23 research outputs found

    Understanding climate change from a global analysis of city analogues

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    Combating climate change requires unified action across all sectors of society. However, this collective action is precluded by the ‘consensus gap’ between scientific knowledge and public opinion. Here, we test the extent to which the iconic cities around the world are likely to shift in response to climate change. By analyzing city pairs for 520 major cities of the world, we test if their climate in 2050 will resemble more closely to their own current climate conditions or to the current conditions of other cities in different bioclimatic regions. Even under an optimistic climate scenario (RCP 4.5), we found that 77% of future cities are very likely to experience a climate that is closer to that of another existing city than to its own current climate. In addition, 22% of cities will experience climate conditions that are not currently experienced by any existing major cities. As a general trend, we found that all the cities tend to shift towards the sub-tropics, with cities from the Northern hemisphere shifting to warmer conditions, on average ~1000 km south (velocity ~20 km.year-1), and cities from the tropics shifting to drier conditions. We notably predict that Madrid’s climate in 2050 will resemble Marrakech’s climate today, Stockholm will resemble Budapest, London to Barcelona, Moscow to Sofia, Seattle to San Francisco, Tokyo to Changsha. Our approach illustrates how complex climate data can be packaged to provide tangible information. The global assessment of city analogues can facilitate the understanding of climate change at a global level but also help land managers and city planners to visualize the climate futures of their respective cities, which can facilitate effective decision-making in response to on-going climate change

    Climate warming disrupts mast seeding and its fitness benefits in European beech

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    © 2020, The Author(s), under exclusive licence to Springer Nature Limited. Many plants benefit from synchronous year-to-year variation in seed production, called masting. Masting benefits plants because it increases the efficiency of pollination and satiates predators, which reduces seed loss. Here, using a 39-year-long dataset, we show that climate warming over recent decades has increased seed production of European beech but decreased the year-to-year variability of seed production and the reproductive synchrony among individuals. Consequently, the benefit that the plants gained from masting has declined. While climate warming was associated with increased reproductive effort, we demonstrate that less effective pollination and greater losses of seeds to predators offset any benefits to the plants. This shows that an apparently simple benefit of climate warming unravels because of complex ecological interactions. Our results indicate that in masting systems, the main beneficiaries of climate-driven increases in seed production are seed predators, not plants

    Native diversity buffers against severity of non-native tree invasions.

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    This is the final version. Available from Nature Research via the DOI in this record. Data availability: Data used in this study can be found in cited references for the Global Naturalized Alien Flora (GloNAF) database6 (non-native status), the KEW Plants of the World database5 (native ranges) and the Global Environmental Composite63,77 (environmental data layers). Plant trait data were extracted from Maynard et al.78. Data from the Global Forest Biodiversity Initiative (GFBI) database57 are not available due to data privacy and sharing restrictions, but can be obtained upon request via Science-I (https://science-i.org/) or GFBI (gfbinitiative.org) and an approval from data contributors.Code availability All code used to complete analyses for the manuscript is available at the following link: https://github.com/thomaslauber/Global-Tree-Invasion. Data analyses were conducted and were visualizations generated in R (v. 4.2.2), Python (v. 3.9.7), Google Earth Engine (earthengine-api 0.1.306), QGIS-LTR (v. 3.16.7) and the ETH Zurich Euler cluster.Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.Swiss National Science FoundationSwiss National Science FoundationBernina FoundationDOB Ecolog

    The global biogeography of tree leaf form and habit

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    This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: Tree occurrence data from the Global Forest Biodiversity initiative (GFBi) is available upon request via Science-I (https://science-i.org) or the GFBi website (https://www.gfbiinitiative.org/). Information on leaf habit (evergreen vs deciduous) and leaf form (broadleaved vs needle-leaved) came from the TRY database (https://www.try-db.org). Additional, leaf-type data came from the Tallo dataset (https://zenodo.org/record/6637599). Plot-level soil information came from the World Soil Information Service (WOSIS) dataset (https://www.isric.org/explore/wosis).Code availability: All code is available at https://doi.org/10.5281/zenodo.7967245.Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling
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