Ecology

In many conservation projects, women are alone on all-male teams.Credit: Getty

My career in conservation spans more than 20 countries, and workplaces ranging from universities, governments and consultancies to community-based and global non-governmental organizations (NGOs). Currently, I work as the Asia-Pacific director of gender and equity at The Nature Conservancy, one of the largest global conservation NGOs: it has more than 4,000 staff members and is active in more than 80 countries. I am responsible for ensuring that all our endeavours across the Asia-Pacific to address biodiversity loss and the climate crisis are inclusive and equitable.My career has been incredibly diverse: from monitoring saltwater crocodiles (Crocodylus porosus) in northern Australia to working with women on gender-based violence in Papua New Guinea to speaking at international climate meetings. But one theme has remained a constant: gender-based discrimination, which not only holds women back, but holds the world back from addressing the crises of climate change and biodiversity loss.Discrimination is by no means an experience unique to me or just a few women. A review of 230 peer-reviewed articles1, of which I was the lead author, confirmed a sobering truth: women everywhere are excluded from decisions about conservation and natural resources, from small and remote communities in biodiversity hotspots to large conservation organizations themselves. In every country, and in almost every setting and organization, women are routinely disadvantaged in conservation just because they are women.
Collection: Fieldwork
Unconscious bias is normal and natural, and all of us have it: it is how our brains make sense of the world. But when unexamined bias or deliberate discrimination influences decision-making, perpetuates stereotypes and keeps women from reaching their potential, they create rippling negative impacts on society and the future of our planet. Whether gender stereotypes are overtly hostile (such as ‘women are too emotional to lead fieldwork’) or seemingly benign (‘women are naturally good at organizing and supporting the team’ or ‘we need a strong, decisive leader’ — that is, a man), they hold women back in their conservation careers.An uneven playing fieldConservation has historically been a male-dominated profession. Just 3–11% of wildlife rangers are women2, and only 11% of the top-publishing authors in conservation and ecology are women3. A strong masculine culture is often associated with the profession, which can intimidate women. Many women in the sector experience sexual harassment and anxiety about their personal safety — particularly when they are the only woman on a project, which is often the case.Furthermore, women usually pay a heavy price for calling out cultures that are not inclusive. From surveying conservation professionals, I found that nearly 20% of women fear reprisal when speaking out against bias4. Their fears are warranted; many are sidelined or branded as ‘difficult’ or ‘frustrating’ if they draw attention to discrimination or poor behaviour, or try to slow down the decision-making process if it is not inclusive.In my career, I have been told that I wouldn’t be considered for an exciting project because it would be too physically demanding, be unsafe for a woman to be alone in a remote setting or require too much time away from my young family. Decisions that are made on your behalf are infuriating — and can come at both a career cost and a financial cost. Conversely, I have been offered opportunities because I have a masculine, gender-neutral name, and the people in charge assumed that I was a man before they had met me. I was then met with surprise and scepticism when I turned up and they realized that ‘Robyn James’ is a woman. I have always held my own in these situations, but the constant pressure to prove I belonged was exhausting and came at a personal cost5,6.My experiences are those of someone who holds deep and unearned privilege: I am a white cis woman with sufficient income to support my family, and I can speak and write English (the primary language of science) well. These factors increase my opportunities to contribute. Many conservationists and scientists who are women do not have those privileges. Some are also discriminated against owing to racism in a world that favours whiteness, and those who live in places where the cost of education and health care is high, wages are low and basic services such as power and Internet are intermittent face further disadvantages.As an ally and sponsor for women in conservation and science, I am determined to leverage my position to change this. I’m focused on breaking down walls and smashing the glass ceiling for women across the sector.Here are a few ways I am using the power I have to make conservation and science more inclusive. Hopefully these ideas will help others to share their solutions or to be better allies to women.Women are needed as leadersWomen who are conservation and environmental-science graduate students or are at early career stages often tell me that they don’t often see women at senior levels7, and that leaders don’t make them feel included. I am part of an informal group of women in senior positions in conservation, representing several organizations, who attend events for undergraduates and early-career professionals. We aim to share our journeys and to be visible to women who are just starting out. We model diverse leadership styles to show alternatives to masculine ‘command and control’ leadership, which these women might have more often experienced.Women routinely undersell themselves and do not apply for promotions, so we actively encourage our younger peers to apply for positions and support them by providing feedback on CVs and sharing interview techniques, for example. I am also part of a formal mentoring and sponsorship programme to support women — especially those in the lower-income countries — to navigate and excel in systems that are not designed with their success in mind. We work through issues to do with self-esteem and confidence: some women have understandably taken biased attitudes on board, and do not realize that they are worthy of progressing in their careers. I work with them to help them to understand how incredible they really are.

Conservation scientist Robyn James works with women on the Solomon Islands.Credit: Madlyn Ero

At The Nature Conservancy, we have developed a network of more than 50 women who can share their experiences and challenges in a safe supportive environment. We ensure that we work with women to address practical challenges they encounter. These efforts range from dedicated sessions on how to address gender bias in their teams and workplaces, to working through examples of how to make progress on gender equity in the field of conservation, where speaking up might clash with cultural norms or put women at risk of retaliation.Making work more inclusiveMy research with The Nature Conservancy on gender and conservation science publishing has shown that women are vastly under-represented8: less than 2% of authors were women in lower-income countries. The organization subsequently enlisted an experienced, well-published conservation scientist to work with women across the Asia-Pacific and support them in the publishing process, from developing research ideas to submitting final publications. I ensure my own published research includes authors with diverse perspectives. For example, for the three publications that were part of my PhD research1,4,8, 86% (19) of the authors are women, of which 68% (13) are first-time authors, 47% (9) are women of colour and 5 (26%) are in lower-income countries. This demonstrates that intentional efforts make a difference.Even the wording of job descriptions can exclude women. Language inherently has gendered associations, so including words such as confident, decisive, strong and outspoken in job postings has been found to attract men and deter women from applying. Many of my colleagues have felt intimidated by the tone of conservation job advertisements, which seem to be written for men. At The Nature Conservancy, we check our job descriptions and organizational plans and strategies for gendered language using a gender decoder, a tool that assesses text for masculine-coded language that could unconsciously discourage women from applying or keep women from feeling engaged with a work programme or strategy. (You can see what the decoder finds in this article here).Wherever patriarchy is deeply entrenched, men are often favoured for higher education and technical training — and women miss out. Many conservation roles have standard and mandatory educational and technical qualifications, so women are often automatically excluded from even being able to apply for a role they could otherwise be suited for.Changes in the fieldMy leadership team and I have worked to address some of the systems and processes that might inadvertently disadvantage women. For example, in the Solomon Islands, an archipelago in the south Pacific, marine conservation and research roles that require a scuba licence immediately exclude many women in the country from applying, because almost none have access to scuba training given that men are generally prioritized for training and development opportunities. In most places where The Nature Conservancy works, our employees will only ever need a mask and snorkel. Therefore, a small change in the job description means that many more women can apply. Adjusting our standard mandatory requirements has led to some fantastic women successfully applying and becoming high-performing members of our conservation teams. We now carefully omit any technical requirements that are not essential to a role or that can be easily obtained through on-the-job training.We ensure women are included in the teams that develop and implement workplace health and safety protocols, and have broadened our definition of workplace health and safety to include psychological safety and protection from gender-based violence (including sexual harassment). We worked with experienced professionals in this area to develop organization-wide guidance for our staff and partners. We also develop tailored plans depending on the country we are in to specifically address safety for women. For example, in Papua New Guinea, some women on our teams made it clear that it was unsafe for them to travel home after dark on public transport. In this country, more than two-thirds of women have experienced violence. We commissioned an official work vehicle to take staff home after hours.We ensure women have basic field equipment that is suitable for them. We provide women’s sizes in all protective gear: everything from gloves for fire protection to life jackets. This is organized before a trip or fieldwork takes place.We are also implementing protocols to ensure our conservation teams are diverse and that women are not on their own among all-male research groups. This is not only safer for women, but has repeatedly led to better conservation outcomes: the women notice things that have previously been missed. For example, in Mongolia, women in herding communities are often unable to attend important research meetings about grassland management because there is no access to toilets or because training sessions are held at times when they have caring obligations. The women on the project noticed this, and worked with the herders to ensure the infrastructure was adequate and the schedule was adjusted so that they could participate and share their unique perspectives on improving grassland conservation.Women benefit from more women being in the sector. From early-career to senior positions, representation matters. But this alone is not enough. Historically male-dominated sectors, such as conservation, that now have a relatively equal gender balance in undergraduate courses need to push for cultural change as well. This is the most difficult part of my role: challenging male leaders and systems that are not designed for women to succeed.Although we need to listen and respond to the needs of women, this is never something that should be the burden of women alone to fix. Strong leadership across our sector that prioritizes gender equity and inclusion in conservation, and provides resources to achieve it, is crucial.Women will thrive in conservation science if we keep pushing to move from equality to inclusion. Inclusion means not only that women are present, but that workplaces and programmes are designed and tailored with and for them. We shouldn’t be surprised or blame women when they don’t succeed in conservation and science workplaces and programmes that are still not actively including them. Women make up more than 50% of the population; we need to have a say in the future of our planet! More

Vitamin B12 biosynthesis potential of different bacteriaB vitamins play a key role in complex marine microbial interactions as they are obligatory cofactors in various essential metabolic reactions in all living organism [13, 14, 39,40,41]. An exciting fact about B12 is that genes for synthesis of this complex cofactor have never made the transition to the eukaryotic kingdom, although it is required by both prokaryotes and eukaryotes. De novo synthesis is restricted to a minor fraction of bacteria and archaea, thus, suggesting that the ability to synthesise B12 is disproportionate to its demand in nature [1, 4]. This phenomenon can be observed in various habitats, for example in the soil microbiome, where the proportion of B12 producers is less than one tenth [8]. Similar findings have been shown for the microbiome on human skin, where only 1% of the core species are predicted to produce B12 de novo, while 39 % of the species are predicted to use B12 for metabolism [42]. In order to adequately answer this fundamental question regarding the balance between B12 availability and consumption, we should aim to better understand the synthesis potential of individual prototrophic prokaryotes.Here we present intra- and extracellular B12 concentrations of various B12 prototrophic, alphaproteobacterial strains. The concentration of intracellular B12 differs widely between the various heterotrophic bacteria examined. Converted, B12 molecules detected per cell ranged between 664 to 26,619 in the analysed bacterial cultures, including B12-provider and B12-retainer. Such strong variation in intracellular B12 concentrations have already been shown for a number of other prokaryotes, including Archaea, heterotrophic bacteria, and cyanobacteria [11, 34]. Also, in these studies, the detected intracellular B12 values differed up to three orders of magnitude and showed values similar to the ones we detected. Whether factors such as cell size, which we did not consider in our analysis, or the exact growth phase in which we took the samples had an influence on the strong variation cannot be clarified here. It is quite conceivable that different B12 requirements of the individual cells or different regulatory mechanisms of B12 synthesis played a decisive role for the intracellular B12 concentrations. Nevertheless, we can conclude that not only the genetic B12 biosynthetic potential within a microbial community is decisive, but rather which prokaryote is actually present is crucial for the availability of B12.The extracellular concentrations of B12 detected in M. algicola and P. inhibens were about 8 and 256 times lower than respective intracellular levels. For example, M. algicola secreted about 936 B12 molecules per cell, which was roughly 85 times more as detected for P. inhibens. On the basis of the detected B12 demand of T. pseudonana determined by the bioassay, we can calculate that the eukaryote requires roughly 135,000 B12 molecules per cell, if we base the limitation of cell number solely on B12 availability. Thus, it would take about 144 living M. algicola cells that release B12 to cover the requirements for the growth of one T. pseudonana cell. In fact, the bacterial cell numbers in the stationary phase of the B12-provider-diatom co-cultures were at least 110 times higher than the cell numbers of T. pseudonana. These calculations are all based on ideal laboratory conditions, with sufficient supply of inorganic nutrients and organic substrates and may differ in natural environments where viral infections or sloppy feeding can lead to cell disruption and subsequent release of intracellular B12 [43, 44]. Also, B12 requirement of T. pseudonana cells can vary under different growth conditions. For example, it has been shown that growth of T. pseudonana even with 1 pM of B12 can result in a significant change in the metabolite pool of the diatom, which in turn may have implications for the interaction with bacteria [45]. Nevertheless, our data give a first approximate insight into the interplay between B12-producers and -consumers in the world of microorganisms.Bacterial effects on the growth of T. pseudonana
Growth characteristics of T. pseudonana in co-culture show not only the obligatory provision of B12 by bacteria but also other bacterial factors that influence growth. For example, we observed that Sulfitobacter litoralis, a representative of the Roseobacter group, showed inhibitory behaviour towards the diatom. Other studies have shown that Roseobacter group isolates can produce inhibitory substances, roseobacticides, which can suppress the growth of eukaryotic phototrophs [46]. The provision of B12 leads to a promotion in growth and, at the same time, growth of the diatom is inhibited. One reason for the different growth characteristics of the diatoms observed in co-culture with different bacteria could be the adaptation to different habitats where the bacterial isolates naturally occur.In contrast to these observations, Celeribacter baekdonensis DSM 27375 significantly stimulated the growth of T. pseudonana. Even though C. baekdonensis did not provide B12 despite being synthesized, its presence in co-culture with B12 addition significantly increased the growth rate and growth yield of T. pseudonana compared to the positive control of the corresponding experimental run. In previous bacterial-diatom co-culture experiments, it has been shown that the excretion of cyclic peptides, diketopiperazines, by a bacterium, significantly increased diatom cell numbers [47]. Another plausible scenario is the synthesis and excretion of indoleacetic acid (IAA) by C. baekdonensis, which is a growth-promoting hormone for diatoms [48]. A similar effect is also conceivable for C. baekdonensis and would be exciting to explore in greater depth.A finding that appears to be overlooked in the context of our actual question is the fact that the expected bacterial cell death does not necessarily lead to the release of B12, which would promote the growth of T. pseudonana, and thus promote the interaction. Even after up to six weeks in co-culture, we cannot observe significant growth of T. pseudonana despite the presence of a bacterial B12 prototroph. This fact highlights the importance of cell lysis mechanisms in nature, for example caused by viral infections or sloppy feeding. Already today, these two natural processes are considered to play a significant role in the turnover of dissolved organic matter [44, 49,50,51] and are likely to also have a decisive influence on the release of B-vitamins in marine ecosystems [23]. Additionally, T. pseudonana is known to secret a B12 binding protein under B12 deficient conditions that has an affinity constant of 2 × 1011 M−1. This protein might help them to acquire B12 from the surroundings, when it is released through bacterial cell lysis mechanism [52]. Other phytoplankton might also have a similar strategy to scavenge B12 from the environment. When intracellular B12 is considered as a reservoir for other B12 auxotrophic microorganisms, then, for example, already 19 M. algicola cells would be sufficient to enable the growth of one T. pseudonana cell.The vital cofactor B12 is not shared by all prototrophic bacteriaAbout half of the marine phytoplankton species are B12 auxotrophs and rely on prototrophic prokaryotes to obtain this essential vitamin [1, 53]. Several co-culture experiments have confirmed that individual marine bacterial isolates, mainly Alphaproteobacteria, enable phytoplankton species to overcome their auxotrophy by providing the essential cofactor [13,14,15,16, 27, 28]. In our study we hypothesised that not all B12 prototrophs share B12 with other microorganisms and to prove that we performed individual co-culture experiments between T. pseudonana and 33 B12 prototrophic bacteria. B12 prototrophy of the bacterial isolates was confirmed by their genetic ability to synthesize B12 (Supplementary table S2) and their ability to grow in B12-free medium. The results of our study support this hypothesis, as we were able to identify one group of bacteria that enables growth of T. pseudonana by the supply of the essential cofactor, B12-providers. On the other hand, we also identified a second group of B12 prototrophic bacteria that did not support the growth of the diatom, the B12-retainers. Moreover, while categorizing them into B12-providers and B12-retainers, we observed that there are species within one genus, such as P. inhibens and P. galleciensis, in which one is a B12-provider and the other is a B12-retainer, respectively, although both of them possess the necessary genes for B12 biosynthesis. Yet, the question remains why some bacteria share the cofactor, and others, despite an obligatory interaction enforced in co-culture, do not. In the following, we describe and discuss three scenarios that we consider plausible, whereby not only one scenario has to be correct, but rather all three can take place in the B12-retainer strains that we have identified.First, biosynthesis of metabolites, such as the energetically costly B12 cofactor, are subject to intracellular regulation. Transcriptional regulation of the B12 biosynthesis pathway determines whether, and in what quantity B12 is synthesised in the cell. For example, sigma factors can alter the specificity of an RNA polymerase for a particular promoter, so that gene expression is enhanced or reduced [54]. In the case of the bacterial isolate Propionibacterium strain UF1, the riboswitch cbiMCbl was identified to regulate the gene expression of the cobA operon and thus controls B12 biosynthesis [55]. It is also known that sufficient availability of B12 can repress B12 biosynthesis gene expression in bacteria [56, 57]. In gram-negative proteobacteria as well as in cyanobacteria, for example, cobalamin (pseudocobalamin, in case of some bacteria) biosynthesis and B12 transport genes are regulated by inhibition of translation initiation, whereas in some gram-positive bacteria gene regulation proceeds by transcriptional antitermination [58]. The mechanisms described above are likely to also occur in the bacterial isolates that we tested. The large difference between the detected intracellular B12 concentrations could therefore be due to differences in gene regulation of the different bacteria and may also have had an influence on the release of B12 in the co-culture with T. pseudonana.Second, cobalamin, which we referred to here as B12 for simplicity, belongs to a group of B12-like metabolites, called cobamides. Each cobamide differs in the lower ligand attached. For example, the common cobamide, cobalamin, which is bioavailable to most microorganisms, carries 5,6-dimethylbenzimidazol (DMB) as its lower ligand, whereas pseudocobalamin synthesised by cyanobacteria in high concentrations in the ocean and being less or not bioavailable to most microorganisms, has adenine attached as its lower ligand [11, 41, 59, 60]. In general, the lower ligands of cobamides can be divided into benzimidazoles, purines, and phenols, and more than a dozen cobamides and cobamide-analogs have already been discovered [61]. However, research into the synthesis and actual diversity of cobamides, especially in marine bacteria and archaea, is still in its infancy. In our study, we were unable to detect intracellular B12 in four out of eight bacterial B12-retainer strains, although the cell counts at the time of sampling should have been sufficient for its detection. However, as is generally the case, our LC-MS analysis only targets cobalamin (B12) with its different upper ligands (adenosyl-, cyano-, methyl-, and hydroxy-cobalamin). Therefore, we cannot exclude the possibility that the here studied bacteria synthesise different cobamides, which are possibly not or less bioavailable to T. pseudonana, and not covered by our analytical measurement method. This speculation was supported by the fact that one of these four B12- retainer strains, Sulfitobacter sp. DFL-23, does not possess the DMB synthesis gene bluB and there was no intracellular B12 detected in this strain (Supplementary table S2 and Table 2). Again, it is difficult to explain this phenomenon solely depending on the presence of annotated DMB synthesis gene, as for Loktanella salsilacus DSM 16199 no bluB gene was annotated, still we detected intracellular B12 in this strain using our detection method (Supplementary table S2 and Table 2).Third, the bacteria we have identified as B12-retainer simply may not have actively released the synthesised B12 into their environment. Regardless of the importance of B12 for the vast majority of living organisms on our planet, its excretion mechanisms are to our knowledge still largely unknown. Its size of more than 1,350 Dalton does not allow sufficient diffusion through the cell membrane, which would enable microbial interactions [32]. Thus, it is likely that an unknown mechanism is required for its release. This assumption is further supported by the fact that we were able to detect intracellular B12 in four of the eight B12-retainer strains and at concentrations comparable to those detected in the B12-provider strains. In addition, we could detect intracellular B12 in P. xiamenensis, but none in its exometabolome. On the other hand, presence of extracellular B12 was detected in the exometabolome of both the provider strains examined, M. algicola and P. inhibens. Our findings show that not all bacteria share the pivotal cofactor with their environment, which has an impact on our current understanding of the marine B12 cycle and presumably in other ecosystems as well. The active exchange of B12 and thus microbial interaction plays a much smaller role than previously assumed for a relatively large number of bacteria. Consequently, for some of the B12 prototrophic bacteria within a community, it is likely that the cofactor is only released upon cell lysis.B12 production in the marine ecosystem and ecological implicationsLooking at the original source of B12 in nature, namely prototrophic bacteria and archaea, the bacteria studied here show pronounced differences between the biosynthetic potentials of the cofactors and the ability to share them with their environment. Thus, the natural source of vitamin B12 within a given ecosystem does not primarily depend on the ratio of prototrophic bacteria, but even more crucially on how much of the cofactor is synthesised by the prototrophic prokaryotes within an ecosystem and is actively released. The fact that some bacteria do not voluntarily share B12 with ambient microorganisms, significantly increases the importance of processes, such as sloppy feeding by zooplankton or virus infections [44, 49,50,51], for the release of vitamins in the marine and likely also other ecosystems.Our results also contribute to the controversially discussed question of whether B12 prototrophic bacteria live in symbiosis with phototrophic microorganisms [13, 30]. Despite numerous co-cultivation experiments demonstrating the obligatory provision of B12 by individual bacteria to phototrophic microorganisms, the decisive question of the mechanism of provision has so far been overlooked [13,14,15,16, 27, 28]. In our view, however, this question is crucial when assessing whether a symbiotic interaction is taking place. Our results support the hypothesis that a bacterial mechanism for the active release is likely to exist, as our experiments distinguish between B12-provider and B12-retainer within prototrophic bacteria. Looking at the ecological niches and the isolation sites of the two respective groups, differences can be identified. Most B12-provider strains were isolated from or discovered in association with eukaryotic microorganisms, whereas most B12-retainer strains were isolated as free-living in the ocean (Supplementary table S4). Moreover, six of the tested bacterial strains were isolated from dinoflagellates and five of them were B12-provider. Since we used a diatom as a B12 auxotrophic organism in our study, it would also be interesting to know if these B12-provider strains also provide B12 to other phytoplankton, such as dinoflagellates. Also, in this study we only studied bacteria from the alphaproteobacteria class, since a large share of them are known to be B12 prototrophs and abundant in the marine ecosystem. For future studies, it would be interesting to see if a similar pattern of B12 provisioning can be observed in bacteria from other classes. Our results indicate that the B12 prototrophy of a bacterium does not necessarily indicate a mutualistic interaction with other auxotrophic microorganisms. However, the bacterial group of B12-provider in particular seems to favour living in close proximity to other microorganisms, which is why the exchange of B12 for e.g. organic compounds can establish itself as a distinct symbiotic interaction between individual microorganisms. More

Synthetic data for Fig. 1To provide examples of the proposed two hypotheses, i.e., species-response hypothesis and community structure hypothesis, for Fig. 1, we generated synthetic data assuming bivariate lognormal distributions of species relative woody productivity pi and species standing biomass Bi, where i for species identity, with log-log linear, (or power-law) correlations, ln pi = k + b ln Bi, as in left-hand panels of Fig. 1. The slope (scaling exponent) b is common at –0.15, and the constant k = –3.4 and –3.8 for tropical and temperate forests respectively for species response hypothesis (Fig. 1a), whereas k = –3.6 for both ‘tropical’ and ‘temperate’ forests for the community structure hypothesis (Fig. 1b). Mean ln Bi are –0.6 for two forests in Fig. 1a, while they are –1.0 and –0.2 for tropical and temperate forest respectively in Fig. 1b, Standard deviations of ln Bi and ln pi are 2.0 and 0.65 respectively for all forests, except those in tropical forest in Fig. 1b are 1.6 and 0.6, respectively. In the left-hand panels, the Bi axis ranges 0.005–500 (Mg C ha–1), and the pi axis ranges 0.001–0.5 (yr–1). In the right-hand panels, the axis for B = Σi Bi ranges 50–500 (Mg C ha–1) and the axis for P = Σi pi Bi ranges 0.5–20 (Mg C ha–1 yr–1).Forest plot dataWe selected 60 forest plots located in old-growth forests along the climatic gradient of insular eastern Asia, located on Java (3 plots), Kalimantan (5 plots), Peninsular Malaysia (2 plots), Taiwan (6 plots), and the Japanese archipelago (44 plots), ranging from 6.8°S to 44.4°N latitude and from 20 to 1,880 m in elevation (Supplementary Fig. 1, Supplementary Data 1). We collected climate data for all the plots for the period 1981–2010 from CHELSA version 2.139; these are the period-average annual and monthly ground surface mean temperature, precipitation, and potential evapotranspiration. The potential evapotranspiration was estimated by Hargreaves-Samani equation40 based on monthly data of these climatic variables. Supplementary Data 2 presents mean annual temperature (MAT, °C), annual precipitation (AP, mm yr–1), annual potential evapotranspiration (PET, mm yr–1), monthly-data-based Thornthwaite moisture index (TMI) and the climatic types defined by TMI26. The target region is in Asian monsoon climate41,42, and moist forest ecosystems predominate from tropics in Southeast Asia to sub-boreal biomes in northern Japan. Across 60 plots, MAT ranges from 2.0 °C to 26.6 °C, AP-PET ranges from 58.5 to 5049 mm yr–1, and plots are classified as “perhumid” or “humid” by TMI (Supplementary Data 2); the smallest TMI for the plot in cloud forest on Hahajima Island, oceanic Ogasawara Islands, where AP-PET was +217 mm yr–1 (against +58.5 by CHELSA39) based on the weather station records on the island. AP-PET sowed no correlation with MAT or with any forest structural or dynamic variable, in contrast to MAT exhibiting significant correlations to all forest variables (Supplementary Fig. 5). We therefore mainly employ MAT to quantify climatic dependence of the 60 plots. According to bioclimatic classification of the region43,44, we define forest biomes into tropical (MAT ≥ 24 °C), subtropical (20–24 °C), warm-temperate (12–20 °C), cool-temperate (5–12 °C) and sub-boreal or subalpine ( More

Liang, J. et al. Positive biodiversity-productivity relationship predominant in global forests. Science 354, aaf8957 (2016).Article 
PubMed 

Google Scholar 
Huang, Y. et al. Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362, 80–83 (2018).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Luo, S. et al. Community‐wide trait means and variations affect biomass in a biodiversity experiment with tree seedlings. Oikos 129, 799–810 (2020).Article 

Google Scholar 
Pérez-Harguindeguy, N. et al. New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 61, 167–234 (2013).Article 

Google Scholar 
Bergmann, J. et al. The fungal collaboration gradient dominates the root economics space in plants. Sci. Adv. 6, 1–10 (2020).Article 

Google Scholar 
Freschet, G. T. et al. Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs. N. Phytol. 232, 1123–1158 (2021).Article 

Google Scholar 
Zhong, Y. et al. Arbuscular mycorrhizal trees influence the latitudinal beta-diversity gradient of tree communities in forests worldwide. Nat. Commun. 12, 1–12 (2021).Article 
ADS 

Google Scholar 
Carteron, A., Vellend, M. & Laliberté, E. Mycorrhizal dominance reduces local tree species diversity across US forests. Nat. Ecol. Evol. 6, 370–374 (2022).Article 
PubMed 

Google Scholar 
Phillips, R. P., Brzostek, E. & Midgley, M. G. The mycorrhizal‐associated nutrient economy: a new framework for predicting carbon–nutrient couplings in temperate forests. N. Phytol. 199, 41–51 (2013).Article 
CAS 

Google Scholar 
Averill, C., Turner, B. L. & Finzi, A. C. Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage. Nature 505, 543–545 (2014).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Craig, M. E. et al. Tree mycorrhizal type predicts within‐site variability in the storage and distribution of soil organic matter. Glob. Chang. Biol. 24, 3317–3330 (2018).Article 
ADS 
PubMed 

Google Scholar 
van der Heijden, M. G. A. et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998).Article 
ADS 

Google Scholar 
Klironomos, J. N., McCune, J., Hart, M. & Neville, J. The influence of arbuscular mycorrhizae on the relationship between plant diversity and productivity. Ecol. Lett. 3, 137–141 (2000).Article 

Google Scholar 
Wagg, C., Jansa, J., Stadler, M., Schmid, B. & Van Der Heijden, M. G. A. Mycorrhizal fungal identity and diversity relaxes plant-plant competition. Ecology 92, 1303–1313 (2011).Article 
PubMed 

Google Scholar 
Luo, S., Schmid, B., De Deyn, G. B. & Yu, S. Soil microbes promote complementarity effects among co‐existing trees through soil nitrogen partitioning. Funct. Ecol. 32, 1879–1889 (2018).Article 

Google Scholar 
Ferlian, O. et al. Mycorrhiza in tree diversity–ecosystem function relationships: conceptual framework and experimental implementation. Ecosphere 9, e02226 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Tedersoo, L. & Bahram, M. Mycorrhizal types differ in ecophysiology and alter plant nutrition and soil processes. Biol. Rev. 94, 1857–1880 (2019).Article 
PubMed 

Google Scholar 
Rineau, F. et al. The ectomycorrhizal fungus Paxillus involutus converts organic matter in plant litter using a trimmed brown-rot mechanism involving Fenton chemistry. Environ. Microbiol. 14, 1477–1487 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lindahl, B. D. & Tunlid, A. Ectomycorrhizal fungi – potential organic matter decomposers, yet not saprotrophs. N. Phytol. 205, 1443–1447 (2015).Article 
CAS 

Google Scholar 
Hodge, A. Arbuscular mycorrhizal fungi influence decomposition of, but not plant nutrient capture from, glycine patches in soil. N. Phytol. 151, 725–734 (2001).Article 
CAS 

Google Scholar 
Read, D. J. & Perez-Moreno, J. Mycorrhizas and nutrient cycling in ecosystems – A journey towards relevance? N. Phytol. 157, 475–492 (2003).Article 
CAS 

Google Scholar 
Toju, H., Kishida, O., Katayama, N. & Takagi, K. Networks depicting the fine-scale co-occurrences of fungi in soil horizons. PLoS ONE 11, 1–18 (2016).Article 

Google Scholar 
Taylor, D. L. et al. A first comprehensive census of fungi in soil reveals both hyperdiversity and fine-scale niche partitioning. Ecol. Monogr. 84, 3–20 (2014).Article 

Google Scholar 
Chen, W. et al. Root morphology and mycorrhizal symbioses together shape nutrient foraging strategies of temperate trees. Proc. Natl Acad. Sci. USA 113, 8741–8746 (2016).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Liu, X. et al. Partitioning of soil phosphorus among arbuscular and ectomycorrhizal trees in tropical and subtropical forests. Ecol. Lett. 21, 713–723 (2018).Article 
PubMed 

Google Scholar 
Averill, C., Bhatnagar, J. M., Dietze, M. C., Pearse, W. D. & Kivlin, S. N. Global imprint of mycorrhizal fungi on whole-plant nutrient economics. Proc. Natl Acad. Sci. USA 116, 23163–23168 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Dietrich, P. et al. Tree diversity effects on productivity depend on mycorrhizae and life strategies in a temperate forest experiment. Ecology 104, e3896 https://doi.org/10.1002/ecy.3896 (2022).Averill, C., Dietze, M. C. & Bhatnagar, J. M. Continental-scale nitrogen pollution is shifting forest mycorrhizal associations and soil carbon stocks. Glob. Chang. Biol. 24, 4544–4553 (2018).Article 
ADS 
PubMed 

Google Scholar 
Jo, I., Fei, S., Oswalt, C. M., Domke, G. M. & Phillips, R. P. Shifts in dominant tree mycorrhizal associations in response to anthropogenic impacts. Sci. Adv. 5, eaav6358, (2019).Fei, S. et al. Impacts of climate on the biodiversity-productivity relationship in natural forests. Nat. Commun. 9, 5436 (2018).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Bongers, F. J. et al. Functional diversity effects on productivity increase with age in a forest biodiversity experiment. Nat. Ecol. Evol. 5, 1594–1603 (2021).Article 
PubMed 

Google Scholar 
Schoener, T. W. Resource partitioning in ecological communities. Science 185, 27–39 (1974).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Tilman, D., Lehman, C. L. & Thomson, K. T. Plant diversity and ecosystem productivity: theoretical considerations. Proc. Natl Acad. Sci. USA 94, 1857–1861 (1997).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Schwilk, D. W. & Ackerly, D. D. Limiting similarity and functional diversity along environmental gradients. Ecol. Lett. 8, 272–281 (2005).Article 

Google Scholar 
Wagg, C., Jansa, J., Schmid, B. & van der Heijden, M. G. A. Belowground biodiversity effects of plant symbionts support aboveground productivity. Ecol. Lett. 14, 1001–1009 (2011).Article 
PubMed 

Google Scholar 
Agerer, R. Exploration types of ectomycorrhizae: a proposal to classify ectomycorrhizal mycelial systems according to their patterns of differentiation and putative ecological importance. Mycorrhiza 11, 107–114 (2001).Article 

Google Scholar 
Cheng, L. et al. Mycorrhizal fungi and roots are complementary in foraging within nutrient patches. Ecology 97, 2815–2823 (2016).Article 
PubMed 

Google Scholar 
Wambsganss, J. et al. Tree species mixing causes a shift in fine-root soil exploitation strategies across European forests. Funct. Ecol. 35, 1886–1902 (2021).Article 
CAS 

Google Scholar 
Gerz, M., Guillermo Bueno, C., Ozinga, W. A., Zobel, M. & Moora, M. Niche differentiation and expansion of plant species are associated with mycorrhizal symbiosis. J. Ecol. 106, 254–264 (2018).Article 
CAS 

Google Scholar 
Niklaus, P. A., Baruffol, M., He, J. S., Ma, K. & Schmid, B. Can niche plasticity promote biodiversity–productivity relationships through increased complementarity? Ecology 98, 1104–1116 (2017).Article 
PubMed 

Google Scholar 
Barry, K. E. et al. The future of complementarity: disentangling causes from consequences. Trends Ecol. Evol. 34, 167–180 (2019).Article 
PubMed 

Google Scholar 
Jacobs, L. M., Sulman, B. N., Brzostek, E. R., Feighery, J. J. & Phillips, R. P. Interactions among decaying leaf litter, root litter and soil organic matter vary with mycorrhizal type. J. Ecol. 106, 502–513 (2018).Article 
CAS 

Google Scholar 
Midgley, M. G., Brzostek, E. & Phillips, R. P. Decay rates of leaf litters from arbuscular mycorrhizal trees are more sensitive to soil effects than litters from ectomycorrhizal trees. J. Ecol. 103, 1454–1463 (2015).Article 

Google Scholar 
Kumar, A., Phillips, R. P., Scheibe, A., Klink, S. & Pausch, J. Organic matter priming by invasive plants depends on dominant mycorrhizal association. Soil Biol. Biochem. 140, 107645 (2020).Article 
CAS 

Google Scholar 
Tedersoo, L., Bahram, M. & Zobel, M. How mycorrhizal associations drive plant population and community biology. Science 367, eaba1223 (2020).Article 
CAS 
PubMed 

Google Scholar 
Kitajima, K. & Poorter, L. Functional basis for resource niche partitioning by tropical trees. Trop. For. community Ecol. 1936, 160–181 (2008).MacArthur, R. H. Patterns of species diverstiy. Biol. Rev. 40, 510–533 (1965).Article 

Google Scholar 
Pellissier, V., Barnagaud, J. Y., Kissling, W. D., Şekercioğlu, Ç. & Svenning, J. C. Niche packing and expansion account for species richness–productivity relationships in global bird assemblages. Glob. Ecol. Biogeogr. 27, 604–615 (2018).Article 

Google Scholar 
Huang, Y. et al. Effects of enemy exclusion on biodiversity–productivity relationships in a subtropical forest experiment. J. Ecol. 110, 2167–2178. https://doi.org/10.1111/1365-2745.13940 (2022).Tilman, D. Community invasibility, recruitment limitation, and grassland biodiversity. Ecology 78, 81–92 (1997).Article 

Google Scholar 
Feng, Y. et al. Multispecies forest plantations outyield monocultures across a broad range of conditions. Science 376, 865–868 (2022).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Harper, J. L. Population biology of plants. (1977).Ewel, J. J. Designing agricultural ecosystems for the humid tropics. Annu. Rev. Ecol. Syst. 17, 245–271 (1986).Article 

Google Scholar 
Grossiord, C. Having the right neighbors: how tree species diversity modulates drought impacts on forests. N. Phytol. 228, 42–49 (2020).Article 

Google Scholar 
Allen, M. F. Mycorrhizal fungi: highways for water and nutrients in arid soils. Vadose Zo. J. 6, 291–297 (2007).Article 

Google Scholar 
Brzostek, E. R. et al. Chronic water stress reduces tree growth and the carbon sink of deciduous hardwood forests. Glob. Chang. Biol. 20, 2531–2539 (2014).Article 
ADS 
PubMed 

Google Scholar 
Liese, R., Lübbe, T., Albers, N. W. & Meier, I. C. The mycorrhizal type governs root exudation and nitrogen uptake of temperate tree species. Tree Physiol. 38, 83–95 (2018).Article 
CAS 
PubMed 

Google Scholar 
Steidinger, B. S. et al. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature 569, 404–408 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Linton, M. J., Sperry, J. S. & Williams, D. G. Limits to water transport in Juniperus osteosperma and Pinus edulis: Implications for drought tolerance and regulation of transpiration. Funct. Ecol. 12, 906–911 (1998).Article 

Google Scholar 
Johnson, D. M. et al. Co-occurring woody species have diverse hydraulic strategies and mortality rates during an extreme drought. Plant. Cell Environ. 41, 576–588 (2018).Article 
CAS 
PubMed 

Google Scholar 
Lin, G. et al. Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry. Glob. Ecol. Biogeogr. 31, 168–182 (2022).Article 

Google Scholar 
Read, D. J. Mycorrhizas in ecosystems. Experientia 47, 376–391 (1991).Article 

Google Scholar 
Hobbie, S. E. Plant species effects on nutrient cycling: revisiting litter feedbacks. Trends Ecol. Evol. 30, 357–363 (2015).Article 
PubMed 

Google Scholar 
De Schrijver, A. et al. Tree species traits cause divergence in soil acidification during four decades of postagricultural forest development. Glob. Chang. Biol. 18, 1127–1140 (2012).Article 
ADS 

Google Scholar 
Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Braghiere, R. K. et al. Modeling global carbon costs of plant nitrogen and phosphorus acquisition. J. Adv. Model. Earth Syst. 14, 1–23 (2022).Article 

Google Scholar 
Eisenhauer, N. et al. Biotic interactions as mediators of context-dependent biodiversity-ecosystem functioning relationships. Res. Ideas Outcomes 8, e85873 (2022).Article 

Google Scholar 
Fisher, J. B. et al. Tree-mycorrhizal associations detected remotely from canopy spectral properties. Glob. Chang. Biol. 22, 2596–2607 (2016).Article 
ADS 
PubMed 

Google Scholar 
Soudzilovskaia, N. A. et al. Global mycorrhizal plant distribution linked to terrestrial carbon stocks. Nat. Commun. 10, 1–10 (2019).Article 
CAS 

Google Scholar 
Burrill, E. A. et al. The forest inventory and analysis database. USDA . Serv. 2, 1026 (2015).
Google Scholar 
Chao, A., Chiu, C.-H. & Jost, L. Unifying species diversity, phylogenetic diversity, functional diversity, and related similarity and differentiation measures through hill numbers. Annu. Rev. Ecol. Evol. Syst. 45, 297–324 (2014).Article 

Google Scholar 
Cleland, D. T. et al. Ecological subregions: Sections and subsections for the conterminous United States. Gen. Tech. Rep. WO-76D (2007).Soudzilovskaia, N. A. et al. FungalRoot: global online database of plant mycorrhizal associations. N. Phytol. 227, 955–966 (2020).Article 

Google Scholar 
Gallion, J. et al. Indiana DNR State Forest Properties Report of Continuous Forest Inventory (CFI) Summary of years 2015–2019. 1–25 (2020).Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30, 609–628 (2007).Article 

Google Scholar 
Craven, D. et al. A cross-scale assessment of productivity–diversity relationships. Glob. Ecol. Biogeogr. 29, 1940–1955 (2020).Article 

Google Scholar 
Paquette, A. & Messier, C. The effect of biodiversity on tree productivity: from temperate to boreal forests. Glob. Ecol. Biogeogr. 20, 170–180 (2011).Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ (2020).Dowle, M. & Srinivasan, A. data.table: Extension of ‘data.frame‘. R package version 1.14.2 (2021).Wickham, H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plots. R package version 0.4.0 (2020).Dunnington, D. ggspatial: Spatial Data Framework for ggplot2. R package version 1.1.5 (2021).Robert, J. Hijmans. raster: Geographic Data Analysis and Modeling. R package version 3.5-2 (2021).Wickham, H., François, R., Henry, L. & Müller, K. dplyr: A Grammar of Data Manipulation. R package version 1.0.8 (2022).Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
Lefcheck, J. S. piecewiseSEM: piecewise structural equation modeling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

Google Scholar 
Luo, S. et al. High productivity in forests with mixed mycorrhizal strategies. Figshare https://doi.org/10.6084/m9.figshare.22060238. (2023). More

Di Lorenzo, E. & Mantua, N. Multi-year persistence of the 2014/15 North Pacific marine heatwave. Nat. Clim. Change 6, 1042–1047 (2016).Article 

Google Scholar 
Bond, N. A., Cronin, M. F., Freeland, H. & Mantua, N. Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophys. Res. Lett. 42, 3414–3420 (2015).Article 

Google Scholar 
Blunden, J. & Arndt, D. S. State of the Climate in 2015. Bull. Am. Meteorol. Soc. 97, s1–s275 (2016).Article 

Google Scholar 
Santoso, A., Mcphaden, M. J. & Cai, W. The Defining Characteristics of ENSO Extremes and the Strong 2015/2016 El Niño. Rev. Geophys. 55, 1079–1129 (2017).Article 

Google Scholar 
Amaya, D. J., Miller, A. J., Xie, S.-P. & Kosaka, Y. Physical drivers of the summer 2019 North Pacific marine heatwave. Nat. Commun. 11. https://doi.org/10.1038/s41467-020-15820-w (2020).Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under global warming. Nature 560, 360–364 (2018).Laufkötter, C., Zscheischler, J. & Frölicher, T. L. High-impact marine heatwaves attributable to human-induced global warming. Science 369, 1621–1625 (2020).Article 
PubMed 

Google Scholar 
Piatt, J. F. et al. Extreme mortality and reproductive failure of common murres resulting from the northeast Pacific marine heatwave of 2014-2016. PLOS ONE 15, 1–32 (2020).Article 

Google Scholar 
Savage, K. Alaska and British Columbia large whale unusual mortality event summary report. NOAA Affiliate Protected Resources Division, NOAA Fisheries Juneau, AK. https://repository.library.noaa.gov/view/noaa/17715 (2017).Cavole, L. M. et al. Biological Impacts of the 2013-2015 Warm-Water Anomaly in the Northeast Pacific: Winners, Losers, and the Future. Oceanography 29, 273–285 (2016).Article 

Google Scholar 
Barbeaux, S. et al. Chapter 2: assessment of the pacific cod stock in the Gulf of Alaska. North Pacific Fish Manag. Counc. Gulf Alaska Stock Assess. Fish Eval. Rep. 140. https://archive.afsc.noaa.gov/refm/docs/2019/GOApcod.pdf (2019).Arimitsu, M. L. et al. Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators. Glob. Change Biol. 27, 1859–1878 (2021).Article 
CAS 

Google Scholar 
Leising, A. W. et al. State of the California Current 2014-15: Impacts of the Warm-Water “Blob”. CalCOFI Rep. 56, 31–68 (2015).
Google Scholar 
Chandler, P. & Yoo, S. Marine Ecosystems of the North Pacific Ocean 2009-2016: Synthesis Report. PICES Spec. Publ. 7, 1–82 (2021).
Google Scholar 
Peterson, W. et al. Ocean Ecosystem Indicators of Salmon Marine Survival in the Northern California Current. NOAA Northwest Fishery Science Center1-94. http://www.nwfsc.noaa.gov/research/divisions/fe/estuarine/oeip/documents/Peterson_etal_2015.pdf (2015).Volk, T. & Hoffert, M. Ocean carbon pumps: analysis of relative strengths and efficiencies in ocean-driven atmospheric CO2 changes. In Sundquist, E. & Broecker, W. (eds.) The carbon cycle and atmospheric CO2 : natural variations Archean to present. Chapman conference papers, 1984, 99–110 (American Geophysical Union; Geophysical Monograph 32, 1985).Whitney, F. A. Anomalous winter winds decrease 2014 transition zone productivity in the NE Pacific. Geophys. Res. Lett. 42, 428–431 (2015).Article 

Google Scholar 
McCabe, R. M. et al. An unprecedented coastwide toxic algal bloom linked to anomalous ocean conditions. Geophys. Res. Lett. 43, 10366–10376 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Du, X., Peterson, W., Fisher, J., Hunter, M. & Peterson, J. Initiation and Development of a Toxic and Persistent Pseudo-nitzschia Bloom off the Oregon Coast in Spring/Summer 2015. PLOS ONE 11, 1–17 (2016).Article 

Google Scholar 
Du, X. & Peterson, W. T. Phytoplankton community structure in 2011-2013 compared to the extratropical warming event of 2014-2015. Geophys. Res. Lett. 45, 1534–1540 (2018).Article 

Google Scholar 
Peña, M. AandNemcek,NandRobert,M. Phytoplankton responses to the 2014-2016 warming anomaly in the northeast subarctic Pacific Ocean. Limnol. Oceanogr. 64, 515–525 (2019).Article 

Google Scholar 
Barth, A., Walter, R. K., Robbins, I. & Pasulka, A. Seasonal and interannual variability of phytoplankton abundance and community composition on the Central Coast of California. Mar. Ecol. Prog. Ser. 637, 29–43 (2020).Article 
CAS 

Google Scholar 
Batten, S. D., Ostle, C., Hélaouët, P. & Walne, A. W. Responses of Gulf of Alaska plankton communities to a marine heat wave. Deep Sea Res. Part II: Topical Stud. Oceanogr. 195, 105002 (2022).Article 

Google Scholar 
Johnstone, J. A. & Mantua, N. J. Atmospheric controls on northeast Pacific temperature variability and change, 1900–2012. Proc. Natl Acad. Sci. 111, 14360–14365 (2014).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Gregg, W. W. & Rousseaux, C. S. Global ocean primary production trends in the modern ocean color satellite record (1998–2015). Environ. Res. Lett. 14, 124011 (2019).Article 
CAS 

Google Scholar 
Hamme, R. C. et al. Volcanic ash fuels anomalous plankton bloom in subarctic northeast Pacific. Geophys. Res. Lett. 37. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2010GL044629. https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2010GL044629 (2010).Rousseaux, C. S. & Gregg, W. W. Climate variability and phytoplankton composition in the Pacific Ocean. J. Geophys. Res. Oceans 117. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2012JC008083. https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2012JC008083 (2012).Lewing, J. Silicification. In Lewin, R. (ed.) Physiology and biochemistry of algae, 445 – 455 (Academic Press, New York, 1962).Pančić, M., Torres, R. R., Almeda, R. & Kiørboe, T. Silicified cell walls as a defensive trait in diatoms. Proc. R. Soc. B: Biol. Sci. 286, 20190184 (2019).Article 

Google Scholar 
Kröger, N. & Poulsen, N. Diatoms—from cell wall biogenesis to nanotechnology. Annu. Rev. Genet. 42, 83–107 (2008).Article 
PubMed 

Google Scholar 
Miklasz, K. A. & Denny, M. W. Diatom sinkings speeds: Improved predictions and insight from a modified stokes’ law. Limnol. Oceanogr. 55, 2513–2525 (2010).Article 

Google Scholar 
Nishioka, J. et al. Subpolar marginal seas fuel the North Pacific through the intermediate water at the termination of the global ocean circulation. Proc. Natl Acad. Sci. 117, 12665–12673 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Nishioka, J. et al. A review: iron and nutrient supply in the subarctic Pacific and its impact on phytoplankton production. J. Oceanogr. 77, 561–587 (2021).Article 
CAS 

Google Scholar 
Dave, A. C. & Lozier, M. S. The impact of advection on stratification and chlorophyll variability in the equatorial Pacific. Geophys. Res. Lett. 42, 4523–4531 (2015).Article 

Google Scholar 
JA, B. Atmospheric teleconnections from the equatorial Pacific. Monthly Weather Rev. 97, 163–172 (1969).Article 

Google Scholar 
Martin, J. H. & Fitzwater, S. E. Iron deficiency limits phytoplankton growth in the north-east Pacific subarctic. Nature 331, 341 – 343 (1988).Article 

Google Scholar 
Ryther, J. H. Photosynthesis and fish production in the sea. Science 166, 72–76 (1969).Article 
CAS 
PubMed 

Google Scholar 
Smetacek, V. Diatoms and the ocean carbon cycle. Protist 150, 25–32 (1999).Article 
CAS 
PubMed 

Google Scholar 
Chavez, F. P., Buck, K. R. & Barber, R. T. Phytoplankton taxa in relation to primary production in the equatorial Pacific. Deep Sea Res. Part A Oceanogr. Res. Pap. 37, 1733–1752 (1990).Article 

Google Scholar 
Uitz, J., Claustre, H., Gentili, B. & Stramski, D. Phytoplankton class-specific primary production in the world’s oceans: Seasonal and interannual variability from satellite observations. Glob. Biogeochem. Cycles 24. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2009GB003680 (2010).Strutton, P. G. & Chavez, F. P. Primary productivity in the equatorial Pacific during the 1997-1998 El Niño. J. Geophys. Res. Oceans 105, 26089–26101 (2000).Article 

Google Scholar 
Ondrusek, M. E., Bidigare, R. R., Sweet, S. T., Defreitas, D. A. & Brooks, J. M. Distribution of phytoplankton pigments in the north pacific ocean in relation to physical and optical variability. Deep Sea Res. Part A. Oceanogr. Res. Pap. 38, 243–266 (1991).Article 
CAS 

Google Scholar 
Behrenfeld, M. J., Bale, A. J., Kolber, Z. S., Aiken, J. & Falkowski, P. G. Confirmation of iron limitation of phytoplankton in the equatorial Pacific Ocean. Nature 383, 508–511 (1996).Article 
CAS 

Google Scholar 
Barber, R. T. & Chavez, F. P. Regulation of primary productivity rate in the equatorial Pacific. Limnol. Oceanogr. 36, 1803–1815 (1991).Article 

Google Scholar 
Coale, K. H., Fitzwater, S. E., Gordon, R. M., Johnson, K. S. & Barber, R. T. Control of community growth and export production by upwelled iron in the equatorial Pacific Ocean. Nature 379, 621–624 (1996).Article 
CAS 

Google Scholar 
Dugdale, R. C. & Wilkerson, F. P. Silicate regulation of new production in the equatorial Pacific upwelling. Nature 391, 270–273 (1998).Article 
CAS 

Google Scholar 
Le Grix, N., Zscheischler, J., Laufkötter, C., Rousseaux, C. S. & Frölicher, T. L. Compound high-temperature and low-chlorophyll extremes in the ocean over the satellite period. Biogeosciences 18, 2119–2137 (2021).Article 

Google Scholar 
Behrenfeld, M. J. & Boss, E. S. Resurrecting the ecological underpinnings of ocean plankton blooms. Annu. Rev. Mar. Sci. 6, 167–194 (2014).Article 

Google Scholar 
Gregg, W. W. & Casey, N. W. Modeling coccolithophores in the global oceans. Deep Sea Res. Part II: Topical Stud. Oceanogr. 54, 447–477 (2007). The Role of Marine Organic Carbon and Calcite Fluxes in Driving Global Climate Change, Past and Future.Article 

Google Scholar 
Wang, B. et al. Historical change of El Niño properties sheds light on future changes of extreme El Niño. Proc. Natl Acad. Sci. 116, 22512–22517 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).Article 

Google Scholar 
Jackson, T., Bouman, H. A., Sathyendranath, S. & Devred, E. Regional-scale changes in diatom distribution in the Humboldt upwelling system as revealed by remote sensing: implications for fisheries. ICES J. Mar. Sci. 68, 729–736 (2011).Article 

Google Scholar 
Suryan, R. M. et al. Ecosystem response persists after a prolonged marine heatwave. Sci. Rep. 11, 6235–6252 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Glantz, M. H. Currents of change: impacts of El Ninño and La Ninña on climate and society. (Cambridge University Press, Cambridge, United Kingdom, 2001).
Google Scholar 
Arteaga, L. A., Boss, E., Behrenfeld, M. J., Westberry, T. K. & Sarmiento, J. L. Seasonal modulation of phytoplankton biomass in the Southern Ocean. Nat. Commun. 11, 5364 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Behrenfeld, M. J., Doney, S. C., Lima, I., Boss, E. S. & Siegel, D. A. Annual cycles of ecological disturbance and recovery underlying the subarctic Atlantic spring plankton bloom. Glob. Biogeochem. Cycles 27, 526–540 (2013).Article 
CAS 

Google Scholar 
Gelaro, R. et al. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). J. Clim. 30, 5419–5454 (2017).Article 

Google Scholar 
Schopf, P. S. & Loughe, A. A Reduced-Gravity Isopycnal Ocean Model: Hindcasts of El Niño. Monthly Weather Rev. 123, 2839–2863 (1995).Article 

Google Scholar 
Rienecker, M. M. et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 24, 3624–3648 (2011).Article 

Google Scholar 
Gregg, W. W. & Casey, N. W. Skill assessment of a spectral ocean-atmosphere radiative model. J. Mar. Syst. 76, 49–63 (2009). Skill assessment for coupled biological/physical models of marine systems.Article 

Google Scholar 
Eppley, R. W. Temperature and phytoplankton growth in the sea. Fish. Bull. 70, 1063–1085 (1972).
Google Scholar 
Csanady, G. T. Mass transfer to and from small particles in the sea. Limnol. Oceanogr. 31, 237–248 (1986).Article 
CAS 

Google Scholar 
McGillicuddy, D. J., McCarthy, J. J. & Robinson, A. R. Coupled physical and biological modeling of the spring bloom in the North Atlantic (I): Model formulation and one dimensional bloom processes. Deep-Sea Res. 42, 1313–1357 (1995).Article 
CAS 

Google Scholar 
Greene, C. A. et al. The climate data toolbox for matlab. Geochem. Geophys. Geosyst. 20, 3774–3781 (2019).Article 

Google Scholar 
Morel, A. et al. Examining the consistency of products derived from various ocean color sensors in open ocean (case 1) waters in the perspective of a multi-sensor approach. Remote Sens. Environ. 111, 69 – 88 (2007).Article 

Google Scholar 
Gregg, W. W. Assimilation of seawifs ocean chlorophyll data into a three-dimensional global ocean model. J. Mar. Syst. 69, 205–225 (2008). Physical-Biological Interactions in the Upper Ocean.Article 

Google Scholar 
Conkright, M. E. et al. World Ocean Atlas 2001. Volume 4, Nutrients. In NOAA atlas NESDIS ; 52, vol. 4, 392 (US Government Printing Office, Washington, DC, 2002). https://repository.library.noaa.gov/view/noaa/1102.Fung, I. Y. et al. Iron supply and demand in the upper ocean. Glob. Biogeochemical Cycles 14, 281–295 (2000).Article 
CAS 

Google Scholar 
Gregg, W. W., Ginoux, P., Schopf, P. S. & Casey, N. W. Phytoplankton and iron: validation of a global three-dimensional ocean biogeochemical model. Deep Sea Res. Part II: Topical Stud. Oceanogr. 50, 3143–3169 (2003). The US JGOFS Synthesis and Modeling Project: Phase II.Article 
CAS 

Google Scholar 
Rousseaux, C. S. & Gregg, W. W. Recent decadal trends in global phytoplankton composition. Glob. Biogeochem. Cycles 29, 1674–1688 (2015).Article 
CAS 

Google Scholar  More

Authors and AffiliationsCenter for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, DenmarkMorten T. Limborg & Jacob A. RasmussenSanger Institute, Wellcome Trust Genome Campus, Hinxton, UKPhysilia Y. S. ChuaAuthorsMorten T. LimborgPhysilia Y. S. ChuaJacob A. RasmussenCorresponding authorsCorrespondence to
Morten T. Limborg or Physilia Y. S. Chua. More

Macreadie, P. I. et al. The future of Blue Carbon science. Nat. Commun. 10, 3998 (2019).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Herbert, E. R., Windham-Myers, L. & Kirwan, M. L. Sea-level rise enhances carbon accumulation in United States tidal wetlands. One Earth 4, 425–433 (2021).Article 
ADS 

Google Scholar 
Rogers, K. et al. Wetland carbon storage controlled by millennial-scale variation in relative sea-level rise. Nature 567, 91–95 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Murray, N. J. et al. The global distribution and trajectory of tidal flats. Nature 565, 222–225 (2019).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Saintilan, N. et al. Thresholds of mangrove survival under rapid sea level rise. Science 368, 1118–1121 (2020).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Waycott, M. et al. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc. Natl Acad. Sci. USA 106, 12377–12381 (2009).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kirwan, M. L. & Gedan, K. B. Sea-level driven land conversion and the formation of ghost forests. Nat. Clim. Change 9, 450–457 (2019).Article 
ADS 

Google Scholar 
Raabe, E. A. & Stumpf, R. P. Expansion of tidal marsh in response to sea-level rise: Gulf Coast of Florida, USA. Estuaries Coast. 39, 145–157 (2016).Article 

Google Scholar 
Ury, E. A., Yang, X., Wright, J. P. & Bernhardt, E. S. Rapid deforestation of a coastal landscape driven by sea-level rise and extreme events. Ecol. Appl. 31, e02339 (2021).Article 
PubMed 

Google Scholar 
Mariotti, G. Revisiting salt marsh resilience to sea level rise: are ponds responsible for permanent land loss? J. Geophys. Res. Earth Surf. 121, 1391–1407 (2016).Article 
ADS 

Google Scholar 
Schepers, L., Brennand, P., Kirwan, M. L., Guntenspergen, G. R. & Temmerman, S. Coastal marsh degradation into ponds induces irreversible elevation loss relative to sea level in a microtidal system. Geophys. Res. Lett. 47, e2020GL089121 (2020).Article 
ADS 

Google Scholar 
Schieder, N. W., Walters, D. C. & Kirwan, M. L. Massive upland to wetland conversion compensated for historical marsh loss in Chesapeake Bay, USA. Estuaries Coasts 41, 940–951 (2018).Article 

Google Scholar 
Chmura, G. L., Anisfeld, S. C., Cahoon, D. R. & Lynch, J. C. Global carbon sequestration in tidal, saline wetland soils. Glob. Biogeochem. Cycles 17, 1111 (2003).Fourqurean, J. W. et al. Seagrass ecosystems as a globally significant carbon stock. Nat. Geosci. 5, 505–509 (2012).Article 
ADS 
CAS 

Google Scholar 
Mcleod, E. et al. A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front. Ecol. Environ. 9, 552–560 (2011).Article 

Google Scholar 
Smart, L. S. et al. Aboveground carbon loss associated with the spread of ghost forests as sea levels rise. Environ. Res. Lett. 15, 104028 (2020).Article 
ADS 
CAS 

Google Scholar 
Smith, A. J. & Kirwan, M. L. Sea level-driven marsh migration results in rapid net loss of carbon. Geophys. Res. Lett. 48, e2021GL092420 (2021).Article 
ADS 
CAS 

Google Scholar 
Phang, V. X. H., Chou, L. M. & Friess, D. A. Ecosystem carbon stocks across a tropical intertidal habitat mosaic of mangrove forest, seagrass meadow, mudflat and sandbar. Earth Surf. Process. Landf. 40, 1387–1400 (2015).Article 
ADS 
CAS 

Google Scholar 
Saavedra-Hortua, D. A., Friess, D. A., Zimmer, M. & Gillis, L. G. Sources of particulate organic matter across mangrove forests and adjacent ecosystems in different geomorphic settings. Wetlands 40, 1047–1059 (2020).Article 

Google Scholar 
Windham-Myers, L., Crooks, S. & Troxler, T. G. A Blue Carbon Primer: The State of Coastal Wetland Carbon Science, Practice and Policy (CRC Press, 2018).Donatelli, C., Kalra, T. S., Fagherazzi, S., Zhang, X. & Leonardi, N. Dynamics of marsh-derived sediments in lagoon-type estuaries. J. Geophys. Res. Earth Surf. 125, e2020JF005751 (2020).Article 
ADS 

Google Scholar 
Hopkinson, C. S., Morris, J. T., Fagherazzi, S., Wollheim, W. M. & Raymond, P. A. Lateral marsh edge erosion as a source of sediments for vertical marsh accretion. J. Geophys. Res. Biogeosci. 123, 2444–2465 (2018).Article 
CAS 

Google Scholar 
Mitchell, M. G. E., Bennett, E. M. & Gonzalez, A. Linking landscape connectivity and ecosystem service provision: current knowledge and research gaps. Ecosystems 16, 894–908 (2013).Article 

Google Scholar 
Pearson, R. M. et al. Disturbance type determines how connectivity shapes ecosystem resilience. Sci. Rep. 11, 1188 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Grande, T. O., Aguiar, L. M. S. & Machado, R. B. Heating a biodiversity hotspot: connectivity is more important than remaining habitat. Landsc. Ecol. 35, 639–657 (2020).Article 

Google Scholar 
Olliver, E. A. & Edmonds, D. A. Hydrological connectivity controls magnitude and distribution of sediment deposition within the Deltaic Islands of Wax Lake Delta, LA, USA. J. Geophys. Res. Earth Surf. 126, e2021JF006136 (2021).Article 
ADS 

Google Scholar 
Ward, N. D. et al. Representing the function and sensitivity of coastal interfaces in Earth system models. Nat. Commun. 11, 2458 (2020).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wohl, E. et al. Connectivity as an emergent property of geomorphic systems. Earth Surf. Process. Landf. 44, 4–26 (2019).Article 
ADS 

Google Scholar 
Kirwan, M. L. & Mudd, S. M. Response of salt-marsh carbon accumulation to climate change. Nature 489, 550–553 (2012).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Rietl, A. J., Megonigal, J. P., Herbert, E. R. & Kirwan, M. L. Vegetation type and decomposition priming mediate brackish marsh carbon accumulation under interacting facets of global change. Geophys. Res. Lett. 48, e2020GL092051 (2021).Article 
ADS 
CAS 

Google Scholar 
Kirwan, M. L., Walters, D. C., Reay, W. G. & Carr, J. A. Sea level driven marsh expansion in a coupled model of marsh erosion and migration. Geophys. Res. Lett. 43, 4366–4373 (2016).Article 
ADS 

Google Scholar 
Mariotti, G. & Fagherazzi, S. A numerical model for the coupled long-term evolution of salt marshes and tidal flats. J. Geophys. Res. Earth Surf. 115, F01004 (2010).Theuerkauf, E. J., Stephens, J. D., Ridge, J. T., Fodrie, F. J. & Rodriguez, A. B. Carbon export from fringing saltmarsh shoreline erosion overwhelms carbon storage across a critical width threshold. Estuar. Coast. Shelf Sci. 164, 367–378 (2015).Article 
CAS 

Google Scholar 
Murray, A. B. Reducing model complexity for explanation and prediction. Geomorphology 90, 178–191 (2007).Article 
ADS 

Google Scholar 
Murray, A. B. & Paola, C. A cellular model of braided rivers. Nature 371, 54–57 (1994).Article 
ADS 

Google Scholar 
Mariotti, G. & Carr, J. Dual role of salt marsh retreat: long-term loss and short-term resilience. Water Resour. Res. 50, 2963–2974 (2014).Article 
ADS 

Google Scholar 
Mudd, S. M., Howell, S. M. & Morris, J. T. Impact of dynamic feedbacks between sedimentation, sea-level rise, and biomass production on near-surface marsh stratigraphy and carbon accumulation. Estuar. Coast. Shelf Sci. 82, 377–389 (2009).Article 
ADS 
CAS 

Google Scholar 
Mudd, S. M., Fagherazzi, S., Morris, J. T. & Furbish, D. J. Flow, sedimentation, and biomass production on a vegetated salt marsh in South Carolina: toward a predictive model of marsh morphologic and ecologic evolution. Ecogeomorphology Tidal Marshes 59, 165–188 (2004).Reeves, I. R. B. et al. Impacts of seagrass dynamics on the coupled long-term evolution of barrier-marsh-bay systems. J. Geophys. Res. Biogeosci. 125, e2019JG005416 (2020).Article 
ADS 

Google Scholar 
Spivak, A. C., Sanderman, J., Bowen, J. L., Canuel, E. A. & Hopkinson, C. S. Global-change controls on soil-carbon accumulation and loss in coastal vegetated ecosystems. Nat. Geosci. 12, 685–692 (2019).Article 
ADS 
CAS 

Google Scholar 
de Broek, M. V. et al. Long-term organic carbon sequestration in tidal marsh sediments is dominated by old-aged allochthonous inputs in a macrotidal estuary. Glob. Change Biol. 24, 2498–2512 (2018).Article 
ADS 

Google Scholar 
Noyce, G. L., Kirwan, M. L., Rich, R. L. & Megonigal, J. P. Asynchronous nitrogen supply and demand produce nonlinear plant allocation responses to warming and elevated CO2. Proc. Natl Acad. Sci. USA 116, 21623–21628 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Smith, A. J., Noyce, G. L., Megonigal, J. P., Guntenspergen, G. R. & Kirwan, M. L. Temperature optimum for marsh resilience and carbon accumulation revealed in a whole-ecosystem warming experiment. Glob. Change Biol. 28, 3236–3245 (2022).Article 
CAS 

Google Scholar 
Guimond, J. & Tamborski, J. Salt marsh hydrogeology: a review. Water 13, 543 (2021).Article 
CAS 

Google Scholar 
Xin, P. et al. Surface water and groundwater interactions in salt marshes and their impact on plant ecology and coastal biogeochemistry. Rev. Geophys. 60, e2021RG000740 (2022).Article 
ADS 

Google Scholar 
Chen, Y. & Kirwan, M. L. Climate-driven decoupling of wetland and upland biomass trends on the mid-Atlantic coast. Nat. Geosci. 15, 913–918 (2022).Article 
ADS 
CAS 

Google Scholar 
Rapalee, G., Trumbore, S. E., Davidson, E. A., Harden, J. W. & Veldhuis, H. Soil Carbon stocks and their rates of accumulation and loss in a boreal forest landscape. Glob. Biogeochem. Cycles 12, 687–701 (1998).Article 
ADS 
CAS 

Google Scholar 
Stewart, C. E., Paustian, K., Conant, R. T., Plante, A. F. & Six, J. Soil carbon saturation: concept, evidence and evaluation. Biogeochemistry 86, 19–31 (2007).Article 
CAS 

Google Scholar 
Zhou, T. et al. Age-dependent forest carbon sink: Estimation via inverse modeling. J. Geophys. Res. Biogeosci. 120, 2473–2492 (2015).Article 
CAS 

Google Scholar 
Morris, J. T., Sundareshwar, P. V., Nietch, C. T., Kjerfve, B. & Cahoon, D. R. Responses of coastal wetlands to rising sea level. Ecology 83, 2869–2877 (2002).Article 

Google Scholar 
Kirwan, M. L., Temmerman, S., Skeehan, E. E., Guntenspergen, G. R. & Fagherazzi, S. Overestimation of marsh vulnerability to sea level rise. Nat. Clim. Change 6, 253–260 (2016).Article 
ADS 

Google Scholar 
Brinson, M. M., Christian, R. R. & Blum, L. K. Multiple states in the sea-level induced transition from terrestrial forest to estuary. Estuaries 18, 648–659 (1995).Article 
CAS 

Google Scholar 
Schieder, N. W. & Kirwan, M. L. Sea-level driven acceleration in coastal forest retreat. Geology 47, 1151–1155 (2019).Article 
ADS 

Google Scholar 
Leonardi, N., Ganju, N. K. & Fagherazzi, S. A linear relationship between wave power and erosion determines salt-marsh resilience to violent storms and hurricanes. Proc. Natl Acad. Sci. USA 113, 64–68 (2016).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Feagin, R. A., Martinez, M. L., Mendoza-Gonzalez, G. & Costanza, R. Salt marsh zonal migration and ecosystem service change in response to global sea level rise: a case study from an urban region. Ecol. Soc. 15, 14 (2010).Sapkota, Y. & White, J. R. Marsh edge erosion and associated carbon dynamics in coastal Louisiana: a proxy for future wetland-dominated coastlines world-wide. Estuar. Coast. Shelf Sci. 226, 106289 (2019).Article 
CAS 

Google Scholar 
Smith, K. E. L., Terrano, J. F., Khan, N. S., Smith, C. G. & Pitchford, J. L. Lateral shoreline erosion and shore-proximal sediment deposition on a coastal marsh from seasonal, storm and decadal measurements. Geomorphology 389, 107829 (2021).Article 

Google Scholar 
Bouma, T. J. et al. Short-term mudflat dynamics drive long-term cyclic salt marsh dynamics. Limnol. Oceanogr. 61, 2261–2275 (2016).Article 
ADS 

Google Scholar 
Gillis, L. G. et al. Potential for landscape-scale positive interactions among tropical marine ecosystems. Mar. Ecol. Prog. Ser. 503, 289–303 (2014).Article 
ADS 

Google Scholar 
Schuerch, M., Dolch, T., Reise, K. & Vafeidis, A. T. Unravelling interactions between salt marsh evolution and sedimentary processes in the Wadden Sea (southeastern North Sea). Prog. Phys. Geogr. Earth Environ. 38, 691–715 (2014).Article 

Google Scholar 
Gonneea, M. E. et al. Salt marsh ecosystem restructuring enhances elevation resilience and carbon storage during accelerating relative sea-level rise. Estuar. Coast. Shelf Sci. 217, 56–68 (2019).Article 
ADS 
CAS 

Google Scholar 
McTigue, N. et al. Sea level rise explains changing carbon accumulation rates in a salt marsh over the past two millennia. J. Geophys. Res. Biogeosci. 124, 2945–2957 (2019).Article 
CAS 

Google Scholar 
Wang, F., Lu, X., Sanders, C. J. & Tang, J. Tidal wetland resilience to sea level rise increases their carbon sequestration capacity in United States. Nat. Commun. 10, 5434 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wang, F. et al. Global blue carbon accumulation in tidal wetlands increases with climate change. Natl Sci. Rev. 8, nwaa296 (2021).Article 
CAS 
PubMed 

Google Scholar 
Ganju, N. K., Defne, Z., Elsey-Quirk, T. & Moriarty, J. M. Role of tidal wetland stability in lateral fluxes of particulate organic matter and carbon. J. Geophys. Res. Biogeosci. 124, 1265–1277 (2019).Article 
CAS 

Google Scholar 
Krauss, K. W. et al. The role of the upper tidal estuary in wetland blue carbon storage and flux. Glob. Biogeochem. Cycles 32, 817–839 (2018).Article 
ADS 
CAS 

Google Scholar 
Baustian, M. M., Stagg, C. L., Perry, C. L., Moss, L. C. & Carruthers, T. J. B. Long-term carbon sinks in marsh soils of coastal louisiana are at risk to wetland loss. J. Geophys. Res. Biogeosci. 126, e2020JG005832 (2021).Article 
ADS 

Google Scholar 
DeLaune, R. D. & White, J. R. Will coastal wetlands continue to sequester carbon in response to an increase in global sea level?: a case study of the rapidly subsiding Mississippi river deltaic plain. Clim. Change 110, 297–314 (2012).Article 
ADS 

Google Scholar 
Lovelock, C. E. & Duarte, C. M. Dimensions of Blue Carbon and emerging perspectives. Biol. Lett. 15, 20180781 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Lovelock, C. E. & Reef, R. Variable impacts of climate change on Blue Carbon. One Earth 3, 195–211 (2020).Article 
ADS 

Google Scholar 
Bernal, B. & Mitsch, W. J. Comparing carbon sequestration in temperate freshwater wetland communities. Glob. Change Biol. 18, 1636–1647 (2012).Article 
ADS 

Google Scholar 
Mack, S. K., Lane, R. R., Deng, J., Morris, J. T. & Bauer, J. J. Wetland carbon models: applications for wetland carbon commercialization. Ecol. Model. 476, 110228 (2023).Article 
CAS 

Google Scholar 
Young, I. R. & Verhagen, L. A. The growth of fetch limited waves in water of finite depth. Part 1. Total energy and peak frequency. Coast. Eng. 29, 47–78 (1996).Article 

Google Scholar 
Mariotti, G. & Fagherazzi, S. Critical width of tidal flats triggers marsh collapse in the absence of sea-level rise. Proc. Natl Acad. Sci. USA 110, 5353–5356 (2013).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Koppel, J., van de, Wal, D., van der, Bakker, J. P. & Herman, P. M. J. Self‐organization and vegetation collapse in salt marsh ecosystems. Am. Nat. 165, E1–E12 (2005).Article 
PubMed 

Google Scholar 
D’Alpaos, A., Lanzoni, S., Marani, M. & Rinaldo, A. Landscape evolution in tidal embayments: modeling the interplay of erosion, sedimentation, and vegetation dynamics. J. Geophys. Res. Earth Surf. 112, F01008 (2007).Kirwan, M. L. et al. Limits on the adaptability of coastal marshes to rising sea level. Geophys. Res. Lett. 37, L23401 (2010).Larsen, L. G. & Harvey, J. W. How vegetation and sediment transport feedbacks drive landscape change in the everglades and wetlands worldwide. Am. Nat. 176, E66–E79 (2010).Article 
PubMed 

Google Scholar 
Smith, J. A. M. The role of Phragmites australis in mediating inland salt marsh migration in a Mid-Atlantic Estuary. PLoS ONE 8, e65091 (2013).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Mariotti, G., Elsey-Quirk, T., Bruno, G. & Valentine, K. Mud-associated organic matter and its direct and indirect role in marsh organic matter accumulation and vertical accretion. Limnol. Oceanogr. 65, 2627–2641 (2020).Article 
ADS 
CAS 

Google Scholar 
Ladd, C. J. T., Duggan-Edwards, M. F., Bouma, T. J., Pagès, J. F. & Skov, M. W. Sediment supply explains long-term and large-scale patterns in salt marsh lateral expansion and erosion. Geophys. Res. Lett. 46, 11178–11187 (2019).Article 
ADS 

Google Scholar 
Törnqvist, T. E., Jankowski, K. L., Li, Y.-X. & González, J. L. Tipping points of Mississippi Delta marshes due to accelerated sea-level rise. Sci. Adv. 6, eaaz5512 (2020).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Fagherazzi, S. et al. Numerical models of salt marsh evolution: ecological, geomorphic, and climatic factors. Rev. Geophys. 50, RG1002 (2012). More

Alston, J. M. et al. Reciprocity in restoration ecology: When might large carnivore reintroduction restore ecosystems?. Biol. Conserv. 234, 82–89 (2019).Article 

Google Scholar 
Ripple, W. J. & Beschta, R. L. Large predators limit herbivore densities in northern forest ecosystems. Eur. J. Wildl. Res. 58, 733–742 (2012).Article 

Google Scholar 
Estes, J. A. & Duggins, D. O. Sea otters and kelp forests in Alaska: Generality and variation in a community ecological paradigm. Ecol. Monogr. 65, 75–100 (1995).Article 

Google Scholar 
Schmitz, O. J., Beckerman, A. P. & O’Brien, K. M. Behaviorally mediated trophic cascades: Effects of predation risk on food web interactions. Ecology 78, 1388–1399 (1997).Article 

Google Scholar 
Power, M. E. Top-down and bottom-up forces in food webs: Do plants have primacy. Ecology 73, 733–746 (1992).Article 

Google Scholar 
Travers, T., Lea, M. A., Alderman, R., Terauds, A. & Shaw, J. Bottom-up effect of eradications: The unintended consequences for top-order predators when eradicating invasive prey. J. Appl. Ecol. 58, 801–811 (2021).Article 

Google Scholar 
Stoessel, M., Elmhagen, B., Vinka, M., Hellström, P. & Angerbjörn, A. The fluctuating world of a tundra predator guild: bottom-up constraints overrule top-down species interactions in winter. Ecography (Cop.) 42, 488–499 (2019).Article 

Google Scholar 
Wolf, C. & Ripple, W. J. Rewilding the world ’s large carnivores. R. Soc. Open Sci. 5, 172235 (2018).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Krofel, M. & Jerina, K. Mind the cat: Conservation management of a protected dominant scavenger indirectly affects an endangered apex predator. Biol. Conserv. 197, 40–46 (2016).Article 

Google Scholar 
Prugh, L. R. & Sivy, K. J. Enemies with benefits: Integrating positive and negative interactions among terrestrial carnivores. Ecol. Lett. https://doi.org/10.1111/ele.13489 (2020).Article 
PubMed 

Google Scholar 
Caro, T. M. & Stoner, C. J. The potential for interspecific competition among African carnivores. Biol. Conserv. 110, 67–75 (2003).Article 

Google Scholar 
Linnell, J. D. C. & Strand, O. Interference interactions, co-existence and conservation of mammalian carnivores. Divers. Distrib. 6, 169–176 (2000).Article 

Google Scholar 
Newsome, T. M. et al. Top predators constrain mesopredator distributions. Nat. Commun. 8, 15469 (2017).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Crooks, K. & Soulé, M. Mesopredator release and avifaunal extinctions in a fragmented system. Nature 400, 563–566 (1999).Article 
ADS 
CAS 

Google Scholar 
Schoener, T. W. Resource partitioning in ecological communities. Science 185, 27–39 (1974).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Fedriani, J. M., Fuller, T. K., Sauvajot, R. M. & York, E. C. Competition and intraguild predation among three sympatric carnivores. Oecologia 125, 258–270 (2000).Article 
ADS 
PubMed 

Google Scholar 
Monterroso, P., Díaz-Ruiz, F., Lukacs, P. M., Alves, P. C. & Ferreras, P. Ecological traits and the spatial structure of competitive coexistence among carnivores. Ecology 101, 1–16 (2020).Article 

Google Scholar 
Karanth, K. U. et al. Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient. Proc. R. Soc. B Biol. Sci. 284, 20161860 (2017).Article 

Google Scholar 
Ferreiro-Arias, I., Isla, J., Jordano, P. & Benítez-López, A. Fine-scale coexistence between Mediterranean mesocarnivores is mediated by spatial, temporal, and trophic resource partitioning. Ecol. Evol. 11, 15520–15533 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Di Bitetti, M. S., De Angelo, C. D., Di Blanco, Y. E. & Paviolo, A. Niche partitioning and species coexistence in a Neotropical felid assemblage. Acta Oecol. 36, 403–412 (2010).Article 
ADS 

Google Scholar 
Carvalho, J. C. & Gomes, P. Feeding resource partitioning among four sympatric carnivores in the Peneda-Gerês National Park (Portugal). J. Zool. 263, 275–283 (2004).Article 

Google Scholar 
Gil-Sánchez, J. M., Mañá-Varela, B., Herrera-Sánchez, F. J. & Urios, V. Spatio-temporal ecology of a carnivore community in middle atlas NW of Morocco. Zoology 146, 125904 (2021).Article 
PubMed 

Google Scholar 
Monterroso, P., Alves, P. C. & Ferreras, P. Plasticity in circadian activity patterns of mesocarnivores in Southwestern Europe: Implications for species coexistence. Behav. Ecol. Sociobiol. 68, 1403–1417 (2014).Article 

Google Scholar 
Gallagher, A. J., Creel, S., Wilson, R. P. & Cooke, S. J. Energy landscapes and the landscape of fear. Trends Ecol. Evol. 32, 88–96 (2017).Article 
PubMed 

Google Scholar 
Sergio, F. & Hiraldo, F. Intraguild predation in raptor assemblages: A review. Ibis 150, 132–145 (2008).Article 

Google Scholar 
Jiménez, J. et al. Restoring apex predators can reduce mesopredator abundances. Biol. Conserv. 238, 108234 (2019).Article 

Google Scholar 
Palomares, F., Ferreras, P., Fedriani, J. M. & Delibes, M. Spatial relationships between Iberian lynx and other carnivores in an area of south-western Spain. J. Appl. Ecol. 33, 5–13 (1996).Article 

Google Scholar 
Wooster, E. I. F., Ramp, D., Lundgren, E. J., O’Neill, A. J. & Wallach, A. D. Red foxes avoid apex predation without increasing fear. Behav. Ecol. 32, 895–902 (2021).Article 

Google Scholar 
Santos, F. et al. Prey availability and temporal partitioning modulate felid coexistence in Neotropical forests. PLoS ONE 14, 1–23 (2019).Article 

Google Scholar 
Barrientos, R. & Virgós, E. Reduction of potential food interference in two sympatric carnivores by sequential use of shared resources. Acta Oecol. 30, 107–116 (2006).Article 
ADS 

Google Scholar 
MacArthur, R. H. & Pianka, E. R. On optimal use of a patchy environment. Am. Nat. 100, 603–609 (1966).Article 

Google Scholar 
López-Martín, J. M. Comparison of feeding behaviour between stone marten and common genet: living in coexistence. Martes Carniv. Communities 137–155 (2006).Sarmento, P. et al. Adapt or perish: How the Iberian lynx reintroduction affects fox abundance and behaviour. Hystrix Ital. J. Mammal. 32, 48–54 (2021).
Google Scholar 
Forsyth, D. M., Ramsey, D. S. L. & Woodford, L. P. Estimating abundances, densities, and interspecific associations in a carnivore community. J. Wildl. Manag. 83, 1090–1102 (2019).Article 

Google Scholar 
Monterroso, P. et al. Disease-mediated bottom-up regulation: An emergent virus affects a keystone prey, and alters the dynamics of trophic webs. Sci. Rep. 6, 1–9 (2016).Article 

Google Scholar 
Ritchie, E. G. et al. Ecosystem restoration with teeth: What role for predators?. Trends Ecol. Evol. 27, 265–271 (2012).Article 
PubMed 

Google Scholar 
Santos-Reis, M. et al. Relationships between stone martens, genets and cork oak woodlands in Portugal. Martens Fish. Hum.-Altered Environ. Int. Perspect. https://doi.org/10.1007/0-387-22691-5_7 (2004).Article 

Google Scholar 
Goszczyński, J., Posłuszny, M., Pilot, M. & Gralak, B. Patterns of winter locomotion and foraging in two sympatric marten species: Martes martes and Martes foina. Can. J. Zool. 85, 239–249 (2007).Article 
ADS 

Google Scholar 
Díaz-Ruiz, F., Caro, J., Delibes-Mateos, M., Arroyo, B. & Ferreras, P. Drivers of red fox (Vulpes vulpes) daily activity: Prey availability, human disturbance or habitat structure?. J. Zool. 298, 128–138 (2016).Article 

Google Scholar 
Zanón Martínez, J. I., Seoane, J., Kelly, M. J., Sarasola, J. H. & Travaini, A. Assessing carnivore spatial co-occurrence and temporal overlap in the face of human interference in a semi-arid forest. Ecol. Appl. https://doi.org/10.1002/eap.2482 (2021).Article 
PubMed 

Google Scholar 
Allen, M. L., Sibarani, M. C., Utoyo, L. & Krofel, M. Terrestrial mammal community richness and temporal overlap between tigers and other carnivores in Bukit Barisan Selatan National Park Sumatra. Anim. Biodivers. Conserv. 1, 97–107 (2020).Article 

Google Scholar 
Vilella, M., Ferrandiz-Rovira, M. & Sayol, F. Coexistence of predators in time: Effects of season and prey availability on species activity within a Mediterranean carnivore guild. Ecol. Evol. 10, 11408–11422 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Santos, N. et al. Protein metabolism and physical fitness are physiological determinants of body condition in Southern European carnivores. Sci. Rep. 10, 1–11 (2020).Article 

Google Scholar 
Ferreras, P., Travaini, A., Cristina Zapata, S. & Delibes, M. Short-term responses of mammalian carnivores to a sudden collapse of rabbits in Mediterranean Spain. Basic Appl. Ecol. 12, 116–124 (2011).Article 

Google Scholar 
Moreno, S. Reproduction of Garden Dormouse Eliomys quercinus lusitanicus, in southwest Spain. Mammalia 52, 401–408 (1988).Article 

Google Scholar 
Bakaloudis, D. E., Vlachos, C. G., Papakosta, M. A., Bontzorlos, V. A. & Chatzinikos, E. N. Diet composition and feeding strategies of the stone marten (Martes foina) in a typical mediterranean ecosystem. Sci. World J. 2012, 1–11 (2012).Article 

Google Scholar 
Pereira, L. M., Owen-Smith, N. & Moleón, M. Facultative predation and scavenging by mammalian carnivores: Seasonal, regional and intra-guild comparisons. Mamm. Rev. 44, 44–55 (2014).Article 

Google Scholar 
Gil-Sánchez, J. M., Ballesteros-Duperón, E. & Bueno-Segura, J. F. Feed ing ecology of the Iberian lynx Lynx pardinus in east ern. Acta Theriol. (Warsz) 51, 85–90 (2006).Article 

Google Scholar 
Krofel, M., Huber, D. & Kos, I. Diet of Eurasian lynx Lynx lynx in the northern Dinaric Mountains (Slovenia and Croatia). Acta Theriol. (Warsz) 56, 315–322 (2011).Article 

Google Scholar 
Virgós, E., Baniandrés, N., Burgos, T. & Recio, M. R. Intraguild predation by the eagle owl determines the space use of a mesopredator carnivore. Diversity 12, 13–15 (2020).Article 

Google Scholar 
Gordon, C. E., Feit, A., Grüber, J. & Letnic, M. Mesopredator suppression by an apex predator alleviates the risk of predation perceived by small prey. Proc. R. Soc. B Biol. Sci. 282, 20142870 (2015).Article 

Google Scholar 
Draper, J. P., Young, J. K., Schupp, E. W., Beckman, N. G. & Atwood, T. B. Frugivory and seed dispersal by carnivorans. Front. Ecol. Evol. 10, 864864 (2022).Article 

Google Scholar 
González-Varo, J. P., López-Bao, J. V. & Guitián, J. Functional diversity among seed dispersal kernels generated by carnivorous mammals. J. Anim. Ecol. 82, 562–571 (2013).Article 
PubMed 

Google Scholar 
Virgós, E., Llorente, M. & Cortés, Y. Geographical variation in genet (Genetta genetta L.) diet: A literature review. Mamm. Rev. 29, 117–126 (1999).Article 

Google Scholar 
Fedriani, J. M., Ayllón, D., Wiegand, T. & Grimm, V. Intertwined effects of defaunation, increased tree mortality and density compensation on seed dispersal. Ecography (Cop.) 43, 1352–1363 (2020).Article 

Google Scholar 
Burgos, T. et al. Predation risk can modify the foraging behaviour of frugivorous carnivores: Implications of rewilding apex predators for plant–animal mutualisms. J. Anim. Ecol. https://doi.org/10.1111/1365-2656.13682 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Escribano-Ávila, G. et al. Spanish juniper gain expansion opportunities by counting on a functionally diverse dispersal assemblage community. Ecol. Evol. 3, 3751–3763 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Gazzola, A. & Balestrieri, A. Nutritional ecology provides insights into competitive interactions between closely related Martes species. Mamm. Rev. 50, 82–90 (2020).Article 

Google Scholar 
Simón, M. A. et al. Diez años de conservación del lince ibérico, 326 (2012).Royle, J. A., Chandler, R. B., Sollmann, R. & Gardner, B. Spatial Capture-Recapture (Elsevier, 2014).
Google Scholar 
Rodríguez, A. & Calzada, J. Lynx pardinus (errata version published in 2020). The IUCN Red List of Threatened Species 2015. https://doi.org/10.2305/IUCN.UK.2015-2.RLTS.T12520A174111773.en (Accessed 27 January 2023) (2015).Gil-Sánchez, J. M. et al. The use of camera trapping for estimating Iberian lynx (Lynx pardinus) home ranges. Eur. J. Wildl. Res. 57, 1203–1211 (2011).Article 

Google Scholar 
Gerber, B. D., Karpanty, S. M. & Kelly, M. J. Evaluating the potential biases in carnivore capture-recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet. Popul. Ecol. 54, 43–54 (2012).Article 

Google Scholar 
Jiménez, J., Díaz-Ruiz, F., Monterroso, P., Tobajas, J. & Ferreras, P. Occupancy data improves parameter precision in spatial capture–recapture models. Ecol. Evol. https://doi.org/10.1002/ece3.9250 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Ferreras, P., DÍaz-Ruiz, F. & Monterroso, P. Improving mesocarnivore detectability with lures in camera-trapping studies. Wildl. Res. 45, 505–517 (2018).Article 

Google Scholar 
Ridout, M. S. & Linkie, M. Estimating overlap of daily activity patterns from camera trap data. J. Agric. Biol. Environ. Stat. 14, 322–337 (2009).Article 
MathSciNet 
MATH 

Google Scholar 
Jiménez, J. et al. Estimating carnivore community structures. Sci. Rep. https://doi.org/10.1038/srep41036 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Genovesi, P., Sinibaldi, I. & Boitani, L. Spacing patterns and territoriality of the stone marten. Can. J. Zool. 75, 1966–1971 (1997).Article 

Google Scholar 
Royle, J. A. & Converse, S. J. Hierarchical spatial capture-recapture models: Modelling population density in stratified populations. Methods Ecol. Evol. 5, 37–43 (2014).Article 

Google Scholar 
Palomares, F. & Delibes, M. Spatio-temporal ecology and behavior of European genets in southwestern Spain. J. Mammal. 75, 714–724 (1994).Article 

Google Scholar 
Camps, D. Jineta – Genetta genetta. En Encicl. Virtual los Vertebr. Españoles. Salvador. A., Barja, I. (Eds.). Mus. Nac. Ciencias Nat. Madrid. https://www.vertebradosibericos.org/ (2017).Efford, M. Density estimation in live-trapping studies. Oikos 106, 598–610 (2004).Article 

Google Scholar 
de Valpine, P. et al. Programming with models: Writing statistical algorithms for general model structures with NIMBLE. J. Comput. Graph. Stat. 26, 403–413 (2017).Article 
MathSciNet 

Google Scholar 
NIMBLE Development Team. NIMBLE user manual (2017).Morin, D. J., Waits, L. P., McNitt, D. C. & Kelly, M. J. Efficient single-survey estimation of carnivore density using fecal DNA and spatial capture-recapture: A bobcat case study. Popul. Ecol. 60, 197–209 (2018).Article 

Google Scholar 
Gelman, A. et al. Bayesian Data Analysis (CRC Press, 2013).Book 

Google Scholar 
Weitzman, M. S. Measure of the Overlap of Income Distribution of White and Negro Families in the United States. Technical report No 22 (1970).Jammalamadaka, S. R. & Sengupta, A. Topics in Circular Statistics. Series on Multivariate Analyisis Vol. 5 (World Scientific, 2001).Book 

Google Scholar 
Efron, B. & Tibshirani, R. J. An Introduction to the Bootstrap (CRC Press, 1994).Book 
MATH 

Google Scholar 
Mielke, P. W., Berry, K. J. & Johnson, E. S. Multi-response permutation proccedures for a priori classifications. Commun. Stat. Theory Methods 5, 1409–1424 (1976).Article 
MATH 

Google Scholar 
Nakagawa, S., Johnson, P. C. D. & Schielzeth, H. The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. J. R. Soc. Interface 14, 20170213 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. lme4: Linear mixed-effects models. R Packag. version 1.1.21 (2020).Barton, K. Package “MuMIn: Multi-model inference” for R. R Packag. Version 1.9.5 45 (2013). More