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In this study, we produced a global fLNR and ({V}_{{c}_{{max }}}^{25}) map using an RF model trained primarily by remote sensing and in situ observations and examined seven ({V}_{{c}_{{max }}}^{25}) models based on 5 competing hypotheses with regard to their assumptions on fLNR. Our results suggested that the global average fLNR was 18.2 ± 6.2%, and the global distribution of fLNR was dominated by the interaction between fLNR and leaf traits (i.e., LMA and LPC), followed by regional influences from climate (i.e., VPD and PAR) and soil characteristics (i.e., soil pH and sand percentage). We used RF fLNR distribution and its relationships with environmental covariates to evaluate five empirical and two optimal ({V}_{{c}_{{max }}}^{25}) models, and found that the models showed different degrees of inefficacy in reproducing RF fLNR. Here, we discuss the mechanisms underlying the detected fLNR responses to leaf traits, climate, and soil characteristics and propose future directions to improve the simulation of fLNR and ({V}_{{c}_{{max }}}^{25}) in models.Negative correlation between fLNR and LMAOur finding that fLNR is negatively related to LMA agrees with a previous meta-analysis that found fLNR decreases by 0.54 ± 0.08% with a 1 g/m2 increase in LMA based on a univariate regression10, though another study reported that the negative relationship between fLNR and LMA was non-significant using a smaller dataset11. Using the global dataset, we found a relatively small sensitivity of fLNR to LMA (−0.19 ± 0.001% per 1 g/m2) when accounting for climate and soil (Fig. 3b).Higher LMA is the result of plants allocating more biomass and nitrogen to building cell walls, which may cause a reduction in CO2 diffusion into the mesophyll as well as relative nitrogen allocated to RuBisCO38. Leaves with greater LMA are tougher and usually have a longer leaf lifespan11,36. Therefore, the negative correlation between fLNR and LMA highlights the trade-off between photosynthesis and persistence along the leaf economic spectrum: on one end, leaves invest more nitrogen in RuBisCO to increase the photosynthetic capacity and enhance carbon uptake; on the other end leaves invest more nitrogen in structural biomass to improve leaf longevity and lengthen the carbon uptake period. The latter is especially true for evergreen species that have greater LMA and smaller fLNR than deciduous and herbaceous species10. The coordination of fLNR and LMA is also consistent with a recent analysis highlighting the role of LMA in determining the variation and predictability of LNC in ecosystem models39.In addition, we found that LPC increases fLNR in tropical evergreen forests and mixed forests, which tend to be more phosphorus limited40. Our result is consistent with previous studies reporting coupled leaf photosynthetic capacity (i.e., ({V}_{{c}_{{max }}}^{25}) or maximum photosynthetic capacity (Amax)) and LPC for tropical species41,42. This result indicates potential widespread adjustments of plants nitrogen use by phosphorus investment for photosynthesis and plant growth43 in tropical and mixed forests. In addition, we note that the productivity of some grasslands44,45 and boreal forests46,47 has also been reported to be limited by phosphorus availability, however, we did not detect a strong positive dependence of fLNR on LPC globally for these ecosystems in our study. The difference potentially suggests that the phosphorus limitation of grasslands and boreal forests is not as prevalent as that for tropical and mixed forests (though some mixed forests are in the boreal region).Climate and soil impacts on fLNRThe response of fLNR to climate is often implicitly included in ({V}_{{c}_{{max }}}^{25}) models. We found that fLNR was sensitive to annual VPD globally. Several studies have reported that plants in arid environments (i.e., high VPD) tend to have a higher Amax and LNC48,49 as plants enhance photosynthetic capacity to maintain a given assimilation rate with lower stomatal conductance and reduced water loss. Such a response to aridity has been described using the least-cost theory19,21. Our results show that other than Amax and LNC, fLNR also increases with VPD, consistent with a recent study reporting higher nutrient use efficiency for plants in semi-arid ecosystems of the African Sahel49. We note that an earlier study reporting differently that a dry site has a smaller ({V}_{{c}_{{max }}}^{25})/LNC ratio (i.e., smaller fLNR) than a wet site19, though it used annual precipitation, not VPD to define aridity.In addition, the positive relationship between PAR and fLNR for non-forests (Fig. 3c) provides a potential explanation of the light acclimation of photosynthesis, as several studies have found that leaf and ecosystem Amax can be enhanced by intermediate to long-term average PAR50,51,52. For non-forest ecosystems, our results suggest that photosynthetic light acclimation emerges as plants increase fLNR in response to increasing annual PAR. However, for forests (except EBF) the results suggest that photosynthetic light acclimation may emerge more due to the increase in LNC as we did not detect a positive response of fLNR to light (Fig. 3c).Soil characteristics have been reported to influence Amax and LNC37, but we found no studies that have examined the impact of soil characteristics on fLNR. Among the eight soil properties we examined, we found positive responses of fLNR to soil pH and soil sand percentage, followed by small influences of bulk density and silt for certain ecosystems (i.e., croplands, needle leaf forests). pH influences the ability of soil to hold on to nutrients, including Ca2+, K2+, and Mg2+, that are essential to plant growth. A higher pH means more available nutrient cations as acid soils replace nutrient cations with H+. Several studies have reported a positive effect of pH on Amax37, non-temperature standardized (V_{c_{max}})20, and LNC39. Soil sand percentage had a positive impact on fLNR, possibly because sandy soils tend to be less fertile53 and thus stimulate plants to use their nitrogen more efficiently for photosynthesis and growth. The global influence of soil on fLNR was generally smaller than leaf traits and climate, but our analysis indicated that on 11.9% of the vegetated surface, soil characteristics contributed more than 15% of the changes in fLNR (Fig. 3a).Notably, our study found that the soil nitrogen content has a limited impact on the spatial variation of fLNR (Fig. 3). The result implies that processes such as nitrogen deposition/addition are unlikely to affect plants fLNR. The soil nitrogen map we used was upscaled from ground observations of soil profiles in the World Soil Information Service (WoSIS) database. About 47.4–81.4% of the soil profiles in WoSIS are collected from the 1980s to 2020s54, when there were strong N deposition effects55. Therefore, we expect the N deposition effect has been implicitly included in our analysis. We acknowledge that some studies have suggested N deposition influenced leaf nitrogen content and photosynthesis56,57, however, the influence is limited to certain biomes, deposition load range, and time after the deposition. It is unclear whether these localized and time-dependent effects can influence the global variation of fLNR.Uncertainty in the derivation of fLNR and ({V}_{{c}_{{max}}})
fLNR was derived based on Eq. (1) (see “Methods”) that mechanistically links ({V}_{{c}_{{max }}}^{25}), LNC, and fLNR, with the assumption that specific activity of RuBisCO (α25) and mass ratio of RuBisCO to nitrogen (fNR) are relatively constant values. The average uncertainty of RF fLNR was about 4.20 ± 2.20% (Supplementary Fig. 3). The uncertainty of fLNR was propagated from several sources including RF ({V}_{{c}_{{ma}x}}^{25}), α25, fNR, and LNC (Supplementary Fig. 3). Among them, the α25 ranges between 47.34 and 60 μmol CO2/g RuBisCO/s, and fNR ranges between 6.11 and 7.16 g RuBisCO/g N4. Our uncertainty test showed that the influence of α25 and fNR uncertainties on global fLNR were only around 1.13 ± 0.39% and 0.80 ± 0.27%, respectively (see “Methods”; Supplementary Fig. 3). Physiologically, α25 is a value that reflects the change in active sites of RuBisCO and the kinetic constant of the enzyme RuBisCO (k25). The number of active sites of RuBisCO is often regarded as a fixed value (set at 6 × 1023/mol RuBisCO) for vegetation on the land surface5, but there are reports showing that k25 varies with species9, leaf ages58, and temperature59. While these dependencies are elusive due to limited observations, previous studies have reported that k25 negatively correlates with LNC60 and LMA61. The negative relationship between k25 and LMA or LNC is potentially caused by the relatively lower drawdown of CO2 from intercellular spaces to the chloroplast as increased LMA increases mesophyll resistance. In that case, the negative dependence of k25 and α25 on LNC and LMA might account for part of the negative dependence of fLNR on LMA that we found (Fig. 3b), though the negative influence of LMA on α25 was weak and within the range of uncertainty, we quantified (Supplementary Fig. 3).Compared to α25 and fNR, the uncertainties in LNC and RF ({V}_{{c}_{{max }}}^{25}) incurred larger uncertainties in fLNR. We found that LNC alone caused changes of 3.35 ± 2.16% in fLNR and RF ({V}_{{c}_{{max }}}^{25}) caused 3.13 ± 1.50% (Supplementary Fig. 3). Our study is the first attempt to upscale in situ ({V}_{{c}_{{max }}}^{25}) to the globe using remote sensing, while similar studies have done that for other leaf traits33. The observations used for training RF were densely distributed in Europe and North America, while inner Asia, Southeast Asia, Africa, and high-latitude regions are much less constrained by observations (Supplementary Fig. 6a). In addition, we did not consider temperature acclimation when standardizing in situ (V_{c_{max}}) to ({V}_{{c}_{{max }}}^{25}) (Eq. (2)), in order to facilitate the comparison with models that only estimate ({V}_{{c}_{{max }}}^{25}). However, the uncertainty related to temperature scaling should be limited as acclimated and non-acclimated temperature scaling factors for (V_{c_{max}}) are similar under 30 °C62,63.The choice of an LNC map is another source of uncertainty in the derivation of fLNR. There are several global LNC maps available other than the EB1728 map we used, namely AMM1833 and CB2031. Each product has been validated in their respective studies (Supplementary Table 3). To examine the uncertainty incurred by the choice of LNC maps, we calculated fLNR using each of the three LNC maps. The three resulting fLNR maps show similar spatial patterns (Supplementary Fig. 10), with the spatial correlation coefficients (r) between them ranging from 0.57 to 0.71 (p  More

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Intra- and interspecific differences: comparison with former studies on Pagellus species and other fish speciesTo understand the relationship between function, shape, and the environment, it is essential to include the morphological variability of otoliths, considering biological and environmental variability leads to otolith shape heterogeneity through morpho-functional adaptation to different habitats. Several authors have highlighted changes in otolith shape between species and, in many cases, among populations of the same species (e.g., herrings, salmonids, and lutjanids). The intra-specific variability of otolith morphology and shape are the basis of stock separation and assessment and is related, especially in sagittae, with environmental (e.g., water temperature, salinity, and depth) and biological factors (e.g., sex, ontogeny, and genetic variability)20.The analysis of the three Pagellus species revealed that otolith morphology and morphometry did not follow those described in a previous study1 conducted in the western Mediterranean Sea and the Atlantic Ocean in term of rectangularity, circularity, sagitta aspect ratio and sagitta length to total fish length ratio. Although the images provided in our study closely resembled those from research in other geographical areas, the morphometric measures (obtained according to the procedures and methods described in the previous literature1,20,23,32) exhibited several differences. Considering the scale of our study compared to previous studies, it is difficult to provide an entirely valid comparison; the differences in sagitta morphology and morphometry could have been triggered by biotic and abiotic parameters (e.g., temperature, salinity, genotype, habitat type, differences in food quality and quantity)13,33,34,35. Such environmental and genetic factors may be primary drivers of otolith morphometry and morphology among fishes in different habitats. Therefore, detected shape differences are at the basis of fish stock differentiation36.Our results indicate that the min–max circularity and rectangularity of P. bogaraveo from the Southern Tyrrhenian Sea differ from those calculated in a previous study1 in the western Mediterranean Sea, and the north and central-eastern Atlantic ocean. Moreover, the increase in circularity in larger specimens, confirms a greater tendency toward circular than elliptical otolith shape in southern Tyrrhenian Sea species compared to those in other Mediterranean and Atlantic areas.Despite statistical differences and correlations in this study supported the hypothesis that some changes in sagitta morphology are related to fish size differences, several aspects and studies should be performed to better understand this relation. The negative correlation between the ratio of sulcus acusticus surface to the entire sagitta, rostral morphology, and the increase in specimen’s size was related to the expansion in the length and surface of the entire sagitta and rostral area in larger specimens. These features, with no statistical relevant increment in sulcus acusticus surface and increased rostrum length, could be correlated with more pronounced peripheral sagitta growth in this species. Sagitta, in fact, after fish pelagic phase, might increases its surface in the rostral area and the margins. Since the present study did not take into account ontogenetic stages and specimens age, it is hard to relate this result with sagitta and sulcus acusticus growth. But reading this increase by an ecological point of view, it could be related to the lifecycle of the species. During the juvenile stage, in the early stage of pelagic life, the species inhabits shallow water. Adults inhabit deep-water environments, migrating down the continental slope to a depth of 800 m after the juvenile stage. These changes in habitat might be the cause of morphological variations in the sagittae, highlighting the relationship between sagitta features and environmental and biological factors.The P. acarne specimens demonstrated the highest number of morphometrical parameters that did not follow those of the same species described in a previous study (i.e., circularity, rectangularity, sagitta length to total fish length ratio, and sagitta aspect ratio)1. These morphometrical changes are reflected in otolith shape. The otoliths from specimens in our study were largely circular, with highly irregular margins and a rostrum that varied in length and width through the left and right sagitta, as indicated by the significant differences in rostrum aspect ratio values.The morphometrical results in P. erythrinus revealed differences in circularity, rectangularity, sagitta length to total fish length ratio and sagitta aspect ratio compared to a previous study1 in the western Mediterranean Sea and north-central eastern Atlantic ocean.The P. erythrinus specimens were characterized by a pentagonal otoliths shape, and increased circularity compared to the same species from other areas. The results also indicated small differences between the left and right sagitta. This small differences were previously described in other Mediterranean sub-areas, for example, otolith width values in P. erythrinus specimens collected in the Gulf of Tunisia37,38.As said above for P. bogaraveo, it is hard to relate the differences between juveniles and adults with fish growth due to the absence in present paper of ontogenetic and age analysis. The higher width than length, demonstrated by min–max width values in Tables 1 and 2, in sagittae of adults P. erythrinus specimens could be correlated with an exponential increment in fish size compared to the sagittal length. Further analyses on ontogenetic development of this species are required to better define the sagitta growth related to fish growth.The increase in sulcus acusticus surface exhibited in the adult specimens could be correlated with feeding habits; during its adult life, this species is a benthic feeder and inhabits deeper environments than juveniles28,29.Although meaningful lateral dimorphism of the sagittae was detected only in flatfish, statistical analysis revealed several small differences between the left and right sagitta in P. erythrinus and P. acarne, as previously described in other round fish species, such as Chelon ramada (Risso, 1827)40, Diplodus annularis (Linnaeus, 1758)41, Diplodus puntazzo (Walbaum, 1792)42, Clupea harengus (Linnaeus, 1758)43, and Scomberomorus niphonius (Cuvier, 1832)44.Our study confirmed slight differences between width values in left and right sagitta previously described in P. erythrinus and extend the differences to other parameters, such as circularity and rectangularity (Tables 1, 2). Concerning P. acarne, however, marginal differences between the left and right sagittae were observed for the first time.This slight differences are supported by the literature concerning genetic and environmental stressors41. Since the functional morphology of otoliths is not completely understood, it is difficult to find a direct link between these small differences and the ecology of the species. However, several eco-functional factors, such as feeding behavior, deserve attention as fundamental for a better understanding of the relationship between otolith features and species habitat. For example, P. erythrinus largely preys on strictly benthic organisms, such as polychaetes, brachyuran crabs, and benthic crustaceans. Most of these species frequently escape predators by hiding under the sandy substrate. Other Sparidae (Lythognathus mormyrus, Linnaeus, 1758) feed on benthic fauna, engulfing sediment and filtering it in the buccal cavity, demonstrated by the high percentage of detritus and benthic remains (e.g., scales, urchin spines, and benthic foraminifers) in the gut and stomach contents29. To engulf sediment, P. erythrinus performs a particular movement with the head and body, laterally shifting and pushing forward, to dig the bottom sand and reach prey. This kind of behavior, common in all benthopelagic species with the same feeding habits, could influence the sagitta growth and morphology, triggering small differences between the left and right sagitta. Further studies on this and other species with this behavior (e.g., L. mormyrus) are necessary to confirm this hypothesis.Concerning inter-specific differences in sagitta morphology among the three species, it is difficult to read the results obtained in this study eco-morphologically since an insufficient understanding of the functional morphology and physiology of otoliths prohibits a direct relationship, valid for all the species, between eco-functional features and otolith morphology. Nevertheless, as expected, the shape analysis (Fig. 1) revealed clear differences between the three congeneric species. Considering several ecological, functional, and biological features in each species, the results have demonstrated a sagitta morphology that could be in accordance with the ecology and lifestyle of these three congeneric seabreams.Relationship between otolith morphology and ecology/lifestyleThe sagittae of P. acarne exhibited a shape resembling those in other pelagic species, with a long rostrum and the entire sagitta elongated and narrower than those in other two seabream species. The species that show the most pelagic habits, with largely planktivorous feeding at a small size, adapt also to benthopelagic feeding activity in adult life. The statistically relevant similarity found in P. bogaraveo could be proof of the ecomorphological adaptation of sagittae to pelagic and demersal environments. This hypothesis may be confirmed by marked differences in shape compared to those in P. erythrinus, which is the most benthic among the three species.Pagellus erythrinus was the species with the shortest rostrum. It also has the most benthic habits, largely preying on epibenthic and infaunal species. Moreover, its ecology and life cycle differ among the three species under study since they are strictly related to the benthic environment. This lifestyle could be in accordance with the differences observed in the shape analysis results. The sagitta contours appeared more circular and wider than those in the other two species. The PCA and LDA also confirmed the most difference in shape among the three species.The species with the most marked antirostrum and sagitta shape was P. bogaraveo, which is a cross between the other two congeneric species. Pagellus bogaraveo is a demersal species, which inhabits the deep biocenosis and feeds in both benthic and mesopelagic environments. Furthermore, the ecology of this species could support the sagitta shape described in our study27,30.Otolith morphology and morphometry in congeneric Pagellus species described in this study has followed the relationship between sagittal parameters, habitat, and depth described in previous literature15. According to several authors, the percentage of species with large otoliths increases with depth, except for abyssal depth. The specimens of P. bogaraveo analyzed in this paper (especially adult individuals) had larger otoliths than the other two Pagellus species due to their demersal habits (they inhabit the continental slope to a depth of 800 m). A larger sagitta is essential in demersal environments to compensate for light reduction by providing improved acoustic communication, sound perception15,45, and a sense of equilibrium46.Sulcus shapeConsidering the sulcus acusticus, in the otolith atlas for the western Mediterranean Sea and Atlantic ocean1, studies describing and comparing otoliths10 and the diversity and variability of otoliths in teleost fishes9, the sulcus in P. bogaraveo, P. acarne and P. erythrinus was described as heterosulcoid, with an ostium shorter than the cauda and a long, narrowed rostrum, especially in adult P. bogaraveo and P. acarne individuals. Heterosulcoid otoliths were also observed in south Tyrrhenian Sea Pagellus individuals, with marked differences between juvenile and adult specimens. In a demersal species, such as P. bogaraveo, juveniles live in shallow, coastal water. Once adults, they inhabit deeper water (to a depth of 800 m). Changes in the crystalline and morphological structure of sulcus acusticus between juveniles and adults reflect this species’ need to adapt to deeper environments with less light.The results indicate that in P. bogaraveo, the sulcus acusticus does not differ in surface between juvenile and adult specimens. This feature could be correlated with earlier sulcus acusticus development in this species, compared to P. erythrinus and P. acarne, emphasizing the role of the sulcus acusticus in this demersal species48,49. This might also confirm the strict correlation between biological and environmental factors and sagitta morphology in studied seabreams species.Another morphological feature of the sulcus acusticus, which might support the ecology of the species, is the deep ostium and cauda. In adult specimens of P. bogaraveo and P. acarne, the sulcus structure deeply penetrated in the sagitta carbonate structure. Conversely, in adult P. erythrinus specimens, the sulcus did not penetrate as deeply as in the other two seabream species. This sulcal feature could correspond with the ecology and feeding behavior of P. erythrinus, which specializes in benthic strategies, including small differences between left and right sagitta and the absence of the notch and antirostrum in sagittae.Although the deeper sulcus acusticus in P. bogaraveo and P. acarne might be linked to depth distribution, as in P. bogaraveo, it may also correspond with high mobility related to feeding behavior, as in both P. bogaraveo and P. acarne. The different depths of sulcus acusticus can change the thickness of the otolithic membrane, by varying the relative motion of otoliths with the macula sacculi2. As previously demonstrated50, the different thicknesses of the otolithic membrane induce differences in mechanical resistance between the otolith and sensory epithelium.The differences in sulcus acusticus and otolith ratio between P. bogaraveo specimens and the other congeneric species, demonstrated by the results, might be also correlated to the differences in habitat, feeding habits, and soundscape.Despite the lack of information concerning the physiological ear response related to variations in macula or sulcus size, the sensory hair cells in macula sacculi are likely to be affected by changes in sulcus depth, shape, 3D structure (planar vs. curved), and surface.The significant difference in relative sulcus area may be due to typical alteration in this parameter concerning differences in the mobility patterns, food, feeding behavior, and spatial niche.Higher relative sulcus area ratios have been observed in the deepest species or those with high mobility49. In our study, the morphometry results concerning the sulcus did not follow those in the previous literature, displaying higher values in P. erythrinus and P. acarne compared to P. bogaraveo, although the latter inhabits a deeper environment than the other congeneric species.This higher relative sulcus acusticus surface and the larger, curved sulcus acusticus of P. acarne and P. erythrinus could be correlated with higher mobility in these species (especially P. acarne). In P. erythrinus, however, these features might be related to its benthic lifestyle.As demonstrated by the PCA and LDA of sulcus acusticus parameters, P. erythrinus and P. acarne, which share similar depths and habitats, revealed marked similarities, whereas P. bogaraveo, which lives in the deepest strata of the water column, displayed the most different sulcus acusticus. However, PCA and LDA indicated that the otolith shape in the entire P. erythrinus sagitta was significantly different compared to those in P. acarne and P. bogaraveo.These features could provide a reading key for sagitta and sulcus acusticus eco-morphology in the life cycle and environmental adaptation of fish.The connection between the otoliths and the macula sacculi is fundamental for transducing environmental acoustic signals and for the relative motion of fish (balance). The sulcus acusticus is the area of the otoliths in which this connection occurs.Features of the textureFurthermore, the external textural organization23 changes between juveniles and adults or when environmental changes occur. The differences in the external textural organization found in juveniles and adults support those reported in the literature concerning other species39. Figures 3b, c and 5a–h, demonstrate that our study supported this prediction. However, P. bogaraveo and P. erythrinus juveniles, compared with other species (such as gurnards)23 displayed a more uniform, mineralized, external textural organization.Figure 5SEM images of the crystalline structure of P. bogaraveo, juveniles (a, b) and adults (c, d), and P. erythrinus, juveniles (e, f) and adults (g, h) sagittae.Full size imageAccording to previous literature8, improved hearing capabilities in a species are closely related to a higher value of relative sulcus area ratio. Habitat features, such as depth, feeding strategies, mobility, trophic distribution, and ontogeny, could also influence this ratio.Hence, it may be concluded that morphological differences in sulcus acusticus shape and surface among species are important for comprehending the ecomorphological and eco-functional role of sagitta 2,48.Comparing the intra-specific differences indicated by our results with those in the literature, discussing other populations, we cannot determine whether site-differences observed in sagitta shape are related to genetic evolution and/or adaptative response to environment. To make this distinction it would require a specific experiment in which offspring from different populations are raised in a controlled environment.Furthermore, the knowledge about physiology and functional morphology is insufficient to provide a clear correlation between inter-specific differences among the three congeneric Pagellus species and their ecological and functional features. However, differences in sagitta morphology and morphometry among these three Pagellus species may be related to differences in lifestyle, ecology, and biology since they follow the ecomorphological features of sagittae and species ecology described in the literature. More

The SYF outbreak that occurred in Brazil from 2016 onwards reached states in the southeast, northeast, and south. It became the most important outbreak in recent decades due to the large number of cases and deaths in humans and NHPs, reaching areas with high population densities and low vaccination coverage5,12,19,20. In SP, this process started in a region with high vaccination coverage and progressed to areas with low coverage and/or without vaccination recommendations, with high population densities11,12. The first region with these characteristics to be affected by the outbreak was Campinas12 and the period resulting from this advance was considered the first wave. In the second half of 2017, SYF advanced to the east, south, southeast, and northeast regions of SP, characterizing the second wave.Hill et al.4 analyzed only the SYF epizootics that occurred in SP between 2016 and 2018 and divided this process into three phases. Although this makes more sense for the epizootic disease analysis, considering the outbreak process in two waves made it possible to adequately capture the spatiotemporal process of SYF diffusion and to characterize it by contagion. Moreover, this characterization allowed a discussion on the relevance of the vaccine strategy adopted by SES-SP, especially during the second wave. The Ministry of Health, in view of the YF outbreak in areas without recommendation and/or low vaccination coverage, advocated the expansion of vaccination based on calculations of affected area/expanded area, with the municipality as smallest unit17. Until mid-2017, this strategy was an adequate response. However, it became demonstrably insufficient when the virus reached populous areas with low coverage and/or without a vaccination recommendation, both in SP12 and in other southeastern Brazilian states21.In SP, the advancement of YF within a period of less than six months from areas with high vaccination coverage to populous areas with low coverage or without vaccination recommendations triggered a public health crisis that generated panic in the population. At that time, there were insufficient time and vaccine doses to serve the entire population at risk21. Hence, SES-SP identified the priority vaccination areas based on the analysis of virus circulation in NHPs at forest fragments, which comprise functional ecological corridors for viral dispersion, and were therefore demarcated and used to select areas where populations were most exposed to YF risk. Instead of considering the entire municipal territory with the same risk level, the new strategy sought to identify priority intra-municipal areas for vaccination, considering the speed of dispersion16. Moreover, this strategy, plus the use of single doses1 and fractional doses22, allowed reasonable equation, in space–time, of the demand for vaccines in a large population contingent with an insufficient supply of the immunobiological product. It should be noted that this strategy had already been recommended by the WHO in outbreaks within the African continent in 2015/201621,23.Our results demonstrated that the YF virus dispersion in SP was caused by the outbreak process of territorial spread by contagion; therefore, the mosquito vectors and NHPs could act as a route of viral amplification and further transmission on epizootic waves. In this situation, there was a cadence in the spatiotemporal pattern of viral dispersion through contiguous and nearby areas. This also shows the appropriateness of the vaccination strategy adopted by SES-SP, which allowed the population to receive the vaccine at least two months before the establishment of on-site transmission risk15. A spatiotemporal process of sequential spreading was observed, wherein municipalities located at shorter distances from the areas with YF virus transmission were more likely to be affected first7,8. Although our analyses are limited by the fact that we used the municipality as a spatial study unit, this spreading pattern can also be observed at the intra-municipal level.The speed of the SYF dispersion that we obtained for the first and second waves, disregarding the RDSs of Registro and Itapeva, were similar to those reported by Hill et al.4. Through phytogeographic analysis of YF genomes in NHPs, they reported spreading speeds of around 1.0 km per day. Notably, they took into account epizootics that occurred in SP up to February 2018, and the occurrences of human cases and epizootics in the RDS of Registro and Itapeva were recorded from February 2018 onwards. The differences in the speed of viral dispersion between these two RDSs and the rest of SP during the second wave may be related to the greater vegetation cover and forest preservation of these areas, which can cause a dilution effect, as already demonstrated for other vectorborne diseases24. The spread of the SYF outbreak by contagion in most of SP, with a speed of approximately 1.0 km per day, opened a spatiotemporal window of opportunity for the vaccine to arrive before the virus15, avoiding or minimizing the occurrence of human cases and deaths. Since 2019, this outbreak has advanced to the southern region of the country and has reached the states of Paraná and Santa Catarina, and is still ongoing. This generated an emergency situation similar to that in SP, and the same vaccination strategy adopted in SP has been applied in this region16,18,20.Our findings (Fig. 2) showed important differences in human cases and epizootics that occurred in SP during the second wave, reflecting the degree to which municipalities have adopted the vaccination strategy advocated by the SES-SP. If this is true, what happened in Mairiporã and Atibaia (37% of the total human cases between 2016 and 2019) could also have occurred in municipalities such as Jundiaí, Bragança Paulista, Itapecerica da Serra, Pinhalzinho, Louveira, and São Paulo. If the YF vaccination strategy had not been adapted for the emergency situation during the second wave, we could have had a worse outcome than that observed. These possible scenarios could be the subject of future studies.At the end of 2016 and 2017, the detection of YF epizootics in NHPs anticipated the notification of human cases by two and three months, respectively. This result is expected, since the seasonality observed among NHPs in Brazil differs from that observed in human cases. In primates, circulation is generally detected in September, whereas in humans, circulation is usually observed in December, with the detection of cases among non-immunized people and those exposed to the virus17,25. This also highlighted the importance of the NHP epizootic surveillance strategy, aimed at the early detection of the circulation of the YF virus while still in the enzootic cycle4,26. However, despite the heavy investment of SES-SP in making municipalities sensitive to detection of NHP mortality, the detection of epizootic diseases is still marked by a strong reporting bias26.One of the causes for the anticipation of epizootics in relation to human cases can be explained by seasonality of the precipitation in SP during the year. From the middle to the end of autumn, depending on the year, the total rain decreased and registered monthly values that were increasingly smaller. This becomes reversed in the beginning of spring, when an increase in the precipitated volume begins to be registered throughout SP27,28. To increase YF transmission, mosquito vectors need to be found in large quantities, and one of the determining factors for the proliferation of mosquitoes is the level of precipitation, as this allows the accumulation of water in reservoirs and the hollows of trees29.Another important factor is the rise in temperatures from the end of winter and the beginning of spring. Temperature increases accelerate the time for larval development of the vectors29 and reduces the extrinsic incubation period of the virus30. Precipitation and temperature directly influence the mosquito’s life cycle and viral replication31, hence their increase is an optimal scenario for the proliferation of YF vectors and for the increased occurrence of epizootic diseases in SP29. By contrast, the increase in the probability of detecting human SYF cases in December may be related to the greater degree of exposure among unvaccinated people due, among other issues, to tourism, and to the fact that this occurs simultaneously with the transmission of the YF virus sustained by NHPs.The occurrence of SYF outbreaks in regions with high population density and without adequate vaccine coverage represents a risk of YF reintroduction in urban areas. Even with the vaccination campaigns carried out so far, a large part of the Brazilian population has not yet been immunized5. UYF has been absent in Brazil since 1942, and in human cases that have occurred so far, there has been no epidemiological link with a possible urban cycle20 or involvement of its main urban vector, Ae. aegypti, in viral transmission3. However, this risk is increased by this vector’s presence in almost all Brazilian municipalities32. Another source of concern for the re-urbanization of YF in Brazil is the presence of Ae. albopictus. This mosquito reportedly transmits the YF virus in the laboratory setting and has already been found naturally infected by this virus in the city of Minas Gerais20,33. Present in both urban areas and the rural and forest areas of the country, this mosquito could be a link between the sylvatic and urban forms of the disease3,34. Efforts must be made to prevent the occurrence of UYF epidemics, as could constitute a major public health issue. Among the measures that can be adopted, the most urgent are investments in the production of vaccines, vaccination of the entire Brazilian population, and the development of effective measures to control Ae. aegypti1,21,35.This study has several limitations, such as the use of secondary surveillance data, which are subject to both notification and underreporting errors. Examples of these problems are the need to eliminate three municipalities from wave modeling and the NHP epizootic underreport. The unavailability of the exact probable site of infection for human cases and epizootics, as well as their occurrence dates, obliged us to consider the centroids of the municipalities and the months of the year. These limitations provide a partial view of the outbreak and did not allow us to investigate, for example, the characteristics of the places where the cases and epizootics occurred. Another limitation was that vaccination coverage was based only on vaccination data for children under 5 years of age.However, this study has strengths that contribute to its internal and external validity. Among them are the use of both information about sylvatic human cases, as well as epizootics, to investigate the outbreak process. Another strong point was the use of kriging geostatistics to assess the spread of SYF. This is a spatiotemporal process, and the use of kriging allowed us to consider the autocorrelation of the phenomenon in space–time and numerically represent it throughout the SP area. More

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CORRESPONDENCE
10 August 2021

Iran: drought must top new government’s agenda

Jamshid Parchizadeh

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Jerrold L. Belant

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Jamshid Parchizadeh

Global Wildlife Conservation Center, State University of New York College of Environmental Science and Forestry, Syracuse, New York, USA.

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Jerrold L. Belant

Global Wildlife Conservation Center, State University of New York College of Environmental Science and Forestry, Syracuse, New York, USA.

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We urge Iran’s incoming government to give priority to resolving the country’s worst drought in 50 years (see go.nature.com/2wkwyqn). In our view, the government needs to consult with international as well as domestic water experts to prevent the imposition of flawed agendas. It should also revise earlier policies that have contributed to the crisis.Outgoing president Hassan Rouhani blamed the drought on a 52% reduction in rainfall since last year. However, unregulated aquifer depletion and mismanagement of water resources by the authorities (see, for example, go.nature.com/3cce7or) have contributed.The drought and its associated dust haze is also severely affecting ecosystems in and around Iran (see go.nature.com/3jhauvc and http://pana.ir/news/1178597).

Nature 596, 189 (2021)
doi: https://doi.org/10.1038/d41586-021-02189-z

Competing Interests
The authors declare no competing interests.

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The data collection protocol is described in Sánchez et al.19 and followed Reporting Standards for Systematic Evidence Syntheses (ROSES) guidelines20. Philibert et al.21, also proposed eight criteria for conducting high quality meta-analysis, which overlap to some extent with ROSES guidelines. Our methods fulfil the Philibert et al. requirement to use a repeatable procedure for paper selection, provide a list of references, and ensure availability of the dataset, while other quality criteria are only relevant at the meta-analysis stage.Search processThe literature search was conducted on 29 November 2019 and updated on 5 January 2021, and aimed to identify relevant English language articles published in peer-reviewed literature. We searched in titles, abstracts and keyword lists of literature in the Scopus and Web of Science databases, using the following search string (formatted for Scopus; see Dataset 1 for the equivalent string formatted for Web of Science): TITLE-ABS-KEY (“agricultur*” AND “biodiversity”) AND TITLE-ABS-KEY (“agro?ecology” OR “agro?biodivers*” OR “agroforestry” OR “border plant*” OR “riparian buffer” OR “woodlot” OR “hedgerow” OR “cover crop*” OR “crop rotation” OR “crop divers*” OR “inter?crop*” OR “mixed crop*” OR “cultivar mixture” OR “plant divers*” OR “polyculture” OR “tree divers*” OR “variet* diversity” OR “fallow” OR “field margin*” OR “grass strip*” OR “*flower strip*” OR “insect* strip” OR “conservation strip” OR “vegetation strip” OR “catch crop” OR “inter?crop*” OR “crop variety” OR “crop sequenc*” OR “mixed farming” OR “land sparing” OR “landscape heterogeneity” OR “heterogeneous landscape” OR “landscape diversi*” OR “divers* landscape” OR “homogeneous landscape” OR “landscape homogeneity” OR “landscape complexity” OR “simplif* landscape” OR “complex landscape” OR “multi?function* landscape” OR “integrated crop-livestock” OR “integrated crop-forest” OR “land sharing”) AND TITLE-ABS-KEY (“ richness” OR “ abundance” OR “species diversity” OR “functional diversity” OR “index”) AND TITLE-ABS-KEY (“crop yield” OR “crop production”) AND (LIMIT-TO (LANGUAGE, “English”)). We extracted the primary studies included in all relevant meta-analyses identified from the database search. In addition, we included a small number of peer-reviewed articles known to scientists consulted through the Sustainable Foods project and which were not retrieved by the search string or from previous meta-analyses. In total, 1590 articles with the potential to be included in the meta-analysis were identified (Fig. 1).Article screeningAll identified articles were screened at full-text level. We used the PICOC (Population, Intervention, Comparator, Outcomes, Context) framework to define the inclusion-exclusion criteria as described in Sánchez et al.19. These criteria required that, to be included: (i) the article presents a quantitative comparison of a diversified farming system (Intervention) compared to either a relatively simplified farming system (first Comparator) or to natural habitat (second Comparator), ii) the article reports quantitative outcomes for any terrestrial organism that is non-domesticated (Population), iii) the article provides the mean or median, variance and sample size for biodiversity outcomes, and outcome measures in comparator and intervention sites were collected using comparable sampling approaches (Outcome), iv) results are from primary field studies and not from experiments conducted in greenhouses or laboratories (Context).Diversified farming systems were defined as agricultural plots where: i) more than one plant species or variety is cultivated at multiple temporal and/or spatial scales, such as crop rotations, intercropping or agroforestry, or ii) semi-natural habitat such as hedgerows and flower strips is embedded into the system, or iii) crop production is integrated with livestock or fish production, such as aquaculture or integrated crop-livestock systems. Simplified farming systems were agricultural plots with less diversity than in eligible interventions, i.e., plots with relatively fewer plant species or varieties (usually monocultures), less semi-natural habitat embedded, or no mixed crop-animal production. Where natural habitat was used as a comparator, this was defined as habitat that is not actively used for human activities, such as primary and secondary forests, wetlands, unmanaged grasslands and shrublands.Suitable outcome metrics for biodiversity included any comparable quantified measure, such as richness, abundance, or Shannon’s diversity index. While studies only needed to report biodiversity outcomes to be considered for inclusion, we recorded harvested yield in all cases where this was reported and met our inclusion criteria. For yield outcomes to be included, the article must have provided means or medians, variance and sample sizes, and outcome measures at intervention and comparator sites must have been collected using comparable sampling approaches. Suitable outcome metrics for yields included the land equivalent ratio, weight of harvested produce per unit land area, or counts of harvested produce per standardized unit (e.g. grape bunch per plant, apples per branch). For comparisons comparing intercropped or agroforestry systems against simplified farming systems, the land equivalent ratio was prioritized as the outcome metric while other metrics were used only when the land equivalent ratio could not be calculated.In total, 237 (14.9%) of retrieved articles met our inclusion criteria (Fig. 1).Data extractionFrom each article that met our inclusion criteria, we extracted qualitative data on: the literature source (e.g. authors, publication year, title); crop type (common name, scientific name); agricultural system (e.g. intercropping, monoculture, agroforestry, integrated crop-livestock system, crop rotation, set aside); non-domesticated taxa sampled (common and scientific names); functional group of the non-domesticated taxa, if specified (e.g. pest, decomposer, predator); biodiversity outcome metric (e.g. species richness, abundance, Shannon’s diversity index); yield metric (e.g. kilogram per hectare, grams per plant, land equivalent ratio); sampling method used (e.g. transect, trap); pesticide use (yes or no, and kg/ha); fertilizer use (yes or no, and chemical fertiliser use yes or no); soil management (e.g. tillage, no tillage, slash and burn); landscape characteristics (e.g. % agricultural land use, climate); and study location (local name, country and geographic coordinates). Following initial data-entry, we classified several variables into categories to facilitate data exploration and analysis. This included categorizing crops by the Food and Agriculture Organisation of the United Nations commodity group, woodiness (e.g. tree, shrub, herb), and growth cycle (perennial, annual), and documenting the phylum, class, order and functional group of each non-domesticated taxon.We extracted quantitative data on: biodiversity outcome means or medians, variance and sample size; yield means or median, variance and sample size; farm size, if specified; length of time that the land has been in its current state, and; sampling duration (in days, from start to finish). Data on biodiversity outcomes and yield were extracted from figures using GetData Graph Digitizer 2.26 or WebPlotDigitizer v4.2. Where outcome values or units in an article were unclear or not provided, the corresponding author was contacted by email to request this information. If the author did not respond, the data entry was removed. We provide a dictionary of how the extracted data were recorded and coded in Dataset 2.Data were organized using R-4.0.0 (R-Core Team, 2013) such that each row contained a pair of biodiversity outcomes and, where provided, a pair of yield outcomes, for a single comparator-intervention pair. In total, 237 studies containing 4076 comparisons of biodiversity outcomes and 1214 comparisons of yield outcomes were retained for analysis (Fig. 1). More