There is a long‐standing idea that the timing of leaf production in seasonally cold climates is linked to xylem anatomy, specifically vessel diameter because of the hydraulic requirements of expanding leaves.We tested for a relationship between the timing of leaf out and vessel diameter in 220 plants in three common gardens accounting for species’ phylogenetic relationships. We investigated how vessel diameter related to wood porosity, plant height and leaf length. We also used dye perfusion tests to determine whether plants relied on xylem produced during the previous growing season at the time of leaf out.In all three gardens, there was later leaf out in species with wider vessels. Ring‐porous species had the widest vessels, exhibited latest leaf out and relied less on xylem made during the previous growing season than diffuse‐porous species. Wood anatomy and leaf phenology did not exhibit a phylogenetic signal.The timing of leaf out is correlated with wood anatomy across species regardless of species’ geographic origin and phylogenetic relationships. This correlation could be a result of developmental and physiological links between leaves and wood or tied to a larger safety efficiency trade‐off. 235: 815–820Olson, .See also the Commentary on this article by  A major component of this shift is driven by early leaf out in deciduous species . The si  and the  that were grown in three common gardens. Our aim was to test whether this relationship exits and determine if wood anatomy can adequately predict leaf phenology. To account for plasticity and intraspecific variation, we observed phenology on the same plants that were used for anatomical analyses. We also investigated how phylogeny, species geographic origin, plant height and leaf length are related to both wood anatomy and leaf phenology. Overall, this study allows us to examine whether there might be developmental and physiological links that exist between stem xylem and leaf phenology.To examine the potential relationship between spring leaf phenology and woody anatomy in the context of phylogenetic relationships and climate of origin, we studied plants from three common gardens Fig. . Initialwww.ncei.noaa.gov).In each common garden, we monitored leaf phenology every 2–7 d in the spring and recorded leaf out, which we defined as when at least three branches or 50% of the plant (whichever came first) had leaves unfolding with the final leaf shape at least partially visible. Any plant that experienced significant dieback was noted. We also measured the height of all the plants. Leaf out dates were reported as day of the year and degree days, cumulative thermal sum of the degrees above 0°C each day starting on January 1 Heide, . WeathermageJ  and 100 vessels in the remaining species. Average vessel diameter for each sample was calculated assuming the vessels were round in cross‐section. We only measured vessels from the most recent, complete year of growth in each branch because these vessels provide the bulk hydraulic support for the newly developing leaves in the spring (if not embolized). This meant that we sampled the second year of growth in 3‐yr‐old samples and could avoid vessels that expanded after leaf out and protoxylem from the first year. Note that there are species in our study that may have vascular and vasicentric tracheids that cannot be easily differentiated from vessels in cross‐section. We did not characterize these cells separately and grouped them with the vessels. Assuming these conduits are conductive, there should be a similar relationship between their diameter and freezing‐induced embolism as observed in vessels . They were stained with 1% safranin O and analyzed using IWe classified each species as diffuse porous (vessels remain a similar width throughout the growth ring), semi‐ring porous  or ring porous (wood has two distinct types of vessels: wide earlywood vessels and narrow latewood vessels). Several salicaceous species exhibited differences in wood porosity among samples. We noted when this was the case and for our subsequent analyses considered a species diffuse porous if most samples were diffuse porous.c. 30 μm in deciduous angiosperms) over which vessels often exhibit freezing‐induced embolism assuming a water potential of −0.5 MPa  was pulled through the stems following Jacobsen et al. . There was some overlap in species from the anatomy work and the addition of five other local species Table . Betweenρw is the density of water, η is the viscosity of water and id is the diameter of the ith vessel.We cut each stem in the middle with a razor blade and imaged the entire section with a stereo microscope to determine the cross‐sectional area of wood that contained dye in the current and past growth rings. We also made thin sections (10–15 μm) using a sledge microtome and imaged the samples using a compound microscope  to estimate hydraulic conductivity of functional conduits based on Poiseuille’s law  of a minimum of 100 vessels in each stem along with the vessel density in the region sampled (D) and the xylem area that contained dye (A). We assumed that vessel width and density were consistent across the sample and then calculated theoretical conductivity of the whole segment using the equation:For diffuse porous species, we estimate the average diameter , S. fuscescens (AUC = 0.85) and Ribes triste (AUC = 0.82). We found a minimum of 100 collection sites per species with the exception of Berberis virgetorum (n = 40), Carya laciniosa (n = 86), Hemiptelea davidii (n = 76), and Liriodendron chinense (n = 80). Three plants were not included in this analysis, two were horticultural hybrids (Ulmus ‘Patriot’ and Ulmus ‘Kansas hybrid’), and one, Pyrus cossonii had no georeferenced data points available. We only excluded records that had questionable origin (e.g. appeared outside of the species documented range). We previously ran a similar analysis on willow and poplar species  and wood anatomy (average vessel diameter) in our largest dataset (diverse garden) when taking into account species’ phylogenetic relationships. For our phylogeny, we used the most broadly sampled time‐calibrated phylogeny of seed plants to date  and compared it to a model where λ = 0 using χ2 likelihood ratio test. This analysis allowed us to test whether the base model was different than a model assuming complete independence (star phylogeny). We also tested for phylogenetic signal in the timing of leaf out and vessel diameter using the ‘phylosig’ function using phytools v.0.7  and growing degree days at the time of leaf out using a least squares multiple regression model. This model was run on a species‐level using average values in the local garden and raw data in the diverse garden where there was no within species replication. Because the variables are likely collinear, we compared all possible linear regression models that involved these variables and selected the model with the lowest Akaike information criterion (AIC). We did a second model that included both datasets and included an interaction parameter (dataset by vessel diameter interaction). For the salicaceous garden analysis, we fit a nonlinear growth model to the relationship between leaf out time and vessel diameter and also completed a logistic regression. We completed similar regression analysis comparing vessel diameter and leaf out time in terms of day of the year. For all our models, we ran them two ways, with raw data and with log‐transformed vessel diameter and height to account for the potential for multiplicative error in these variables  and the Flora of China . We also examined the relationship between vessel diameter and the minimum temperature in each species climatic niche (based on the Maxent model) directly using regression analysis and by examining the relationship between the residuals of the vessel–leaf length–height relationship and climatic niche. For cross‐species comparison of anatomy and conductivity estimates, we used ANOVA and Tukey honestly significant difference (HSD) multiple comparisons. These analyses were conducted in JMP Pro (v.13.0.0). Maps in this article were created using ArcGIS® software by Esri . ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license.To examine how vessel diameter is influenced by scaling within the plant, we modeled the relationship between vessel diameter, maximum leaf length and plant height using linear regression. Maximum leaf length was determined based on the literature . The relationship between leaf out time and vessel diameter was also robust when examining day of the year . The window for leaf out in these two datasets ranged from 5 to 7 wk with the shortest range occurring in the local garden (6 May–6 June 2019) and the longest in the diverse garden (12 April–24 May 2017). Most of the plants with an average vessel diameter over the critical size threshold for freezing‐induced embolism (30 μm) did not experience leaf out until the risk of freezing was low (< 10% chance of temperatures below 0°C) at each site , and there was no significant difference between the model that included phylogeny and one that assumed complete independence, where λ = 0 . We also ran the analysis on local and diverse gardens combined. To combine these datasets, we compared the relationships between leaf out time and vessel diameter. Because the slopes of these regressions were not different among sites, we adjusted the two lines to have the same intercept by adding the difference between the intercepts to the growing degree days of the local species  and still was not different than a model assuming phylogenetic independence . We also found little evidence of phylogenetic signal in both average leaf out time (in growing degree days) and vessel diameter using Blomberg’s K  and Pagel’s lambda  when examining the combined dataset.In the diverse garden, the correlation of growing degree days at leaf out with vessel diameter remained significant when phylogenetic relationships were taken into account  with over 50% of its vessels above the threshold were ring and semi‐ring porous, leading to a significant difference in the width distribution of vessels with wood porosity  and not the diverse garden . There were no species with ring‐porous wood in the salicaceous garden. Across all datasets, average vessel diameter linearly correlated with the proportion of vessels > 30 μm  and lowest for woody plants that leaf out later in the spring . There was also a significant difference in the diameter of vessels containing dye in the spring  with the latest species to leaf out having dye only in wide, earlywood vessels . There was no correlation when the residuals of the vessel–leaf length–height relationship was analyzed in relationship to climatic niche .When examining all our data, only leaf length had a significant effect on vessel diameter when both plant height and average maximum leaf length were included in the same model .et al., et al., et al., et al., et al., et al., Sampling design in this type of study is critical because of spatial variation in xylem conduit diameter and vascular phenology along the length of a plant  and vessel diameter.Fig. S3 Relationship between percent of vessels over 30 μm and average vessel diameter.Fig. S4 Relationship between vessel diameter, height, maximum leaf length and climatic niche.Table S1 Data and species list from Bagley Nature Area, Duluth, MN, USA.Table S2 Data and species list from the Arnold Arboretum, Boston, MA, USA.Table S3 Data and species list from Franklinville, NY, USA.Table S4 Data and species list for dye perfusion tests.Table S5 Species locations used in modeling climatic niche.Table S6 Linear model of growing degree days at leaf out in local group with raw data.Table S7 Linear model of growing degree days at leaf out in local group with partially log‐transformed data.Table S8 Linear model of growing degree days at leaf out in diverse group with raw data.Table S9 Linear model of growing degree days at leaf out in diverse group with partially log‐transformed data.New Phytologist Central Office.Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries  should be directed to the Click here for additional data file.


The objective of this study was to evaluate the possibility of analysing quality indicators for uncomplicated primary rhegmatogenous retinal detachment in a hospital department of ophthalmology without the support of a national registry or need to collect data from referring ophthalmological centres.In 2014, we operated 231 consecutive eyes with uncomplicated retinal detachment. Our quality indicators were primary anatomical success, final anatomical success and postoperative endophthalmitis. We reviewed medical records in our university surgical department retrospectively and compared them with medical records from the regional hospitals that had referred most of the operated patients and done their own postoperative examination. Our hypothesis was that any retinal re‐detachment and/or serious postoperative complication would be reported back.The medical records at the surgical department revealed primary anatomic success for 91.3% of eyes and final anatomical success of 99.6%. The data from the regional hospitals confirmed that our hypothesis was correct. All patients with adverse outcomes were referred back for reoperation. Patients who were not referred again had an attached retina and showed no signs of endophthalmitis.Our hypothesis that data in the surgical department's medical records would closely reflect those in referring hospitals was borne out. This supports, under current conditions, an effective strategy for analysing chosen quality indicators without relying on a national registry or reviewing records from regional hospitals. Primary rhegmatogenous retinal detachment is one of the most common eye diseases surgically treated at the vitreoretinal centre in Örebro University Hospital in Sweden. While some countries have national registries to follow up retinal detachment surgery .Thorough follow‐up of vitreoretinal surgery is necessary and desirable. The most obvious reason for this is to educate new surgeons and to keep them and more experienced surgeons up to date as new technologies develop. Follow‐up knowledge also facilitates the transfer of information to patients about their expected results and any potential complications. Politicians have been increasingly interested in ensuring that different regions have equal access to resources and demonstrate equal competence and quality of care, leading currently to both political and healthcare demands that surgical units publish or otherwise present their results.In everyday clinical practice, it is not always possible or desirable to monitor operated patients for 6 months simply to meet the requirements for an academic report. All regional records in this study were reviewed at least 2 years after the primary operation. Patients who died before 6 months were excluded, and the date of the last visit was the end date for follow‐up. Had the patient not made new contact at the time of journal review, we assumed that the process was uncomplicated.Our hypothesis in this study was that regional hospitals reliably notify the surgical unit or re‐refer patients who suffer a postoperative detached retina and/or other significant postoperative complications. If the hypothesis were true, the surgical unit charts would contain all relevant information about deviant recoveries and major complications for all patients, both local and referred from a regional hospital.This would mean that if there was no other information in the medical journal at the surgical unit other than the discharge notes, we could assume the recovery developed as intended.The purpose of this study was to review a simple method to continuously evaluate our chosen quality indicators in uncomplicated primary retinal detachment surgery , final success  and postoperative endophthalmitis following the primary operation as our quality indicators. Follow‐up time is defined by the last complete retinal assessment.The inclusion criterion for defining a condition as ‘uncomplicated’ was rhegmatogenous retinal detachment, regardless of refraction, preoperative laserpexy around retinal breaks, number of retinal breaks and/or uncomplicated cataract surgery. We used the same exclusion criteria as Mazinani et al. •giant retinal tears (4 eyes)•ongoing PVR process •detachments affected by other retinal diseases; proliferative diabetic retinopathy, full‐thickness macular hole, extensive vitreous haemorrhage and vasoproliferative tumours (10 eyes)•earlier eye trauma, vitreous surgery or complicated glaucoma surgery (16 eyes)•Optic pit (1 eye)•Unclear breaks (1 eye)Exclusions due to complex diagnosis:•Refusal to give access to medical records (5 eyes)•Did not return for planned visit (1 eye)•Lived abroad and was followed up outside of Sweden (1 eye)•Died before 6 months had elapsed from the day of surgery (1 eye)•17 years old at the time of operation (1 eye)•Endophthalmitis after the primary surgery and secondary retinal detachment (1 eye) *Exclusion due to administrative reasons:Removal of silicone oil (SO) was not considered a failed surgery. Follow‐up of primary and final successes therefore included 230 of the 231 eyes in the entire sample of 228 patients .The operations were performed by 11 different retinal specialists. In some surgeries, a retinal fellow also participated, but there was always an experienced retinal surgeon present. All surgeons made their own decisions about surgical technique, medical treatment and postoperative mobilization. Patients in the university area were called to postoperative examination at the university's outpatient clinic, and those from regional hospitals to those centres. Examining doctors decided when to complete the examination and when to assess the condition as stable. At the final examination, patients were instructed to return if they developed recurrent or new symptoms. The length of follow‐up was decided individually based on baseline status and the course of the disease; therefore, observation times may vary from months to years.Primary or final anatomic success was defined as the absence of any indication for retina reattachment during follow‐up. Retina reattaching procedures included additional gas injection, second vitrectomy or additional scleral buckling (SB). Indication for any of those was regarded as treatment failure  was performed using the Alcon Accurus vitrectomy system and consisted of a standard 3 or 4 port 20/23 or 25 G vitrectomy using a non‐contact wide‐angle viewing system. Retinopexies of breaks were performed with endolaser probes. The use of heavy perfluorocarbon liquids was optional, and the choice of tamponade was left to the surgeon's preference. Pars plana vitrectomy/SB consisted of PPV as described above combined with an encircling 2.5‐mm silicon band. No other techniques such as pneumatic retinopexy, single buckle or Lincoff balloon were performed. The most common surgical technique was vitrectomy .2F6  eyes were vitrectomized. The majority of eyes were phakic 63.1% (130/206). In 19 (14.6%) of these, we operated using a combined procedure involving 18 faco/IOL and 1 faco without IOL due to capsula rupture. Besides these 19 cataract operations, one lensectomy was performed due to increasing preoperative lens opacities. The main ocular tamponade agent used to treat these diseases in vitrectomized eyes was intraocular gas, usually CIn total, 228 patients and 231 eyes were operated (53 patients and 54 eyes from the Örebro area.) Most patients who were referred had no postoperative follow‐up notes in our records because they were examined at their home hospital. Our hypothesis was that regional patients who were not re‐referred had presented themselves with an attached retina and no serious complications. If we assume that the hypothesis applies, then primary success = 91.3%  did have an uncomplicated postoperative follow‐up with attached retina and lack of serious complications. Thus, our hypothesis was confirmed: The outcomes of success and endophthalmitis can be read from the records at the university hospital.vitrectomy‐laserpexy‐gas. Of these, 14 eyes were reattached after a total of 25 additional operations. The remaining eye underwent two reoperations, but although the retina was attached centrally, it had a peripheral detachment behind the SO. Due to its poor visual acuity, we aborted further operations on this eye and defined this case as a failure. Only one eye that had a failed primary surgery was successfully attached after one reoperation using vitrectomy‐encircling band‐gas, and four others were attached with scleral buckling after a total of six additional operations. Among those eyes included as final successes, we found three eyes with either a small retinal vesicle or a shallow peripheral detachment/retinoschisis in the periphery. These patients were unaware of the findings. We demarcated the alterations with external laserpexy, and they remained stable without any further surgery.Of the eyes that did not achieve primary success, 15 were reoperated using The results of this confirmed our hypothesis to be true and justify the policy of following‐up operative results on chosen indicators by assuming that the charts from the surgical department mirror the whole material. Although our study and those of other researchers differ in many respect, and inclusion and exclusion criteria are not fully consistent across studies, our study shows us that our overall primary and final success rates are well within the ranges found in other international studies , they have the same median age (64 years).Pars plana vitrectomy has both advantages and disadvantages. There are obvious benefits in the presence of vitreous pathology, multiple large or central retinal breaks and poor transparency due to peripheral capsule opacities in patients with pseudophakia. Local anaesthesia is usually effective, and the operation and postoperative period are often experienced as less strenuous and uncomplicated than with SB (Mohamed et al. The disadvantages of PPV include the development of cataracts in phakic patients, the inconvenience of the gas tamponade and the risk of macular detachment when the gas is resorbed. Iatrogenic ruptures, dislocation of intraocular lenses and unexpected loss of vision and secondary glaucoma are also sometimes seen, especially during and after SO tamponade (Christensen & la Cour 2F6 use. Many surgeons probably choose the type of gas tamponade based on the number of breaks and their locations, but the choice is also determined by the patient's ability to position or other aspects based on the patient's preference (Sahanne et al. Our material also has a preponderance of CIn selecting a type of treatment, one must also consider the risk of complications and the patient's preferences. We prefer to individualize decisions and are not looking for fixed solutions that should apply to all patients.While we continue to refine our choice and use of current technology, future developments in retinal surgery have already been reported and will surely influence future decisions. Such new developments include endolaser cerclage (Chaturvedi et al. One of the limitations of this study is its wide‐ranging follow‐up period. Because the study was retrospective, we could not influence the follow‐up time because the physician responsible for each visit determined when the patient's retina could be considered stable. However, one should always be aware that recurrent retinal detachment may be asymptomatic. Although most re‐detachments occur in the first half‐year after the primary operation, the risk of missing re‐detachments increases with shorter follow‐up periods (Goezinne et al. Another limitation could be that the hypothesis is only valid under very special conditions with regard to the national and regional organization of healthcare. We believe that in Sweden, our method may be successful regardless of whether you provide public or private care and regardless of the size of the clinic or the size of society. There are probably opportunities in other countries as well, but it is likely to depend entirely on what policy towards regional clinics and patients the surgical department decides to follow.The primary goal of this study was to investigate whether the surgical unit could follow up primary uncomplicated retinal detachment without requesting medical records from the referring clinics. The hypothesis was proven true, which means follow‐up of the results of retinal surgery can be simplified and performed more efficiently. For our clinic, it is important to reflect on why this hypothesis is true. There will always be patients who discontinue their follow‐up, return to their home country before follow‐up, move to another region, die within 6 months after their operation, refuse access to their medical records or refuse further treatment after a recurrence, and in addition, regional hospitals may fail to return that information to the surgical unit.We believe that close cooperation with all our regional partners is required. Regularly, recurring joint meetings with invited colleagues from all regional clinics to convey new technology, changes in indications and administrative routines have been taking place for a long time and is much appreciated. We also provide for younger colleagues from the regional hospitals to temporarily work at the university hospital for a shorter period of time. Retinal surgeons should also sometimes visit the regional clinics to inform and hold joint discussions together. All contacts between the University Hospital and the Regional Hospital, as well as regional patients, should take place with understanding and helpfulness and an intention of creating a good atmosphere between those involved.In summary, the eye clinic at Örebro University Hospital has, under current conditions, a professional relationship with our regional clinics that allows us to follow up surgical results of patients with uncomplicated primary retinal detachment based on the medical records available in the university hospital's own medical record system.


By far the most widespread human activity occurring on the seabed is bottom trawling/dredging for fish and shellfish. A global first‐order estimate suggested mobile demersal fishing activities may cause 0.16–0.4 Gt of organic carbon (OC) to be remineralized annually from seabed sediment carbon stores . There are, however, many uncertainties in this calculation. Here, we discuss the potential drivers of change in seabed sediment OC stores due to mobile demersal fishing activities and conduct a literature review, synthesizing studies where this interaction has been directly investigated. Under certain environmental settings, we hypothesize that mobile demersal fishing would reduce OC in seabed stores due to lower production of flora and fauna, the loss of fine flocculent material, increased sediment resuspension, mixing and transport and increased oxygen exposure. Reductions would be offset to varying extents by reduced faunal bioturbation and community respiration, increased off‐shelf transport and increases in primary production from the resuspension of nutrients. Studies which directly investigated the impact of demersal fishing on OC stocks had mixed results. A finding of no significant effect was reported in 61% of 49 investigations; 29% reported lower OC due to fishing activities, with 10% reporting higher OC. In relation to remineralization rates within the seabed, four investigations reported that demersal fishing activities decreased remineralization, with three reporting higher remineralization rates. Patterns in the environmental and experimental characteristics between different outcomes were largely indistinct. More evidence is urgently needed to accurately quantify the impact of anthropogenic physical disturbance on seabed carbon in different environmental settings and to incorporate full evidence‐based carbon considerations into global seabed management.Subtidal marine sediments are one of the planet's primary carbon stores and strongly influence the oceanic sink for atmospheric CO 2. Considering basic principles, we hypothesize that under certain environmental settings, trawling/dredging for fish and shellfish would reduce seabed sediment carbon storage; however, this may be offset by positive feedback mechanisms in some circumstances. A review of studies which directly investigated this impact in situ also highlighted mixed results. More evidence is urgently needed to accurately quantify this impact in different environmental settings, and incorporate full evidence‐based carbon considerations into global seabed management.Subtidal marine sediments are one of the planet's primary carbon stores and strongly influence the oceanic sink for atmospheric CO The 38 A variety of experimental set‐ups were employed including impact–control site comparisons (39%), before–after fishing impact (24%) and low–high impact contrasts which lacked controls 21%). Additionally, 13% of studies used a before–after control–impact design either alone or in combination with an impact–control experiment, and one investigated the recovery of seabed sediment OC after a long‐term closure to mobile demersal fishing (Table %. AdditiOf the 38 studies identified, 10 investigated the effect of mobile demersal fishing across multiple sites, habitat types or gear types and made inferences for each investigation separately Table . Most ofThere were only seven inferences regarding the impact of mobile demersal fishing pressure on in situ seabed sediment carbon remineralization rates. Of these, four reported that demersal fishing activity decreased remineralization rate in seabed sediments, with three concluding the opposite Table . AlthougOf the 51 individual investigations, 49 measured changes in OC/OM concentration/content. A finding of no significant effect was reported in 61% of investigations; 29% reported lower OC in fished sites compared to unfished control sites or in areas with higher fishing intensities; with the remaining 10% of investigations reporting higher OC Table . PatternWhile this literature review gives a summary of empirical research and an indication into patterns and drivers of experimental outcomes, it is not exhaustive so cannot be considered fully systematic. For example, it only considered peer‐reviewed primary literature obtainable from two bibliographic databases and ignored grey literature. Additionally, we made no attempt to critically assess the quality or validity of each study before its inclusion, and the data extracted were largely qualitative or semiquantitative in nature. A more thorough systematic review and meta‐analysis may provide further evidence and/or varying results.4As highlighted by the varied experimental results, there is a clear need for further research into the potential impact of mobile demersal fishing on OC burial and long‐term storage in seabed sediments under different environmental settings. Recent first‐order estimates have suggested that globally, mobile demersal fishing could remineralize between 0.16 and 0.4 Gt of OC from marine sediment stores annually (Sala et al., 2, as they consider the fate of sediment which stays in suspension as unknown. In their paper, Sala et al. (Following disturbance and/or resuspension by mobile demersal fishing, a proportion of OC may become remineralized in the seabed or in the water column due to the processes discussed above; however, some will simply remain in situ and be reburied, and a further proportion will be transported over a range of distances eventually being consumed or reburied (Lovelock et al., a et al.  considera et al. , with tha et al.  use an uAlthough the studies by Sala et al.  and LuisThe cumulative or finite nature of disturbance by demersal mobile fishing on OC stores must also be considered, and currently, it is not clear how much of the estimated 360 Gt of OC in the top 1 m of sediment is actually threated by the activity (Atwood et al., The scale of penetration and legacy of disturbance must also be considered alongside differing sediment depth OC profiles (Martín, Puig, Masque, et al., There is also a need to identify a clear baseline from which changes in OC can be measured. Standing stock of OC in global seabed sediments is relatively well resolved at a number of spatial scales (Atwood et al., On land, retrospective analyses of changes in human use and vegetation cover have been critical to estimating how people have altered the planetary carbon cycle. It is vital that this historical context is also considered when further investigating the potential impact of mobile demersal fishing on global seabed OC storage, and the opportunities for recovery if this pressure is removed. Due to the extended timeframes needed for some seabed habitats to fully recover, true long‐term protection and monitoring of OC are needed to fully deduce carbon storage potential. Without considering areas of seabed that have experienced genuine long‐term protection, it is not possible to gain an accurate baseline from which impacts can be compared (Pinnegar & Engelhard, It is important that future research into the impact of mobile demersal fishing on carbon storage is focused in areas which are expected to contain significant stocks of OC or have large future burial potential, based on their geography (Atwood et al., 52 (Atwood et al., 2.Seabed sediments are one of the planet's primary OC stores and strongly influence the oceanic sink for atmospheric CO2 produced from disturbance to seabed sediments by mobile demersal fishing must be viewed with both concern and caution (Luisetti et al., The results of recent regional and global scale publications which have calculated first‐order estimates of COThe authors declare that they have no conflict of interest.GE prepared the original draft and undertook the literature review. CR & CN contributed to conceptualization and planning. All authors contributed to writing, reviewing and editing.Table S1Click here for additional data file.Table S2Click here for additional data file.


Permutation tests are widely used to test null hypotheses with animal social network data, but suffer from high rates of type I and II error when the permutations do not properly simulate the intended null hypothesis.Two common types of permutations each have limitations. Pre‐network (or datastream) permutations can be used to control ‘nuisance effects’ like spatial, temporal or sampling biases, but only when the null hypothesis assumes random social structure. Node (or node‐label) permutation tests can test null hypotheses that include nonrandom social structure, but only when nuisance effects do not shape the observed network.We demonstrate one possible solution addressing these limitations: using pre‐network permutations to adjust the values for each node or edge before conducting a node permutation test. We conduct a range of simulations to estimate error rates caused by confounding effects of social or non‐social structure in the raw data.Regressions on simulated datasets suggest that this ‘double permutation’ approach is less likely to produce elevated error rates relative to using only node permutations, pre‐network permutations or node permutations with simple covariates, which all exhibit elevated type I errors under at least one set of simulated conditions. For example, in scenarios where type I error rates from pre‐network permutation tests exceed 30%, the error rates from double permutation remain at 5%.The double permutation procedure provides one potential solution to issues arising from elevated type I and type II error rates when testing null hypotheses with social network data. We also discuss alternative approaches that can provide robust inference, including fitting mixed effects models, restricted node permutations, testing multiple null hypotheses and splitting large datasets to generate replicated networks. Finally, we highlight ways that uncertainty can be explicitly considered and carried through the analysis. They are commonly used in ecology  are used to test how observed social network structure differs from what is expected if animals made random social decisions. This approach permutes the observed data to create many expected networks that could have occurred in the absence of any social preferences. The null hypothesis here is that, after removing the specified effects, the social structure itself is random . This is a different null hypothesis than what researchers typically want when performing a correlation or regression with network data , as used in Mantel tests and the quadratic assignment procedure (QAP) tests. By only permuting the node labels, this approach removes the statistical relationship, while preserving the same observed network properties in all expected networks. For a typical node permutation test, the null hypothesis is that there is no statistical relationship between a predictor (e.g. kinship) and response (e.g. association rate) in the observed network, which is correct for regression‐based questions.The first issue is caused by the fact that different kinds of permutations create different null hypotheses. observed social network is typically a non‐random sample that does not directly or even accurately represent the ‘real’ social network of dyadic social preferences or contact . Specifically, we use pre‐network permutations to estimate the deviation of each unit's observed measure from its expected random value . We call this observed–expected difference the deviation score (e.g. ∆degree). These deviation scores, which account for nuisance effects, are then fit into a model of interest to generate a test statistic, and a node permutation test provides the p‐value for the test statistic.Our goal in this paper is to address this limitation of pre‐network permutation tests, allowing them to be applied to regression while robustly accounting for multiple common nuisance effects. We propose an initial solution, which we show can maintain rates of both false positives and false negatives to around 5% under a range of scenarios. Our approach Figure  uses prePotential Improvements in Appendix Using deviation scores is conceptually similar to generalised affiliation indices , but one could also opt to enter the deviation scores into an appropriate parametric model. Indeed, the basic procedure can be applied to any model for calculating test statistics, such as those generated from regressions, Mantel tests Mantel, , network2p‐values using several tests: node permutations, node permutations in which the model controls for covariates , pre‐network permutations, pre‐network permutations on the t‐statistic , focal sampling data (simulation 2) and dyadic observations (simulation 3), both in the absence of any real relationship and when there are strong nuisance effects. In simulations 1 and 2, we simulate the process of testing for a relationship between an individual trait and a social network metric, using three common weighted metrics , whereby individuals with higher trait values choose to be in larger groups and (c) individual choice is predicted by a spatial preference (LS), whereby individuals with higher trait values are not more social but prefer sites with more resources that also hold more individuals. The last scenario represents an alternative driver of gregariousness that is challenging to control in model fitting or using node permutations by location because individual spatial preferences cannot be reduced down to a single value. Such variation in spatial distribution of individuals is common, for example the number of great tits Parus major in Wytham Woods varied 10‐fold across different parts of the woodland  and t statistics by fitting the model, weighted metric ~ trait (+ covariates where applicable), using the lm function in r. Note that pre‐network permutations inherently control for the number of observations of each individual, and we also control for where observations were made by restricting swaps to within locations. Further details for simulation 1 are in Appendix We first simulate a researcher using group‐based observations to test whether individuals with a given trait value are more gregarious under three biological scenarios: (a) individuals choose groups at random, (b) individual choice is predicted by a social trait , in the lm function in r. Simulation 2 has been used in several studies to estimate performance of permutation approaches  weak associates, (b) preferred associates and (c) strongly bonded associates. Our simulations comprise two scenarios. In the first, association rates (edge weights) are independent of kinship, which we achieve by randomising the kinship matrix after generating it. In the second, associations are kin biased such that strongly bonded associates have higher kinship on average and weak associates and non‐associates (missing edges) have on average lower kinship. For each type of social network and scenario, we created ‘real’ social networks and then create ‘observed’ social networks by simulating observations. We simulate 100 replications for combinations of network sizes, with 5–120 individuals and the mean numbers of observations per individual ranging from 5 to 40. For each simulation (one network), we conduct a MRQAP with the model: edge weight ~ kinship (+ covariates). Further details for simulation 3 are in Appendix 3t value as a test statistic are also prone to false positives, and perform relatively poorly at detecting a true effect (detecting them consistently less often than other approaches). Combining pre‐network permutation tests together with model structures that also control for nuisance effects, when estimating the test statistic, also appears to produce unreliable results. As expected, node permutation tests perform particularly poorly when the effects are driven by non‐social nuisance effects, such as variation in the spatial distribution of individuals, even when controlling for individuals' locations in the model. The parametric p‐values produced similar results to the node permutations. When node permutations were applied to a more informed model, the p‐values were not clearly better or worse.Our simulations confirm that the double permutation method is robust to type I errors across a range of scenarios. In simulation 1 Table . We furtp‐values when no effect is present, detecting the relationship between a trait and social metrics when present, and being more conservative than other tests when the effect is driven by non‐social factors.The double permutation test performs generally better than the other methods we tested across the three scenarios, producing conservative All tests appeared to struggle with confounded measures of eigenvector centrality and betweenness, but this is likely driven by the simulations not always producing datasets in which eigenvector centrality was strongly linked to spatial location, thereby largely over‐estimating the false positive rate. However, because all methods were tested on identical simulated datasets, their relative performance can still be meaningfully compared.In simulation 2 .Our results confirm that pre‐network permutations by themselves cannot be used to generate a Our results suggest that across scenarios, the double permutation test often performs better at testing null hypotheses using regressions than the other approaches when there are strong confounds, such as sampling biases or spatial preference drivers. These create high rates of false positives in tests that do not include pre‐network permutations. However, the double permutation test can be too conservative when applied to unstable global node metrics such as betweenness Table , which mr) as descriptive metrics rather than as interpretable parameters of biological meaning. However, this limits inference to null hypothesis testing, rather than estimation of the magnitude and confidence of effect sizes  are necessarily superior to parametric models. Carefully fitting a parametric model (or a generative model) that can explicitly capture all effects (both effects of interest and nuisance effects), identified through careful inspections of residuals and other model diagnostics, can have many benefits . For better or worse, one benefit of nonparametric tests is that they avoid the process of having to specify the best possible statistical model to fit the data. A permutation test simply compares observed and expected model coefficients , yet controlling for the number of observations of each individual consistently inflates the estimated coefficient size  and estimated coefficient (with the observation bias) are correlated  would have on average only 10 individuals per class if both parameters are binary, only six to seven per class if one is trinary, and only four to five per class if both are trinary.6.3p‐value. This result can be also reported as evidence of the selected method's reliability. It is worth exploring further how this study‐specific information might be used. For example, one might be able to correct the threshold for rejecting the null hypothesis to the point where the expected false positive rate will be 5%. Shuffling the actual node values and running a pre‐network permutation test (and repeating these two steps many times) might provide an even more precise estimation of the true false positive rate, as it will be fully conditioned on the real observation data.How can we be sure that a chosen method is effective? One approach is to explicitly test how sensitive a given dataset is to generating false positives or false negatives under different hypothesis‐testing approaches. The procedure we used here—simulating a random trait value for each node in a network and running through the full hypothesis‐testing procedure—can be a straightforward way of characterising the robustness of any given study's results. This procedure simply involves generating a random trait variable  and testing how this value corresponds to the metric of interest from the observed network using the same code as for the real variable(s) being studied. By repeating this procedure many times, one can observe the proportion of the tests that incorrectly produce a significant 6.4Testing one null hypothesis can encourage confirmation bias, and might only reject a strawman hypothesis of little interest (e.g. that chimpanzees have random interactions). Strong inference Platt,  therefor6.5Another approach that is often considered to be useful for estimating uncertainty  is bootstrapping .Although within‐study replication can improve our confidence in a given result, ultimately the gold standard is replication across studies, as within‐study replications cannot control for many of the nuances in how data are collected, stored and analysed. One example of a replication study tested the effects of developmental conditions on the social network position of juvenile zebra finches 7We propose an approach that avoids the elevated false positives that occur from pre‐network permutations assuming random network structure under the null hypothesis and node permutations assuming an unbiased observed network under the null hypothesis. Our proposed solution, or the use of permutation tests more generally, does not negate the need to carefully consider statistical issues that have been highlighted for more orthodox statistical practices  creates a specific null model (see Figure Permutation tests can control for a large range of nuisance effects within the null model without explicitly identifying, measuring and controlling for every source of bias. There are both pros and cons of this approach, but we believe that the strength and robustness of permutation tests lies in their flexibility and simplicity. By using a range of permutation tests to measure the relative deviations of the observed data from different null expectations, it is also possible to evaluate the relative contribution of different processes shaping a network. Regardless of the method used, inference with social network data requires thinking carefully about what specific processes may have produced the patterns in a given observed dataset.The authors declare no conflict of interest.D.R.F. and G.G.C. developed the method, and wrote the manuscript together; D.R.F. developed and ran the simulations.https://publons.com/publon/10.1111/2041‐210X.13741.The peer review history for this article is available at Supplementary MaterialClick here for additional data file.


We examined whether breast cancer survivors' experiences with care differed by a recent history of clinical depression, and whether associations differed by race/ethnicity.Using the Epidemiology and End Results‐Consumer Assessment of Healthcare Providers and Systems (SEER‐CAHPS) dataset, we analyzed records of breast cancer survivors who completed a survey at least 12 months after their cancer diagnosis. We assessed clinical depression 12 months prior to survey completion using Medicare claims. We used separate multivariable logistic regressions to examine the associations between depression and excellent (vs. less than excellent) ratings of experiences with care . We also assessed interactions of depression by race/ethnicity. All models were adjusted for demographics and cancer prognostic and treatment factors.Of the 2271 survivors, 7.6% were clinically depressed. After adjusting for covariates, survivors with clinical depression had lower odds of reporting excellent ratings of their ability to get needed care, care by their specialist, and overall care, compared to those without depression . Among Hispanics, having depression was associated with higher odds of excellent ratings of one's ability to get needed care . No other statistically significant associations by race/ethnicity were found.Breast cancer survivors with depression report poorer patient experiences with care. Further research is needed to understand complexities of ratings of experiences with care among survivors of diverse backgrounds.Survivors with a recent history of clinical depression may benefit from additional supportive care services. Breast cancer survivors with a recent history of clinical depression were less likely to report excellent ratings of care on three domains assessing experiences of care, compared to those without a recent history of depression. Survivors with a recent history of depression appear to be particularly vulnerable to difficulties in some of their healthcare encounters, as reflected by their reported ratings of care.  We hypothesized that breast cancer survivors with a recent history of depression would report poorer ratings of care compared to those without a history of depression. A secondary objective was to determine whether clinical depression was more detrimental on patient experiences with care depending on the respondents' race/ethnicity. We hypothesized that racial/ethnic minorities with depression would report worse experiences with care, compared to Whites with depression.2We conducted a retrospective cohort study using the Epidemiology and End Results‐Consumer Assessment of Healthcare Providers and Systems (SEER‐CAHPS) linked dataset.2.1Overall Care, and Care by Specialist, scored on a 0‐to‐10 scale, with higher scores indicating better ratings of care.Doctor Communication, Getting Care Quickly, Getting Needed Care, and Getting Needed Prescriptions. Survey respondents were asked to answer each item thinking of their experiences with care in the last 6 months using the following response scale: 1 = never, 2 = sometimes, 3 = usually, and 4 = always. The original response scales for the composite measures were transformed to a 0‐to‐100 scale using linear scoring,The outcome variables, patient experiences with care, were assessed using two global ratings and four composite reports. We selected these CAHPS measures because previous research found that race/ethnicity and depression status varied by these characteristics.The independent variable was clinical depression status. We identified breast cancer patients with at least two distinct medical claims with a diagnostic code for depression at least 12 months before survey completion. We used the International Classification of Disease, 9th edition (ICD‐9) and Current Procedural Terminology codes to identify individuals clinically diagnosed with depression  individuals as having a recent diagnosis of clinical depression. The comparison group consisted of 2099 (92.4%) individuals without a recent diagnosis of depression or any other psychiatric diagnosis. As shown in Table 3.1Compared to survivors who did not have a recent history of depression, those with depression had lower odds of having excellent reports of their ability to get needed care , lower odds of having excellent ratings of care by a specialist , and lower odds of having excellent ratings of overall care , but the sample size was too small to detect a statistically significant association between depression status and reports of their ability to get needed care , Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER‐CAHPS data resource. Efforts by MA were supported by a pre‐doctoral fellowship at the University of Texas Health Science Center at Houston, School of Public Health, Susan G. Komen Traineeship in Breast Cancer Disparities (GTDR14300827). SEER‐CAHPS data were procured by AJF with support from a University of Texas Health Science Center at Houston School of Public Health Cancer Education and Career Development Program grant from the National Cancer Institute (R25‐CA57712). The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official views of the funding bodies.This study was reviewed and granted exempt status by the UTHealth Committee for Protection of Human Subjects (HSC‐SPH‐20‐0812).Table A1Click here for additional data file.


Interactions between species are widely understood to have promoted the diversification of life on Earth, but how interactions spur the formation of new species remains unclear. Interacting species often become locally adapted to each other, but they may also be subject to shared dispersal limitations and environmental conditions. Moreover, theory predicts that different kinds of interactions have different effects on diversification. To better understand how species interactions promote diversification, we compiled population genetic studies of host plants and intimately associated herbivores, parasites, and mutualists. We used Bayesian multiple regressions and the BEDASSLE modeling framework to test whether host and associate population structures were correlated over and above the potentially confounding effects of geography and shared environmental variation. We found that associates' population structure often paralleled their hosts' population structure, and that this effect is robust to accounting for geographic distance and climate. Associate genetic structure was significantly explained by plant genetic structure somewhat more often in antagonistic interactions than in mutualistic ones. This aligns with a key prediction of coevolutionary theory that antagonistic interactions promote diversity through local adaptation of antagonists to hosts, while mutualistic interactions more often promote diversity via the effect of hosts' geographic distribution on mutualists' dispersal. A wide diversity of living things spend much of their lives in close association with the plants that provide them with food and shelter. These associates include herbivores and plant parasites, but also mutualists like pollinators and beneficial microbes. Natural selection created by intimate association with plants is thought to be responsible for the evolution of some highly diverse groups like beetles and butterflies, but we are still learning exactly when and how plant‐associate interactions promote the formation of new species. One way to examine the process of plant‐associate diversification up close is to look at the genetic variation of populations within a single species of associates and its host plant. We compiled this kind of data from published studies of 20 plant‐associate pairs, and tested for evidence that populations of associates from less genetically similar populations of their host plant were themselves less genetically similar—a possible consequence of natural selection created by close association with the host plant, and a first step towards the formation of new species. We found evidence for this pattern in a majority of the plant‐associate pairs we examined, and we found that the pattern was somewhat stronger for antagonistic associates than for mutualistic ones. This demonstrates that the evolution of associate species in response to their host plants can contribute to the earliest stages of species formation, and that different types of plant‐associate interaction may have different effects on long‐term, global patterns of evolution and biodiversity.Interactions between species have long been recognized as key drivers in the diversification of life on Earth , keywords referring to species interactions , and always included the keyword plant. All keyword sets returned at least 1500 results, and many had more than 20,000; we reviewed titles and abstracts for the first 200 papers returned in each search, and generally found that relevant results were not found after the first 100. We found, in total, 24 papers discussing or reporting population genetic data for both a plant species and at least one associated mutualist, herbivore, or pathogen. Of these, we retained papers that provided either pairwise genetic differentiation estimates, or genetic data that would support such estimates, for both a host plant and an associate species at four or more geographically distinct sites. As a check on the thoroughness of our literature search, we used Google Scholar to examine all papers citing the final set of studies. The final compiled data set included results from 15 published papers . We searched varying combinations of keywords referring to population structure . For instance, a locus with alleles A, B, and C, would be recoded as three loci, the first with alleles A/not A, the second with alleles B/not B, and the third with alleles C/not C. Six studies representing seven plant‐associate pairs  species pair(s). In the case of plant‐associate pairs from studies that provided insufficient information to infer sampling site locations  , and geographic distances, we first calculated simple correlations between all possible pairwise combinations of distance metrics for each plant‐associate pair, as Spearman rank correlations. We used the base‐10 logarithm of geographic distances, and the standard transformation of genetic distances as Rousset, . To estibrms package , and host plant genetic distance. To cope with the highly non‐normal distribution of the data, we fitted models using the Bayesian framework implemented in the Bürkner, , 2018, wBürkner, , generatalpha terms, in the BEDASSLE model) of geographic distance, climate distances between sampling sites, and host genetic distances between sampling sites. Following recommended practice, we performed pilot runs of the BEDASSLE Markov chain Monte Carlo model‐fitting procedure and inspected parameter estimate and acceptance rate traces, adjusting the size of parameter changes allowed between MCMC steps until the acceptance rates showed the Markov chain achieving stationarity. When we had identified appropriate parameter change values, we ran a final model‐fitting procedure for 5 × 106 iterations. We used the last 1 × 106 generations for posterior parameter estimation and discarded the rest as burn‐in.For the 13 plant‐associate pairs with genotype data available Table . For eacmetacor function) and mean effect estimates (the metamean function) provided in the meta package . Because of the highly skewed range of phylogenetic distances among associates, we did not employ a formal control for phylogenetic non‐independence in our meta‐analyses, but we tested the robustness of our conclusions by systematically re‐running each meta‐analysis with each possible permutation of the dataset created by excluding one member from each of these four pairs of close relatives.Finally, we used formal meta‐analysis to examine the overall strength of the pairwise distance correlations, predictor effects in the multiple linear regressions, and ecological isolation estimates from BEDASSLE. We used the random‐effects methods for correlations , plant‐ants (genus Crematogaster), and yucca moths (genus Tegeticula) were each represented in two host‐associate pairs. Of the 15 original papers providing data that we could use for synthesis, eight included explicit comparisons of host plant and associate population structure, generally a regression of associate genetic distances on host plant genetic distances  in 11 of 20 pairs, and significant isolation by climate differences in 7 of 16 pairs for which climate data were available. Associates showed correlations consistent with isolation by geographic distance in 14 of 20 pairs, and isolation by climate in 10 of 16 pairs.Pairwise correlations between genetic and geographic distance , between genetic and climate distance (isolation by climate), and between genetic distances for plants and associate species (isolation by host) varied considerably across plant‐associate pairs Figure . Host plLysimachia vulgaris and the pollinating bee Macropis europaea, by Triponez et al. . The meta‐analytic pooled correlation between plant and associate genetic distances was also significantly greater than zero within antagonistic and mutualistic interactions . Although the mean correlation was somewhat greater for antagonistic interactions than for mutualistic interactions, this difference was not greater than expected by chance . Excluding closely related associates from the data set did not qualitatively alter any of these results. Overall, this is consistent with associates experiencing widespread isolation by host plant, across different types of interactions.The general signal revealed by meta‐analysis was also that plant and associate genetic distances are significantly and positively correlated  and significant isolation by climate for plants and associates . These results were generally robust to pruning closely related associates.However, meta‐analysis also found correlations with distance and climate that may be confounded with the correlations in genetic distances see above. Meta‐analysis across all plant‐associate pairs found significant isolation by distance for plants and associates . These differences between interaction types were not greater than expected by chance in the random effects model, however (p>0.05 for both isolation by distance and isolation by climate). These results were also robust to pruning closely related associates, with the exception that pruning the Pinus banksiana/Arceuthobium americanum species pair resulted in non‐significant pooled isolation by distance correlations for host plants in antagonistic interactions.Meta‐analysis of only antagonistic interactions or only mutualistic interactions found similar results to the overall pattern, with the exception that pooled correlations between genetic distance and climate distance were not greater than zero in antagonistic interactions, potentially consistent with a smaller or less consistent effect of isolation by climate in these systems . However, we did find a significant negative correlation between sample size and the correlation coefficients for plant and associate population structure . This pattern was also significant when assessed only for mutualistic species pairs , although not for antagonistic pairs . This is consistent with the prospect that studies failing to find correlated population structure in host plants and associated taxa are more likely to go unpublished.Comparing the pairwise correlation coefficients to the sample sizes for individual studies revealed no pattern consistent with publication bias in isolation by distance for host or associate taxa, or in isolation by climate , and host plant genetic distance returned results that generally paralleled patterns in the simple pairwise correlations Figure . Correlae Figure .Meta‐analysis across all plant‐associate pairs found a significant effect of plant genetic distance ; and, although antagonisms showed greater mean isolation by host plant than mutualisms, this was also non‐significant (p=0.10). Pruning close relatives generally did not change the qualitative results—except that the pooled effect of isolation by host plant in mutualisms was not significantly different from zero when Macropis fulvipes was excluded, or when both Macropis fulvipes and Crematogaster nigriceps were excluded. Overall, this is consistent with antagonistic associates experiencing isolation by host plant but not by geographic distance, while mutualistic associates experience isolation by distance and, to a lesser extent, by host plant.Meta‐analysis of only antagonistic pairs found no significant isolation by distance , but significant isolation by host plant ; whereas meta‐analysis of the mutualist pairs found significant isolation by distance  and significant isolation by host plant . Isolation by climate was not significantly greater than zero in meta‐analysis of either interaction type . The random‐effects meta‐analysis found that the difference in isolation by distance with associate type was not significantly greater than expected by chance . All α terms for all species pairs had 95% posterior densities that did not cross zero, though this likely reflects a constraint of the BEDASSLE model, which enforces α terms greater than zero. Meta‐analysis of α terms yielded more nuanced results: across all 13 species pairs, the pooled α terms for geographic distance and climate distance had 95% posterior density intervals that included zero ; while the pooled α term for host plant genetic distance was strongly significantly greater than zero , consistent with associate genetic differentiation explained predominately by host plant genetic differentiation.The 13 species pairs for which we could obtain genotype data produced widely varying estimates of isolating effects for geographic distance, climate distance, and host plant genetic differentiation in analysis with BEDASSLE Figure , and theAmyema gibberula and its host Hakea recurva, was antagonistic, sharply limiting our power to compare antagonistic and mutualistic interactions in meta‐analysis. With this caveat, the random effects meta‐analysis found that Amyema gibberula did not differ significantly from the mutualistic associates in posterior estimates of the α for geographic distance and climate distance; but antagonist had a posterior median α for host plant genetic distances substantially and significantly greater than the mutualists . Pruning close relatives from the meta‐analysis did not change this qualitative result.Only one of the 13 species pairs in the BEDASSLE analysis, the mistletoe A wide range of experimental and observational evidence describes the ways in which plants may shape the evolutionary history of species that depend upon them. Population genetic data from plants and associates interacting across a shared landscape provides a look at local adaptation, the process by which the ecological dynamics of plant‐associate interactions are translated into global patterns of biodiversity  in addition to the effects of shared geography (isolation by distance). We find that the meta‐analytic mean effect of climate differences on associate genetic distance is not significantly greater than zero, reflecting the fact that we found nonzero effects of climate in only three of 16 plant‐associate pairs for which we could obtain climate data Figure . On the Perhaps most interestingly, we find indications of different trends in different types of plant‐associate interaction. In the multiple linear regression framework, we find a significantly nonzero effect of host plant genetic distances on the population structure of both mutualistic and antagonistic associates, but a somewhat stronger effect of host plant genetic distances for antagonistic associates Figure . FindingCamellia japonica/Curculio camelliae, we have good documentation for arms‐race dynamics mediated by physical defenses: the thickness of the host plant pericarp (Toju et al., Datura stramonium/Lema trilineata and Populus angustifolia/Aceria parapopuli we often see arms‐race dynamics, with plants producing defensive chemicals and herbivores overcoming them by detoxification or sequestration (Agrawal et al., Yucca/Tegeticula, Smith et al. Medicago/Ensifer, Yoder These expectations from theory are based on assumptions about the forms of selection operating in mutualistic versus antagonistic interactions, which have not been evaluated in most of the plant‐associate pairs we examine here. However, educated inferences can be made many cases. For one antagonistic plant‐associate pair in our dataset, Whether a host‐associate interaction will create isolation‐by‐host for the associate species is likely determined by the genetic basis of the host and associate traits mediating the interaction, as well as the forms of coevolutionary selection acting on those traits. For the host‐associate pairs in our compiled dataset, the specific genetic basis of interacting traits is even less well characterized than the forms of selection that may be operating. Strong selection acting on a trait determined by one or a few loci is expected to create patterns of differentiation at those loci that would deviate from genome‐wide population structure (Hoban et al., The results of our literature search reveal considerable opportunities for future studies of population genetic patterns across trophic levels. Although population genetic tools have been applied to the broad subject of plant‐associate diversification for decades, we find just 15 papers reporting data for both a plant and at least one intimate associate species—11 published in the past 10 years. The majority of these studies use codominant elecrophoretic markers, which have relatively poor resolution to characterize diversity and differentiation compared to modern DNA sequencing methods; and this is reflected in the wide range of precision we find when we estimate correlations between genetic, geographic, and environmental distances Fig . We expeFinally, 16 of 20 associate taxa in our compiled data set are insects. This pattern is not surprising in light of the historical focus on angiosperm‐insect co‐diversification (Ehrlich & Raven, Compiling population genetic data for plants and closely associated taxa, we find support for the widespread understanding that intimate interactions across trophic levels create diversifying natural selection. Although both antagonistic and mutualistic associates frequently evolve population structures that parallel those of their host plants, our analysis finds that antagonists are somewhat more likely than mutualists to experience ecological isolation attributable to host population structure. Future studies of plant‐associate population genetics will, we hope, expand the taxonomic scope of this data, to further illuminate how plant‐associate interactions have fueled the diversification of life on Earth.The authors have declared no conflict of interest.All authors contributed to the literature search and data compilation; JBY conducted data analysis; all authors contributed to drafting the manuscript. All authors reviewed and approved the final text.Supporting data and scripts have been uploaded to the Dryad repository, doi 10.5061/dryad.fxpnvx0w3.


We studied the formation of AuRh nanoalloys (between 20–150 atoms) in the gas phase by means of Molecular Dynamics (MD) calculations, exploring three possible formation processes: one‐by‐one growth, coalescence, and nanodroplets annealing. As a general trend, we recover a predominance of Rh@Au core‐shell ordering over other chemical configurations. We identify new structural motifs with enhanced thermal stabilities. The physical features of those selected systems were studied at the Density Functional Theory (DFT) level, revealing profound correlations between the nanoalloys morphology and properties. Surprisingly, the arrangement of the inner Rh core seems to play a dominant role on nanoclusters’ physical features like the HOMO‐LUMO gap and magnetic moment. Strong charge separations are recovered within the nanoalloys suggesting the existence of charge‐transfer transitions. The synthesis and physical properties of AuRh nanoalloys, with size range between 20–150 atoms, are studied by means of molecular dynamics and density functional theory calculations. The best synthetic route towards stable nanosystems is reported along with their physical features, which show unique characteristics that have active potential in photocatalytic applications. However, it was shown that such an experimental setting induces phase segregation, affecting the catalytic potential that remains largely unexpressed.[Most of the nowadays chemical production is based on reactions catalysed by transition metals and their alloys. These catalysts usually offer high activities and recyclability, but suffer from poor selectivity and, usually, require a high amount of energy to work properly.xpressed.21, 26To date, the computational efforts spent on the study of this nanoalloy mainly focus on the characterisation of the systems, barely accounting for its dynamics. Several studies indicate how the most stable configuration for the isolated nanoalloy seems to be the one with the rhodium encapsulated inside gold, forming a core‐shell structure, consistent with arguments pertaining to the relative surface energy of the two components.To date, what appears to be certain by mixing Au and Rh is that the shapes and properties strongly deviate from the ones of pure metal systems and this mismatch can be recovered even in aggregates composed of a few atoms.19 double‐icosahedron (Rh19‐DI), Rh38 truncated cuboctahedron (Rh38−Co), and Rh55 icosahedron (Rh55−Ih), while the growth of Rh atoms over gold was performed only for a single seed, i. e. the Au20 tetrahedron seed (Au20−Th). Graphical representations of these nanoclusters, as well as the excess energy trend as a function of the alloy composition and total number of atoms are collected in Figure 20−Th and Rh19−DI are known stable structures for these two particular metal species.[20−Th (red line) seems to follow an opposite trend in the bottom panel of Figure 19‐DI (black line) where 5 local minima can be identified. These points correspond to the 5 morphologies, depicted at the bottom panel of Figure 19 core enclosed in a gold‐shell which covering extension and motif depend on the number of Au‐atoms. Among these 5 structures, the ones with lower number of atoms are worth of particular interest as they present very unusual and exotic arrangements. The 39 atoms Au20Rh19 structure is composed by an inner Rh19 core surrounded by an atomic gold stripe; the 55 icosahedral Au36Rh19 system presents a ball‐cup arrangement where an Rh tip emerges from the inner part of the icosahedron and the 71 atom Au52Rh19 which shows a chiral core‐shell motif. For the sake of brevity from now on these clusters will be named 39‐GS (gold stripe), 55‐BC  and 71‐CM .The first explored synthetic route was the one‐by‐one growth in the gas phase. Here, a nanocluster of a certain species (Au or Rh) acts as a nucleation site for the nanoalloy growth which is performed by subsequent deposition of atoms of the other species. We explored the growth of Au over three different Rh seeds, namely the Rh species.42, 4319 seed seems to play a major role in determining the formation process of those structures. While in the case of 71‐CM, the seed still shows a double‐icosahedron symmetry, in the case of 39‐GS and 55‐BC, the Rh19 seed presents a fused icosahedron‐decahedron geometry, as visible from Figure 19−ID. The role the seed geometry has on the whole structure stability, together with a thorough analysis of the mentioned notable structures is given in the following section, where DFT calculations results will be presented and discussed.At this stage of the investigation, it is worth noticing that the configuration of the Rh19  or incomplete (Au73Rh19) icosahedral geometries.The two morphologies corresponding to the other excess energy minima in the one‐by‐one deposition of Au over Rh38‐Co and Rh55‐Ih), the excess energy trend does not reveal any particular structure corresponding to a given nanocluster size or composition, except for the icosahedral Au92Rh55 147 atoms nanocluster, coming from the growth of Au over Rh55−Ih which is stable due to the geometrical closure of the shell enveloping the inner seed. Lastly, the deposition of Rh atoms over a gold seed does not produce any notable structures. The mild variation of the excess energy trend in Figure −17 cm2/s) suggests a strong tendency to form segregated phases with Rh preferably confined within a gold shell, in line with what observed in the previously discussed simulations where the seed was made of Rh atoms. Despite the general consensus in reputing the Rh@Au core‐shell arrangement as the most stable for AuRh arising from computational inspections,[Focusing on the growth over the other Rh seeds . In general, they have energies higher than the ones obtainable through metal deposition and nucleation on a seed. At finite temperatures, it is likely that coalesced morphologies will evolve to those shapes obtained from the one‐by‐one growth. We do not consider asymmetric morphologies for further analysis. Before proceeding with the presentation of the results concerning the last explored synthetic procedure, it is interesting to highlight the spontaneous propensity to generate Rh@Au core‐shell nanoclusters where the Au atoms tend to cover the surface of the Rh counterpart as is noticeable in the inset images reported in Figure Despite the different structural arrangements, isomers obtained through these two synthetic approaches have sufficiently similar excess energy, indicating the same relative stability compared to other possible shapes. This suggests that, although coalescence can produce structures energetically identical to the one of the growths over seeds in some specific cases, this technique can be used to synthesise isomers of the same nanocluster whose properties could be sensibly different from its one‐by‐one growth counterpart. These considerations are however valid only in some specific cases. As observable from Figure Finally, we consider our tertiary formation process for AuRh nanoalloys is the annealing of small nanodroplets. In these simulations, some of the tested systems were collected from the trajectories of the processes already discussed, while others were specifically built for this purpose. A detailed list of the tested systems is available in the Computational method section. Compared to the previous synthetic approaches, this process allows for the formation of the thermodynamically stable isomer for a certain nanocluster and this highlight which structures are more likely to be obtained in an opportunely designed experimental setup. Indeed, our simulations focus on the formation of individual nanoclusters but neglect the coexistence or the assembly of several nanoparticles at finite temperatures. Our calculations should be treated as a reference for gas‐phase experiments where the concentration of nanoalloys is low enough to prevent sensible clusters interactions.50, 51m) of the investigated alloys, since the solid‐liquid phase transition can be directly observed from the trend of the excess energy as a function of the temperature in both melting and subsequent freezing processes. An example of this plot is given in Figure 42Rh13 icosahedral nanocluster is given as a function of temperature, in both processes. In this case, the systems present a phase transition that begins at 1000 K and terminates around 1200 K, leading to a liquid nanodroplet. We define the Tm of the nanocluster as the inflection point of the functions which in this case falls around 1100 K. The overlap of the two lines referring to the melting and freezing processes indicates that the transition is thermodynamically reversible and that the geometries recovered from the solidification, i. e. the thermodynamically stable isomer of the alloy, coincide with the nanocluster initially melted.We calculate the meting temperature  and anyway is not coherent with the fact that the 147 atoms Au128Rh19 present a higher Tm compared to Au73Rh19. Furthermore, all those structures arise from the same synthesis, and thus this peculiar Tm behaviour cannot be related to differences in chemical ordering or nanoclusters inner morphology. The explanation of this phenomenon must lie elsewhere. Thinking about the relative structures stabilities it can be noticed that the 71‐CM and the Au128Rh19 nanoclusters possess remarkable energetic stabilities given by the geometrical closure of the gold shell surrounding the inner part of the system. Being stacked within a well‐defined texture, the gold atoms have a high kinetic diffusion barrier and texture is less affected by the enhanced thermal vibrations. Conversely, the superficial atoms of Au73Rh19 are not constrained within any particular motif and further suffer from low‐coordinated Au atoms, making them more sensitive to the temperature changes. Generally speaking, symmetric isomers are likely to show a higher melting point than less symmetrical structures, because of a lower contribution to the vibrational entropy.m differences.It is indeed surprising how the Tm is that all nanoalloys show remarkably high thermal stabilities. There are nanoalloys such as 55‐BC with remarkably high Tm (around 1000 K), which is an outstanding value for a 55 atom aggregate. The case of 147 atom structures is even more surprising. Even though some of them have a very low Rh content (around 13 % in the case of Au128Rh19), the Tm are still surprisingly large, being located around 1000 K. This indicates that even a small amount of Rh can heavily modify the physical properties of these systems and influence their thermal stabilities. This, in turn suggests that an Rh doping of gold structures could effectively increase the thermal stability of the system and extend the range of temperature in which gold‐nanostructured devices can be applied, potentially leading to important improvements in technologically relevant applications.Another interesting aspect that emerges from the analysis of Tm which we related to the structures of the alloys themselves and their structural closure.These latter observations, which are here based on a theoretical approach to the problem, follow what is experimentally known about the thermal stabilities of these nanoalloys. In a work from 2017, Shubin et al. studied the formation and stability of gold‐based nanoalloys exploring also the AuRh system.conversion chemistry mechanism where Au seeds act as nucleation spots for Rh growth, which gradually migrates towards the inner part of the structure as the sizes increase.To conclude this section on the results of MD simulations, we want to comment and integrate the synthetic mechanism Shubin et al. proposed in their work. From the data obtained through X‐Ray Diffraction, they proposed the synthesis of AuRh could occur through a The experimental conditions indeed forced the synthesis to proceed that way and it was demonstrated to generate thermally stable nanoclusters. However, the melting temperature recovered by the authors are sensibly smaller compared to the ones we predict in our simulations, being around 700–800 K for nanoparticles with sizes around 5 nm. In our opinion this is due to the chosen synthetic procedure (Rh nucleation over Au seeds), which we demonstrated is not the most suitable for these kinds of nanoalloys, leading to relatively unstable systems. On the contrary, performing the growth the opposite way i. e., by depositing Au onto Rh seeds could bring us to structures with higher thermal stabilities, lower topological disorder and could lead to a more accurate atomic species distribution, selectively producing minimum energy alloy isomers.19‐DI and Rh19‐ID. We furthermore extend the calculations on the pure forms of metal structures, i. e. on Rh19, Au20‐Th, Rh55‐Ih and Au55‐Ih. The data recovered from the DFT calculations are collected in Table bond, which estimates the nanoalloys stability with respect to the isolated atoms case . Such values are always higher for the isomers recovered through MD . However, the relative stability between the two isomers is not constant and seems to increase as the gold shell covers the inner seed. The total energy separating the two isomers at the DFT level are 0.16 eV, 0.24 eV and 1.36 eV for 39‐GS, 55‐BC and 71‐CM nanostructures, respectively. We calculated the relative stabilities between isomers at the MD level, quenching the structures obtained during the dynamics. We obtained energy differences between DI and ID isomers of 0.66 eV, 0.80 eV and 1.08 eV for 39‐GS, 55‐BC and 71‐CM, respectively. Although the agreement with DFT is only qualitative as expected, the energy ordering is the same, suggesting with a larger gold envelop, it is less likely to rearrange its core. Energetically speaking, there is also a net energy gain in forming the alloy compared from the pure nanoclusters, as confirmed by the positive values of the mixing energy ϵmix. This indicates that the production of those systems should be an exothermic process that occurs spontaneously and could in principle catalyse the production of isomers with similar energy, if the kinetic energy barrier for the isomer's transition is small enough.In the second part of this work we deepen our insight on some specific AuRh structures and investigate their features by means of DFT calculations, using a plane‐waves basis and the PBE exchange‐correlation functional.19 seeds. This however is not connected to a larger number of Rh constituting the nanocluster, since the seeds always have the same number of atoms; indeed this effect arises from the sole covering effect given by Au, which stimulates an elongation of the Rh−Rh bonds, allowing them to approach and reach the bulk PBE calculated value of 2.72 Å.The geometrical analysis of the DFT‐relaxed nanoalloys reveals interesting trends for the nearest neighbour interatomic distances. At first, our analysis of the data demonstrates that as the size of the system increases, the average Au−Au bond length increases and approaches the bulk PBE estimated reference value of about 2.95 Å.19 seed itself whose geometrical configurations strongly affect its electronic properties  could lead to interesting photocatalytic processes. Indeed, simple Coulombic interactions could favour the adsorption of electron rich molecules on top of these sites. Then by optically stimulating charge transfer transitions within the alloy, these adsorption points easily take part to the optical activity and this in turn would probably affect the vibrational and/or the electronic structure of the adsorbed molecule, activating chemical reactions. Such a mechanism could also involve the generation of hot‐carriers as already proposed for these nanoalloys.19 seed revealed that the shape assumed by the inner parts of the nanostructures plays a major role in determining the system's physical features, especially regarding the magnetic moment and HOMO‐LUMO gap. An analysis of the charge distribution demonstrates the existence of a net charge separation within the nanoclusters, with gold atoms attracting electrons from rhodium. This suggests the existence of optically active charge transfer transitions that could potentially play a major role in the system's photocatalytic capabilities. To date these are nothing more than theoretical speculations, however we believe this route deserves to be explored since it could bring practical improvements in the use of AuRh nanosystems as effective photocatalysts. Globally, our results represent a solid step toward the comprehension of the dynamics and the physical properties of these notable nanoclusters.In this work, we studied the formation and the physical properties of AuRh nanoalloys, between 20 and 150 atoms, by means of a multiscale protocol involving molecular MD and DFT simulations. Among the tested synthetic procedures, the one‐by‐one growth produces the most favourable geometries, especially when Au atoms are deposited over an Rh seed. Such processes generate structures with exotic shapes, whose growth is driven by the symmetry assumed by the Rh seed, and were found to have extremely interesting physical features. All simulations generate structures marked by a strong phase segregation presenting an Rh@Au core‐shell ordering. Any other arrangement was found to be highly unstable, sometimes even at room temperature . All tested AuRh nanoalloys are characterised by a remarkably high melting temperature, sometimes above 1000 K, even in cases where the Rh content is below 20 %. Moreover, we noted that structures presenting geometrical closures were, in general, more stable at higher temperatures. Ab‐initio investigations performed on structures built from an Rh57, using a potential derived in the second moment approximation to tight‐binging theory to describe the interatomic potential.[All calculations were performed as implemented in the open‐source package LoDiSotential.58, 5920 seed (Au20−Th) and of Au over various Rh seeds, namely double‐icosahedron Rh19 (Rh19−DI), truncated cuboctahedron Rh38 (Rh38−Co) and icosahedron Rh55 (Rh55−Ih). These structures are visible in the bottom panel of Figure One‐by‐one growth: we simulated the growth of Rh over a tetrahedron Au20−Th, Au38‐Co, Au55−Ih and Au75−Co with the rhodium Rh19−DI, Rh55−Ih and Rh75−Co nanoclusters. This allowed us to obtain and analyze the dynamics of formation of several alloyed structures that differ in sizes and compositions. The collision always occurs along the same cartesian axis, thus using the same nanoclusters impact angle. All systems were simulated at 600 K for a total amount of 500 ns, allowing the system to relax after the impact which always takes place within the first 50 ns. Snapshots showing coalesced structures are reported within the graphs in Figure Nanocluster's coalescence: we simulated the collision and further coalescence of the gold‐based systems Au55−Ih, Au147−Ih; Rh55−Ih, Rh147−Ih; Rh@Au core‐shell 55 atoms Au42Rh13−Ih and Au36Rh19−Ih, 71 atoms Au52Rh19, 92 atoms Au73Rh19, 147 atoms Au92Rh55−Ih, Au128Rh19−Ih and Au134Rh13−Ih; Au@Rh inverse core‐shell 55 atoms Au13Rh42−Ih; randomly mixed chemical ordered 55 atoms Au26Rh29−Ih; Janus ordered 55 atoms Au27Rh28−Ih. Notice that most of the chosen nanoalloys come from the simulations described in 1) and 2) while other structures were built ad hoc to be tested in these simulations and to determine their Tm. The systems were first melted by gradually increasing the temperature and then cooled down using an heating (and cooling) rate of 1 K/ns, which is small enough to consider the solid‐liquid transitions as a reversible process and was proven to give reliable Tm within a ±50 K range.13Rh42, randomly mixed chemical ordered Au26Rh29−Ih and Janus ordered Au27Rh28−Ih) are highly unstable and naturally assume core‐shell motifs during the initial heating, giving caloric patterns and structure similar to the core‐shell cases (e. g. Au42Rh13−Ih or Au36Rh19−Ih). The caloric profiles of these particular alloys are attached as Supporting Information.Nanodroplets annealing: we simulated the annealing process of several Au, Rh and AuRh systems. In particular we tested the following structures: Au11 Hz. This protocol has already been assessed as reliable by other simulations involving metallic nanoclusters.[Before performing the simulations, all nanoclusters were quenched through a 5 ns long equilibration. The simulations were performed via the Velocity‐Verlet, using a time‐step of 5 fs and imposing a temperature control through an Andersen thermostat with a stochastic collision frequency of 5 ⋅ 10clusters.63, 6455 using plane‐waves basis sets, as implemented in the code Quantum ESPRESSO version 6.6.[As discussed in the Result and Discussion section, we performed ground‐state DFT calculations on the most favorable geometries recovered along the MD simulations and relative isomers. These calculations were conducted at the PBE levelsion 6.6.65, 66Qeff=ne-qwhere neis the number of accounted valence electrons for Rh and Au, while qis the Bader charge calculated through the Bader partitioning charge analysis.[The effective atomic charges assigned on each atom of the nanoalloys were calculated as To characterise the thermodynamics of the trajectories and estimate the stabilities of various isomers, we exploited some useful quantities that allow a characterization of the processes and systems energetics. These quantities are defined as follows:• Excess energy: this represents the energy required to form a certain alloyed structure starting from the Au and Rh bulk phases. This quantity was proved to be a reliable descriptor for the relative stability of alloys with different sizes and compositions.46, 71NAuand NRhare the number of Au and Rh atoms constituting the alloy, EAucohand ERhcohare the cohesive energy of bulk Au and Rh and Ealloyis the total energy of the nanoalloy, estimated classically by MD. In all cases we impose EAucoh=3.55 eV and ERhcoh=5.75 eV which are the values of cohesive energies predicted by the adopted force field.where • Binding energy: the energy gained by the systems when the atoms bind together starting from their gas phase, defined as:EAufreeand ERhfreeare the energy of single Au and Rh atoms in the gas phases, estimated at the DFT level. In this case Ealloyrefers to the total energy of the relaxed nanoalloy, calculated at the DFT level.where • Mixing energy: energy gained by the systems when alloys with specific geometries are formed, compared to the pure metal nanoclusters. It is defined as:EAualloyand ERhalloyare the DFT calculated energy of pure Au and Rh nanoclusters at the geometry of the considered alloy. Even in this case Ealloyis the total energy of the relaxed nanoalloy computed at the DFT level.where ϵmixvalues collected in Table The Finally, the graphical representations of all nanocluster structures were obtained using the visualization code OVITO.The authors declare no conflict of interest.1As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.Supporting InformationClick here for additional data file.