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Biodiversity in human-dominated landscapes is declining, but evidence-based conservation targets to guide international policies for such landscapes are lacking. We present a framework for informing habitat conservation policies based on the enhancement of habitat quantity and quality and define thresholds of habitat quantity at which it becomes effective to also prioritize habitat quality. We applied this framework to pollinators, an important part of agroecosystem biodiversity, by synthesizing 59 studies from 19 countries. Given low habitat quality, hoverflies had the lowest threshold at 6% semi-natural habitat cover, followed by solitary bees (16%), bumble bees (18%), and butterflies (37%). These figures represent minimum habitat thresholds in agricultural landscapes, but when habitat quantity is restricted, marked increases in quality are required to reach similar outcomes.

Human activity and disturbance are thought to be perceived as a source of risk analogous to predation risk in wildlife. As such, can alter behaviour and habitat use of foraging animals. Through increased exposure to human disturbance, urban wildlife may face an increase in perceived risk during food acquisition. Urban habitats also include novel resources that could result in urban wildlife having to face distinct trade-offs associated with foraging and patch use. To examine how a successful invasive mammal, the eastern grey squirrel, balances risk and safety under human disturbance, we measured giving-up densities (GUD) at artificial food patches placed at sites subject to varying levels of urbanisation to investigate how features associated with human disturbance might influence feeding decisions. We found differences in GUDs between ‘safe’ and risky’ patches were reduced closer to roads under noisy conditions, suggesting that the risk of predation is perceived by squirrels as reduced when disturbance from human activities is highest. There was also a significant effect of the variability in noise levels on patterns of patch exploitation associated with roads, with the larger GUD differences between safe and risky patches found further from roads exacerbated under more variable noise levels, suggesting the consistency of human disturbances also moderated squirrel risk perception while foraging close to roads. Our results suggest that human activities can have doubled-edged impacts on the urban landscape of fear through offering reduced risk from predators whilst increasing foraging costs via noise disturbance.

Data for "G6-1.5K-MCB: Marine Cloud Brightening Scenario design for the Geoengineering Model Intercomparison Project (GeoMIP)", a manuscript under review at Geoscientific Model Development.

Data for "G6-1.5K-MCB: Marine Cloud Brightening Scenario design for the Geoengineering Model Intercomparison Project (GeoMIP)", a manuscript under review at Geoscientific Model Development.

Contests over resources are widespread in nature. To optimize outcomes, animals assess fighting abilities, deciding to escalate conflicts based on their own strength (self-assessment) or comparing their own strength with that of their rival (mutual assessment). While most research focuses on one-on-one (dyadic) contests, the assessment strategies employed by groups remain poorly understood, even though animal groups from ants to humans engage in intergroup conflict. Mutual assessment is frequently assumed, as more information is thought to improve decision-making; however, this assumption has rarely been tested. Here we used a dataset spanning 23 years and 641 intergroup contests in a banded mongoose (Mungos mungo) population in Queen Elizabeth National Park, Uganda. Our results support a model of self-assessment: groups with many males tend to escalate conflicts regardless of the rival group's strength, thus contrasting the commonly held assumption that decisions during intergroup contests are made by mutual assessment. We suggest that assessing rival group strength during conflict could be disproportionately costly, compared with assessing one's own group strength, which can be done over longer time periods and is easier to obtain. Greater understanding of these dynamics can shed light on the drivers and escalation patterns of intergroup conflict across social species, including humans.

This Zenodo archive contains data supporting the publication “Limb Asymmetries on WASP-39b: A Multi-GCM Comparison of Chemistry, Clouds, and Hazes” by Steinrueck, Savel, Christie et al. (2025). Publication abstractWith JWST, observing separate spectra of the morning and evening limbs of hot Jupiters has finally become a reality. The first such observation was reported for WASP-39b, where the evening terminator was observed to have a larger transit radius by about 400 ppm and a stronger 4.3 µm CO2 feature than the morning terminator. Multiple factors, including temperature differences, photo/thermochemistry, clouds and hazes, could cause such limb asymmetries. To interpret these new limb asymmetry observations, a detailed understanding of how the relevant processes affect morning and evening spectra grounded in forward models is needed. Focusing on WASP-39b, we compare simulations from five different general circulation models (GCMs), including one simulating disequilibrium thermochemistry and one with cloud radiative feedback, to the recent WASP-39b limb asymmetry observations. We also post-process the temperature structures of all simulations with a 2D photochemical model and one simulation with a cloud microphysics model. Although the temperatures predicted by the different models vary considerably, the models are remarkably consistent in their predicted morning--evening temperature differences. Several equilibrium-chemistry simulations predict strong methane features in the morning spectrum, not seen in the observations. When including disequilibrium processes, horizontal transport homogenizes methane, and these methane features disappear. However, even after including photochemistry and clouds, our models still cannot reproduce the observed ~2000 ppm asymmetry in the CO2 feature. A combination of factors, such as varying metallicity and unexplored parameters in cloud models, may explain the discrepancy, emphasizing the need for future models integrating cloud microphysics and feedback across a broader parameter space.Content DescriptionContentsThe folder “Vulcan2DInput” contains the 2D pressure-temperature and velocity profiles that were used as input for 2D Vulcan. (See below for a more detailed description of files.)The folder “spectra” contains the spectra presented in the publication.PT.ipynb is a Jupyter notebook for reproducing Figures 1 (temperature profiles at terminator) and  2 (temperature profiles at substellar and anti stellar point) in the paper.VelProf.ipynb reproduces Figures 18 (vertical profiles of zonal velocity).Spectra.ipynb reproduces Figures 3, 8, 9 and 14. Note that in order to work, this script needs the observational data from Espinoza et al. (2024) in the form of the file catwoman_res100_priorlds.txt, which can be downloaded from https://github.com/nespinoza/wasp39-terminators in the folder “figure3” (permalink: https://github.com/nespinoza/wasp39-terminators/blob/57587796023fee9051121ea17d435f0ad6852589/figure3/catwoman_res100_priorlds.txt). The correct citation for the observational data is:Espinoza, N., Steinrueck, M.E., Kirk, J. et al. (2024): Inhomogeneous terminators on the exoplanet WASP-39 b. Nature 632, 1017–1020. https://doi.org/10.1038/s41586-024-07768-4Description of files in Vulcan2DInputFilenames: The first part of each filename describes the model that contributed the model. For each model, there are two files, one ending in “RMSwind”, describing the velocities in the simulation, and one ending in “TP”, describing the temperature structure. Each file contains three lines of header. The first line in the header includes the number of longitudes included, then a list of the values of the longitudes, with a longitude of zero referring to the substellar point. The second line specifies the units of the columns. The third line lists the columns individually.The first column of each “TP” file contains pressure, the other columns contain the temperatures at each of the longitudes included.The first column of each “RMSwind” file contains pressure, the next N_lon columns contain zonal (=longitudinal) velocities at the longitudes listed in the header, where N_lon is the number of longitudes included, and the final N_lon columns contain the vertical velocities.All quantities (temperature, zonal velocity, vertical velocity) were averaged latitudinally from -30 degrees to +30 degrees latitude. For temperature and zonal velocities, the mean was used. Zonal (=longitudinal) velocities are reported as positive for eastward velocities. For vertical velocities, the root-mean-square was used.Description of files in spectraFor each simulation, there is a separate file for the morning and evening spectrum each. The first column contains the wavelength in micrometers, the second column contains the transit depth in percent. When calculating the transit depths separately for the morning and evening terminator, the morning or evening side was mirrored onto the other half of the planet for the 3D ray-striking radiative transfer calculation, as described in section 2.5 in Steinrueck, Savel, Christie et al. When comparing to the limb depths reported by Espinoza et al. (2024) derived with catwoman, these transit depths have to be divided by a factor of two, as the limb depths correspond to the area of a semi-circle rather than a full circle.For the spectra including photochemistry, “B1” in the filenames corresponds to the “Full limb” post-processing and “B2” corresponds to the “Jet” post-processing.For the figures in Steinrueck et al. (2025), the spectra were shifted up or down to provide the best match to the full-transit transmission spectrum calculated using a least-squares minimization. See Section 3.3 in the paper or Spectra.ipynb for more details.AttributionPlease cite Steinrueck, Christie, Savel et al. (2025) as well as the Zenodo record when using the model outputs or spectra included in this repository.

This Zenodo archive contains data supporting the publication “Limb Asymmetries on WASP-39b: A Multi-GCM Comparison of Chemistry, Clouds, and Hazes” by Steinrueck, Savel, Christie et al. (2025). Publication abstractWith JWST, observing separate spectra of the morning and evening limbs of hot Jupiters has finally become a reality. The first such observation was reported for WASP-39b, where the evening terminator was observed to have a larger transit radius by about 400 ppm and a stronger 4.3 µm CO2 feature than the morning terminator. Multiple factors, including temperature differences, photo/thermochemistry, clouds and hazes, could cause such limb asymmetries. To interpret these new limb asymmetry observations, a detailed understanding of how the relevant processes affect morning and evening spectra grounded in forward models is needed. Focusing on WASP-39b, we compare simulations from five different general circulation models (GCMs), including one simulating disequilibrium thermochemistry and one with cloud radiative feedback, to the recent WASP-39b limb asymmetry observations. We also post-process the temperature structures of all simulations with a 2D photochemical model and one simulation with a cloud microphysics model. Although the temperatures predicted by the different models vary considerably, the models are remarkably consistent in their predicted morning--evening temperature differences. Several equilibrium-chemistry simulations predict strong methane features in the morning spectrum, not seen in the observations. When including disequilibrium processes, horizontal transport homogenizes methane, and these methane features disappear. However, even after including photochemistry and clouds, our models still cannot reproduce the observed ~2000 ppm asymmetry in the CO2 feature. A combination of factors, such as varying metallicity and unexplored parameters in cloud models, may explain the discrepancy, emphasizing the need for future models integrating cloud microphysics and feedback across a broader parameter space.Content DescriptionContentsThe folder “Vulcan2DInput” contains the 2D pressure-temperature and velocity profiles that were used as input for 2D Vulcan. (See below for a more detailed description of files.)The folder “spectra” contains the spectra presented in the publication.PT.ipynb is a Jupyter notebook for reproducing Figures 1 (temperature profiles at terminator) and  2 (temperature profiles at substellar and anti stellar point) in the paper.VelProf.ipynb reproduces Figures 18 (vertical profiles of zonal velocity).Spectra.ipynb reproduces Figures 3, 8, 9 and 14. Note that in order to work, this script needs the observational data from Espinoza et al. (2024) in the form of the file catwoman_res100_priorlds.txt, which can be downloaded from https://github.com/nespinoza/wasp39-terminators in the folder “figure3” (permalink: https://github.com/nespinoza/wasp39-terminators/blob/57587796023fee9051121ea17d435f0ad6852589/figure3/catwoman_res100_priorlds.txt). The correct citation for the observational data is:Espinoza, N., Steinrueck, M.E., Kirk, J. et al. (2024): Inhomogeneous terminators on the exoplanet WASP-39 b. Nature 632, 1017–1020. https://doi.org/10.1038/s41586-024-07768-4Description of files in Vulcan2DInputFilenames: The first part of each filename describes the model that contributed the model. For each model, there are two files, one ending in “RMSwind”, describing the velocities in the simulation, and one ending in “TP”, describing the temperature structure. Each file contains three lines of header. The first line in the header includes the number of longitudes included, then a list of the values of the longitudes, with a longitude of zero referring to the substellar point. The second line specifies the units of the columns. The third line lists the columns individually.The first column of each “TP” file contains pressure, the other columns contain the temperatures at each of the longitudes included.The first column of each “RMSwind” file contains pressure, the next N_lon columns contain zonal (=longitudinal) velocities at the longitudes listed in the header, where N_lon is the number of longitudes included, and the final N_lon columns contain the vertical velocities.All quantities (temperature, zonal velocity, vertical velocity) were averaged latitudinally from -30 degrees to +30 degrees latitude. For temperature and zonal velocities, the mean was used. Zonal (=longitudinal) velocities are reported as positive for eastward velocities. For vertical velocities, the root-mean-square was used.Description of files in spectraFor each simulation, there is a separate file for the morning and evening spectrum each. The first column contains the wavelength in micrometers, the second column contains the transit depth in percent. When calculating the transit depths separately for the morning and evening terminator, the morning or evening side was mirrored onto the other half of the planet for the 3D ray-striking radiative transfer calculation, as described in section 2.5 in Steinrueck, Savel, Christie et al. When comparing to the limb depths reported by Espinoza et al. (2024) derived with catwoman, these transit depths have to be divided by a factor of two, as the limb depths correspond to the area of a semi-circle rather than a full circle.For the spectra including photochemistry, “B1” in the filenames corresponds to the “Full limb” post-processing and “B2” corresponds to the “Jet” post-processing.For the figures in Steinrueck et al. (2025), the spectra were shifted up or down to provide the best match to the full-transit transmission spectrum calculated using a least-squares minimization. See Section 3.3 in the paper or Spectra.ipynb for more details.AttributionPlease cite Steinrueck, Christie, Savel et al. (2025) as well as the Zenodo record when using the model outputs or spectra included in this repository.

Wild animal species often use human-modified environments for foraging and reproduction, but this may require dietary diversification with fitness consequences. The extent to which colonising species successfully exploit such habitats is poorly understood. We used stable isotope analysis of egg yolk to investigate the association between foraging choices and reproductive success in 102 female Herring Gulls (Larus argentatus) over 3 years in a roof-nesting, pericoastal breeding colony. Stable isotopes of egg yolk predominantly reflect maternal diet during egg production. We measured δ13C as an indicator of foraging habitat, and δ15N as an indicator of trophic level. We predicted diverse foraging choices across marine, terrestrial, and urban environments due to gulls’ generalist foraging strategy and the variety of nearby foraging opportunities. We also predicted higher reproductive success associated with marine feeding compared to terrestrial feeding or feeding on human food and refuse, because marine food has historically been gulls’ natural food type and has been previously associated with greater reproductive success. Surprisingly, δ13C values indicated predominantly terrestrial foraging for egg production. Egg mass increased significantly with lower δ13C, indicative of more terrestrial feeding. These findings may reflect the availability of habitats and foods nearby or indicate adaptive dietary choices. Fledging success increased significantly with elevated δ15N, indicating that mothers feeding at higher trophic levels before laying produced higher quality eggs and/or had superior offspring-rearing capacity. A high trophic level maternal diet may nutritionally benefit offspring or improve parental condition. Egg stable isotope ratios of δ13C and δ15N were highly repeatable within clutches, enabling us to predict stable isotope values of unsampled eggs from sampled sibling eggs. Our results highlight high usage of terrestrial foods for egg production, whereas marine and anthropogenic feeding were rare. The reasons for this preference warrant further investigation to advance understanding of species that use human-modified environments.

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