Global Change Drivers Research Articles

Disaster plant pathology: Smart solutions for threats to global plant health from natural and human-driven disasters.

Disaster plant pathology addresses how natural and human-driven disasters impact plant diseases, and the requirements for smart management solutions. Local to global drivers of plant disease change in response to disasters, often creating environments more conducive to plant disease. Most disasters have indirect effects on plant health through factors such as disrupted supply chains and damaged infrastructure. There is also the potential for direct effects from disasters, such as pathogen or vector dispersal due to floods, hurricanes, and human migration driven by war. Pulse stressors such as hurricanes and war require rapid responses, while press stressors such as climate change leave more time for management adaptation but may ultimately cause broader challenges. Smart solutions for the effects of disasters can be deployed through digital agriculture and decision support systems supporting disaster preparedness and optimized humanitarian aid across scales. Here we use the disaster plant pathology framework to synthesize the effects of disasters in plant pathology and outline solutions to maintain food security and plant health in catastrophic scenarios. We recommend actions for improving food security before and following disasters, including (1) strengthening regional and global cooperation, (2) capacity building for rapid implementation of new technologies, (3) effective clean seed systems that can act quickly to replace seed lost in disasters, (4) resilient biosecurity infrastructure and risk assessment ready for rapid implementation, and (5) decision support systems that can adapt rapidly to unexpected scenarios.

Quantifying uncertainty in carbon emission estimation: Metrics and methodologies

Carbon emissions are a significant driver of global climate change in today's world. A central concern in discussing carbon emissions is the level of uncertainty associated with them. This study aims to assess the feasibility of using the Mean Squared Error (MSE) as a point estimation measure and confidence interval (CI) as an interval estimation measure to quantify the uncertainty surrounding carbon emissions. To achieve this goal, the bootstrap and Markov Chain Monte Carlo (MCMC) sampling methods were used, utilizing both classical and Bayesian inference methods to uncover the true parameter value.In the context of Bayesian inference, a 2-chain MCMC method proved to be the optimal choice for generating posterior distributions and accurately estimating the true parameter of the distribution θ. The analysis also shows that, while a CI is valuable as an evaluative measure, it does not inherently provide a quantified form of uncertainty and should not be used for quantitative uncertainty assessment. Instead, the Relative Standard Error (RSE) emerges as a promising quantitative measure for capturing the uncertainty of θ, while the percentage uncertainty offers a qualitative perspective. These combined measures provide a comprehensive toolkit for computing and communicating the uncertainty in carbon emission and emission factor values. This reinforces a move towards incorporating transparent uncertainty metrics, ensuring that stakeholders have access to reliable and accurate carbon emission values.

Environmental and anthropogenic drivers of invasive plant diversity and distribution in the Himalaya

Invasive alien species (IAS) are currently considered as one of the major drivers of global environmental change. To manage the IAS, it is crucial to identify the different environmental and associated anthropogenic drivers that contribute to invasion of alien species to non-native regions. Although multiple drivers of invasion have been identified at a global scale, the relative roles of these are known to vary considerably at regional scales. Here, we investigate the role of key environmental and anthropogenic drivers in determining the diversity and distribution of selected invasive alien plant species in Kashmir Himalaya. We generated an extensive distribution dataset of these species through field sampling across the region and supplemented it with novel herbarium records. We also extracted data on the relevant environmental (climatic, soil and topographic) and anthropogenic drivers for the study region. The random forest model was employed to quantify the relative contribution of these drivers to determine the two common diversity metrics (species richness and abundance) of selected invasive alien plants. We found that soil water content followed by distance to city, the maximum air temperature, soil pH, soil temperature and human population density exerted the greatest influence on richness of invasive species. Species abundance was significantly affected by the maximum air temperature followed by soil temperature, distance to city, slope, soil pH and population density. Overall, our findings help in disentangling the individual and interactive roles of multiple drivers of plant invasions, with wide-ranging implications for management in this Himalayan region and similar landscapes elsewhere.

The exposure of the world’s mountains to global change drivers

The exposure of the world’s mountains to global change drivers

Mixed signals of environmental change and a trend towards ecological homogenization in ground vegetation across different forest types

AbstractForest ground vegetation may serve as an early warning system for monitoring anthropogenic global-change impacts on temperate forests. Climate warming may induce a decline of cool-adapted species to the benefit of more thermophilous plants. Nitrogen deposition has been documented to potentially result in soil eutrophication or acidification, which can increase the proportion of species with higher nutrient requirements and species impoverishment caused by competitive exclusion. Abiotic forest disturbances are changing the light conditions in the forest understorey environment. In this resurvey study, we tested the magnitude and direction of change in alpha (species richness) and beta (within-site dissimilarity) diversity and composition of forest ground vegetation in forests of different types in Slovenia over fifteen years. Using plant-derived characteristics (Ellenberg-type indicator values) and by testing a priori predictions concerning expected effects of environmental drivers, we show that the magnitude and direction of forest ground vegetation diversity and floristic changes varies greatly between forest sites. Divergent responses at different sites resulted in low net change of alpha and beta diversity and a weak overall environmental signal. The largest decrease in species number was observed in lowland oak-hornbeam forests, which were also among the sites with the greatest compositional shifts. Changes in beta diversity did not show any consistent trend, and anticipated floristic convergence was not confirmed when all sites were considered. Thermophilization was mainly detected in montane beech sites and alpine spruce forests whereas eutrophication signal was most significant on nutrient-poor sites. Vegetation responses were strongly dependent on initial site conditions. Shrinkage of ecological gradients (process of ecological homogenization) suggests that sites positioned at the ends of the gradients are losing their original ecological character and are becoming more similar to mid-gradient sites that generally exhibit smaller changes. Our results point to the importance of local stand dynamics and overstorey disturbances in explaining the temporal trends in forest ground vegetation. Ground vegetation in Slovenian forests is changing in directions also dictated by multiple regional and global change drivers.

Unintended consequences of planting native and non‐native trees in treeless ecosystems to mitigate climate change

Abstract Naturally treeless ecosystems are being replaced by native and non‐native trees worldwide, often through deliberate afforestation using forestry tree species. By introducing species having novel traits, such as relatively rapid growth, many afforestation efforts also produce numerous changes in ecosystems, at the landscape scale. Trees are considered critical for climate change mitigation; indeed, many current carbon sequestration strategies rely on trees. Planting trees or allowing trees to naturally colonize through range expansions can be seen as an ideal way to increase atmospheric carbon capture. For example, a snapshot approach may show that introducing trees into treeless ecosystems enhances aboveground accumulation of carbon, helping increase ecosystem carbon storage. However, considering other impacts such as reductions in soil carbon or albedo and increased fire severity (through increases in fuel loads and connectivity) reduces the effectiveness of afforestation strategies for climate change amelioration. Additional negative impacts of afforestation are also likely, such as the reduction of native biodiversity and productivity, substantial water yield losses, and changes in nutrient cycles, which can exacerbate other global change drivers. Further, tree invasions originating from afforestation can exacerbate these negative impacts. Synthesis. This review highlights that the positive and negative impacts of planting trees in naturally treeless ecosystems as a strategy to mitigate climate change are idiosyncratic, depending on the location where trees are introduced, the time period trees are allowed to grow, and risks of spread and impacts associated with specific tree species. Although planting trees can potentially be a tool to fight climate change, a greater consideration of their impacts is required to minimize the unexpected negative consequences of afforestation efforts.

Species richness: A pivotal factor mediating the effects of land use intensification and climate on grassland multifunctionality

Abstract Temperate seminatural grasslands harbour unique biodiversity, support livestock farming through forage production, and deliver many essential ecosystem services (ESs) to human society; they are highly multifunctional. However, temperate grassland ecosystems are also among the most threatened ecosystems on earth due to land use and climate changes. Understanding how biodiversity, climate and land use intensification impact grassland multifunctionality through complex direct and indirect pathways is critical to better anticipate the future of these fragile ecosystems. Here, we evaluate how local plant species richness (SR) modulates the effect of land use intensification and climate on grassland multifunctionality (using six key ESs: biomass productivity and stability, forage quality, carbon storage, pollination and local plant rarity) in the French Massif Central, the largest grassland in Western Europe. We sampled 100 grasslands with contrasted fertilization rates and SR, over large elevational and latitudinal gradients related to variation in mean annual temperature (MAT), and drought severity (DS), two key climate change drivers predicted to increase in the future. Using a confirmatory path analysis, we found that SR was the main driver of multifunctionality. We also found significant SR × MAT and SR × fertilization interactions suggesting that warm climate and high fertilization rates alter the biodiversity–ecosystem multifunctionality relationships. Furthermore, increasing temperature and fertilization indirectly influenced multifunctionality by decreasing SR and consequent multifunctionality in warm lowland and highly fertilized grasslands compared to colder montane grasslands or less fertilized ones. DS only impacted some ES individually (e.g. forage quality). Synthesis and applications: We identified species richness (SR) as a pivotal factor mediating the effects of land use intensification and climate on multifunctionality through both direct and indirect pathways. Failing to account for changes in SR could thus bias any prediction of, or aggravate, the effects of land use intensification and climate change on ecosystem services delivery in temperate grassland ecosystems. Considering that SR, mean annual temperature and fertilization are major proxies of three main global change drivers (biodiversity loss, climate change and land use intensification) our study may help to better anticipate the effect of multiple interacting global change drivers on grassland ecosystems.

Land-use change in the past 40 years explains shifts in arthropod community traits.

Understanding how anthropogenic activities induce changes in the functional traits of arthropod communities is critical to assessing their ecological consequences. However, we largely lack comprehensive assessments of the long-term impact of global-change drivers on the trait composition of arthropod communities across a large number of species and sites. This knowledge gap critically hampers our ability to predict human-driven impacts on communities and ecosystems. Here, we use a dataset of 1.73 million individuals from 877 species to study how four functionally important traits of carabid beetles and spiders (i.e. body size, duration of activity period, tolerance to drought, and dispersal capacity) have changed at the community level across ~40 years in different types of land use and as a consequence of land use changes (that is, urbanisation and loss of woody vegetation) at the landscape scale in Switzerland. The results show that the mean body size in carabid communities declined in all types of land use, with particularly stronger declines in croplands compared to forests. Furthermore, the length of the activity period and the tolerance to drought of spider communities decreased in most land use types. The average body size of carabid communities in landscapes with increased urbanisation in the last ~40 years tended to decrease. However, the length of the activity period, the tolerance to drought, and the dispersal capacity did not change significantly. Furthermore, urbanisation promoted increases in the average dispersal capacities of spider communities. Additionally, urbanisation favoured spider communities with larger body sizes and longer activity periods. The loss of woody areas at the landscape level was associated with trait shifts to carabid communities with larger body sizes, shorter activity periods, higher drought tolerances and strongly decreased dispersal capacities. Decreases in activity periods and dispersal capacities were also found in spider communities. Our study demonstrates that human-induced changes in land use alter key functional traits of carabid and spider communities in the long term. The detected trait shifts in arthropod communities likely have important consequences for their functional roles in ecosystems.

Recognizing Agricultural Headwaters as Critical Ecosystems.

Agricultural headwaters are positioned at the interface between terrestrial and aquatic ecosystems and, therefore, at the margins of scientific disciplines. They are deemed devoid of biodiversity and too polluted by ecologists, overlooked by hydrologists, and are perceived as a nuisance by landowners and water authorities. While agricultural streams are widespread and represent a major habitat in terms of stream length, they remain understudied and thereby undervalued. Agricultural headwater streams are significantly modified and polluted but at the same time are the critical linkages among land, air, and water ecosystems. They exhibit the largest variation in streamflow, water quality, and greenhouse gas emission with cascading effects on the entire stream networks, yet they are underrepresented in monitoring, remediation, and restoration. Therefore, we call for more intense efforts to characterize and understand the inherent variability and sensitivity of these ecosystems to global change drivers through scientific and regulatory monitoring and to improve their ecosystem conditions and functions through purposeful and evidence-based remediation.

Microclimate modulation: An overlooked mechanism influencing the impact of plant diversity on ecosystem functioning.

Changes in climate and biodiversity are widely recognized as primary global change drivers of ecosystem structure and functioning, also affecting ecosystem services provided to human populations. Increasing plant diversity not only enhances ecosystem functioning and stability but also mitigates climate change effects and buffers extreme weather conditions, yet the underlying mechanisms remain largely unclear. Recent studies have shown that plant diversity can mitigate climate change (e.g. reduce temperature fluctuations or drought through microclimatic effects) in different compartments of the focal ecosystem, which as such may contribute to the effect of plant diversity on ecosystem properties and functioning. However, these potential plant diversity-induced microclimate effects are not sufficiently understood. Here, we explored the consequences of climate modulation through microclimate modification by plant diversity for ecosystem functioning as a potential mechanism contributing to the widely documented biodiversity-ecosystem functioning (BEF) relationships, using a combination of theoretical and simulation approaches. We focused on a diverse set of response variables at various levels of integration ranging from ecosystem-level carbon exchange to soil enzyme activity, including population dynamics and the activity of specific organisms. Here, we demonstrated that a vegetation layer composed of many plant species has the potential to influence ecosystem functioning and stability through the modification of microclimatic conditions, thus mitigating the negative impacts of climate extremes on ecosystem functioning. Integrating microclimatic processes (e.g. temperature, humidity and light modulation) as a mechanism contributing to the BEF relationships is a promising avenue to improve our understanding of the effects of climate change on ecosystem functioning and to better predict future ecosystem structure, functioning and services. In addition, microclimate management and monitoring should be seen as a potential tool by practitioners to adapt ecosystems to climate change.

Multiple stressors mediate the effects of warming on leaf decomposition in a large regulated river

AbstractPredicting how increasing temperatures interact with other global change drivers to influence the structure and dynamics of Earth's ecosystems is a primary challenge in ecology. Our study made use of multiple simultaneous “natural experiments” to examine how rapid warming, declining nutrients, invasive consumers, and riparian invasive species management interact to influence leaf decomposition in a large and regulated river. Specifically, we compared the breakdown of cottonwood (Populus fremontii), willow (Salix exigua), and saltcedar (Tamarix sp.) leaf litter in 2022 to a previous experiment from 1998 that occurred under much cooler water temperatures, and had higher water phosphorus concentrations, low numbers of invasive New Zealand mudsnails (Potamopyrgus antipodarum), and unaltered litter chemistry from the herbivory of saltcedar leaf beetles (Diorhabda carinulata). We found that the effects of up to 10°C warmer temperatures on leaf decomposition were mediated by the establishment and management of invasive species and declining water nutrient concentrations arising from upstream reservoir lowering. Such interactions led to accelerated breakdown of saltcedar, but relatively minor effects of warming on the rate of cottonwood and willow decomposition. Additionally, our results demonstrate the potential for favorable invasive species management outcomes in the terrestrial environment to produce unintended responses in adjacent freshwater ecosystems. As temperatures continue to rise, it is critical that future studies consider how warming interacts with multiple stressors and environmental factors to influence processes such as decomposition in freshwater ecosystems.

Applications of Fractional Order Logistic Grey Models for Carbon Emission Forecasting

In recent years, global attention to carbon emissions has increased, becoming one of the main drivers of global climate change. Accurate prediction of carbon emission trends in small and medium-sized countries and scientific regulation of carbon emissions can provide theoretical support and policy references for the effective and rational use of energy and the promotion of the coordinated development of energy, environment, and economy. This paper establishes a grey prediction model using the classical Logistic mathematical model in a determined environment to investigate the carbon emission system. At the same time, we use the basic principle of fractional-order accumulation to establish a grey prediction model with fractional-order Logistic and obtain the parameter estimation and time-response equation of the new model by solving the model through the theory related to fractional-order operators. The particle swarm optimization algorithm is used to complete the optimization process of the order of the fractional order grey prediction model and obtain the optimal model order. Then, the new model is applied to predict carbon emissions in five medium-emission countries: Ethiopia, Djibouti, Ghana, Belgium, and Austria. The new model shows better advantages in the validity analysis process, and the simulation results indicate that the new model proposed in this paper has stronger stability and better simulation and prediction accuracy than other comparative models, proving the model’s validity. Finally, the model is used to forecast the carbon emissions of these five countries for the five years of 2021–2025, and the results are analyzed, and relevant policy recommendations are made.

Contrasting biomass allocations explain adaptations to cold and drought in the world's highest-growing angiosperms.

Understanding biomass allocation among plant organs is crucial for comprehending plant growth optimization, survival and responses to global change drivers. Yet, mechanisms governing mass allocation in vascular plants from extreme elevations exposed to cold and drought stresses remain poorly understood. We analyzed organ mass weights and fractions in 258 Himalayan herbaceous species across diverse habitats (wetland, steppe, alpine), growth forms (annual, perennial taprooted, rhizomatous, cushiony), and climatic gradients (3500-6150 m elevation) to explore whether biomass distribution adhered to fixed allometric or optimal partitioning rules, and how variation in size, phylogeny, and ecological preferences influence their strategies for resource allocation. Following the optimal partitioning theory, Himalayan plants distribute more biomass to key organs vital for acquiring and preserving limited resources necessary for their growth and survival. Allocation strategies are mainly influenced by plant growth forms and habitat conditions, notably temperature, water availability, and evaporative demands. Alpine plants primarily invest in belowground stem bases for storage and regeneration, reducing aboveground stems while increasing leaf mass fraction to maximize carbon assimilation in their short growing season. Conversely, arid steppe plants prioritize deep roots over leaves to secure water and minimize transpiration. Wetland plants allocate resources to aboveground stems and belowground rhizomes, enabling them to resist competition and grazing in fertile environments. Himalayan plants from extreme elevations optimize their allocation strategies to acquire scarce resources under specific conditions, efficiently investing carbon from supportive to acquisitive and protective functions with increasing cold and drought. Intraspecific variation and shared ancestry did not significantly alter Himalayan plants' biomass allocation strategies. Despite diverse evolutionary histories, plants from similar habitats have developed comparable phenotypic structures to adapt to their specific environments. This study offers new insights into plant adaptations in diverse Himalayan environments and underscores the importance of efficient resource allocation for survival and growth in challenging conditions.

Utilization of Macadamia nut oil as a feedstock for a Sustainable Biodiesel Production

Although fossil fuel continues to play a dominant role in global energy system unfortunately their life span is threatened as the fossil reserves are running out. Except for the fact that they are readily available, tried and tested, unfortunately they bring about a negative environmental and climate impact. When the fossil fuels are burned, they produce both carbon dioxide and carbon monoxide which is the largest driver of global climate change and air pollution. This has caused a need to explore and transition to a cleaner and renewable energy resource like biofuel. Biofuel is a combination of fatty acid alkyl esters achieved by the esterification and transterification of triglycerides that can either be animal fats and vegetable oil with methanol and ethanol. Biodiesel provides several positive benefits by helping in decreasing the country’s dependence on the importation of crude oils, it also reduces the greenhouse gas emissions and advances the lubricating property. Biodiesel is produced and deployed globally with China being the country with the highest biofuel capacity in the world, with nearly 29.8 gigawatts as of 2021. It is followed by Brazil which is ranked second, with a biofuel capacity of 16.3 gigawatts. The selection of a feedstock in biofuel production has a noticeable impact as it determines if a biofuel will be formed or not from the transesterification process performed. The fatty acid / triglyceride content especially the Mono-Unsaturated Fatty Acids (MUFA’s) are of interest. The higher the MUFA’s, the higher possibility of a successful transterification hence biofuel being the by-products/formation with less catalyst and alcohol used. Feedstocks with over 40% fatty acids, especially the MUFA’s are favorable for biodiesel formation. Almost 80% of Macadamia’s fatty acids (MFAs) are palmitoleic acids (C16:1; ~20%) and Monounsaturated, mostly oleic (C18:1; ~60%). This study reviews the preparation of biofuel utilizing Macadamia nut oil (MNO) as a feedstock for sustainable biodiesel Production.

Addressing the challenge of wildlife conservation in urban landscapes by increasing human tolerance for wildlife

Abstract Urbanization is a key driver of global environmental change and is adversely impacting wildlife populations. Human tolerance for wildlife is critical to wildlife conservation in urban areas. Using metropolitan Atlanta, Georgia, United States, as a case study, we investigated human tolerance for a range of different wildlife species. Almost half of the human–wildlife interactions that are reported to the state wildlife agency originate from metropolitan Atlanta, which is one of the fastest growing metropolises in the United States. We surveyed a representative sample of 1006 residents of metropolitan Atlanta in 2022. We found heterogeneity in respondents' tolerance for various species, although most respondents were intolerant of bobcats, coyotes, opossums and snakes. Respondents' tolerance for different species largely depended on their attitudes and emotions towards species, and their basic beliefs pertaining to wildlife and the relationships between humans and wildlife. We found some evidence that tolerance also depended on people's prior interactions with wildlife, their beliefs that they can mitigate conflicts with wildlife and their demographic characteristics. Our results suggest that communication that improves urban residents' attitudes towards wildlife and/or reinforces positive emotions towards wildlife may increase wildlife tolerance in urban areas. Read the free Plain Language Summary for this article on the Journal blog.

Forces driving ecological degradation in southern China during the MIS3: Natural or anthropogenic?

The role of natural forces in ecological degradation remains controversial owing to the scarcity of records of past land cover destruction with no or less anthropogenic disturbance. Here, we reconstructed land cover changes during the Marine Isotope Stage 3 (MIS3) in the Nanling Mountains in southern China using the δ13C and saturation magnetisation (Ms) records of a speleothem from Zuixian Cave. The persistently positive δ13C values since 51.9 ka B.P. suggest vegetation reduction and karst rocky desertification in the Nanling Mountains. This prolonged ecological degradation was exposed to reduced precipitation, weak pedogenesis (as indicated by less depleted δ18O ratios and low Ms values), and recurring forest fires. Our results highlight the critical role of natural forces in ecosystem degradation, challenging the view of human domination on environmental change. These findings could improve our understanding of the drivers of current ecological evolution and global change.

Rapid turnover of a pea aphid superclone mediated by thermal endurance in central Chile.

Global change drivers are imposing novel conditions on Earth's ecosystems at an unprecedented rate. Among them, biological invasions and climate change are of critical concern. It is generally thought that strictly asexual populations will be more susceptible to rapid environmental alterations due to their lack of genetic variability and, thus, of adaptive responses. In this study, we evaluated the persistence of a widely distributed asexual lineage of the alfalfa race of the pea aphid, Acyrthosiphon pisum, along a latitudinal transect of approximately 600 km in central Chile after facing environmental change for a decade. Based on microsatellite markers, we found an almost total replacement of the original aphid superclone by a new variant. Considering the unprecedented warming that this region has experienced in recent years, we experimentally evaluated the reproductive performance of these two A. pisum lineages at different thermal regimes. The new variant exhibits higher rates of population increase at warmer temperatures, and computer simulations employing a representative temperature dataset suggest that it might competitively displace the original superclone. These results support the idea of a superclone turnover mediated by differential reproductive performance under changing temperatures.

The impact of extreme weather events exceeds those due to global-change drivers on coastal phytoplankton assemblages

Extreme wind and rainfall events have become more frequent phenomena, impacting coastal ecosystems by inducing increased mixing regimes in the upper mixed layers (UML) and reduced transparency (i.e. browning), hence affecting phytoplankton photosynthesis. In this study, five plankton assemblages from the South Atlantic Ocean, from a gradient of environmental variability and anthropogenic exposure, were subjected to simulated extreme weather events under a global change scenario (GCS) of increased temperature and nutrients and decreased pH, and compared to ambient conditions (Control). Using multiple linear regression (MLR) analysis we determined that evenness and the ratio of diatoms/ (flagellates + dinoflagellates) significantly explained the variations (81–91 %) of the photosynthesis efficiency (i.e. Pchla/ETRchla ratio) for each site under static conditions. Mixing speed and the optical depth (i.e. attenuation coefficient * depth, kdz), as single drivers, explained 40–76 % of the variability in the Pchla/ETRchla ratio, while GCS drivers <9 %. Overall, assemblages with high diversity and evenness were less vulnerable to extreme weather events under a GCS. Extreme weather events should be considered in global change studies and conservation/management plans as even at local/regional scales, they can exceed the predicted impacts of mean global climate change on coastal primary productivity.

Resource asynchrony and landscape homogenization as drivers of virulence evolution: The case of a directly transmitted disease in a social host.

Throughout the last decades, the emergence of zoonotic diseases and the frequency of disease outbreaks have increased substantially, fuelled by habitat encroachment and vectors overlapping with more hosts due to global change. The virulence of pathogens is one key trait for successful invasion. In order to understand how global change drivers such as habitat homogenization and climate change drive pathogen virulence evolution, we adapted an established individual-based model of host-pathogen dynamics. Our model simulates a population of social hosts affected by a directly transmitted evolving pathogen in a dynamic landscape. Pathogen virulence evolution results in multiple strains in the model that differ in their transmission capability and lethality. We represent the effects of global change by simulating environmental changes both in time (resource asynchrony) and space (homogenization). We found an increase in pathogenic virulence and a shift in strain dominance with increasing landscape homogenization. Our model further indicated that lower virulence is dominant in fragmented landscapes, although pulses of highly virulent strains emerged under resource asynchrony. While all landscape scenarios favoured co-occurrence of low- and high-virulent strains, the high-virulence strains capitalized on the possibility for transmission when host density increased and were likely to become dominant. With asynchrony likely to occur more often due to global change, our model showed that a subsequent evolution towards lower virulence could lead to some diseases becoming endemic in their host populations.

Economic costs of invasive non-native species in urban areas: An underexplored financial drain

Urbanization is an important driver of global change associated with a set of environmental modifications that affect the introduction and distribution of invasive non-native species (species with populations transported by humans beyond their natural biogeographic range that established and are spreading in their introduced range; hereafter, invasive species). These species are recognized as a cause of large ecological and economic losses. Nevertheless, the economic impacts of these species in urban areas are still poorly understood. Here we present a synthesis of the reported economic costs of invasive species in urban areas using the global InvaCost database, and demonstrate that costs are likely underestimated. Sixty-one invasive species have been reported to cause a cumulative cost of US$ 326.7 billion in urban areas between 1965 and 2021 globally (average annual cost of US$ 5.7 billion). Class Insecta was responsible for >99 % of reported costs (US$ 324.4 billion), followed by Aves (US$ 1.4 billion), and Magnoliopsida (US$ 494 million). The reported costs were highly uneven with the sum of the five costliest species representing 80 % of reported costs. Most reported costs were a result of damage (77.3 %), principally impacting public and social welfare (77.9 %) and authorities-stakeholders (20.7 %), and were almost entirely in terrestrial environments (99.9 %). We found costs reported for 24 countries. Yet, there are 73 additional countries with no reported costs, but with occurrences of invasive species that have reported costs in other countries. Although covering a relatively small area of the Earth's surface, urban areas represent about 15 % of the total reported costs attributed to invasive species. These results highlight the conservative nature of the estimates and impacts, revealing important biases present in the evaluation and publication of reported data on costs. We emphasize the urgent need for more focused assessments of invasive species' economic impacts in urban areas.