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    The scientists who switched focus to fight climate change

    Sophie Gilbert left a tenured position to join a start-up that allows small private landowners to sell carbon credits for preserving forests on their land.Credit: Sophie Gilbert

    It was during a car journey to California in temperatures sometimes exceeding 40 °C that Sophie Gilbert decided she needed to make a major career change.Driving to visit family from her home in Moscow, Idaho, she passed columns of wildfire smoke, the oppressive heat limiting the time she could spend out of her air-conditioned car. The two-day drive midway through last year helped to crystallize a feeling that she urgently needed to do something more concrete to help deal with the threat of climate change.“It hit at a gut level,” says Gilbert. “Climate change isn’t something that’s going to happen to someone else later on. It felt deeply, viscerally real for me and my family and what I care about.”Given her role as a wildlife ecologist at the University of Idaho in Moscow, it might seem that Gilbert was already well placed to have a positive impact on climate change. But the slow, incremental pace of academia, and the difficulty of getting policymakers to act on her findings, left her feeling that she was not making as much of a difference as she’d hoped.“I’ve been studying how wildlife responds to environmental change to inform conservation planning for 15 years now, researching and publishing and waiting for something to happen and then having it not happen, even when I’ve worked closely with wildlife and land-management agencies,” she says. “The system just isn’t designed to respond to the urgent challenges we’re facing,” she says.Gilbert took stock of her skills and knowledge, and how they could be put to use, settling on nature-based solutions such as forest-carbon storage and biodiversity. She made a shortlist of companies and non-governmental organizations (NGOs) doing that kind of work and started contacting them to discuss her options.In April this year, a month after securing tenure, Gilbert joined Natural Capital Exchange, a start-up firm based in San Francisco, California. The company allows small private landowners to sell carbon credits for preserving forests on their land. Gilbert’s role as senior lead for natural capital involves adding biodiversity credits to the company’s offerings, to provide incentives for conserving functioning, well-managed forests.Giving up the security and freedom that tenure offers was a big step, but Gilbert says that the hardest part of the decision was actually breaking the news to her graduate students, whose reactions ranged from anger, to understanding, to some combination of the two. “There’s a lot of mentoring and mutual responsibility there, so telling them and helping them through the process of finding a new adviser has been by far the most emotionally gruelling part,” she says.But she is excited to be taking up the challenge of working in the fast-paced world of a start-up company. “The company is full of rigorous, smart people who want to do good work,” she says. “It’s going to be a wild and exciting ride.”Spreading the wordIt’s a ride that Alice Bell knows well. By 2015, she had spent 11 years working as a lecturer in science communication at Imperial College London, and as a research fellow in the Science Policy Research Unit at the University of Sussex in Brighton, UK. She decided to leave academia for good and took up a position as head of communications at the climate-change campaign group Possible, based in London.The move came about partly by necessity — Bell’s contract was due to end, and she felt that UK government cuts were making academia an ever-more precarious occupation — but it stemmed mainly from a desire to be more directly involved in tackling the climate crisis.While at Imperial, she had built and launched a college-wide interdisciplinary course on climate change that had forced her to look more deeply into the issue. “I felt a greater urgency to put my skills somewhere they would be best utilized,” she says.Bell says leaving academia was the right choice. She thinks she is having a bigger impact on the climate crisis, and that her work–life balance has improved; she also feels more engaged in her work. “I feel more intellectually stimulated in workshops with NGOs than I did in most academic meetings,” she says, adding that she finds it liberating to be freed from academia’s pressure to publish, and from the weight of that pressure on career progression.But there are some drawbacks. “When you’re working for a small charity, no one knows who you are,” says Bell. “I was taken more seriously when I could say I was from Imperial.”Some might fear that leaving academia could arouse suspicions that they weren’t good enough to stay. “Ignore that voice,” she advises. “For many individuals, it could well be the best decision to give up.”Change from withinNot everyone, however, is ready or willing to give up on an academic career that they have spend years building up. And some find opportunities to get more involved in concrete climate solutions from within academia.

    Meade Krosby provides natural-resource managers and policymakers with scientific evidence on climate-change impacts and adaptation actions.Credit: Eric Bruns

    Since 2017, Meade Krosby has combined an academic post as a senior scientist at the University of Washington’s Climate Impacts Group in Seattle, where she works on climate vulnerability assessment and adaptation planning, with a director’s role at the university’s Northwest Climate Adaptation Science Center. The centre provides natural-resource managers and policymakers in the region with scientific evidence on climate-change impacts and adaptation actions. Krosby calls it a “boundary organization”, an interface between science and society, “acting as a conduit between the two”.“We bring applied science to decision-making around climate change, and bring decision-makers’ and communities’ concerns and knowledge back into academia to inform the kind of research that is done,” she says.Between 2016 and 2018, Krosby collaborated with Indigenous scholars, tribal organizations and other university scientists to develop the Tribal Climate Tool, a free online resource that aims to get the best available climate projections into the hands of Indigenous communities, to inform their planning for climate change. The tool, which launched in 2018, is now being used in many hazard-mitigation plans, such as the Samish Indian Nation’s 2019 climate-change vulnerability assessment. Krosby is also writing a paper on its development and use, producing a more conventional academic output to complement a tool that makes a difference in the real world.“You can do really useful work that doesn’t look like basic science, but it’s not always a trade-off between doing cool science and useful science,” she says.Funding challengeKrosby knew early on in her academic career that she wanted to make practical contributions that would help society to prepare for climate change. She started looking for this kind of applied work in 2009, during her postdoctoral research at the University of Washington, but found it hard at first to find funding — either from federal funding agencies or from private foundations. Then, in 2010, she received funding from the US Department of the Interior to look at species mobility and connectivity, and was able to use that to create a position for herself in the Climate Impacts Group.But she quickly found that her experience in more conventional academic settings had not prepared her for the kinds of project that the group undertook, with the aim of making science useful for policymakers and the public. “It was shocking how ill-prepared I was for transdisciplinary work,” she says. “We’re not trained to do, or to value, those kinds of collaborations.” The centre now supports fellowships and training in societally engaged research, and Krosby teaches a graduate course on how to connect science to society. “It’s an opportunity to train early-career scientists to do the work we never got trained to do,” she says. In 2020, she co-authored a paper1 calling for changes in how scientists are trained, by emphasizing skills such as collaboration and communication1.Academic career structures are not set up to promote and reward work that requires lots of collaboration with people outside the university, and which doesn’t necessarily result in a typical scientific publication, says Krosby. “The work I want to do wouldn’t be rewarded in a tenure-track position,” she adds. “To do this effectively, universities need to think about their incentive structure. Is a peer-reviewed paper really the most important outcome?”Reef encounterJulia Baum, a marine ecologist at the University of Victoria in Canada, has found a way to do practical, climate-focused work in a standard academic job. For her, the turning point came in 2015, when a massive marine heatwave nearly wiped out the tropical reef she was studying. “I watched a beautiful pristine reef melt down in 10 months,” she says. “I used to think overfishing was the biggest threat — then climate change came and hit me over the head.”

    Julia Baum records data on the Pacific atoll of Kiritimati, after a marine heatwave in 2015 nearly destroyed the coral reef.Credit: Kristina Tietjen

    That experience prompted her to completely overhaul her research programme to focus exclusively on climate impacts and how to mitigate them. “I want to do more than just document a sinking ship — I want to help right it,” she says.Baum’s tenured position offers her the flexibility of making that change, and she says she felt a moral obligation to apply her knowledge in a way that would help address the biggest threat facing the planet. As well as redirecting her research, Baum is designing a cross-university graduate-training programme focused on coastal climate solutions. This will offer training in professional skills that are crucial for climate work but are rarely taught in universities — such as how to collaborate and negotiate with non-academic partners, and how to deal with the media.But, like Krosby, Baum says she and many of her colleagues feel frustrated that a lot of universities don’t seem to value or support any kind of work outside conventional academic publications. Those who want to apply their findings to real-world problems often have to do it on their own, with no real benefit to their academic career. “Universities need to rise to the challenge and find innovative ways to support their faculty, by valuing and rewarding solutions work in their hiring and promotion criteria,” she says.If they don’t, universities risk losing more dedicated researchers such as Gilbert and Bell to the private sector. “If there comes a point when the climate-solutions impact I can have within academia seems too small, then yes, I would make the leap,” says Baum.Maximum impactFor academics looking for a way to take on a bigger role in the fight against climate change, there are a lot of options — from finding or making your own position in a university, to leaving for a company or charity that is doing more immediate, hands-on work. But the first step is working out where you can have the most impact, and what you can bring to the table. “For many people, the biggest impact you can have is through your students,” says Gilbert. “If you can focus on that and feel satisfied, that’s great.”For those who choose to leave, however, it pays to spend some time doing your research, finding companies and organizations that are doing the kind of work you are interested in, and talking to them about what you could offer. You might be surprised to find just how useful your skills can be outside academia — not just the disciplinary knowledge you have gained, but transferable skills such as technical writing and the ability to review and synthesize complex research. “The list of things we’re good at is pretty awesome,” says Gilbert. More

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    Plant phenology changes and drivers on the Qinghai–Tibetan Plateau

    Lieth, H. Phenology and Seasonality Modeling Vol. 8 (Springer, 2013).Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Change Biol. 25, 1922–1940 (2019).Article 

    Google Scholar 
    Shen, M. et al. Can changes in autumn phenology facilitate earlier green-up date of northern vegetation? Agric. For. Meteorol. 291, 108077 (2020).Article 

    Google Scholar 
    Menzel, A. et al. Climate change fingerprints in recent European plant phenology. Glob. Change Biol. 26, 2599–2612 (2020).Article 

    Google Scholar 
    Shen, X. et al. Asymmetric effects of daytime and nighttime warming on spring phenology in the temperate grasslands of China. Agric. For. Meteorol. 259, 240–249 (2018).Article 

    Google Scholar 
    Rudolf, V. H. W. The role of seasonal timing and phenological shifts for species coexistence. Ecol. Lett. 22, 1324–1338 (2019).
    Google Scholar 
    Zhu, J., Zhang, Y. & Wang, W. Interactions between warming and soil moisture increase overlap in reproductive phenology among species in an alpine meadow. Biol. Lett. 12, 20150749 (2016).Article 

    Google Scholar 
    Chen, J. et al. Plants with lengthened phenophases increase their dominance under warming in an alpine plant community. Sci. Total Environ. 728, 138891 (2020).Article 

    Google Scholar 
    Lian, X. et al. Summer soil drying exacerbated by earlier spring greening of northern vegetation. Sci. Adv. 6, eaax0255 (2020).Article 

    Google Scholar 
    Wolkovich, E. M. & Donahue, M. J. How phenological tracking shapes species and communities in non-stationary environments. Biol. Rev. Camb. Philos. Soc. 96, 2810–2827 (2021).Article 

    Google Scholar 
    Xu, X., Riley, W. J., Koven, C. D., Jia, G. & Zhang, X. Earlier leaf-out warms air in the north. Nat. Clim. Chang. 10, 370–375 (2020).Article 

    Google Scholar 
    D’Amato, G. et al. The effects of climate change on respiratory allergy and asthma induced by pollen and mold allergens. Allergy 75, 2219–2228 (2020).Article 

    Google Scholar 
    Garcia-Mozo, H. Poaceae pollen as the leading aeroallergen worldwide: a review. Allergy 72, 1849–1858 (2017).Article 

    Google Scholar 
    Ge, Q., Dai, J., Liu, J., Zhong, S. & Liu, H. The effect of climate change on the fall foliage vacation in China. Tour. Manag. 38, 80–84 (2013).Article 

    Google Scholar 
    Liu, J., Cheng, H., Jiang, D. & Huang, L. Impact of climate-related changes to the timing of autumn foliage colouration on tourism in Japan. Tour. Manag. 70, 262–272 (2019).Article 

    Google Scholar 
    Fan, B. et al. Earlier vegetation green-up has reduced spring dust storms. Sci. Rep. 4, 6749 (2014).Article 

    Google Scholar 
    Minoli, S. et al. Global response patterns of major rainfed crops to adaptation by maintaining current growing periods and irrigation. Earths Future 7, 1464–1480 (2019).Article 

    Google Scholar 
    Shen, M. et al. Plant phenological responses to climate change on the Tibetan Plateau: research status and challenges. Natl Sci. Rev. 22, 454–467 (2015).Article 

    Google Scholar 
    You, Q., Wang, D., Jiang, Z. & Kang, S. Diurnal temperature range in CMIP5 models and observations on the Tibetan Plateau. Q. J. R. Meteorol. Soc. 143, 1978–1989 (2017).Article 

    Google Scholar 
    You, Q. et al. Temperature dataset of CMIP6 models over China: evaluation, trend and uncertainty. Clim. Dyn. 57, 17–35 (2021).Article 

    Google Scholar 
    Zhu, Y.-Y. & Yang, S. Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5. Adv. Clim. Change Res. 11, 239–251 (2020).Article 

    Google Scholar 
    Lun, Y. et al. Assessment of GCMs simulation performance for precipitation and temperature from CMIP5 to CMIP6 over the Tibetan Plateau. Int. J. Climatol. 41, 3994–4018 (2021).Article 

    Google Scholar 
    Song, L., Zhuang, Q., Yin, Y., Wu, S. & Zhu, X. Intercomparison of model-estimated potential evapotranspiration on the Tibetan Plateau during 1981–2010. Earth Interact. 21, 1–22 (2017).Article 

    Google Scholar 
    You, Q., Min, J. & Kang, S. Rapid warming in the Tibetan Plateau from observations and CMIP5 models in recent decades. Int. J. Climatol. 36, 2660–2670 (2016).Article 

    Google Scholar 
    He, J.-S. et al. Above-belowground interactions in alpine ecosystems on the roof of the world. Plant Soil 458, 1–6 (2020).Article 

    Google Scholar 
    Kuang, X. & Jiao, J. J. Review on climate change on the Tibetan Plateau during the last half century. J. Geophys. Res. Atmos. 121, 3979–4007 (2016).Article 

    Google Scholar 
    Shen, M., Piao, S., Cong, N., Zhang, G. & Jassens, I. A. Precipitation impacts on vegetation spring phenology on the Tibetan Plateau. Glob. Change Biol. 21, 3647–3656 (2015).Article 

    Google Scholar 
    Shen, M., Tang, Y., Chen, J., Zhu, X. & Zheng, Y. Influences of temperature and precipitation before the growing season on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau. Agric. For. Meteorol. 151, 1711–1722 (2011).Article 

    Google Scholar 
    Ganjurjav, H. et al. Warming and precipitation addition interact to affect plant spring phenology in alpine meadows on the central Qinghai-Tibetan Plateau. Agric. For. Meteorol. 287, 107943 (2020).Article 

    Google Scholar 
    Peng, J., Wu, C., Wang, X. & Lu, L. Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau. Int. J. Climatol. 41, 3725–3742 (2021).Article 

    Google Scholar 
    Chen, X., An, S., Inouye, D. W. & Schwartz, M. D. Temperature and snowfall trigger alpine vegetation green-up on the world’s roof. Glob. Change Biol. 21, 3635–3646 (2015).Article 

    Google Scholar 
    Zheng, Z. et al. Continuous but diverse advancement of spring-summer phenology in response to climate warming across the Qinghai-Tibetan Plateau. Agric. For. Meteorol. 223, 194–202 (2016).Article 

    Google Scholar 
    Zhu, W. et al. Divergent shifts and responses of plant autumn phenology to climate change on the Qinghai-Tibetan Plateau. Agric. For. Meteorol. 239, 166–175 (2017).Article 

    Google Scholar 
    Sun, Q., Li, B., Jiang, Y., Chen, X. & Zhou, G. Declined trend in herbaceous plant green-up dates on the Qinghai–Tibetan Plateau caused by spring warming slowdown. Sci. Total Environ. 772, 145039 (2021).Article 

    Google Scholar 
    Sun, Q., Li, B., Zhou, G., Jiang, Y. & Yuan, Y. Delayed autumn leaf senescence date prolongs the growing season length of herbaceous plants on the Qinghai–Tibetan Plateau. Agric. For. Meteorol. 284, 107896 (2020).Article 

    Google Scholar 
    Jiang, Y. et al. Divergent shifts in flowering phenology of herbaceous plants on the warming Qinghai–Tibetan plateau. Agric. For. Meteorol. 307, 108502 (2021).Article 

    Google Scholar 
    Cong, N., Shen, M. & Piao, S. Spatial variations in responses of vegetation autumn phenology to climate change on the Tibetan Plateau. J. Plant Ecol. 10, 744–752 (2016).
    Google Scholar 
    Shi, C. et al. Effects of warming on chlorophyll degradation and carbohydrate accumulation of Alpine herbaceous species during plant senescence on the Tibetan Plateau. PLoS ONE 9, e107874 (2014).Article 

    Google Scholar 
    Morisette, J. T. et al. Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century. Front. Ecol. Environ. 7, 253–260 (2009).Article 

    Google Scholar 
    Kharouba, H. M. et al. Global shifts in the phenological synchrony of species interactions over recent decades. Proc. Natl Acad. Sci. USA 115, 5211–5216 (2018).Article 

    Google Scholar 
    Vitasse, Y. et al. Phenological and elevational shifts of plants, animals and fungi under climate change in the European Alps. Biol. Rev. Camb. Philos. Soc. 96, 1816–1835 (2021).Article 

    Google Scholar 
    Richardson, A. D. et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 169, 156–173 (2013).Article 

    Google Scholar 
    Keenan, T. F. et al. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nat. Clim. Chang. 4, 598–604 (2014).Article 

    Google Scholar 
    Estiarte, M. & Penuelas, J. Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency. Glob. Change Biol. 21, 1005–1017 (2015).Article 

    Google Scholar 
    Penuelas, J., Rutishauser, T. & Filella, I. Ecology. Phenology feedbacks on climate change. Science 324, 887–888 (2009).Article 

    Google Scholar 
    Piao, S. et al. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands. Nat. Clim. Chang. 7, 359–363 (2017).Article 

    Google Scholar 
    Ran, Y., Li, X. & Cheng, G. Climate warming over the past half century has led to thermal degradation of permafrost on the Qinghai–Tibet Plateau. Cryosphere 12, 595–608 (2018).Article 

    Google Scholar 
    Gao, T. et al. Accelerating permafrost collapse on the eastern Tibetan Plateau. Environ. Res. Lett. 16, 054023 (2021).Article 

    Google Scholar 
    Sun, R. et al. Interannual variability of the North Pacific mixed layer associated with the spring Tibetan Plateau thermal forcing. J. Clim. 32, 3109–3130 (2019).Article 

    Google Scholar 
    Zhang, J., Wu, L., Huang, G., Zhu, W. & Zhang, Y. The role of May vegetation greenness on the southeastern Tibetan Plateau for East Asian summer monsoon prediction. J. Geophys. Res. Atmos. 116, D05106 (2011).Article 

    Google Scholar 
    Wu, G. et al. Tibetan Plateau climate dynamics: recent research progress and outlook. Natl Sci. Rev. 2, 100–116 (2015).Article 

    Google Scholar 
    Wang, Y., Zhao, P., Yu, R. & Rasul, G. Inter-decadal variability of Tibetan spring vegetation and its associations with eastern China spring rainfall. Int. J. Climatol. 30, 856–865 (2010).Article 

    Google Scholar 
    Yu, H., Luedeling, E. & Xu, J. Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proc. Natl Acad. Sci. USA 107, 22151–22156 (2010).Article 

    Google Scholar 
    Shen, M. et al. Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai–Tibetan Plateau. Agric. For. Meteorol. 189-190, 71–80 (2014).Article 

    Google Scholar 
    Wang, X. et al. No consistent evidence for advancing or delaying trends in spring phenology on the Tibetan Plateau. J. Geophys. Res. Biogeosci. 122, 3288–3305 (2017).Article 

    Google Scholar 
    Wang, C. et al. Assessing phenological change and climatic control of alpine grasslands in the Tibetan Plateau with MODIS time series. Int. J. Biometeorol. 59, 11–23 (2015).Article 

    Google Scholar 
    Wang, K. et al. Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau. Int. J. Digit. Earth 8, 58–75 (2013).Article 

    Google Scholar 
    Meng, F., Huang, L., Chen, A., Zhang, Y. & Piao, S. Spring and autumn phenology across the Tibetan Plateau inferred from normalized difference vegetation index and solar-induced chlorophyll fluorescence. Big Earth Data 5, 182–200 (2021).Article 

    Google Scholar 
    Wang, X., Wu, C., Peng, D., Gonsamo, A. & Liu, Z. Snow cover phenology affects alpine vegetation growth dynamics on the Tibetan Plateau: satellite observed evidence, impacts of different biomes, and climate drivers. Agric. For. Meteorol. 256–257, 61–74 (2018).Article 

    Google Scholar 
    Li, P. et al. Change in autumn vegetation phenology and the climate controls from 1982 to 2012 on the Qinghai–Tibet Plateau. Front. Plant Sci. 10, 1677 (2019).Article 

    Google Scholar 
    Zhu, W., Zheng, Z., Jiang, N. & Zhang, D. A comparative analysis of the spatio-temporal variation in the phenologies of two herbaceous species and associated climatic driving factors on the Tibetan Plateau. Agric. For. Meteorol. 248, 177–184 (2018).Article 

    Google Scholar 
    Xia, J. et al. Interannual variation in the start of vegetation growing season and its response to climate change in the Qinghai–Tibet Plateau derived from MODIS data during 2001 to 2016. J. Appl. Remote Sens. 13, 048506 (2019).Article 

    Google Scholar 
    Huang, K. et al. Impacts of snow cover duration on vegetation spring phenology over the Tibetan Plateau. J. Plant Ecol. 12, 583–592 (2019).Article 

    Google Scholar 
    Li, P. et al. Dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China. Sci. Total Environ. 637-638, 855–864 (2018).Article 

    Google Scholar 
    Liu, X. et al. Driving forces of the changes in vegetation phenology in the Qinghai–Tibet Plateau. Remote Sens. 13, 4952 (2021).Article 

    Google Scholar 
    Piao, S. et al. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai–Xizang Plateau. Agric. For. Meteorol. 151, 1599–1608 (2011).Article 

    Google Scholar 
    Wang, Z. et al. Causes for the unimodal pattern of biomass and productivity in alpine grasslands along a large altitudinal gradient in semi-arid regions. J. Veg. Sci. 24, 189–201 (2013).Article 

    Google Scholar 
    Du, M. et al. in Proc. MODSIM 2007 Int. Congr. Model. Simul. (eds Oxley, L. & Kulasiri, D.) 2146–2152 (Modelling and Simulation Society of Australia and New Zealand, 2007).Wang, S. P. et al. Asymmetric sensitivity of first flowering date to warming and cooling in alpine plants. Ecology 95, 3387–3398 (2014).Article 

    Google Scholar 
    Che, M. et al. Spatial and temporal variations in the end date of the vegetation growing season throughout the Qinghai–Tibetan Plateau from 1982 to 2011. Agric. For. Meteorol. 189–190, 81–90 (2014).Article 

    Google Scholar 
    Zhang, G., Zhang, Y., Dong, J. & Xiao, X. Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011. Proc. Natl Acad. Sci. USA 110, 4309–4314 (2013).Article 

    Google Scholar 
    Maisongrande, P., Duchemin, B. & Dedieu, G. VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products. Int. J. Remote Sens. 25, 9–14 (2010).Article 

    Google Scholar 
    Didan, K., Munoz, A. B., Solano, R. & Huete, A. MODIS vegetation index user’s guide (MOD13 series) version 3.00, June 2015 (collection 6) (Univ. Arizona, 2015).Beck, H. E. et al. Global evaluation of four AVHRR–NDVI data sets: intercomparison and assessment against Landsat imagery. Remote Sens. Environ. 115, 2547–2563 (2011).Article 

    Google Scholar 
    Zhang, Y., Song, C., Band, L. E., Sun, G. & Li, J. Reanalysis of global terrestrial vegetation trends from MODIS products: browning or greening? Remote Sens. Environ. 191, 145–155 (2017).Article 

    Google Scholar 
    Zhang, Y., Joiner, J., Alemohammad, S. H., Zhou, S. & Gentine, P. A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks. Biogeosciences 15, 5779–5800 (2018).Article 

    Google Scholar 
    Ding, M. et al. Temperature dependence of variations in the end of the growing season from 1982 to 2012 on the Qinghai–Tibetan Plateau. GISci. Remote Sens. 53, 147–163 (2015).Article 

    Google Scholar 
    Cheng, M., Jin, J. & Jiang, H. Strong impacts of autumn phenology on grassland ecosystem water use efficiency on the Tibetan Plateau. Ecol. Indic. 126, 107682 (2021).Article 

    Google Scholar 
    Pedelty, J. et al. in Proc. 2007 IEEE Int. Geosci. Remote Sensing Symp. 1021–1025 (IEEE, 2007).Pinzon, J. & Tucker, C. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sens. 6, 6929–6960 (2014).Article 

    Google Scholar 
    Liu, Y., Liu, R. & Chen, J. M. Retrospective retrieval of long-term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data. J. Geophys. Res. Biogeosci. 117, G04003 (2012).Article 

    Google Scholar 
    Yang, B. et al. New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data. Proc. Natl Acad. Sci. USA 114, 6966–6971 (2017).Article 

    Google Scholar 
    Shishov, V. V. et al. VS-oscilloscope: a new tool to parameterize tree radial growth based on climate conditions. Dendrochronologia 39, 42–50 (2016).Article 

    Google Scholar 
    Zhao, Y., Zhou, T., Zhang, W. & Li, J. Change in precipitation over the Tibetan Plateau projected by weighted CMIP6 models. Adv. Atmos. Sci. 39, 1133–1150 (2022).Article 

    Google Scholar 
    Lalande, M., Ménégoz, M., Krinner, G., Naegeli, K. & Wunderle, S. Climate change in the High Mountain Asia in CMIP6. Earth Syst. Dyn. 12, 1061–1098 (2021).Article 

    Google Scholar 
    Jin, Z. et al. Temporal variability in the thermal requirements for vegetation phenology on the Tibetan plateau and its implications for carbon dynamics. Clim. Change 138, 617–632 (2016).Article 

    Google Scholar 
    Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).Article 

    Google Scholar 
    Cao, R., Shen, M., Zhou, J. & Chen, J. Modeling vegetation green-up dates across the Tibetan Plateau by including both seasonal and daily temperature and precipitation. Agric. For. Meteorol. 249, 176–186 (2018).Article 

    Google Scholar 
    Li, P. et al. Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change. Agric. For. Meteorol. 308–309, 108571 (2021).Article 

    Google Scholar 
    Lang, W., Chen, X., Qian, S., Liu, G. & Piao, S. A new process-based model for predicting autumn phenology: how is leaf senescence controlled by photoperiod and temperature coupling? Agric. For. Meteorol. 268, 124–135 (2019).Article 

    Google Scholar 
    Yang, Z. et al. Phylogenetic conservatism in heat requirement of leaf-out phenology, rather than temperature sensitivity, in Tibetan Plateau. Agric. For. Meteorol. 304-305, 108413 (2021).Article 

    Google Scholar 
    Gao, B., Li, J. & Wang, X. Impact of frozen soil changes on vegetation phenology in the source region of the Yellow River from 2003 to 2015. Theor. Appl. Climatol. 141, 1219–1234 (2020).Article 

    Google Scholar 
    Jiang, H. et al. The impacts of soil freeze/thaw dynamics on soil water transfer and spring phenology in the Tibetan Plateau. Arct. Antarct. Alp. Res. 50, e1439155 (2018).Article 

    Google Scholar 
    Li, G., Jiang, C., Cheng, T. & Bai, J. Grazing alters the phenology of alpine steppe by changing the surface physical environment on the northeast Qinghai-Tibet Plateau, China. J. Environ. Manage. 248, 109257 (2019).Article 

    Google Scholar 
    Du, J. et al. Interacting effects of temperature and precipitation on climatic sensitivity of spring vegetation green-up in arid mountains of China. Agric. For. Meteorol. 269–270, 71–77 (2019).Article 

    Google Scholar 
    Liu, L. et al. Effects of elevation on spring phenological sensitivity to temperature in Tibetan Plateau grasslands. Chin. Sci. Bull. 59, 4856–4863 (2014).Article 

    Google Scholar 
    Cong, N. et al. Little change in heat requirement for vegetation green-up on the Tibetan Plateau over the warming period of 1998–2012. Agric. For. Meteorol. 232, 650–658 (2017).Article 

    Google Scholar 
    Shen, M. et al. Strong impacts of daily minimum temperature on the green-up date and summer greenness of the Tibetan Plateau. Glob. Change Biol. 22, 3057–3066 (2016).Article 

    Google Scholar 
    Du, J. et al. Daily minimum temperature and precipitation control on spring phenology in arid-mountain ecosystems in China. Int. J. Climatol. 40, 2568–2579 (2020).Article 

    Google Scholar 
    Shen, M. Spring phenology was not consistently related to winter warming on the Tibetan Plateau. Proc. Natl Acad. Sci. USA 108, E91–E92 (2011).Article 

    Google Scholar 
    An, S. et al. Precipitation and minimum temperature are primary climatic controls of alpine grassland autumn phenology on the Qinghai-Tibet Plateau. Remote Sens. 12, 431 (2020).Article 

    Google Scholar 
    Zu, J. et al. Biological and climate factors co-regulated spatial-temporal dynamics of vegetation autumn phenology on the Tibetan Plateau. Int. J. Appl. Earth Obs. Geoinf. 69, 198–205 (2018).
    Google Scholar 
    Qiao, C. et al. Vegetation phenology in the Qilian mountains and its response to temperature from 1982 to 2014. Remote Sens. 13, 286 (2021).Article 

    Google Scholar 
    Yang, Z. et al. Asymmetric responses of the end of growing season to daily maximum and minimum temperatures on the Tibetan Plateau. J. Geophys. Res. Atmos. 122, 13,78–13,287 (2017).
    Google Scholar 
    Dorji, T. et al. Plant functional traits mediate reproductive phenology and success in response to experimental warming and snow addition in Tibet. Glob. Change Biol. 19, 459–472 (2013).Article 

    Google Scholar 
    Li, X., Zhang, L. & Luo, T. Rainy season onset mainly drives the spatiotemporal variability of spring vegetation green-up across alpine dry ecosystems on the Tibetan Plateau. Sci. Rep. 10, 18797 (2020).Article 

    Google Scholar 
    Zhang, X. et al. Effects of climate change on the growing season of alpine grassland in Northern Tibet, China. Glob. Ecol. Conserv. 23, e01126 (2020).Article 

    Google Scholar 
    Sun, Q. et al. A prognostic phenology model for alpine meadows on the Qinghai–Tibetan Plateau. Ecol. Indic. 93, 1089–1100 (2018).Article 

    Google Scholar 
    Zhu, J., Zhang, Y. & Jiang, L. Experimental warming drives a seasonal shift of ecosystem carbon exchange in Tibetan alpine meadow. Agric. For. Meteorol. 233, 242–249 (2017).Article 

    Google Scholar 
    Shen, M. et al. No evidence of continuously advanced green-up dates in the Tibetan Plateau over the last decade. Proc. Natl Acad. Sci. USA 110, E2329 (2013).
    Google Scholar 
    Fu, Y. S. et al. Variation in leaf flushing date influences autumnal senescence and next year’s flushing date in two temperate tree species. Proc. Natl Acad. Sci. USA 111, 7355–7360 (2014).Article 

    Google Scholar 
    Delpierre, N. et al. Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France. Agric. For. Meteorol. 149, 938–948 (2009).Article 

    Google Scholar 
    Keenan, T. F. & Richardson, A. D. The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models. Glob. Change Biol. 21, 2634–2641 (2015).Article 

    Google Scholar 
    Meng, F. D. et al. Changes in flowering functional group affect responses of community phenological sequences to temperature change. Ecology 98, 734–740 (2017).Article 

    Google Scholar 
    Wang, S. et al. Timing and duration of phenological sequences of alpine plants along an elevation gradient on the Tibetan plateau. Agric. For. Meteorol. 189–190, 220–228 (2014).Article 

    Google Scholar 
    Jiang, L. L. et al. Relatively stable response of fruiting stage to warming and cooling relative to other phenological events. Ecology 97, 1961–1969 (2016).Article 

    Google Scholar 
    Li, X. et al. Responses of sequential and hierarchical phenological events to warming and cooling in alpine meadows. Nat. Commun. 7, 12489 (2016).Article 

    Google Scholar 
    Meng, F. et al. Nonlinear responses of temperature sensitivities of community phenophases to warming and cooling events are mirroring plant functional diversity. Agric. For. Meteorol. 253–254, 31–37 (2018).Article 

    Google Scholar 
    Meng, F. et al. Divergent responses of community reproductive and vegetative phenology to warming and cooling: asymmetry versus symmetry. Front. Plant Sci. 10, 1310 (2019).Article 

    Google Scholar 
    Zhang, Z., Niu, K., Liu, X., Jia, P. & Du, G. Linking flowering and reproductive allocation in response to nitrogen addition in an alpine meadow. J. Plant Ecol. 7, 231–239 (2013).Article 

    Google Scholar 
    Xi, Y. et al. Nitrogen addition alters the phenology of a dominant alpine plant in Northern Tibet. Arct. Antarct. Alp. Res. 47, 511–518 (2018).Article 

    Google Scholar 
    Yin, T.-F., Zheng, L.-L., Cao, G.-M., Song, M.-H. & Yu, F.-H. Species-specific phenological responses to long-term nitrogen fertilization in an alpine meadow. J. Plant Ecol. 10, 301–309 (2016).
    Google Scholar 
    Liu, L. et al. Altered precipitation patterns and simulated nitrogen deposition effects on phenology of common plant species in a Tibetan Plateau alpine meadow. Agric. For. Meteorol. 236, 36–47 (2017).Article 

    Google Scholar 
    Liu, Y. et al. Effects of nitrogen addition and mowing on reproductive phenology of three early-flowering forb species in a Tibetan alpine meadow. Ecol. Eng. 99, 119–125 (2017).Article 

    Google Scholar 
    Zhu, J., Zhang, Y. & Liu, Y. Effects of short-term grazing exclusion on plant phenology and reproductive succession in a Tibetan alpine meadow. Sci. Rep. 6, 27781 (2016).Article 

    Google Scholar 
    Li, Y. et al. The effects of grazing regimes on phenological stages, intervals and divergences of alpine plants on the Qinghai–Tibetan Plateau. J. Veg. Sci. 30, 134–145 (2019).Article 

    Google Scholar 
    Dorji, T. et al. Impacts of climate change on flowering phenology and production in alpine plants: the importance of end of flowering. Agric. Ecosyst. Environ. 291, 106795 (2020).Article 

    Google Scholar 
    Meng, F. et al. Opposite effects of winter day and night temperature changes on early phenophases. Ecology 100, e02775 (2019).Article 

    Google Scholar 
    Meng, F. et al. Temperature sensitivity thresholds to warming and cooling in phenophases of alpine plants. Clim. Change 139, 579–590 (2016).Article 

    Google Scholar 
    Suonan, J., Classen, A. T., Sanders, N. J. & He, J. S. Plant phenological sensitivity to climate change on the Tibetan Plateau and relative to other areas of the world. Ecosphere 10, e02543 (2019).Article 

    Google Scholar 
    Ganjurjav, H. et al. Phenological changes offset the warming effects on biomass production in an alpine meadow on the Qinghai–Tibetan Plateau. J. Ecol. 109, 1014–1025 (2020).Article 

    Google Scholar 
    Jiang, Z. et al. Extreme climate events in China: IPCC-AR4 model evaluation and projection. Clim. Change 110, 385–401 (2011).Article 

    Google Scholar 
    Huang, X. et al. Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China. Cryosphere 10, 2453–2463 (2016).Article 

    Google Scholar 
    Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2019).Article 

    Google Scholar 
    Wang, C. & Tang, Y. Responses of plant phenology to nitrogen addition: a meta-analysis. Oikos 128, 1243–1253 (2019).Article 

    Google Scholar 
    Chen, H., Zhu, Q., Wu, N., Wang, Y. & Peng, C. H. Delayed spring phenology on the Tibetan Plateau may also be attributable to other factors than winter and spring warming. Proc. Natl Acad. Sci. USA 108, E93 (2011).
    Google Scholar 
    Zhang, L. et al. Effect of warming and degradation on phenophases of Kobresia pygmaea and Potentilla multifida on the Tibetan Plateau. Agric. Ecosyst. Environ. 300, 106998 (2020).Article 

    Google Scholar 
    Lin, X. et al. Fluxes of CO2, CH4, and N2O in an alpine meadow affected by yak excreta on the Qinghai-Tibetan plateau during summer grazing periods. Soil Biol. Biochem. 41, 718–725 (2009).Article 

    Google Scholar 
    Sa, C. et al. Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau. J. Arid Land 13, 332–349 (2021).Article 

    Google Scholar 
    Zheng, J., Xu, X., Jia, G. & Wu, W. Understanding the spring phenology of Arctic tundra using multiple satellite data products and ground observations. Sci. China Earth Sci. 63, 1599–1612 (2020).Article 

    Google Scholar 
    Wu, W., Sun, Y., Xiao, K. & Xin, Q. Development of a global annual land surface phenology dataset for 1982–2018 from the AVHRR data by implementing multiple phenology retrieving methods. Int. J. Appl. Earth Obs. Geoinf. 103, 102487 (2021).
    Google Scholar 
    Karkauskaite, P., Tagesson, T. & Fensholt, R. Evaluation of the plant phenology index (PPI), NDVI and EVI for start-of-season trend analysis of the Northern Hemisphere boreal zone. Remote Sens. 9, 485 (2017).Article 

    Google Scholar 
    Yang, Y., Guan, H., Shen, M., Liang, W. & Jiang, L. Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010. Glob. Change Biol. 21, 652–665 (2015).Article 

    Google Scholar 
    Zhang, J. et al. Comparison of land surface phenology in the Northern Hemisphere based on AVHRR GIMMS3g and MODIS datasets. ISPRS J. Photogramm. Remote Sens. 169, 1–16 (2020).Article 

    Google Scholar 
    Shen, M. et al. Earlier-season vegetation has greater temperature sensitivity of spring phenology in northern hemisphere. PLoS ONE 9, e88178 (2014).Article 

    Google Scholar 
    Zhang, H., Yuan, W., Liu, S., Dong, W. & Fu, Y. Sensitivity of flowering phenology to changing temperature in China. J. Geophys. Res. Biogeosci. 120, 1658–1665 (2015).Article 

    Google Scholar 
    Cook, B. I. et al. Sensitivity of spring phenology to warming across temporal and spatial climate gradients in two independent databases. Ecosystems 15, 1283–1294 (2012).Article 

    Google Scholar 
    Wang, C., Cao, R., Chen, J., Rao, Y. & Tang, Y. Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere. Ecol. Indic. 50, 62–68 (2015).Article 

    Google Scholar 
    Gao, M. et al. Three-dimensional change in temperature sensitivity of northern vegetation phenology. Glob. Change Biol. 26, 5189–5201 (2020).Article 

    Google Scholar 
    Zohner, C. M., Benito, B. M., Fridley, J. D., Svenning, J. C. & Renner, S. S. Spring predictability explains different leaf-out strategies in the woody floras of North America, Europe and East Asia. Ecol. Lett. 20, 452–460 (2017).Article 

    Google Scholar 
    Fu, Y. H. et al. Daylength helps temperate deciduous trees to leaf-out at the optimal time. Glob. Change Biol. 25, 2410–2418 (2019).Article 

    Google Scholar 
    Huang, J. G. et al. Photoperiod and temperature as dominant environmental drivers triggering secondary growth resumption in Northern Hemisphere conifers. Proc. Natl Acad. Sci. USA 117, 20645–20652 (2020).Article 

    Google Scholar 
    Iler, A. M., CaraDonna, P. J., Forrest, J. R. K. & Post, E. Demographic consequences of phenological shifts in response to climate change. Annu. Rev. Ecol. Evol. Syst. 52, 221–245 (2021).Article 

    Google Scholar 
    Chen, S., Huang, Y., Gao, S. & Wang, G. Impact of physiological and phenological change on carbon uptake on the Tibetan Plateau revealed through GPP estimation based on spaceborne solar-induced fluorescence. Sci. Total Environ. 663, 45–59 (2019).Article 

    Google Scholar 
    Jin, J. et al. Grassland production in response to changes in biological metrics over the Tibetan Plateau. Sci. Total Environ. 666, 641–651 (2019).Article 

    Google Scholar 
    Kang, X. et al. Variability and changes in climate, phenology, and gross primary production of an alpine wetland ecosystem. Remote Sens. 8, 391 (2016).Article 

    Google Scholar 
    Zheng, Z., Zhu, W. & Zhang, Y. Direct and lagged effects of spring phenology on net primary productivity in the alpine grasslands on the Tibetan Plateau. Remote Sens. 12, 1223 (2020).Article 

    Google Scholar 
    Wang, S. et al. Responses of net primary productivity to phenological dynamics in the Tibetan Plateau, China. Agric. For. Meteorol. 232, 235–246 (2017).Article 

    Google Scholar 
    Li, S., Zhang, H., Zhou, X., Yu, H. & Li, W. Enhancing protected areas for biodiversity and ecosystem services in the Qinghai–Tibet Plateau. Ecosyst. Serv. 43, 101090 (2020).Article 

    Google Scholar 
    Meng, F. et al. Enhanced spring temperature sensitivity of carbon emission links to earlier phenology. Sci. Total Environ. 745, 140999 (2020).Article 

    Google Scholar 
    Hu, G. et al. The divergent impact of phenology change on the productivity of alpine grassland due to different timing of drought on the Tibetan Plateau. Land Degrad. Dev. 32, 4033–4041 (2021).Article 

    Google Scholar 
    Li, P., Zhu, W. & Xie, Z. Diverse and divergent influences of phenology on herbaceous aboveground biomass across the Tibetan Plateau alpine grasslands. Ecol. Indic. 121, 107036 (2021).Article 

    Google Scholar 
    He, M. et al. Relationships between wood formation and cambium phenology on the Tibetan Plateau during 1960–2014. Forests 9, 86 (2018).Article 

    Google Scholar 
    Wang, J., Li, M., Yu, C. & Fu, G. The change in environmental variables linked to climate change has a stronger effect on aboveground net primary productivity than does phenological change in alpine grasslands. Front. Plant Sci. 12, 798633 (2022).Article 

    Google Scholar 
    Shen, W., Zhang, L. & Luo, T. Causes for the increase of early-season freezing events under a warmer climate at alpine treelines in southeast Tibet. Agric. For. Meteorol. 316, 108863 (2022).Article 

    Google Scholar 
    Ye, D.-Z. & Wu, G.-X. The role of the heat source of the Tibetan Plateau in the general circulation. Meteorol. Atmos. Phys. 67, 181–198 (1998).Article 

    Google Scholar 
    Cao, R., Feng, Y., Liu, X., Shen, M. & Zhou, J. Uncertainty of vegetation green-up date estimated from vegetation indices due to snowmelt at northern middle and high latitudes. Remote Sens. 12, 190 (2020).Article 

    Google Scholar 
    Zeng, L., Wardlow, B. D., Xiang, D., Hu, S. & Li, D. A review of vegetation phenological metrics extraction using time-series, multispectral satellite data. Remote Sens. Environ. 237, 111511 (2020).Article 

    Google Scholar 
    Cao, R. et al. A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter. Remote Sens. Environ. 217, 244–257 (2018).Article 

    Google Scholar 
    Chen, J. et al. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter. Remote Sens. Environ. 91, 332–344 (2004).Article 

    Google Scholar 
    Wang, C. et al. A snow-free vegetation index for improved monitoring of vegetation spring green-up date in deciduous ecosystems. Remote Sens. Environ. 196, 1–12 (2017).Article 

    Google Scholar 
    Yang, W. et al. A semi-analytical snow-free vegetation index for improving estimation of plant phenology in tundra and grassland ecosystems. Remote Sens. Environ. 228, 31–44 (2019).Article 

    Google Scholar 
    Wang, C., Chen, J., Tang, Y., Black, T. A. & Zhu, K. A novel method for removing snow melting-induced fluctuation in GIMMS NDVI3g data for vegetation phenology monitoring: a case study in deciduous forests of North America. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 11, 800–807 (2018).Article 

    Google Scholar 
    Helman, D. Land surface phenology: What do we really ‘see’ from space? Sci. Total Environ. 618, 665–673 (2018).Article 

    Google Scholar 
    Steltzer, H. & Post, E. Ecology. Seasons and life cycles. Science 324, 886–887 (2009).Article 

    Google Scholar 
    Liang, L., Schwartz, M. D. & Fei, S. Validating satellite phenology through intensive ground observation and landscape scaling in a mixed seasonal forest. Remote Sens. Environ. 115, 143–157 (2011).Article 

    Google Scholar 
    Li, R. et al. Leaf unfolding of Tibetan alpine meadows captures the arrival of monsoon rainfall. Sci. Rep. 6, 20985 (2016).Article 

    Google Scholar 
    Tang, J. et al. Emerging opportunities and challenges in phenology: a review. Ecosphere 7, e01436 (2016).Article 

    Google Scholar 
    Van Nuland, M. E. et al. Natural soil microbiome variation affects spring foliar phenology with consequences for plant productivity and climate-driven range shifts. New Phytol. 232, 762–775 (2021).Article 

    Google Scholar 
    Mutz, J., McClory, R., van Dijk, L. J. A., Ehrlen, J. & Tack, A. J. M. Pathogen infection influences the relationship between spring and autumn phenology at the seedling and leaf level. Oecologia 197, 447–457 (2021).Article 

    Google Scholar 
    Radville, L., McCormack, M. L., Post, E. & Eissenstat, D. M. Root phenology in a changing climate. J. Exp. Bot. 67, 3617–3628 (2016).Article 

    Google Scholar 
    Gao, M. et al. Divergent changes in the elevational gradient of vegetation activities over the last 30 years. Nat. Commun. 10, 2970 (2019).Article 

    Google Scholar  More

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    Author Correction: A new wave of marine fish invasions through the Panama and Suez canals

    Authors and AffiliationsSmithsonian Tropical Research Institute – STRI, Balboa, Republic of PanamaGustavo A. Castellanos-Galindo, D. Ross Robertson, Diana M. T. Sharpe & Mark E. TorchinLeibniz Centre for Tropical Marine Research (ZMT), Bremen, GermanyGustavo A. Castellanos-GalindoAuthorsGustavo A. Castellanos-GalindoD. Ross RobertsonDiana M. T. SharpeMark E. TorchinCorresponding authorCorrespondence to
    Gustavo A. Castellanos-Galindo. More

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    Structural diagnosis of benthic invertebrate communities in relation to salinity gradient in Baltic coastal lake ecosystems using biological trait analysis

    Dauvin, J. C. et al. The well sorted fine sand community from the western Mediterranean Sea: A resistant and resilient marine habitat under diverse human pressures. Environ. Pollut. 224, 336–351 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Obolewski, K. & Glińska-Lewczuk, K. Connectivity and complexity of coastal lakes as determinants for their restoration-A case study of the southern Baltic Sea. Ecol. Eng. 155, 1700 (2020).Article 

    Google Scholar 
    Dobrowolski, Z. Occurrence of macrobenthos in different littoral habitats of the polymictic Lebsko lake. Ekologia Polska 42, 19–40 (1994).
    Google Scholar 
    Paturej, E., Gutkowska, A. & Durczak, K. Biodiversity and indicative role of zooplankton in the shallow macrophyte-dominated lake Łuknajno. Pol. J. Nat. Sci. 27, 53–66 (2012).
    Google Scholar 
    Obolewski, K. et al. Patterns of salinity regime in coastal lakes based on structure of benthic invertebrates. PLoS ONE 13, 150 (2018).Article 
    CAS 

    Google Scholar 
    Lew, S., Glińska-Lewczuk, K. & Lew, M. The effects of environmental parameters on the microbial activity in peat-bog lakes. PLoS ONE 14, 179 (2019).
    Google Scholar 
    Bremner, J. Species’ traits and ecological functioning in marine conservation and management. J. Exp. Mar. Biol. Ecol. 366, 37–47 (2008).Article 

    Google Scholar 
    Törnroos, A. & Bonsdorff, E. Developing the multitrait concept for functional diversity: Lessons from a system rich in functions but poor in species. Ecol. Appl. 22, 2221–2236 (2012).PubMed 
    Article 

    Google Scholar 
    Baldrighi, E. & Manini, E. Deep-sea meiofauna and macrofauna diversity and functional diversity: are they related?. Mar. Biodivers. 45, 469–488 (2015).Article 

    Google Scholar 
    Belley, R. & Snelgrove, P. V. R. Relative contributions of biodiversity and environment to benthic ecosystem functioning. Front. Mar. Sci. 3, 7598 (2016).Article 

    Google Scholar 
    Díaz, S. & Cabido, M. Vive la différence: Plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).Article 

    Google Scholar 
    Gagic, V. et al. Functional identity and diversity of animals predict ecosystem functioning better than species-based indices. Proc. R. Soc. B Biol. Sci. 282, 689 (2015).
    Google Scholar 
    Ding, N. et al. Different responses of functional traits and diversity of stream macroinvertebrates to environmental and spatial factors in the Xishuangbanna watershed of the upper Mekong River Basin, China. Sci. Total Environ. 574, 288–299 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Kenny, A. J. et al. Assessing cumulative human activities, pressures, and impacts on North Sea benthic habitats using a biological traits approach. ICES J. Mar. Sci. 75, 1080–1092 (2018).Article 

    Google Scholar 
    Llanos, E. N., Saracho Bottero, M. A., Jaubet, M. L., Elías, R. & Garaffo, G. V. Functional diversity in the intertidal macrobenthic community at sewage-affected shores from Southwestern Atlantic. Mar. Pollut. Bull. 157, 7448 (2020).Article 
    CAS 

    Google Scholar 
    Paganelli, D., Marchini, A. & Occhipinti-Ambrogi, A. Functional structure of marine benthic assemblages using Biological Traits Analysis (BTA): A study along the Emilia-Romagna coastline (Italy, North-West Adriatic Sea). Estuar. Coast. Shelf Sci. 96, 245–256 (2012).ADS 
    Article 

    Google Scholar 
    Nasi, F. et al. Functional biodiversity of marine soft-sediment polychaetes from two Mediterranean coastal areas in relation to environmental stress. Mar. Environ. Res. 137, 121–132 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Harwell, M. A. et al. Conceptual framework for assessing ecosystem health. Integr. Environ. Assess. Manag. 15, 544–564 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hu, C. et al. Macrobenthos functional trait responses to heavy metal pollution gradients in a temperate lagoon. Environ. Pollut. 253, 1107–1116 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ramsay, K., Kaiser, M. J. & Hughes, R. N. Responses of benthic scavengers to fishing disturbance by towed gears in different habitats. J. Exp. Mar. Biol. Ecol. 224, 4458 (1998).Article 

    Google Scholar 
    Sigala, K., Reizopoulou, S., Basset, A. & Nicolaidou, A. Functional diversity in three Mediterranean transitional water ecosystems. Estuar. Coast. Shelf Sci. 110, 202–209 (2012).ADS 
    Article 

    Google Scholar 
    de Loiola, P. P., Cianciaruso, M. V., Silva, I. A. & Batalha, M. A. Functional diversity of herbaceous species under different fire frequencies in Brazilian savannas. Flora Morphol. Distrib. Funct. Ecol. Plants 205, 674–681 (2010).Article 

    Google Scholar 
    Schleuter, D., Daufresne, M., Massol, F. & Argillier, C. A user’s guide to functional diversity indices. Ecological Monographs vol. 80 http://www.scopus.com/scopus/search/form.urli (2010).Wan, H. W. M. R., Cooper, K. M., Froján, C. R. S. B., Defew, E. C. & Paterson, D. M. Impacts of physical disturbance on the recovery of a macrofaunal community: A comparative analysis using traditional and novel approaches. Ecol. Indicators 12, 37–45 (2012).Article 

    Google Scholar 
    Millet, B. & Guelorget, O. Spatial and seasonal variability in the relationships between benthic communities and physical environment in a lagoon ecosystem. Mar. Ecol. Prog. Ser. 108, 161–174 (1994).ADS 
    Article 

    Google Scholar 
    McLusky, D. S. & Elliott, M. The Estuarine Ecosystem (Oxford University Press, 2004). https://doi.org/10.1093/acprof:oso/9780198525080.001.0001.Book 

    Google Scholar 
    Mrozińska, N. & Bąkowska, M. Effects of heavy metals in lake water and sediments on bottom invertebrates inhabiting the brackish coastal lake Łebsko on the southern baltic coast. Int. J. Environ. Res. Public Health 17, 1–19 (2020).Article 
    CAS 

    Google Scholar 
    Petchey, O. L. & Gaston, K. J. Functional diversity: Back to basics and looking forward. Ecol. Lett. 9, 741–758 (2006).PubMed 
    Article 

    Google Scholar 
    Villéger, S., Miranda, J. R., Hernández, D. F. & Mouillot, D. Contrasting changes in taxonomic vs. functional diversity of tropical fish communities after habitat degradation. Ecol. Appl. 20, 1512–1522 (2010).PubMed 
    Article 

    Google Scholar 
    Dolédec, S. & Statzner, B. Theoretical habitat templets, species traits, and species richness: 548 plant and animal species in the Upper Rhône River and its floodplain. Freshw. Biol. 31, 523–538 (1994).Article 

    Google Scholar 
    Usseglio-Polatera, P., Bournaud, M., Richoux, P. & Tachet, H. Biomonitoring through biological traits of benthic macroinvertebrates: How to use species trait databases?. Hydrobiologia 422, 153–162 (2000).Article 

    Google Scholar 
    Charvet, S., Statzner, B., Usseglio-Polatera, P. & Dumont, B. Traits of benthic macroinvertebrates in semi-natural French streams: An initial application to biomonitoring in Europe. Freshw. Biol. 43, 277–296 (2000).Article 

    Google Scholar 
    Statzner, B., Dolédec, S. & Hugueny, B. Biological trait composition of European stream invertebrate communities: Assessing the effects of various trait filter types. Ecography 27, 470–488 (2004).Article 

    Google Scholar 
    Bremner, J., Rogers, S. I. & Frid, C. L. J. Assessing functional diversity in marine benthic ecosystems: A comparison of approaches. Mar Ecol Prog Ser 254, 5589 (2003).Article 

    Google Scholar 
    Tillin, H., Hiddink, J., Jennings, S. & Kaiser, M. Chronic bottom trawling alters the functional composition of benthic invertebrate communities on a sea-basin scale. Mar. Ecol. Prog. Ser. 318, 31–45 (2006).ADS 
    Article 

    Google Scholar 
    Marchini, A., Munari, C. & Mistri, M. Functions and ecological status of eight Italian lagoons examined using biological traits analysis (BTA). Mar. Pollut. Bull. 56, 1076–1085 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Boikova, E., Botva, U. & Līcīte, V. Implementation of trophic status index in brackish water quality assessment of baltic coastal waters. Proc. Latv. Acad. Sci. Sect. B 62, 115–119 (2008).CAS 

    Google Scholar 
    Wielgat-Rychert, M., Jarosiewicz, A., Ficek, D., Pawlik, M. & Rychert, K. Nutrient fluxes and their impact on the phytoplankton in a Shallow Coastal Lake. Polish J. Environ. Stud. 24, 7780 (2015).Article 
    CAS 

    Google Scholar 
    Kruk, C., Devercelli, M. & Huszar, V. L. Reynolds Functional Groups: A trait-based pathway from patterns to predictions. Hydrobiologia 848, 113–129 (2021).Article 

    Google Scholar 
    Trojanowski, J., Trojanowska, C. & Korzeniewski, K. Trophic state of coastal lakes. Polish Arch. Hydrobiol. 38, 23–34 (1975).
    Google Scholar 
    Astel, A. M., Bigus, K., Obolewski, K. & Glińska-Lewczuk, K. Spatiotemporal assessment of water chemistry in intermittently open/closed coastal lakes of Southern Baltic. Estuar. Coast. Shelf Sci. 182, 47–59 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Choiński, A. Changes in morphometrics of the coastal lakes. in Hydroecological Determinants of Functioning of Southern Baltic Coastal Lakes (eds. Obolewski, K., Astel, A. & Kujawa, R.) 26–37 (PWN, 2017).Obolewski, K., Glińska-Lewczuk, K., Bąkowska, M., Szymańska, M. & Mrozińska, N. Patterns of phytoplankton composition in coastal lakes differed by connectivity with the Baltic Sea. Sci. Total Environ. 631–632, 951–961 (2018).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Szymańska-Walkiewicz, M., Glińska-Lewczuk, K., Burandt, P. & Obolewski, K. Phytoplankton sensitivity to heavy metals in Baltic Coastal Lakes. Int. J. Environ. Res. Public Health 19, 4131 (2022).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Mrozińska, N., Glińska-Lewczuk, K. & Obolewski, K. Salinity as a key factor on the benthic fauna diversity in the coastal lakes. Animals 11, 7440 (2021).Article 

    Google Scholar 
    Bremner, J., Rogers, S. I. & Frid, C. L. J. Methods for describing ecological functioning of marine benthic assemblages using biological traits analysis (BTA). Ecol. Ind. 6, 609–622 (2006).Article 

    Google Scholar 
    Papageorgiou, N., Sigala, K. & Karakassis, I. Changes of macrofaunal functional composition at sedimentary habitats in the vicinity of fish farms. Estuar. Coast. Shelf Sci. 83, 561–568 (2009).ADS 
    CAS 
    Article 

    Google Scholar 
    Lam-Gordillo, O., Baring, R. & Dittmann, S. Ecosystem functioning and functional approaches on marine macrobenthic fauna: A research synthesis towards a global consensus. Ecol Indic 115, 5589 (2020).Article 

    Google Scholar 
    Kołodziejczyk, A. & Koperski, P. Bezkręgowce słodkowodne Polski: klucz do oznaczania oraz podstawy biologii i ekologii makrofauny. (Wydawnictwa Uniwersytetu Warszawskiego, 2000).Wiederholm, Torgny. Chironomidae of the Holarctic Region: Keys and Diagnoses. Part 1: larvae. (1983).Antsulevich, A. et al. Helcom, 2012. Development of a set of core indicators: Interim report of the HELCOM CORESET project. PART A. Description of the selection process. (2012).Piechocki, A. & Wawrzyniak-Wydrowska, B. Guide to Freshwater and Marine Mollusca of Poland. (2016).Zettler, M. L. et al. Biodiversity gradient in the Baltic Sea: A comprehensive inventory of macrozoobenthos data. Helgol. Mar. Res. 68, 49–57 (2014).ADS 
    Article 

    Google Scholar 
    Palomares, M. L. D. & Pauly, D. SeaLifeBase. https://www.sealifebase.ca/ (2021).MarLIN. BIOTIC-biological traits information catalogue. Marine Life Information Network. Plymouth: Marine Biological Association of the UK. http://www.marlin.ac.uk/biotic/ (2006).Horton, T. et al. World Register of Marine Species (WoRMS). https://www.marinespecies.org (2021).Chevene, F., Doleadec, S. & Chessel, D. A fuzzy coding approach for the analysis of long-term ecological data. Freshw. Biol. 31, 295–309 (1994).Article 

    Google Scholar 
    Oug, E., Fleddum, A., Rygg, B. & Olsgard, F. Biological traits analyses in the study of pollution gradients and ecological functioning of marine soft bottom species assemblages in a fjord ecosystem. J. Exp. Mar. Biol. Ecol. 432–433, 94–105 (2012).Article 

    Google Scholar 
    Egres, A. G., Hatje, V., Miranda, D. A., Gallucci, F. & Barros, F. Functional response of tropical estuarine benthic assemblages to perturbation by Polycyclic Aromatic Hydrocarbons. Ecol. Ind. 96, 229–240 (2019).CAS 
    Article 

    Google Scholar 
    Charvet, S., Kosmala, A. & Statzner, B. Biomonitoring through biological traits of benthic macroinvertebrates: Perspectives for a general tool in stream management. Fundam. Appl. Limnol. 142, 415–432 (1998).Article 

    Google Scholar 
    Clarke, K. R. & Gorley, R. N. PRIMER v6: User Manual/Tutorial. (2006).Dobrowolski, Z. Density, biomass, and distribution of benthic invertebrates in the mid-lake zone of the coastal Lake Gardno. Oceanol. Stud. 30, 39–58 (2001).
    Google Scholar 
    Michaud, E., Desrosiers, G., Mermillod-Blondin, F., Sundby, B. & Stora, G. The functional group approach to bioturbation: II. The effects of the Macoma balthica community on fluxes of nutrients and dissolved organic carbon across the sediment-water interface. J. Exp. Mar. Biol. Ecol. 337, 178–189 (2006).CAS 
    Article 

    Google Scholar 
    Taurusman, A. A. Community structure of macrozoobenthic feeding guilds in responses to eutrophication in Jakarta Bay. Biodivers. J. Biol. Divers. 11, 998 (2010).Article 

    Google Scholar 
    Uwadiae, R. E. Macroinvertebrates functional feeding groups as indices of biological assessment in a tropical aquatic ecosystem: implications for ecosystem functions. New York Sci. J. 3, 778 (2010).
    Google Scholar 
    Obolewski, K., Glińska-Lewczuk, K., Sidoruk, M. & Szymańska, M. M. Response of benthic fauna to habitat heterogeneity in a shallow temperate lake. Animals 11, 558 (2021).Article 

    Google Scholar 
    Rhoads, D. C. Organism-sediment relations on the muddy sea floor. in Oceanography and Marine Biology: An Annual Review. vol. 12 263–300 (Aberdeen University Press/Allen & Unwin, 1974).Thrush, S. F., Hewitt, J. E., Gibbs, M., Lundquist, C. & Norkko, A. Functional role of large organisms in intertidal communities: Community effects and ecosystem function. Ecosystems 9, 1029–1040 (2006).Article 

    Google Scholar 
    Frid, C. L. J., Harwood, K. G., Hall, S. J. & Hall, J. A. Long-term changes in the benthic communities on North Sea fishing grounds. in ICES Journal of Marine Science vol. 57 1303–1309 (Academic Press, 2000).Bradshaw, C., Veale, L. O. & Brand, A. R. The role of scallop-dredge disturbance in long-term changes in Irish Sea benthic communities: A re-analysis of an historical dataset. J. Sea Res. 47, 161–184 (2002).ADS 
    Article 

    Google Scholar 
    Cañedo-Argüelles, M. et al. Can salinity trigger cascade effects on streams? A mesocosm approach. Sci. Total Environ. 540, 3–10 (2016).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Herbst, D. B. Salinity controls on trophic interactions among invertebrates and algae of solar evaporation ponds in the Mojave Desert and relation to shorebird foraging and selenium risk. Wetlands 26, 475–485 (2006).Article 

    Google Scholar 
    Merritt, R. W. et al. Development and application of a macroinvertebrate functional-group approach in the bioassessment of remnant river oxbows in southwest Florida. Am. Benthol. Soc. 21, 550 (2002).Article 

    Google Scholar 
    de Roos, A. M., Persson, L. & McCauley, E. The influence of size-dependent life-history traits on the structure and dynamics of populations and communities. Ecol. Lett. 6, 473–487 (2003).Article 

    Google Scholar 
    Reizopoulou, S. & Nicolaidou, A. Index of size distribution (ISD): A method of quality assessment for coastal lagoons. Hydrobiologia 577, 141–149 (2007).Article 

    Google Scholar 
    Basset, A., Pinna, M., Sabetta, L., Barbone, E. & Galuppo, N. Hierarchical scaling of biodiversity in lagoon ecosystems. Trans. Waters Bull. 2, 75–86 (2008).
    Google Scholar 
    Basset, A. et al. A benthic macroinvertebrate size spectra index for implementing the Water Framework Directive in coastal lagoons in Mediterranean and Black Sea ecoregions. Ecol. Ind. 12, 72–83 (2012).Article 

    Google Scholar 
    Robson, B. J., Barmuta, L. A. & Fairweather, P. G. Methodological and conceptual issues in the search for a relationship between animal body-size distributions and benthic habitat architecture. Mar. Freshw. Res. 56, 1–11 (2005).Article 

    Google Scholar 
    Parry, D. M., Kendall, M. A., Rowden, A. A. & Widdicombe, S. Species body size distribution patterns of marine benthic macrofauna assemblages from contrasting sediment types. J. Mar. Biol. Assoc. U.K. 79, 793–801 (1999).Article 

    Google Scholar 
    Netto, S. A., Domingos, A. M. & Kurtz, M. N. Effects of artificial breaching of a temporarily open/closed estuary on benthic macroinvertebrates (Camacho Lagoon, Southern Brazil). Estuaries Coasts 35, 1069–1081 (2012).CAS 
    Article 

    Google Scholar 
    Folke, C. et al. Regime shifts, resilience, and biodiversity in ecosystem management. Annu. Rev. Ecol. Evol. Syst. 35, 557–581 (2004).Article 

    Google Scholar 
    Montefalcone, M., Parravicini, V. & Bianchi, C. N. Quantification of Coastal Ecosystem Resilience. in Treatise on Estuarine and Coastal Science 49–70 (Elsevier, 2011). https://doi.org/10.1016/B978-0-12-374711-2.01003-2.Sasaki, T., Furukawa, T., Iwasaki, Y., Seto, M. & Mori, A. S. Perspectives for ecosystem management based on ecosystem resilience and ecological thresholds against multiple and stochastic disturbances. Ecol. Ind. 57, 395–408 (2015).Article 

    Google Scholar 
    Smee, D. L., Reustle, J. W., Belgrad, B. A. & Pettis, E. L. Storms promote ecosystem resilience by alleviating fishing. Curr. Biol. 30, R869–R870 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Gilby, B. L. et al. Umbrellas can work under water: Using threatened species as indicator and management surrogates can improve coastal conservation. Estuar. Coast. Shelf Sci. 199, 132–140 (2017).ADS 
    Article 

    Google Scholar 
    Henderson, C. J. et al. Landscape transformation alters functional diversity in coastal seascapes. Ecography 43, 138–148 (2020).Article 

    Google Scholar 
    Yeager, L. A., Geyer, J. K. & Fodrie, F. J. Trait sensitivities to seagrass fragmentation across spatial scales shape benthic community structure. J. Anim. Ecol. 88, 1743–1754 (2019).PubMed 
    Article 

    Google Scholar 
    Darr, A., Gogina, M. & Zettler, M. L. Functional changes in benthic communities along a salinity gradient- a western Baltic case study. J. Sea Res. 85, 315–324 (2014).ADS 
    Article 

    Google Scholar 
    Statzner, B., Bady, P., Dolédec, S. & Schöll, F. Invertebrate traits for the biomonitoring of large European rivers: An initial assessment of trait patterns in least impacted river reaches. Freshw. Biol. 50, 2136–2161 (2005).Article 

    Google Scholar  More

  • in

    Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world

    IPCC. Climate Change 2021: The Physical Science Basis. (eds Masson-Delmotte, V. et al.) Contribution of working group 1 to the ‘Sixth assessment report of the intergovernmental panel on climate change’ (Cambridge University Press, 2021).Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion under climate change. Nat. Clim. Change 6, 166–171 (2016).Article 

    Google Scholar 
    Greve, P. et al. Global assessment of trends in wetting and drying over land. Nat. Geosc. 7, 716–721 (2014).CAS 
    Article 

    Google Scholar 
    Lin, L., Gettelman, A., Feng, S. & Fu, Q. Simulated climatology and evolution of aridity in the 21st century. J. Geophys. Res. Atmos. 120, 5795–5815 (2015).Article 

    Google Scholar 
    Coumou, D. & Rahmstorf, S. A decade of weather extremes. Nat. Clim. Change 2, 491–496 (2012).Article 

    Google Scholar 
    Williams, A. P. et al. Large contribution from anthropogenic warming to an emerging North American megadrought. Science 368, 314–318 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Touma, D., Ashfaq, M., Nayak, M. A., Kao, S.-C. & Diffenbaugh, N. S. A multi-model and multi-index evaluation of drought characteristics in the 21st century. J. Hydrol. 526, 196–207 (2015).Article 

    Google Scholar 
    Liu, W. et al. Global drought and severe drought-affected populations in 1.5 and 2 °C warmer worlds. Earth Syst. Dyn. 9, 267–283 (2018).Article 

    Google Scholar 
    Ault, T. R. On the essentials of drought in a changing climate. Science 368, 256–260 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Swann, A. L., Hoffman, F. M., Koven, C. D. & Randerson, J. T. Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity. Proc. Natl Acad. Sci. USA 113, 10019–10024 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Milly, P. C. D. & Dunne, K. A. Potential evapotranspiration and continental drying. Nat. Clim. Change 6, 946–949 (2016).Article 

    Google Scholar 
    Zhou, S. et al. Soil moisture–atmosphere feedbacks mitigate declining water availability in drylands. Nat. Clim. Change 11, 38–44 (2021).Article 

    Google Scholar 
    Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K. & Rasmussen, R. Slower snowmelt in a warmer world. Nat. Clim. Change 7, 214–219 (2017).Article 

    Google Scholar 
    Harpold, A. A. et al. Soil moisture response to snowmelt timing in mixed-conifer subalpine forests. Hydrol. Process. 29, 2782–2798 (2015).Article 

    Google Scholar 
    Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Choat, B. et al. Triggers of tree mortality under drought. Nature 558, 531–539 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).Song, J. et al. A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change. Nat. Ecol. Evol. 3, 1309–1320 (2019).PubMed 
    Article 

    Google Scholar 
    Parton, W. et al. Global-scale similarities in nitrogen release patterns during long-term decomposition. Science 315, 361–364 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Adair, E. C. et al. Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates. Glob. Change Biol. 14, 2636–2660 (2008).Article 

    Google Scholar 
    Adair, E. C., Parton, W. J., King, J. Y., Brandt, L. A. & Lin, Y. Accounting for photodegradation dramatically improves prediction of carbon losses in dryland systems. Ecosphere 8, e01892 (2017).Article 

    Google Scholar 
    Chen, M. et al. Simulation of the effects of photodecay on long-term litter decay using DayCent. Ecosphere 7, e01631 (2016).
    Google Scholar 
    Asao, S., Parton, W. J., Chen, M. & Gao, W. Photodegradation accelerates ecosystem N cycling in a simulated California grassland. Ecosphere 9, e02370 (2018).Article 

    Google Scholar 
    Berdugo, M. et al. Global ecosystem thresholds driven by aridity. Science 367, 787–790 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Feng, S. & Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. 13, 10081–10094 (2013).CAS 
    Article 

    Google Scholar 
    Berg, A. & McColl, K. A. No projected global drylands expansion under greenhouse warming. Nat. Clim. Change 11, 331–337 (2021).Article 

    Google Scholar 
    Whitford, W. G. & Duval, B. D. Ecology of Desert Systems 2nd edn (Academic Press, 2020).Maestre, F. T. et al. Structure and functioning of dryland ecosystems in a changing world. Annu. Rev. Ecol. Evol. Syst. 47, 215–237 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Schimel, J. P. Life in dry soils: effects of drought on soil microbial communities and processes. Annu. Rev. Ecol. Evol. Syst. 49, 409–432 (2018).Article 

    Google Scholar 
    Nielsen, U. N. & Ball, B. A. Impacts of altered precipitation regimes on soil communities and biogeochemistry in arid and semi-arid ecosystems. Glob. Change Biol. 21, 1407–1421 (2015).Article 

    Google Scholar 
    Collins, S. L. et al. A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems. Annu. Rev. Ecol. Evol. Syst. 45, 397–419 (2014).Article 

    Google Scholar 
    Kim, D.-G., Mu, S., Kang, S. & Lee, D. Factors controlling soil CO2 effluxes and the effects of rewetting on effluxes in adjacent deciduous, coniferous, and mixed forests in Korea. Soil Biol. Biochem. 42, 576–585 (2010).Article 
    CAS 

    Google Scholar 
    Curiel Yuste, J., Janssens, I. A., Carrara, A., Meiresonne, L. & Ceulemans, R. Interactive effects of temperature and precipitation on soil respiration in a temperate maritime pine forest. Tree Physiol. 23, 1263–1270 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Savage, K., Davidson, E. A., Richardson, A. D. & Hollinger, D. Y. Three scales of temporal resolution from automated soil respiration measurements. Agric. Meteorol. 149, 2012–2021 (2009).Article 

    Google Scholar 
    Hao, Y., Wang, Y., Mei, X. & Cui, X. The response of ecosystem CO2 exchange to small precipitation pulses over a temperate steppe. Plant Ecol. 209, 335–347 (2010).Article 

    Google Scholar 
    Krüger, J. P., Beckedahl, H., Gerold, G. & Jungkunst, H. F. Greenhouse gas emission peaks following natural rewetting of two wetlands in the southern Ukhahlamba-Drakensberg Park, South Africa. S. Afr. Geogr. J. 96, 113–118 (2013).Article 

    Google Scholar 
    Haverd, V., Ahlström, A., Smith, B. & Canadell, J. G. Carbon cycle responses of semi-arid ecosystems to positive asymmetry in rainfall. Glob. Change Biol. 23, 793–800 (2017).Article 

    Google Scholar 
    Kim, D. G., Vargas, R., Bond-Lamberty, B. & Turetsky, M. R. Effects of soil rewetting and thawing on soil gas fluxes: a review of current literature and suggestions for future research. Biogeosciences 9, 2459–2483 (2012).CAS 
    Article 

    Google Scholar 
    Barnard, R. L., Blazewicz, S. J. & Firestone, M. K. Rewetting of soil: revisiting the origin of soil CO2 emissions. Soil Biol. Biochem. 147, 107819 (2020).Prieto, I., Armas, C. & Pugnaire, F. I. Water release through plant roots: new insights into its consequences at the plant and ecosystem level. New Phytol. 193, 830–841 (2012).PubMed 
    Article 

    Google Scholar 
    Neumann, R. B. & Cardon, Z. G. The magnitude of hydraulic redistribution by plant roots: a review and synthesis of empirical and modeling studies. New Phytol. 194, 337–352 (2012).PubMed 
    Article 

    Google Scholar 
    Mooney, H. A., Gulmon, S. L., Rundel, P. W. & Ehleringer, J. Further observations on the water relations of Prosopis tamarugo of the northern Atacama desert. Oecologia 44, 177–180 (1980).CAS 
    PubMed 
    Article 

    Google Scholar 
    Richards, J. H. & Caldwell, M. M. Hydraulic lift: substantial nocturnal water transport between soil layers by Artemisia tridentata roots. Oecologia 73, 486–489 (1987).CAS 
    PubMed 
    Article 

    Google Scholar 
    Caldwell, M. M., Dawson, T. E. & Richards, J. H. Hydraulic lift: consequences of water efflux from the roots of plants. Oecologia 113, 151–161 (1998).PubMed 
    Article 

    Google Scholar 
    Brooks, J. R., Meinzer, F. C., Coulombe, R. & Gregg, J. Hydraulic redistribution of soil water during summer drought in two contrasting Pacific Northwest coniferous forests. Tree Physiol. 22, 1107–1117 (2002).PubMed 
    Article 

    Google Scholar 
    Lee, J. E., Oliveira, R. S., Dawson, T. E. & Fung, I. Root functioning modifies seasonal climate. Proc. Natl Acad. Sci. USA 102, 17576–17581 (2005).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Robinson, J. L., Slater, L. D. & Schäfer, K. V. R. Evidence for spatial variability in hydraulic redistribution within an oak–pine forest from resistivity imaging. J. Hydrol. 430-431, 69–79 (2012).Article 

    Google Scholar 
    Oliveira, R. S., Dawson, T. E., Burgess, S. S. O. & Nepstad, D. C. Hydraulic redistribution in three Amazonian trees. Oecologia 145, 354–363 (2005).PubMed 
    Article 

    Google Scholar 
    Zapater, M. et al. Evidence of hydraulic lift in a young beech and oak mixed forest using 18O soil water labelling. Trees 25, 885–894 (2011).Article 

    Google Scholar 
    Sardans, J. & Peñuelas, J. Hydraulic redistribution by plants and nutrient stoichiometry: shifts under global change. Ecohydrology 7, 1–20 (2014).Article 

    Google Scholar 
    Schenk, H. J. & Jackson, R. B. Rooting depths, lateral root spreads and below‐ground/above‐ground allometries of plants in water‐limited ecosystems. J. Ecol. 90, 480–494 (2002).Article 

    Google Scholar 
    Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wang, L., Kaseke, K. F. & Seely, M. K. Effects of non-rainfall water inputs on ecosystem functions. WIREs Water 4, e1179 (2017).
    Google Scholar 
    Dawson, T. E. & Goldsmith, G. R. The value of wet leaves. New Phytol. 219, 1156–1169 (2018).PubMed 
    Article 

    Google Scholar 
    Agam, N. & Berliner, P. R. Dew formation and water vapor adsorption in semi-arid environments – a review. J. Arid. Environ. 65, 572–590 (2006).Article 

    Google Scholar 
    Dirks, I., Navon, Y., Kanas, D., Dumbur, R. & Grünzweig, J. M. Atmospheric water vapor as driver of litter decomposition in Mediterranean shrubland and grassland during rainless seasons. Glob. Change Biol. 16, 2799–2812 (2010).Article 

    Google Scholar 
    Jacobson, K. et al. Non-rainfall moisture activates fungal decomposition of surface litter in the Namib Sand Sea. PLoS ONE 10, e0126977 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    McHugh, T. A., Morrissey, E. M., Reed, S. C., Hungate, B. A. & Schwartz, E. Water from air: an overlooked source of moisture in arid and semiarid regions. Sci. Rep. 5, 13767 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gliksman, D. et al. Biotic degradation at night, abiotic degradation at day: positive feedbacks on litter decomposition in drylands. Glob. Change Biol. 23, 1564–1574 (2017).Article 

    Google Scholar 
    Goldsmith, G. R., Matzke, N. J. & Dawson, T. E. The incidence and implications of clouds for cloud forest plant water relations. Ecol. Lett. 16, 307–314 (2013).PubMed 
    Article 

    Google Scholar 
    Binks, O. et al. Foliar water uptake in Amazonian trees: evidence and consequences. Glob. Change Biol. 25, 2678–2690 (2019).Article 

    Google Scholar 
    Benzing, D. H. Vulnerabilities of tropical forests to climate change: the significance of resident epiphytes. Clim. Change 39, 519–540 (1998).Article 

    Google Scholar 
    Evans, S., Todd-Brown, K. E. O., Jacobson, K. & Jacobson, P. Non-rainfall moisture: a key driver of microbial respiration from standing litter in arid, semiarid, and mesic grasslands. Ecosystems 23, 1154–1169 (2020).CAS 
    Article 

    Google Scholar 
    Newell, S. Y., Fallon, R. D., Rodriguez, R. M. C. & Groene, L. C. Influence of rain, tidal wetting and relative-humidity on release of carbon-dioxide by standing-dead salt-marsh plants. Oecologia 68, 73–79 (1985).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kuehn, K. A., Steiner, D. & Gessner, M. O. Diel mineralization patterns of standing-dead plant litter: implications for CO2 flux from wetlands. Ecology 85, 2504–2518 (2004).Article 

    Google Scholar 
    Doerr, S. H., Shakesby, R. A. & Walsh, R. P. D. Soil water repellency: its causes, characteristics and hydro-geomorphological significance. Earth Sci. Rev. 51, 33–65 (2000).Article 

    Google Scholar 
    Goebel, M.-O., Bachmann, J., Reichstein, M., Janssens, I. A. & Guggenberger, G. Soil water repellency and its implications for organic matter decomposition – is there a link to extreme climatic events? Glob. Change Biol. 17, 2640–26596 (2011).Article 

    Google Scholar 
    Mao, J., Nierop, K. G. J., Dekker, S. C., Dekker, L. W. & Chen, B. Understanding the mechanisms of soil water repellency from nanoscale to ecosystem scale: a review. J. Soils Sediments 19, 171–185 (2019).Article 

    Google Scholar 
    Doerr, S. H., Shakesby, R. A., Dekker, L. W. & Ritsema, C. J. Occurrence, prediction and hydrological effects of water repellency amongst major soil and land-use types in a humid temperate climate. Eur. J. Soil Sci. 57, 741–754 (2006).Article 

    Google Scholar 
    Lebron, I., Robinson, D. A., Oatham, M. & Wuddivira, M. N. Soil water repellency and pH soil change under tropical pine plantations compared with native tropical forest. J. Hydrol. 414-415, 194–200 (2012).CAS 
    Article 

    Google Scholar 
    Buczko, U., Bens, O. & Hüttl, R. F. Variability of soil water repellency in sandy forest soils with different stand structure under Scots pine (Pinus sylvestris) and beech (Fagus sylvatica). Geoderma 126, 317–336 (2005).Article 

    Google Scholar 
    Dekker, L. W. & Ritsema, C. J. Variation in water content and wetting patterns in Dutch water repellent peaty clay and clayey peat soils. CATENA 28, 89–105 (1996).CAS 
    Article 

    Google Scholar 
    de Blas, E., Almendros, G. & Sanz, J. Molecular characterization of lipid fractions from extremely water-repellent pine and eucalyptus forest soils. Geoderma 206, 75–84 (2013).Article 
    CAS 

    Google Scholar 
    MacDonald, L. H. & Huffman, E. L. Post-fire soil water repellency. Soil Sci. Soc. Am. J. 68, 1729–1734 (2004).CAS 
    Article 

    Google Scholar 
    Hewelke, E. et al. Intensity and persistence of soil water repellency in pine forest soil in a temperate continental climate under drought conditions. Water 10, 1121 (2018).Article 
    CAS 

    Google Scholar 
    Borken, W. & Matzner, E. Reappraisal of drying and wetting effects on C and N mineralization and fluxes in soils. Glob. Change Biol. 15, 808–824 (2009).Article 

    Google Scholar 
    Siteur, K. et al. Soil water repellency: a potential driver of vegetation dynamics in coastal dunes. Ecosystems 19, 1210–1224 (2016).CAS 
    Article 

    Google Scholar 
    Austin, A. T. & Vivanco, L. Plant litter decomposition in a semi-arid ecosystem controlled by photodegradation. Nature 442, 555–558 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    King, J. Y., Brandt, L. A. & Adair, E. C. Shedding light on plant litter decomposition: advances, implications and new directions in understanding the role of photodegradation. Biogeochemistry 111, 57–81 (2012).Article 

    Google Scholar 
    Moorhead, D. L. & Callaghan, T. Effects of increasing ultraviolet B radiation on decomposition and soil organic matter dynamics: a synthesis and modelling study. Biol. Fertil. Soils 18, 19–26 (1994).CAS 
    Article 

    Google Scholar 
    Sulzberger, B., Austin, A. T., Cory, R. M., Zepp, R. G. & Paul, N. D. Solar UV radiation in a changing world: roles of cryosphere-land-water-atmosphere interfaces in global biogeochemical cycles. Photochem. Photobiol. Sci. 18, 747–774 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Austin, A. T., Mendez, M. S. & Ballaré, C. L. Photodegradation alleviates the lignin bottleneck for carbon turnover in terrestrial ecosystems. Proc. Natl Acad. Sci. USA 113, 4392–4397 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Brandt, L. A., King, J. Y., Hobbie, S. E., Milchunas, D. G. & Sinsabaugh, R. L. The role of photodegradation in surface litter decomposition across a grassland ecosystem precipitation gradient. Ecosystems 13, 765–781 (2010).CAS 
    Article 

    Google Scholar 
    Pieristè, M. et al. Solar UV-A radiation and blue light enhance tree leaf litter decomposition in a temperate forest. Oecologia 191, 191–203 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wu, C. et al. Photodegradation accelerates coarse woody debris decomposition in subtropical Chinese forests. For. Ecol. Manage. 409, 225–232 (2018).Article 

    Google Scholar 
    Marinho, O. A., Martinelli, L. A., Duarte-Neto, P. J. R., Mazzi, E. A. & King, J. Y. Photodegradation influences litter decomposition rate in a humid tropical ecosystem, Brazil. Sci. Total Environ. 715, 136601 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wang, Q. W. et al. The contribution of photodegradation to litter decomposition in a temperate forest gap and understorey. New Phytol. 229, 2625–2636 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rutledge, S., Campbell, D. I., Baldocchi, D. & Schipper, L. A. Photodegradation leads to increased carbon dioxide losses from terrestrial organic matter. Glob. Change Biol. 16, 3065–3074 (2010).
    Google Scholar 
    Williamson, C. E. et al. Solar ultraviolet radiation in a changing climate. Nat. Clim. Change 4, 434–441 (2014).Article 

    Google Scholar 
    Zepp, R. G., Erickson, D. J. III, Paul, N. D. & Sulzberger, B. Effects of solar UV radiation and climate change on biogeochemical cycling: interactions and feedbacks. Photochem. Photobiol. Sci. 10, 261–271 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Austin, A. Has water limited our imagination for aridland biogeochemistry? Trends Ecol. Evol. 26, 229–235 (2011).PubMed 
    Article 

    Google Scholar 
    McCalley, C. K. & Sparks, J. P. Abiotic gas formation drives nitrogen loss from a desert ecosystem. Science 326, 837–840 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lee, H., Rahn, T. & Throop, H. L. An accounting of C-based trace gas release during abiotic plant litter degradation. Glob. Change Biol. 18, 1185–1195 (2012).Article 

    Google Scholar 
    Wang, B., Lerdau, M. & He, Y. Widespread production of nonmicrobial greenhouse gases in soils. Glob. Change Biol. 23, 4472–4482 (2017).Article 

    Google Scholar 
    Soper, F. M., McCalley, C. K., Sparks, K. & Sparks, J. P. Soil carbon dioxide emissions from the Mojave desert: isotopic evidence for a carbonate source. Geophys. Res. Lett. 44, 245–251 (2017).CAS 
    Article 

    Google Scholar 
    Day, T. A. & Bliss, M. S. Solar photochemical emission of CO2 from leaf litter: sources and significance to C loss. Ecosystems 23, 1344–1361 (2020).CAS 
    Article 

    Google Scholar 
    Throop, H. L. & Belnap, J. Connectivity dynamics in dryland litter cycles: moving decomposition beyond spatial stasis. Bioscience 69, 602–614 (2019).Article 

    Google Scholar 
    Throop, H. L. & Archer, S. R. Resolving the dryland decomposition conundrum: some new perspectives on potential drivers. Prog. Bot. 70, 171–194 (2009).CAS 

    Google Scholar 
    Barnes, P. W. et al. in Progress in Botany Vol. 76 (eds Lüttge, U. & Beyschlag, W.) 273–302 (Springer, 2015).Barnes, P. W., Throop, H. L., Hewins, D. B., Abbene, M. L. & Archer, S. R. Soil coverage reduces photodegradation and promotes the development of soil-microbial films on dryland leaf litter. Ecosystems 15, 311–321 (2012).CAS 
    Article 

    Google Scholar 
    Joly, F. X., Kurupas, K. L. & Throop, H. L. Pulse frequency and soil-litter mixing alter the control of cumulative precipitation over litter decomposition. Ecology 98, 2255–2260 (2017).PubMed 
    Article 

    Google Scholar 
    Weber, B., Büdel, B. & Belnap, J. Biological Soil Crusts: An Organizing Principle in Drylands Vol. 226 (Springer, 2016).Belnap, J. & Lange, O. L. Biological Soil Crusts: Structure, Function, and Management (Springer, 2001).Ferrenberg, S., Tucker, C. L. & Reed, S. C. Biological soil crusts: diminutive communities of potential global importance. Front. Ecol. Environ. 15, 160–167 (2017).Article 

    Google Scholar 
    Belnap, J. The world at your feet: desert biological soil crusts. Front. Ecol. Environ. 1, 181–189 (2003).Article 

    Google Scholar 
    Rodríguez-Caballero, E. et al. Dryland photoautotrophic soil surface communities endangered by global change. Nat. Geosci. 11, 185–189 (2018).Article 
    CAS 

    Google Scholar 
    Hawkes, C. V. & Flechtner, V. R. Biological soil crusts in a xeric Florida shrubland: composition, abundance, and spatial heterogeneity of crusts with different disturbance histories. Microb. Ecol. 43, 1–12 (2002).CAS 
    PubMed 
    Article 

    Google Scholar 
    Langhans, T. M., Storm, C. & Schwabe, A. Community assembly of biological soil crusts of different successional stages in a temperate sand ecosystem, as assessed by direct determination and enrichment techniques. Microb. Ecol. 58, 394–407 (2009).PubMed 
    Article 

    Google Scholar 
    Veluci, R. M., Neher, D. A. & Weicht, T. R. Nitrogen fixation and leaching of biological soil crust communities in mesic temperate soils. Microb. Ecol. 51, 189–196 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cabała, J. & Rahmonov, O. Cyanophyta and algae as an important component of biological crust from the Pustynia Błędowska Desert (Poland). Pol. Bot. J. 49, 93–100 (2004).
    Google Scholar 
    Thiet, R. K., Boerner, R. E. J., Nagy, M. & Jardine, R. The effect of biological soil crusts on throughput of rainwater and N into Lake Michigan sand dune soils. Plant Soil 278, 235–251 (2005).CAS 
    Article 

    Google Scholar 
    Jentsch, A. & Beyschlag, W. Vegetation ecology of dry acidic grasslands in the lowland area of Central Europe. Flora 198, 3–25 (2003).Article 

    Google Scholar 
    Dümig, A. et al. Organic matter from biological soil crusts induces the initial formation of sandy temperate soils. CATENA 122, 196–208 (2014).Article 
    CAS 

    Google Scholar 
    Chamizo, S., Cantón, Y., Rodríguez-Caballero, E. & Domingo, F. Biocrusts positively affect the soil water balance in semiarid ecosystems. Ecohydrology 9, 1208–1221 (2016).Article 

    Google Scholar 
    Couradeau, E. et al. Bacteria increase arid-land soil surface temperature through the production of sunscreens. Nat. Commun. 7, 10373 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Eldridge, D. J. & Greene, R. S. B. Microbiotic soil crusts: a review of their roles in soil and ecological processes in the rangelands of Australia. Aust. J. Soil Res. 32, 389–415 (1994).Article 

    Google Scholar 
    Elbert, W. et al. Contribution of cryptogamic covers to the global cycles of carbon and nitrogen. Nat. Geosci. 5, 459–462 (2012).CAS 
    Article 

    Google Scholar 
    Delgado-Baquerizo, M., Maestre, F. T., Rodríguez, J. G. P. & Gallardo, A. Biological soil crusts promote N accumulation in response to dew events in dryland soils. Soil Biol. Biochem. 62, 22–27 (2013).CAS 
    Article 

    Google Scholar 
    Meron, E. From patterns to function in living systems: dryland ecosystems as a case study. Annu. Rev. Condens. Matter Phys. 9, 79–103 (2018).Article 

    Google Scholar 
    Rietkerk, M. et al. Self-organization of vegetation in arid ecosystems. Am. Nat. 160, 524–530 (2002).PubMed 
    Article 

    Google Scholar 
    Meron, E. Vegetation pattern formation: the mechanisms behind the forms. Phys. Today 72, 30–36 (2019).Article 

    Google Scholar 
    Gandhi, P., Iams, S., Bonetti, S. & Silber, M. in Dryland Ecohydrology 2nd edn (eds D’Odorico, P. et al.) 469–509 (Springer, 2019).Rietkerk, M., Dekker, S. C., de Ruiter, P. C. & van de Koppel, J. Self-organized patchiness and catastrophic shifts in ecosystems. Science 305, 1926–1929 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lejeune, O., Tlidi, M. & Couteron, P. Localized vegetation patches: a self-organized response to resource scarcity. Phys. Rev. E 66, 010901 (2002).CAS 
    Article 

    Google Scholar 
    Belyea, L. R. & Lancaster, J. Inferring landscape dynamics of bog pools from scaling relationships and spatial patterns. J. Ecol. 90, 223–234 (2002).Article 

    Google Scholar 
    Eppinga, M. B. et al. Regular surface patterning of peatlands: confronting theory with field data. Ecosystems 11, 520–536 (2008).CAS 
    Article 

    Google Scholar 
    Hiemstra, C. A., Liston, G. E. & Reiners, W. A. Observing, modelling, and validating snow redistribution by wind in a Wyoming upper treeline landscape. Ecol. Modell. 197, 35–51 (2006).Article 

    Google Scholar 
    Crain, C. M. & Bertness, M. D. Community impacts of a tussock sedge: is ecosystem engineering important in benign habitats? Ecology 86, 2695–2704 (2005).Article 

    Google Scholar 
    Stanton, D. E., Armesto, J. J. & Hedin, L. O. Ecosystem properties self-organize in response to a directional fog-vegetation interaction. Ecology 95, 1203–1212 (2014).PubMed 
    Article 

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

    Google Scholar 
    Rietkerk, M. & van de Koppel, J. Regular pattern formation in real ecosystems. Trends Ecol. Evol. 23, 169–175 (2008).PubMed 
    Article 

    Google Scholar 
    Aguiar, M. R. & Sala, O. E. Patch structure, dynamics and implications for the functioning of arid ecosystems. Trends Ecol. Evol. 14, 273–277 (1999).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bera, B. K., Tzuk, O., Bennett, J. J. & Meron, E. Linking spatial self-organization to community assembly and biodiversity. eLife 10, e73819 (2021).Garcia-Moya, E. & McKell, C. M. Contribution of shrubs to the nitrogen economy of a desert-wash plant community. Ecology 51, 81–88 (1970).Article 

    Google Scholar 
    Peters, D. P. C. et al. Disentangling complex landscapes: new insights into arid and semiarid system dynamics. Bioscience 56, 491–501 (2006).Article 

    Google Scholar 
    Okin, G. S. et al. Connectivity in dryland landscapes: shifting concepts of spatial interactions. Front. Ecol. Environ. 13, 20–27 (2015).Article 

    Google Scholar 
    Ludwig, J. A., Wilcox, B. P., Breshears, D. D., Tongway, D. J. & Imeson, A. C. Vegetation patches and runoff–erosion as interacting ecohydrological processes in semiarid landscapes. Ecology 86, 288–297 (2005).Article 

    Google Scholar 
    Fahnestock, J. T., Povirk, K. L. & Welker, J. M. Ecological significance of litter redistribution by wind and snow in Arctic landscapes. Ecography 23, 623–631 (2000).Article 

    Google Scholar 
    Schlesinger, W. H. et al. Biological feedbacks in global desertification. Science 247, 1043–1048 (1990).CAS 
    PubMed 
    Article 

    Google Scholar 
    Okin, G. S., Sala, O. E., Vivoni, E. R., Zhang, J. & Bhattachan, A. The interactive role of wind and water in functioning of drylands: what does the future hold? Bioscience 68, 670–677 (2018).Article 

    Google Scholar 
    Finzi, A. C. et al. Responses and feedbacks of coupled biogeochemical cycles to climate change: examples from terrestrial ecosystems. Front. Ecol. Environ. 9, 61–67 (2011).Article 

    Google Scholar 
    Yuan, Z. Y. et al. Experimental and observational studies find contrasting responses of soil nutrients to climate change. eLife 6, e23255 (2017).Delgado-Baquerizo, M. et al. Decoupling of soil nutrient cycles as a function of aridity in global drylands. Nature 502, 672–676 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Jiao, F., Shi, X. R., Han, F. P. & Yuan, Z. Y. Increasing aridity, temperature and soil pH induce soil C-N-P imbalance in grasslands. Sci. Rep. 6, 19601 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wang, X.-G. et al. Changes in soil C:N:P stoichiometry along an aridity gradient in drylands of northern China. Geoderma 361, 114087 (2020).CAS 
    Article 

    Google Scholar 
    Mulder, C. et al. Connecting the green and brown worlds: allometric and stoichiometric predictability of above- and below-ground networks. Adv. Ecol. Res. 49, 69–175 (2013).Article 

    Google Scholar 
    Yuan, Z. Y. & Chen, H. Y. H. Decoupling of nitrogen and phosphorus in terrestrial plants associated with global changes. Nat. Clim. Change 5, 465–469 (2015).CAS 
    Article 

    Google Scholar 
    Rotenberg, E. & Yakir, D. Contribution of semi-arid forests to the climate system. Science 327, 451–454 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Banerjee, T., De Roo, F. & Mauder, M. Explaining the convector effect in canopy turbulence by means of large-eddy simulation. Hydrol. Earth Syst. Sci. 21, 2987–3000 (2017).Article 

    Google Scholar 
    Teuling, A. J. et al. Contrasting response of European forest and grassland energy exchange to heatwaves. Nat. Geosci. 3, 722–727 (2010).CAS 
    Article 

    Google Scholar 
    Alkama, R. & Cescatti, A. Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Huang, K. et al. Enhanced peak growth of global vegetation and its key mechanisms. Nat. Ecol. Evol. 2, 1897–1905 (2018).De Jong, R., Verbesselt, J., Schaepman, M. E. & De Bruin, S. Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Glob. Change Biol. 18, 642–655 (2012).Article 

    Google Scholar 
    Pan, N. et al. Increasing global vegetation browning hidden in overall vegetation greening: insights from time-varying trends. Remote Sens. Environ. 214, 59–72 (2018).Article 

    Google Scholar 
    Mueller, T. et al. Human land-use practices lead to global long-term increases in photosynthetic capacity. Remote Sens. 6, 5717–5731 (2014).Article 

    Google Scholar 
    Beck, P. S. A. et al. Changes in forest productivity across Alaska consistent with biome shift. Ecol. Lett. 14, 373–379 (2011).PubMed 
    Article 

    Google Scholar 
    Myers-Smith, I. H. et al. Complexity revealed in the greening of the Arctic. Nat. Clim. Change 10, 106–117 (2020).Article 

    Google Scholar 
    Aguirre-Gutiérrez, J. et al. Drier tropical forests are susceptible to functional changes in response to a long-term drought. Ecol. Lett. 22, 855–865 (2019).PubMed 
    Article 

    Google Scholar 
    Peñuelas, J. et al. Shifting from a fertilization-dominated to a warming-dominated period. Nat. Ecol. Evol. 1, 1438–1445 (2017).PubMed 
    Article 

    Google Scholar 
    Stocker, B. D. et al. Drought impacts on terrestrial primary production underestimated by satellite monitoring. Nat. Geosci. 12, 264–270 (2019).CAS 
    Article 

    Google Scholar 
    Berg, A., Sheffield, J. & Milly, P. C. D. Divergent surface and total soil moisture projections under global warming. Geophys. Res. Lett. 44, 236–244 (2017).Article 

    Google Scholar 
    Davenport, D. W., Breshears, D. D., Wilcox, B. P. & Allen, C. D. Viewpoint: sustainability of piñon-juniper ecosystems – a unifying perspective of soil erosion thresholds. J. Range Manage. 51, 231 (1998).Article 

    Google Scholar 
    Briske, D. D., Fuhlendorf, S. D. & Smeins, F. E. A unified framework for assessment and application of ecological thresholds. Rangel. Ecol. Manage. 59, 225–236 (2006).Article 

    Google Scholar 
    Kayler, Z. E. et al. Experiments to confront the environmental extremes of climate change. Front. Ecol. Environ. 13, 219–225 (2015).Article 

    Google Scholar 
    Haase, P. et al. The next generation of site-based long-term ecological monitoring: linking essential biodiversity variables and ecosystem integrity. Sci. Total Environ. 613–614, 1376–1384 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    Halbritter, A. H. et al. The handbook for standardised field and laboratory measurements in terrestrial climate‐change experiments and observational studies (ClimEx). Methods Ecol. Evol. 11, 22–37 (2020).Article 

    Google Scholar 
    De Boeck, H. J. et al. Global change experiments: challenges and opportunities. Bioscience 65, 922–931 (2015).Article 

    Google Scholar 
    Kreyling, J. et al. To replicate, or not to replicate – that is the question: how to tackle nonlinear responses in ecological experiments. Ecol. Lett. 21, 1629–1638 (2018).De Boeck, H. J. et al. Understanding ecosystems of the future will require more than realistic climate change experiments – a response to Korell et al. Glob. Change Biol. 26, e6–e7 (2020).Article 

    Google Scholar 
    Hanson, P. J. & Walker, A. P. Advancing global change biology through experimental manipulations: where have we been and where might we go? Glob. Change Biol. 26, 287–299 (2020).Article 

    Google Scholar 
    Paschalis, A. et al. Rainfall manipulation experiments as simulated by terrestrial biosphere models: where do we stand? Glob. Change Biol. 26, 3336–3355 (2020).Article 

    Google Scholar 
    Scheffer, M., Carpenter, S. R., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591–596 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Diaz, S. et al. Assessing nature’s contributions to people. Science 359, 270–272 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Thonicke, K. et al. Advancing the understanding of adaptive capacity of social‐ecological systems to absorb climate extremes. Earths Future 8, e2019EF001221 (2020). More

  • in

    Impacts of urban expansion on natural habitats in global drylands

    Ecosystems and Human Well-being: Synthesis (Millennium Ecosystem Assessment, 2005).Huang, J. et al. Dryland climate change: recent progress and challenges. Rev. Geophys. 55, 719–778 (2017).Article 

    Google Scholar 
    Fu, B. et al. The Global-DEP conceptual framework — research on dryland ecosystems to promote sustainability. Curr. Opin. Environ. Sustain. 48, 17–28 (2021).Article 

    Google Scholar 
    He, C. et al. Detecting global urban expansion over the last three decades using a fully convolutional network. Environ. Res. Lett. 14, 034008 (2019).Article 

    Google Scholar 
    Güneralp, B., Reba, M., Hales, B. U., Wentz, E. A. & Seto, K. C. Trends in urban land expansion, density, and land transitions from 1970 to 2010: a global synthesis. Environ. Res. Lett. 15, 044015 (2020).Article 

    Google Scholar 
    McDonald, R. I. et al. Research gaps in knowledge of the impact of urban growth on biodiversity. Nat. Sustain. 3, 16–24 (2019).Article 

    Google Scholar 
    Liu, X. et al. High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. Nat. Sustain. 3, 564–570 (2020).Article 

    Google Scholar 
    Güneralp, B. & Seto, K. C. Futures of global urban expansion: uncertainties and implications for biodiversity conservation. Environ. Res. Lett. 8, 014025 (2013).Article 

    Google Scholar 
    McDonald, R. I., Kareiva, P. & Forman, R. T. T. The implications of current and future urbanization for global protected areas and biodiversity conservation. Biol. Conserv. 141, 1695–1703 (2008).Article 

    Google Scholar 
    McDonald, R. I., Marcotullio, P. J. & Güneralp, B. Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities (Springer, 2013).van Vliet, J. Direct and indirect loss of natural area from urban expansion. Nat. Sustain. 2, 755–763 (2019).Article 

    Google Scholar 
    Sharp, R. et al. InVEST 3.2.0 User’s Guide (The Natural Capital Project, Stanford Univ., Univ. Minnesota, The Nature Conservancy and World Wildlife Fund, 2015).Terrado, M. et al. Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning. Sci. Total Environ. 540, 63–70 (2016).CAS 
    Article 

    Google Scholar 
    Bai, Y. et al. Developing China’s Ecological Redline Policy using ecosystem services assessments for land use planning. Nat. Commun. 9, 3034 (2018).Article 
    CAS 

    Google Scholar 
    McDonald, R. I. et al. Urban effects, distance, and protected areas in an urbanizing world. Landsc. Urban Plan. 93, 63–75 (2009).Article 

    Google Scholar 
    Mirzabaev, A. et al. in Climate Change and Land (eds Shukla, P. R. et al.) 249–343 (IPCC, 2019).Friis, C. & Nielsen, J. Telecoupling. Exploring Land-use Change in a Globalised World (Palgrave Macmillan, 2019).Maestre, F. et al. Structure and functioning of dryland ecosystems in a changing world. Annu. Rev. Ecol. Evol. Syst. 47, 215–237 (2016).Article 

    Google Scholar 
    Leh, M. D. K., Matlock, M. D., Cummings, E. C. & Nalley, L. L. Quantifying and mapping multiple ecosystem services change in West Africa. Agric. Ecosyst. Environ. 165, 6–18 (2013).Article 

    Google Scholar 
    Xie, W., Huang, Q., He, C. & Zhao, X. Projecting the impacts of urban expansion on simultaneous losses of ecosystem services: a case study in Beijing, China. Ecol. Indic. 84, 183–193 (2018).Article 

    Google Scholar 
    Whitford, W. & Wade, E. L. Ecology of Desert Systems (Academic Press, 2002).Brito, J. C. et al. Conservation biogeography of the Sahara‐Sahel: additional protected areas are needed to secure unique biodiversity. Divers. Distrib. 22, 371–384 (2016).Article 

    Google Scholar 
    Jenkins, C. N., Pimm, S. L. & Joppa, L. N. Global patterns of terrestrial vertebrate diversity and conservation. Proc. Natl Acad. Sci. USA 110, E2602–E2610 (2013).CAS 
    Article 

    Google Scholar 
    Salafsky, N. et al. A standard lexicon for biodiversity conservation: unified classifications of threats and actions. Conserv. Biol. 22, 897–911 (2008).Article 

    Google Scholar 
    Oliver, T. H. et al. Declining resilience of ecosystem functions under biodiversity loss. Nat. Commun. 6, 10122 (2015).Article 
    CAS 

    Google Scholar 
    Powers, R. P. & Jetz, W. Global habitat loss and extinction risk of terrestrial vertebrates under future land-use-change scenarios. Nat. Clim. Change 9, 323–329 (2019).Article 

    Google Scholar 
    Díaz, S. M. et al. The Global Assessment Report on Biodiversity and Ecosystem Services: Summary for Policy Makers (IPBES, 2019).Seto, K. C., Guneralp, B. & Hutyra, L. R. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc. Natl Acad. Sci. USA 109, 16083–16088 (2012).CAS 
    Article 

    Google Scholar 
    Pautasso, M. Scale dependence of the correlation between human population presence and vertebrate and plant species richness. Ecol. Lett. 10, 16–24 (2007).Article 

    Google Scholar 
    Luck, G. W. A review of the relationships between human population density and biodiversity. Biol. Rev. Camb. Phil. Soc. 82, 607–645 (2007).Article 

    Google Scholar 
    McDonald, R. I., Güneralp, B., Huang, C.-W., Seto, K. C. & You, M. Conservation priorities to protect vertebrate endemics from global urban expansion. Biol. Conserv. 224, 290–299 (2018).Article 

    Google Scholar 
    The IUCN Red List of Threatened Species Version 2017-3 (IUCN, 2017); https://www.iucnredlist.org/resources/spatial-data-downloadTucker, M. A. et al. Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science 359, 466–469 (2018).CAS 
    Article 

    Google Scholar 
    Howard, C., Flather, C. H. & Stephens, P. A. A global assessment of the drivers of threatened terrestrial species richness. Nat. Commun. 11, 993 (2020).CAS 
    Article 

    Google Scholar 
    Guidelines for Geoconservation in Protected and Conserved Areas (IUCN, 2020).Gao, J. How China will protect one-quarter of its land. Nature 569, 457 (2019).CAS 
    Article 

    Google Scholar 
    Chen, C. et al. China and India lead in greening of the world through land-use management. Nat. Sustain. 2, 122–129 (2019).Article 

    Google Scholar 
    Gao, B., Huang, Q., He, C., Sun, Z. & Zhang, D. How does sprawl differ across cities in China? A multi-scale investigation using nighttime light and census data. Landsc. Urban Plan. 148, 89–98 (2016).Article 

    Google Scholar 
    Mace, G. M. et al. Aiming higher to bend the curve of biodiversity loss. Nat. Sustain. 1, 448–451 (2018).Article 

    Google Scholar 
    Lambin, E. A. & Meyfroidt, P. Global land use change, economic globalization, and the looming land scarcity. Proc. Natl Acad. Sci. USA 108, 3465–3472 (2011).CAS 
    Article 

    Google Scholar 
    Arlidge, W. et al. A global mitigation hierarchy for nature conservation. Bioscience 68, 336–347 (2018).Article 

    Google Scholar 
    Moallemi, E. A., Kwakkel, J., de Haan, F. J. & Bryan, B. A. Exploratory modeling for analyzing coupled human-natural systems under uncertainty. Glob. Environ. Change 65, 102186 (2020).Article 

    Google Scholar 
    Luck, M. A., Jenerette, G. D., Wu, J. & Grimm, N. B. The urban funnel model and the spatially heterogeneous ecological footprint. Ecosystems 4, 782–796 (2001).Article 

    Google Scholar 
    Ramaswami, A. et al. A social‐ecological‐infrastructural systems framework for interdisciplinary study of sustainable city systems. J. Ind. Ecol. 16, 801–813 (2012).Article 

    Google Scholar 
    Boerema, A. et al. Soybean trade: balancing environmental and socio-economic impacts of an intercontinental market. PLoS ONE 11, e0155222 (2016).Article 
    CAS 

    Google Scholar 
    Garrett, R. D., Lambin, E. F. & Naylor, R. L. Land institutions and supply chain configurations as determinants of soybean planted area and yields in Brazil. Land Use Policy 31, 385–396 (2013).Article 

    Google Scholar 
    Friess, D. A., Rogers, K., Lovelock, C. E., Krauss, K. W. & Shi, S. The state of the world’s mangrove forests: past, present, and future. Annu. Rev. Environ. Resour. 44, 89–115 (2019).Article 

    Google Scholar 
    Ferreira, A. C. & Lacerda, L. D. Degradation and conservation of Brazilian mangroves, status and perspectives. Ocean Coast. Manage. 125, 38–46 (2016).Article 

    Google Scholar 
    Richards, D. R. & Friess, D. A. Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012. Proc. Natl Acad. Sci. USA 113, 201510272 (2016).
    Google Scholar 
    García-Vega, D. & Newbold, T. Assessing the effects of land use on biodiversity in the world’s drylands and Mediterranean environments. Biodivers. Conserv. 29, 393–408 (2020).Article 

    Google Scholar 
    Martínez-Valderrama, J., Guirado, E. & Maestre, F. Desertifying deserts. Nat. Sustain. 3, 572–575 (2020).Article 

    Google Scholar 
    Maestre, F. et al. Biogeography of global drylands. New Phytol. 231, 540–558 (2021).Article 

    Google Scholar 
    United Nations Environment World Conservation Monitoring Centre. World dryland areas according to UNCCD and CBD definitions. https://resources.unep-wcmc.org/products/789fcac8959943ab9ed7a225e5316f08 (2022).Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51, 933–938 (2001).Article 

    Google Scholar 
    Goldewijk, K. K., Beusen, A., Doelman, J. & Stehfest, E. Anthropogenic land use estimates for the Holocene – HYDE 3.2. Earth Syst. Sci. Data 9, 927–953 (2017).Article 

    Google Scholar 
    Revision of World Urbanization Prospects (United Nations, 2018); https://esa.un.org/unpd/wupLand Cover CCI—Product User Guide Version 2.0. (European Space Agency, 2017); http://maps.elie.ucl.ac.be/CCI/viewer/index.phpGrekousis, G., Mountrakis, G. & Kavouras, M. An overview of 21 global and 43 regional land-cover mapping products. Int. J. Remote Sens. 36, 5309–5335 (2015).Article 

    Google Scholar 
    Xu, X., Jain, A. K. & Calvin, K. V. Quantifying the biophysical and socioeconomic drivers of changes in forest and agricultural land in South and Southeast Asia. Glob. Change Biol. 25, 2137–2151 (2019).Article 

    Google Scholar 
    Gong, P. et al. Annual maps of global artificial impervious area (GAIA) between 1985 and 2018. Remote Sens. Environ. 236, 111510 (2020).Article 

    Google Scholar 
    Huang, Q. et al. The occupation of cropland by global urban expansion from 1992 to 2016 and its implications. Environ. Res. Lett. 15, 084037 (2020).Article 

    Google Scholar 
    He, C., Liu, Z., Tian, J. & Ma, Q. Urban expansion dynamics and natural habitat loss in China: a multiscale landscape perspective. Glob. Change Biol. 20, 2886–2902 (2014).Article 

    Google Scholar 
    Di Febbraro, M. et al. Expert-based and correlative models to map habitat quality: which gives better support to conservation planning? Glob. Ecol. Conserv. 16, e00513 (2018).Article 

    Google Scholar 
    Anselin, L. Local Indicators of Spatial Association—LISA. Geogr. Anal. 27, 93–115 (2010).Article 

    Google Scholar  More

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    Comparative analysis of temperature preference behavior and effects of temperature on daily behavior in 11 Drosophila species

    Effects of temperature on total daily locomotor activitiesTo understand the effect of temperature on the daily behavior of Drosophila species distributed in different temperature regions, we examined the daily locomotor activity at different temperatures in the following 11 sequenced Drosophila species: cosmopolitan (D. melanogaster and D. simulans), tropical (D. ananassae, D. erecta, D. yakuba, and D. sechellia), subtropical (D. willistoni and D. mojavensis), and temperate (D. persimilis, D. pseudoobscura, and D. virilis) species. Using the Drosophila Activity Monitor system25, we were able to analyze the amount of daily locomotor activity quantitatively at five experimental temperatures, i.e., 17 °C, 20 °C, 23 °C, 26 °C, and 29 °C. As the viability of the adults of D. persimilis and D. pseudoobscura was low at 29 °C, these two species were analyzed at only four experimental temperatures. First, we compared the amount of daily locomotor activities among these Drosophila species (Supplementary Fig. 1). The ranges of the total daily activity were quite diverse in these species (Kruskal–Wallis test: χ2 = 833.18, p  More

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    Agro-pastoralists’ perception of climate change and adaptation in the Qilian Mountains of northwest China

    Basic information of intervieweesResults of the descriptive analysis summarized in Table 2 show that more than half of the respondents were males (69%) and were on average 41.3 years old while more than 32 years of farming experience. The study area is comprised of multiple ethnic groups (Han, Tibetan, Yugur, Mongolian, Hui, etc.). In most cases, the main livelihood activity of the Ethnic Minorities (Tibetan, Yugur, Mongolian, Hui, etc.) is livestock, while Han people main livelihood activity is farming. The majority of respondents (64%) were minority nationality. The vast majority of the agro-pastoralists (86%) have a primary school education or above, even though only 1% of them have Undergraduate education or Above. The results also reveal that 92% of respondents have access to weather information. The average cultivated land Per household is 10.23 Mu and Grassland is 156.21 Mu, respectively. The average per household income is RMB78000, and agricultural income is RMB52000.Table 2 Descriptive statistics of agro-pastoralist characteristics.Full size tableDue to their long-term farming experience, the agro-pastoralists were expected to have a high-level of understanding of local climate knowledge. Also contributing to this could be the information they receive about climate change and for some, the associated training through agro-pastoralists’ associations. Therefore, they also have a propensity to adapt to adverse conditions resulting from climate change impacts. In addition, the high-level of farming experience, the cultivated-land size, grassland size, Credit loan, Insurance, Village cadres all have a positive impact on the level of agro-pastoralists’ adaptation to new climate scenarios.However, the education level and cadres experience may be the major limiting factors for adopting specific long-term adaptation strategies. Ethnicity and gender are also expected to be key factors influencing awareness and adaptation to climate change. There are differences in relative perception intensity between Ethnic Minority and Han because of their cultural ecology (the main livelihood activity of minorities nationality is livestock, while Han main livelihood activity is farming.). In terms of gender, women in rural areas are less mobile and have less access to information and rights. They are also heavily involved in domestic work. However, men may have easier access to information (socializing, going out to work, etc.) Therefore, male headed households are expected to be more likely to adapt to the impact of climate change.Climate change trend in the study areaFigure 2 shows the trend of annual precipitation, annual rainfall and annual snow at different meteorological stations in the study area. As shown in the Fig. 2, precipitation, rainfall and snow show an increasing trend, but the increase range of snow (0.0325–0.375/a) is significantly lower than that of precipitation (1.22–3.1/a) and rainfall (1.04–2.81/a). Similarly, through the inspection, it is found that the multi-collinearity among precipitation, rainfall and snow at each meteorological station is obvious (most R2  > 0.5, and p  More