of Epiphyllum phyllanthus (L.) Haw. under future climate scenarios in the Caatinga biome. An. Acad. Bras. Cienc. 92, 351–358 (2020).
Google Scholar 
Tellez-Valdes, O. & DiVila-Aranda, P. Protected areas and climate change: a case study of the cacti in the Tehuacan-Cuicatlan biosphere reserve, Mexico. Conserv. Biol. 17, 846–853 (2003).
Google Scholar 
dos Santos Simões, S., Zappi, D., da Costa, G. M., de Oliveira, G. & Aona, L. Y. S. Spatial niche modelling of five endemic cacti from the Brazilian Caatinga: past, present and future. Austral Ecol. 45, 1–13 (2019).
Google Scholar 
Gorostiague, P., Sajama, J. & Ortega-Baes, P. Will climate change cause spatial mismatch between plants and their pollinators? A test using Andean cactus species. Biol. Conserv. 226, 247–255 (2018).
Google Scholar 
Butler, C. J., Wheeler, E. A. & Stabler, L. B. Distribution of the threatened lace hedgehog cactus (Echinocereus reichenbachii) under various climate change scenarios. J. Torre. Bot. Soc. 139, 46–55 (2012).
Google Scholar 
Johnson, C. N. Species extinction and the relationship between distribution and abundance. Nature 394, 272–274 (1998).CAS 

Google Scholar 
Thuiller, W., Lavorel, S. & Araújo, M. B. Niche properties and geographical extent as predictors of species sensitivity to climate change. Glob. Ecol. Biogeogr. 14, 347–357 (2005).
Google Scholar 
Enquist, B. J. Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. Preprint at PeerJ https://doi.org/10.7287/peerj.preprints.2615v2 (2016).Buisson, L., Thuiller, W., Casajus, N., Lek, S. & Grenouillet, G. Uncertainty in ensemble forecasting of species distribution. Glob. Change Biol. 16, 1145–1157 (2010).
Google Scholar 
Thuiller, W., Guéguen, M., Renaud, J., Karger, D. N. & Zimmermann, N. E. Uncertainty in ensembles of global biodiversity scenarios. Nat. Commun. 10, 1446 (2019).PubMed 
PubMed Central 

Google Scholar 
Goettsch, B., Durán, A. P. & Gaston, K. J. Global gap analysis of cactus species and priority sites for their conservation. Conserv. Biol. 33, 369–376 (2018).PubMed 

Google Scholar 
Maitner, B. S. et al. The bien R package: A tool to access the Botanical Information and Ecology Network (BIEN) database. Methods Ecol. Evol. 9, 373–379 (2018).
Google Scholar 
Karger, D. N. et al. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 170122 (2017).PubMed 
PubMed Central 

Google Scholar 
Sanderson, B. M., Knutti, R. & Caldwell, P. A representative democracy to reduce interdependency in a multimodel ensemble. J. Clim. 28, 5171–5194 (2015).
Google Scholar 
Brodzik, M. J., Billingsley, B., Haran, T., Raup, B. & Savoie, M. H. EASE-Grid 2.0: Incremental but significant improvements for Earth-gridded data sets. ISPRS Int. J. Geo-Inf. 1, 32–45 (2012).
Google Scholar 
Venter, O. et al. Global terrestrial human footprint maps for 1993 and 2009. Sci. Data 3, 160067 (2016).PubMed 
PubMed Central 

Google Scholar 
Phillips, S. maxnet: Fitting ‘maxent’ species distribution models with ‘glmnet’. R package version 0.1.4. https://CRAN.R-project.org/package=maxnet (2017).Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).PubMed 
PubMed Central 

Google Scholar 
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).
Google Scholar 
Franklin, S. B., Gibson, D. J., Robertson, P. A., Pohlmann, J. T. & Fralish, J. S. Parallel analysis: a method for determining significant principal components. J. Veg. Sci. 6, 99–106 (1995).
Google Scholar 
Roberts, D. R. et al. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913–929 (2017).
Google Scholar 
Merow, C., Smith, M. J. & Silander, J. A. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36, 1058–1069 (2013).
Google Scholar 
Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).
Google Scholar 
Calabrese, J. M., Certain, G., Kraan, C. & Dormann, C. F. Stacking species distribution models and adjusting bias by linking them to macroecological models. Glob. Ecol. Biogeogr. 23, 99–112 (2014).
Google Scholar 
R Core Team R: A Language and Environment for Statistical Computing Version 3.6.0 (R Foundation for Statistical Computing, 2019). https://www.R-project.org/ More

Systematic palaeontology
Tetrapoda Jaekel, 1909 fide Sues20
Family undesignated
Termonerpeton makrydactylus gen. et sp. nov. (Fig. 1)Fig. 1: Termonerpeton makrydactylus gen. et sp. nov. holotype UMZC 2019.1.a Specimen photograph. b Interpretive drawing. Scale bars 10 mm. Abbreviations: acet acetabulum, fem femur, fib fibula, ha haemal arch, ic intercentrum, l left, na neural arch, phal phalanx, piliac p post-iliac process, plc pleurocentrum, r right, sac rib sacral rib, tib tibia.Full size image

EtymologyGenus: from τέρμωυ (térmon) meaning boundary and ερπετό (erpetó) meaning ‘crawler’, referring to the field boundary walls near the East Kirkton quarry where the late Stan Wood initially discovered fossils from the East Kirkton Limestone and from where the type specimen may have been collected; species: from μακρύς (makrýs) meaning ‘elongate’ and δάχτυλο (dáchtylo; more precisely, δάχτυλο ποδιού, dáchtylo podioú) meaning ‘toe’, referring to the very long pedal digit IV.HolotypeUniversity of Cambridge Museum of Zoology (UMZC) 2019.1. A partial tetrapod postcranium, preserving both pelves, a femur, fibula, tibia, and an almost complete but disarticulated pes. Closely associated with the appendicular elements are dorsally open hoop-shaped centra, a few neural and haemal arches, curved ribs, and a section of articulated gastralia.Locality and horizonEast Kirkton quarry, near Bathgate, Scotland, UK. East Kirkton Limestone, Bathgate Hills Volcanic Formation. Exact horizon is unknown. Brigantian, Viséan, early Carboniferous (=Mississippian)21.Differential diagnosisPossible autapomorphies: ilium with drawn-out, flat, blade-like dorsal process; very large, stout, and elongate metatarsal IV, greatly exceeding the length of metatarsals III and V (~30% or more). Possible tetrapod synapomorphies among post-Devonian taxa: distinct interepipodial space between tibia and fibula; well-ossified tarsus comprising tibiale, fibulare, intermedium, four centralia, and five distal tarsals. Possible amniote synapomorphies, but often showing reversed polarity in several stem- and crown amniote taxa: presumed pedal phalangeal formula 23454; robust and long pedal digit IV; enlarged intermedium and fibulare, together occupying more than half of proximal moiety of tarsus; curved ribs. Characters of uncertain polarity (also present in Caerorhachis): elongate, slender, and posterodorsally oblique post-iliac process; short puboischiadic plate with almost vertical anterior margin; stout femur with poorly pronounced waisting along the shaft, longer than puboischiadic plate; hoop-shaped centra.Attributed specimenNational Museums Scotland (NMS) G.1992.22.1. An articulated, partially complete, large tetrapod pes, preserving a nearly complete array of tarsals, all metatarsals, and the proximal phalanges of digits I–III. Unit 82, East Kirkton Limestone, East Kirkton quarry, near Bathgate, Scotland, UK.
Specimen description
Appendicular skeletonMost of the description is based upon the holotype. Both pelves are preserved, one mainly as a natural mould. The puboichiadic plates are short and deep, with an almost vertical anterior margin to the pubis (Fig. 1). In one, the surface of the puboischiadic plate is strongly convex, in the other it is strongly concave. The concave plate may belong to the left pelvis, with the concavity indicating the acetabulum. Both iliac processes of the presumed right ilium are overlain by a neural arch and part of the femur and cannot be seen. The presumed left ilium shows a long, posteriorly pointing post-iliac process that extends as far backward as the posterior edge of the ischium. It retains the proximal, stump-like portion of a dorsal iliac process, continued distally in natural mould as a mediolaterally flattened and blade-like structure. Both processes sit above a short iliac neck. The dorsal iliac process is proportionally longer than in other tetrapods and its knife-like appearance is unique. The angle between the two processes is much more acute than in most other tetrapods, and the nearest comparison is with the divided iliac process of the microsaurs Tuditanus and Ricnodon22 which, however, could merely represent a bifid post-iliac process. Two gaps in ossification are taken as evidence of an ilio-ischiadic suture half-way down the posterior margin on the left pelvis and an ilio-pubic suture halfway down the anterior margin of the right pelvis (Fig. 1). There is no evidence of a puboischiadic suture, although a shallow depression along the ventral margin of the left puboischiadic plate probably marks the junction between pubis and ischium. The complete left puboischiadic plate is 20 mm deep behind the ilium and 30 mm long, with the pubis contributing about one-third of its length and the ischium the remaining two thirds. The anterior margin of the pubis is almost vertical. The dorsal margin of the ischium is shallowly convex for half its length before extending posteroventrally to meet the upturned posterior extremity of the ischium’s ventral margin. There is no evidence as to the angle at which the two pelvic plates met at the symphysis, which would affect the position of the acetabulum relative to the substrate, and thus the effective resting posture of the hindlimb.The left femur is at least 39 mm in length, and longer than the puboischiadic plate. The entire bone is crushed, and its distal end lies partly beneath one of the pelvic halves and a neural arch so that its features cannot easily be made out. A possible intercondylar groove may be present distally, and the extensor surface of its proximal extremity appears to show a subcentral depression. The femur itself is robust with little waisting at mid-shaft. A small internal trochanter lies near its proximal end. The left fibula is approximately 26 mm long along its lateral margin. Its proximal end is narrow and grooved. Its broad and strongly flared distal end suggests a broad contact with the tarsus. The medial turn of the distal end indicates a large interepipodial space. The left tibia is about 20 mm long, slender, and shallowly waisted at mid-shaft. It is not clear which end is proximal and which distal, although probably the proximal is the broader. The tibia is probably more than half the length of the femur. Based upon the femur and tibia lengths, and omitting the ankle and pes, the above figures indicate a total stylopod-zeugopod length of about 65 mm, assuming a fully extended limb.Most of the morphology of the left pes is preserved, showing many well-ossified tarsal bones (Fig. 2). Several of these, including possible distal tarsals II and III lie more or less in anatomical continuity relative to metatarsals II and III, respectively. Other tarsal elements, including possible fibulare, tibiale, centralia, and distal tarsals, are illustrated in Fig. 2. Metatarsal IV lies in anatomical position relative to metatarsals II and III and, at 7 mm in length, it is significantly larger than the latter. The presumed first phalanx of pedal digit IV lies close to metatarsal IV, at an angle of nearly 90° to the latter. It is long and slender, indicating an unusually elongate fourth pedal digit.Fig. 2: Termonerpeton makrydactylus gen. et sp. nov. left hindlimb of UMZC 2019.1.a Specimen photograph, showing close-up view of hindlimb skeleton, b Interpretive drawing, with centralia, distal tarsals, and metatarsals indicated by red, blue, and black Roman numerals, respectively, c Interpretive drawing with dashed lines connecting elements of individual digits, d Reconstruction of left tibia, fibula and pes. Scale bars 10 mm. Abbreviations: interm intermedium, tib tibialia.Full size imageAn array of about 12 phalanges is preserved. They are all disrupted but occur in proximity to one another and, like the first phalanx of pedal digit IV, also mainly lie at right angles to metatarsals III and IV. An additional, acutely angled pointed ungual phalanx, possibly associated with digit II, is also visible. A further two phalanges have been displaced and rest along the anterior edge of the left pelvis. In total, we were, therefore, able to identify 15 elements. The preservation of the pes suggests it was strongly flexed either at death or from tissue shrinkage thereafter. An isolated metatarsal, presumably from the other, missing foot, lies some distance away near the edge of the block. Together, the pedal elements suggest a relatively large foot.A second specimen, NMS G.1992.22.1 (Fig. 3), is represented by an isolated pes. It may belong to Termonerpeton, although it is from a much larger individual. It shows five metatarsals of which the fourth is much longer and more robust than the other four and about twice as long as that of the holotype, while metatarsal V is the smallest. There are three phalanges, plus five distal tarsals. A D-shaped element closely associated with three centralia could be either a fibulare, a displaced intermedium, or centrale IV.Fig. 3: Termonerpeton makrydactylus gen. et sp. nov partial pes, attributed specimen NMS G.1992.22.1.a Specimen photograph, b with centralia, distal tarsals, and metatarsals indicated by red, blue, and black Roman numerals, respectively. Scale bars 10 mm.Full size imageAxial skeletonWhere visible, neural arches have short neural spines and prominent zygapophyses, but their shape is hard to assess as none is well preserved. The element overlying part of the right pelvis and the femur is 7 mm high in total. Numerous dorsally open, hoop-shaped centra about 5 mm in diameter are visible, as well as a few small, oval, shallowly curved elements (Fig. 1). Without further evidence, it is uncertain which of these elements are intercentra and which pleurocentra, though we assume that the larger elements are pleurocentra. The preserved ribs are slender and curved, and include trunk ribs, a possible presacral rib, a possible sacral rib, and a possible postsacral rib. This is long but more or less straight. A bone situated among a cluster of centra, somewhat distant from the other tarsal bones, was originally interpreted by us as a possible fibulare, similar to the fibulare in Proterogyrinus23. However, it might also be interpreted as a sacral rib. If so, its morphology is unique. It is short and widens distally into a fan-shaped structure but does not appear to have a bifid proximal end, unlike the sacral rib in Proterogyrinus23. Three haemal arches are present, one still attached to its half-hoop centrum, a second slightly longer, and a third very short and presumably from a more posterior region of the tail.ComparisonsThe exceptional preservation of tetrapods from the East Kirkton Limestone provides a unique opportunity to study portions of the skeletal anatomy that are otherwise poorly preserved or absent among Mississippian tetrapods. In particular, hindlimbs with a complete or near-complete array of tarsal elements and digits are notably rare. The unusual construction of the pes of Termonerpeton prompted us to examine the hindlimb morphology of six other East Kirkton tetrapods (Fig. 4a–g) alongside a selection of additional, mostly Carboniferous taxa (Fig. 4h–n). We focus on epipodials, tarsi, phalangeal formulae and digit length and proportions. To facilitate visual inspection of these elements, all hindlimbs are drawn to a common tibial length, except for the stem diapsid Petrolacosaurus, in which the epipodials are greatly elongate.Fig. 4: Comparison of the left tibia, fibula, tarsus, and digits of early tetrapods.a Balanerpeton after 2, b Eucritta after 12, c Eldeceeon after 6, d Silvanerpeton after 4, e Westlothiana after 7, f Kirktonecta original, see 15 (the grey area marks the estimated position and extent of the tarsus), g Termonerpeton, h Pederpes after 24, i, Greererpeton after 27, j Caerorhachis after 31, k Archeria after 30, l Hylonomus after 28, m Tuditanus after 22, n Petrolacosaurus after 29. Drawn to the same tibial length apart from n. Scale bars 10 mm.Full size imageIn terms of pes size relative to the tibia, the East Kirkton taxa Balanerpeton, Eucritta, and Silvanerpeton (Fig. 4a, b, d) are similarly proportioned. In contrast, Eldeceeon and Westlothiana (Fig. 4c, e) exhibit somewhat larger pedes. Kirktonecta has proportionally the largest pedes of all (Fig. 4f). Termonerpeton (Fig. 4g) has a pes of similar size to the first three taxa except that digit IV is relatively much longer than in any of the others, with an exceptionally large metatarsal IV. In all those taxa in which digit IV is fully preserved, it is the longest, especially in Eldeceeon and Kirktonecta, but in none does it approach in size and proportions that of Termonerpeton. The illustrated limbs also differ from one another in the degree of ossification of the tarsal bones. Most taxa except Eucritta have some indication of ossified tarsal elements, and some of them, including Balanerpeton and Silvanerpeton, show a complete or almost complete tarsal set. Kirktonecta does have an ossified tarsus, but specimen preservation does not allow us to identify individual elements. The phalangeal count, where known, also varies: 22343 in Balanerpeton2; 223?? in Eucritta12; 23455 in Silvanerpeton4; 23454 in Eldeceeon6, Kirktonecta15, Termonerpeton, and Westlothiana7.In addition, we compared the pedes of East Kirkton tetrapods with those of seven other taxa (Fig. 4h–n): one earlier, Pederpes24; one almost contemporary, Caerorhachis25; four later Carboniferous, Greererpeton26, Hylonomus27, Tuditanus22, and Petrolacosaurus28; and one early Permian, Archeria29. Of these, Greererpeton has relatively the smallest pes. In most, digit IV is the longest, though in Pederpes and Caerorhachis it is incomplete. The pes of Caerorhachis was originally restored with only three phalanges in digit IV30. This is probably incorrect and would be unusual in Carboniferous tetrapods. The pes of the anthracosaur Archeria was originally reconstructed with digit V as the longest29, but again this is unusual among later Carboniferous and early Permian tetrapods and we suspect that digits IV and V have been transposed, and Romer himself expressed doubt about this reconstruction29. In either case, the phalangeal formula of Archeria is similar to that of the East Kirkton anthracosaur Silvanerpeton, as 23455.Among Carboniferous tetrapods, temnospondyls such as Balanerpeton and colosteids such as Greererpeton show a digit IV that is somewhat longer than the others, but metatarsal IV is very similar in length and breadth to the adjacent metatarsals. In anthracosaurs, digit IV is the longest, but again metatarsal IV is not significantly broader than adjacent metatarsals. This is also the case in the early amniote Hylonomus and the microsaur Tuditanus. Among the taxa illustrated here, Termonerpeton shows a strikingly similar pes to that of the Late Pennsylvanian araeoscelidian diapsid Petrolacosaurus (Fig. 4n). In both, metatarsal IV is significantly longer and stouter than others and forms part of a similarly long digit IV. In early amniotes, an elongate digit IV coupled with an elongate metatarsal IV is a common occurrence in other taxa, such as protothyridids (e.g. Anthracodromeus31), basal araeoscelidians (e.g. Spinoaequalis32), younginids (e.g. Youngina33), saurians33, and basal synapsids (e.g. Heleosaurus34,35,36), among others.Based upon available evidence, an elongate digit IV is likely to be the plesiomorphic condition for crown amniotes, being present in Hylonomus, Paleothyris, and Petrolacosaurus (Fig. 4l, n), and shortening of this digit certainly represents a derived feature. In later crown amniotes, the conditions vary, with larger, heavier-bodied tetrapods such as dicynodonts and diadectids having generally shorter toes and adopting a more clearly plantigrade posture. An elongate metatarsal IV and associated digit, however, are not universal among Palaeozoic amniotes, and modifications of these conditions occur repeatedly across clades. For instance, in the eureptile captorhinid Eocaptorhinus, digit IV is also the longest, but the length of metatarsal IV does not greatly exceed that of other metatarsals37. The same is true of some early Permian clades, including seymouriamorphs (e.g. Seymouria38; Discosauriscus39), and diadectids (e.g. Diadectes40), although in the diadectomorph Orobates digit III is a little longer than digit IV41. Among synapsids, dicynodonts such as Diictodon42 and caseids43, to name a few, have five pedal digits of approximately uniform length.We further point out that, while digit IV attains a certain degree of elongation in other early tetrapod groups, such as temnospondyls, in none of them do the relative proportions of this digit (where known) compare to those of several stem and crown amniotes (Fig. 4).Phylogenetic relationshipsThe results of various phylogenetic analyses lend some support to the interpretation of Termonerpeton as a stem amniote, despite its uncertain placement in the unweighted character parsimony analysis (Fig. 5a). In the latter analysis, Termonerpeton appears in a polytomous node alongside baphetids (Eucritta; Baphetes; Megalocephalus), temnospondyls (Balanerpeton; Dendrysekos), the anthracosauroids Eldeceeon and Silvanerpeton, and the problematic Caerorhachis. In all other analyses—implied weights, reweighted characters, and Bayesian—Termonerpeton is placed on the amniote stem group, albeit in different positions, among a diverse array of ‘reptiliomorph’ clades and grades. In the implied weights analysis (Fig. 5b), Termonerpeton, Silvanerpeton, and Eldeceeon form a monophyletic group branching crownward of chroniosaurs plus anthracosaurs and anti-crownward of paraphyletic gephyrostegids. In the reweighted analysis (Fig. 5c), Termonerpeton and Caerorhachis appear as successive sister taxa, in that order, to monophyletic anthracosaurs. In the Bayesian analysis (Fig. 5d), the amniote total group receives moderate support with a credibility value (c.v.) of 76 with Caerorhachis as the most plesiomorphic stem amniote. Crownward of Caerorhachis is a polytomy with low support (c.v. = 59) that subtends Termonerpeton, a clade consisting of Eldeceeon plus Silvanerpeton, a clade of anthracosaurs, and a clade that includes all remaining taxa. In crownward succession, these taxa include chroniosaurs, gephyrostegids, seymouriamorphs, Solenodonsaurus, and Westlothiana as successive sister groups to a strongly supported (c.v. = 100) clade containing diadectomorphs, synapsids, and eureptiles. Although eureptile monophyly is not retrieved, strong support (c.v. = 100) is given to the branch subtending diadectomorphs plus synapsids44.Fig. 5: Results of phylogenetic analyses.a Strict consensus of 120 shortest trees from unweighted analysis (tree length = 1286 steps, ensemble consistency index C.I. = 0.2738 without uninformative characters, ensemble retention index R.I. = 0.5768), b Single tree from implied weights analysis (tree length = 1298 steps, Goloboff fit = −202.59266, C.I. = 0.2712, R.I. = 0.5713), c Single tree from reweighted analysis (tree length = 212,68965 steps, C.I. = 0.4755, R.I. = 0.774), d Bayesian topology with branches reporting credibility values.Full size image More

Species used in the experimentsMilnesium inceptum32 (Fig. 1A, a picture taken using Olympus BX41 Phase Contrast light Microscope associated with Olympus SC50 digital camera) is an obligatory predatory species with the body length ranging from 326 to 848 μm. It feeds on rotifers, nematodes and other tardigrades and lays smooth eggs in exuviae. To stay active, M. inceptum needs a thin water film around its body14. The species inhabits places exposed to shorter and longer periods of drying i.e. frequently drying mosses growing on cement walls32. Till now it was reported in Poland, Germany, Japan, Switzerland and Bulgaria32. At the same time, it is a perfect organism for our research because (1) it is large and easy to observe, (2) it tolerates frequent periods of entering and leaving anhydrobiosis, (3) it easily creates a tun stage. Milnesium inceptum for experimental purposes were acquired from a moss sample from a cement wall in Poznań, Poland (52°24′15″N, 16°53′18″E). The extraction of tardigrades was conducted under stereomicroscope (Olympus SZ51) using standard methods33. Then specimens, further used in our experiments, have been cultured based on protocol proposed by Roszkowska et al.34. Only fully active, adult specimens were selected for the experiments.Figure 1Model animals used in experiments: (A) Milnesium inceptum; insert shows tardigrade in the tun state; (B) Cepaea nemoralis in its natural environment; (C) a tardigrade that appeared on moss surface during in vivo observation of rehydrated moss cushion (red arrow). Figures were assembled in Corel Photo-Paint 2017 (http://www.corel.com).Full size imageCepaea nemoralis35 (Fig. 1B, a picture taken using Motorola g(9), Camera version 7.3.63.53-whitney) is a stylommatophoran European land snail species, which is widespread and common throughout the continent36. The average maximum shell diameter is 20 to 22 mm37. It feeds on plant materials available, yet has a strong preference for dead and senescent herbs38. C. nemoralis occurs in variable habitats (frequently in synanthropic ones) such as forests, meadows, gardens, near shrubs or dunes36.The period of its activity falls on the growing season; it usually comes out of the shell and crawls when the air humidity reaches 70% or more, independently from solar radiation and air temperature28. The species is a good model for our study due to its: (1) large size compared to tardigrades, and (2) co-occurrence with M. inceptum in natural environments. Individuals of C. nemoralis were harvested from anthropogenic environment: gardens adjacent to detached houses (52°25′28″N, 16°46′52″E). Snails were collected from plants, cement walls and ground surfaces. After collection, all C. nemoralis specimens were washed-up and placed in 30 L (480 × 360 × 252 mm) transparent plastic box with mesh covering for ventilation. Soil and rocks were placed in the box allowing to maintain a moist shelter for snails, and a sepia was used as a source of a calcium. Animals were fed with lettuce, cabbage and nettle twice a week and sprinkled with water to stimulate their activity. Box containing snails was kept in a rearing room, at 17 °C in 12:12 photoperiod. Snails were kept in the box for 1.5 months prior to the experiments. For the experiments we used only adult animals. The snails were checked under Olympus SZX7 stereomicroscope prior to the experiment to ensure they were free of tardigrades.Pilot studiesDoes the tardigrades’ distribution within a moss cushion enable tardigrade-snail contact?To check whether tardigrades may come into a close encounter with the snail in the natural environment (which would be impossible if the tardigrades were only present in the lower layers of the moss), we investigated the distribution of water bears within moss cushions. The observations were performed for 6 samples of dried moss cushions (ca. 1 cm high and 3 cm in diameter). The moss containing M. inceptum specimens, was collected from a concrete wall in Poznań, Poland (52°24′15″N, 16°53′18″E), the same from which tardigrades were initially collected for the culturing purposes. Three moss cushions were rehydrated, and left for 3 h followed by further observation to check whether tardigrades may actively move across the moss cushion. On the remaining three moss samples, a horizontal cut was made through the center of the moss cushion to check in which layer tardigrade tuns are present while the moss remains dry. The extraction of tardigrades from separated layers was conducted under stereomicroscope (Olympus SZ51) using standard methods33.Within the dry moss cushions tardigrades were present in both the upper and lower moss layers. We did not observe any difference in the number of individuals of M. inceptum that would be dependent on the moss layer. A total of 353 tardigrades were extracted from one moss cushion (dry weight of moss = 0.332 g), what gives the density of tardigrades per 1 g of dry moss sample equal to 1063 specimens. The observation of rehydrated moss cushions conducted in vivo using Olympus SZX16 stereomicroscope associated with Olympus DP74 digital camera and cellSens software revealed that single active tardigrades may also appear on the moss surface (Fig. 1C, red arrow). Therefore, observed in the pilot studies tardigrades distribution within the moss cushion enables tardigrade-snail contact.Is it possible for a tardigrade to take a snail ride?The initial observations were carried out for snails and tardigrades to check whenever a tardigrade may be transferred by a snail. In total, 10 snails and 20 active tardigrades were used. Two variants of Petri dishes (ø 90 mm) were prepared: (1) with smooth and (2) scratched bottom, to avoid and allow tardigrade attachment to the bottom of the dish, respectively. We repeated the observation five times per option. For each single observation we used one snail and two tardigrades.Snails and tardigrades were split equally between the pilot’s experimental options (in total 5 snails and 10 tardigrades per option). We checked whether tardigrades may be transferred by snails by putting tardigrades in the drop of water in the center of a Petri dish and releasing an active snail to crawl through the drop. In total, in the case of the smooth-bottom option, three tardigrades glued to the snail’s body within which two were moved to a distance up to a few centimeters. The third one fixed to a snail’s leg and had a potential to be transferred to a greater distance. In the case of the dishes with the scratched bottom, we did not notice any transfer. Tardigrades were attached tightly to the dishes’ bottom and remained unmoved after the snail had passed through them. Therefore, the observation in the pilot study confirmed that tardigrades may stick to snails’ body and be transferred by a gastropod at least when the substratum (bottom of the dish) is smooth.Experimental design
Experiment 1. Do snails have a significant effect on tardigrade dispersion that depends on the substrate type?As the laboratory environment offers limited possibilities to reflect natural conditions, we aimed to create an environment similar to the natural one by eliminating as many artificial elements as possible and, at the same time, enabling observation and data collection. To imitate a natural microhabitat of water bears we used a piece of moss as a substrate. Moss is a natural shelter and a hunting space for these animals, and a gripping surface that prevents them from being easily carried away by a stream of water or wind. The moss Vesicularia dubyana39 used in the experiment was purchased in an aquarium shop and was derived from an in vitro culture. It was checked under Olympus SZX7 stereomicroscope prior to the experiment to ensure it was free of tardigrades. For experimental purposes we used plastic ventilated boxes with dimensions 950 mm × 950 mm × 600 mm, tightly closed with a plastic lid. The bottom of each box was scratched with sandpaper in order to (1) imitate a rough surface of a concrete wall to which mosses are attached in the natural environment; (2) allow tardigrade locomotion. At the same time, moss and (unfortunately) plastic elements are quite common surroundings of C. nemoralis frequently found in anthropogenic habitats36.Using transparent, non-toxic aquarium silicone, a square with a side length of 3 cm and a height of 0.5 cm was mounted on the bottom of the box. Before starting the experiment, the tightness of the square silicone barrier was checked by pouring 2.5 ml of water inside and leaving the boxes for observation for 24 h. After this time, all silicone squares turned out to be impermeable to water.Boxes for each of the experimental option, namely: (A) control (further in the text referred as C), (B) tardigrades + snail (referred as TS), and (C) tardigrades + snail + moss (referred as TSM, see Fig. 2), were prepared in a following way: 2.5 ml of water was added to the scratched bottom of the box inside the silicone square and 7.5 ml to the area outside of the silicone square to enable survival and active locomotion of tardigrades on both sides of the silicone barrier. Then, 10 active individuals of M. inceptum taken from the culture were transferred to the center of the silicone square. It was repeated for 90 boxes (30 boxes per each C, TS and TSM option). Therefore we used 300 tardigrades per each experimental option which gives 900 tardigrades in total for all experimental options. In case of 30 boxes with TSM option, a piece of moss (ca. 2.5 cm in diameter) was added. It was situated in the center of the silicone square, just after the tardigrades were placed at the boxes in order to isolate tardigrades from the snail during the experiment.Figure 2Graphical representation of three designed experimental options of the experiment 1. (A) 10 tardigrades in the silicone square (control (C)); (B) 10 tardigrades in the silicone square and one snail placed in the box (tardigrades + snail (TS)); (C) 10 tardigrades in the silicone square, one snail placed in the box and additional piece of the moss added as a barrier between tardigrades and snail (tardigrades + snail + moss (TSM)). Figures were assembled in Corel Photo-Paint 2017 (http://www.corel.com).Full size imageFinally, in the boxes targeted for TS and TSM experimental options, one adult and active individual of C. nemoralis snail was placed in each box outside the silicone square. In total, 60 snails were used (30 individuals per experimental option).The boxes were then placed in the rearing room (17 °C, 80% of humidity, photoperiod 12:12) for 72 h. After this time, the number of tardigrades inside and outside the silicone square was counted (both: live and dead) separately for each box, using Olympus SZX7 stereomicroscope.Experiment 2. Effect of the snail’s mucus on tardigrade recovery to active life after anhydrobiosis
Milnesium inceptum anhydrobiosis protocolOnly fully active, adult specimens of medium body length were selected for the experiment. The animals were transferred to ø 3.5 cm vented Petri-dishes with bottom scratched by sandpaper to allow tardigrade locomotion. Five tardigrade individuals were placed to each Petri dish together with 450 µl of water and then dehydrated. In total, 16 Petri dishes with 5 tardigrades on each were prepared. Dehydration process lasted 72 h and was performed in the Q-Cell incubator (40–50% RH, 20 °C, darkness). After that time tardigrade tuns were kept under the abovementioned conditions for 7 days.Impact of the snail’s mucus on tardigrade tunsAfter 7 days of anhydrobiosis, one individual of C. nemoralis was transferred to each dish with tardigrade tuns and was left there for 1 min allowing the snail to actively crawl over the tuns. 30 min after the snail was removed from the dish, tardigrade tuns were observed under the Olympus SZX7 stereomicroscope for any animal movements. Then, all covered and vented dishes were left in the Q-Cell incubator overnight. After 24 h, the dried tuns were rehydrated by adding 3 ml of water to each Petri dish to check whether snail’s mucus affected mortality rates of tardigrades. After 3 and 24 h following rehydration tardigrade tuns were observed for any animal movements. Pictures of tuns were taken using Olympus SZ61 stereomicroscope associated with Olympus UC30 camera (Fig. 3). As reference data on the rehydration of the M. inceptum tuns free of the snail’s mucus, we used the data from Roszkowska et al.20 who tested anhydrobiosis survivability of above-mentioned species. Individuals used for the tuns preparation in the control option were collected from the same laboratory breeding stock, and prepared at the same laboratory conditions as those used in our experiments20.Figure 3Milnesium inceptum tuns: (A,B) before contact with snail mucus; (C,D) coated with wet snail mucus; (E,F) coated with dry snail mucus. Figures were assembled in Corel Photo-Paint 2017 (http://www.corel.com).Full size imageStatistical analysesThe number of tardigrades relocated in each experimental option (C, TS and TSM) was compared with a one-way ANOVA randomized version using RundomPro 3.14 software40. We used non-parametric methods because of the lack of normality. Differences were considered significant at p  More