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Workflow for generating variables describing base climate, variability and extremes using monthly maximum temperature, minimum temperature and precipitation data at a single location approximately 7 km east of Melbourne, Australia.
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Extreme weather can have significant impacts on plant species demography; however, most studies have focused on responses to a single or small number of extreme events. Long‐term patterns in climate extremes, and how they have shaped contemporary distributions, have rarely been considered or tested. BIOCLIM variables that are commonly used in corre...
Citations
... Our results support our initial hypothesis that the maximum experienced stresses are closely related to the physiological limits of the species, despite the uncertainty in the calculation of maximum drought stress. This is consistent with recent studies that have emphasised the importance of using climatic extremes rather than averages to explain ecological patterns, despite being well correlated (Stewart et al. 2021). Moreover, this agrees with Blackman et al. (2012) and Brodribb et al. (2014) who also showed this pattern when looking at correlation of Ψ 50 with the 5th percentile of map or the driest quarter rainfall. ...
Species distribution models are key to evaluate how climate change threatens European forests and tree species distributions. However, current models struggle to integrate ecophysiological processes. Mechanistic models are complex and have high parameter requirements. Some correlative species distribution models have tried to include traits but so far have struggled to directly connect to ecophysiological processes. Here, we propose a new strategy in which species distributions are based on safety margins which represent species' proximity to their physiological thresholds. We derived frost and drought safety margins for 38 European tree species as the difference between physiological tolerance traits and local maximum stress. We used LT50 and Ψ50 as tolerance traits for frost and drought, respectively, and local minimum temperature and minimum soil water potential as maximum stress. We integrated these safety margins into a species distribution model, which tests if the probability of species presence declines rapidly when the safety margin reaches zero, when physiological stress exceeds the species' tolerance traits. Our results showed thaet 35 of the 38 studied species had their distribution explained by one or both safety margins. We demonstrated that safety‐margins‐based model can be efficiently transferred to species for which occurrence data are not available. The probability of presence dropped dramatically when the frost safety margin reached zero, whereas it was less sensitive to the drought safety margin. This differential sensitivity may be due to the more complex regulation of drought stress, especially as water is a shared resource, whereas frost is not. Our analysis provides a new approach to link species distributions to their physiological limits and shows that, in Europe, frost and drought safety margins are important determinants of species distributions.
... SDMs relate climatic conditions to the probability of observing a species, and have been used to estimate the current and future distributions of species. However, a major limitation of current SDMs and the niche ideas they are based on is they do not account for inter-annual climate variability, even though variability is known by demographers to play a crucial role in population dynamics and therefore probably also in species distributions [4,5,6]. Because climate change is altering climate variability, e.g. by modifying the intensity, frequency, and duration of extreme environmental events such as heat waves and floods [7,8], addressing the shortcomings of current SDMs with respect to climate variability is crucial for mitigating the impacts of climate change on biodiversity. ...
Inter-annual climate variability affects the long-term growth rate and thus the viability of populations. Despite the importance of climate variability, niche models and species distribution models (SDMs) typically do not account for it. This causes systematic biases in the projected distributions of species and can mislead conservation measures. Here, we use ideas from stochastic demography to quantify the effects of inter-annual climate variability on population performance and distributions of species, developing a new SDM framework which we call XSDM. The new framework expands the traditional deterministic notion of the fundamental niche, re-conceptualizing the niche to account for stochasticity. XSDM can be applied widely, requiring only occurrence data, e.g. from GBIF, and it shows superior performance to commonly-used SDMs in simulation studies. Using XSDM, we assessed the impacts of inter-annual climate variability on 10 North-American species chosen as illustrative examples. We found that climate variability reduces the potential distribution of the species on average by 26% and up to 57%. SDMs and niche concepts that do not incorporate variability cannot account for this reduction and can thus be strongly biased.
Because climate change is altering not only average conditions, but also the frequency and intensity of extreme events, which are aspects of variability, it is paramount to better understand how climate variability influences the distributions of species in order to help mitigate future biodiversity losses due to climate change. Our new XSDM approach provides a new foundation for such a research program by helping reorient niche theory to include stochastic effects.
... Unfortunately, using a single average can hide trends and variability in climate (Zimmermann et al. 2009, Ingenloff and Peterson 2021, Perez-Navarro et al. 2022, Pinilla-Buitrago 2023 or could fail to represent the current climate due to recent changes in temperature and precipitation (Livezey et al. 2007, Arguez and Vose 2011, Wilks and Livezey 2013. One approach to address these limitations is to incorporate explicit temporal variables, such as extremes during the reference period (Zimmermann et al. 2009, Moran-Ordonez et al. 2018, Stewart et al. 2021) and inter-annual variability variables (Zimmermann et al. 2009, Brodie et al. 2021, Gardner et al. 2021). However, this may not completely solve the issue of occurrence-environment mismatch since occurrences are associated with the climatic variability or extreme values that occurred after their observation date, especially for records from the beginning of the reference period (Fig. 1a). ...
Ecological niche models, crucial for estimating species’ potential distribution under global change, can face reduced accuracy when the timing of occurrence data does not align with the environmental data. One solution is to ensure a close temporal match between the environment and the observation date. While this approach is typically recommended for highly mobile species, a few findings support its use for species with limited mobility, whose distributions may be responding to climate change via local population changes. Additionally, it remains unclear what specific temporal resolution could improve model performance. This study assesses the effectiveness of temporal matching for a species with low mobility, the Mexican small-eared shrew (Cryptotis mexicanus), by evaluating different temporal resolutions (one-, five-, and ten-year averaged environmental data) against the standard method (30-year). Occurrences between 1971 and 2000 were used for model training and cross-validation, while those outside this range were used for external evaluation. Based on the omission rate of the external evaluation occurrences, the approach that matched environmental data using the prior ten-year resolution performed better than the standard 30-year average approach, while the rest of evaluation metrics (for any temporal resolution) were not different. Visual inspection indicated that the geographic prediction resulting from a ten-year resolution was as realistic as the one from the standard 30-year approach. In contrast, the shorter temporal resolutions (one and five years) resulted in unrealistic estimates. Therefore, matching the timing of occurrences and environmental data for other species with low mobility may also improve model performance and geographic predictions. Additionally, this correlative approach identifies a potential time lag between climatic changes and population responses in this species. Studies can select the optimal temporal resolution by exploring several or using available information about population responses to climate change.
... A broader implication is that the many studies that have used regionally aggregated data to investigate the effects of climate on population dynamics of organisms with limited mobility might have underestimated the role of climate as a driver of population dynamics. The ecological significance of climate extremes (Stewart et al., 2021), combined with the predicted future increase in the frequency of extreme climate events (IPCC, Seneviratne et al., 2021), implies that our findings of discrepancies between the effects of local and regional temperatures on plant performance point to the urgent need to use organism-relevant estimates of climate when assessing risks and developing mitigation strategies. ...
Climate is assumed to strongly influence species distribution and abundance. Although the performance of many organisms is influenced by the climate in their immediate proximity, the climate data used to model their distributions often have a coarse spatial resolution. This is problematic because the local climate experienced by individuals might deviate substantially from the regional average. This problem is likely to be particularly important for sessile organisms like plants and in environments where small‐scale variation in climate is large. To quantify the effect of local temperature on vital rates and population growth rates, we used temperature values measured at the local scale (in situ logger measures) and integral projection models with demographic data from 37 populations of the forest herb Lathyrus vernus across a wide latitudinal gradient in Sweden. To assess how the spatial resolution of temperature data influences assessments of climate effects, we compared effects from models using local data with models using regionally aggregated temperature data at several spatial resolutions (≥1 km). Using local temperature data, we found that spring frost reduced the asymptotic population growth rate in the first of two annual transitions and influenced survival in both transitions. Only one of the four regional estimates showed a similar negative effect of spring frost on population growth rate. Our results for a perennial forest herb show that analyses using regionally aggregated data often fail to identify the effects of climate on population dynamics. This emphasizes the importance of using organism‐relevant estimates of climate when examining effects on individual performance and population dynamics, as well as when modeling species distributions. For sessile organisms that experience the environment over small spatial scales, this will require climate data at high spatial resolutions.
... However, these variables are the most important predictors in some studies (Booth, 2022). Fourth, species distributions often depend more on extremes than on annual means, and extremes are underrepresented in the BCV dataset (Bradie & Leung, 2017;Stewart et al., 2021). ...
Bioclimatic variables (BCVs) are the most widely used predictors within the field of species distribution modeling, but recent studies imply that BCVs alone are not sufficient to describe these limits. Unfortunately, the most popular database, WorldClim, offers only a limited selection of bioclimatological predictors; thus, other climatological datasets should be considered, and, for data consistency, the BCVs should also be derived from the respective datasets. Here, we investigate how well the BCVs are represented by different datasets for the extended Mediterranean area within the period 1970–2020, how different calculation schemes affect the representation of BCVs, and how deviations among the datasets differ regionally. We consider different calculation schemes for quarters/months, the annual mean temperature (BCV‐1), and the maximum temperature of the warmest month (BCV‐5). Additionally, we analyzed the effect of different temporal resolutions for BCV‐1 and BCV‐5. Differences resulting from different calculation schemes are presented for ERA5‐Land. Selected BCVs are analyzed to show differences between WorldClim, ERA5‐Land, E‐OBS, and CRU. Our results show that (a) differences between the two calculation schemes for BCV‐1 diminish as the temporal resolution decreases, while the differences for BCV‐5 increase; (b) with respect to the definition of the respective month/quarter, intra‐annual shifts induced by the calculation schemes can have substantially different effects on the BCVs; (c) all datasets represent the different BCVs similarly, but with partly large differences in some subregions; and (d) the largest differences occur when specific month/quarters are defined by precipitation. In summary, (a) since the definition of BCVs matches different calculation schemes, transparent communication of the BCVs calculation schemes is required; (b) the calculation, integration, or elimination of BCVs has to be examined carefully for each dataset, region, period, or species; and (c) the evaluated datasets provide, except in some areas, a consistent representation of BCVs within the extended Mediterranean region.
... Average climate is associated with the long-term geographic distributions of many species, but climate extremes (e.g. droughts, floods, heat waves), which are becoming more frequent and intense (Meehl andTebaldi 2004, IPCC 2012), may be equally relevant to organisms' body condition and population dynamics (Zimmerman et al 2009, Germain and Lutz 2020, Rangwala et al 2021, Stewart et al 2021. Extremes can affect wildlife physiologically or via changes in the amount and quality of habitat or components of habitat (Parmesan et al 2000, Maxwell et al 2019, Román-Palacios and Wiens 2020, Turner et al 2020. ...
Assessments of the potential responses of animal species to climate change often rely on correlations between long-term average temperature or precipitation and species’ occurrence or abundance. Such assessments do not account for the potential predictive capacity of either climate extremes and variability or the indirect effects of climate as mediated by plant phenology. By contrast, we projected responses of wildlife in desert grasslands of the southwestern United States to future climate means, extremes, and variability and changes in the timing and magnitude of primary productivity. We used historical climate data and remotely sensed phenology metrics to develop predictive models of climate-phenology relations and to project phenology given anticipated future climate. We used wildlife survey data to develop models of wildlife-climate and wildlife-phenology relations. Then, on the basis of the modeled relations between climate and phenology variables, and expectations of future climate change, we projected the occurrence or density of four species of management interest associated with these grasslands: Gambel’s Quail (Callipepla gambelii), Scaled Quail (C. squamat), Gunnison’s prairie dog (Cynomys gunnisoni), and American pronghorn (Antilocapra americana). Our results illustrated that climate extremes and plant phenology may contribute more to projecting wildlife responses to climate change than climate means. Monthly climate extremes and phenology variables were influential predictors of population measures of all four species. For three species, models that included climate extremes as predictors outperformed models that did not include extremes. The most important predictors, and months in which the predictors were most relevant to wildlife occurrence or density, varied among species. Our results highlighted that spatial and temporal variability in climate, phenology, and population measures may limit the utility of climate averages-based bioclimatic niche models for informing wildlife management actions, and may suggest priorities for sustained data collection and continued analysis.
... For climatic and anthropogenic variables, we relied on the Global Environmental Composite 76,77 . This global database contains spatially explicit geographic information system (GIS) layers of more than 260 unique environmental variables, encompassing climate, soil, land cover and land use, plant biomass, topography, human footprint, and disturbance 78,79 . Climate variables were extracted from the CHELSA (climatologies at high resolution for the earth's land surface areas) dataset 78 , whereas soil variables were from the SoilGrids 80 dataset. ...
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.
... When incorporated into ENMs, these values can result in inaccurate estimations of extinction risk and ineffective conservation plans (Gardner et al., 2021;Perez-Navarro et al., 2021;Reside et al., 2010). Including climate extremes (i.e., the frequency of shortterm extreme weather events such as heatwaves and droughts) has improved model performance, leading to better range shift forecasting (Germain and Lutz, 2020;Stewart et al., 2021). Despite this, the practice does not provide insights into whether species are already responding to climate change. ...
... The adverse impacts of thermal exposure (for example, declines of fitness or increased mortality) are probably driven by the increasing intensity and frequency of extreme temperatures rather than changes in long-term climate averages 24,25 . In this study, we define thermal exposure as the year after which the annual maximum monthly air or sea-surface temperatures in a grid cell consistently (for at least 5 consecutive years) exceeds the most extreme monthly temperature experienced by a species across its geographical range over recent history (1850-2014), hereafter its 'upper realized thermal limit' 10 (Methods). ...
Climate change is already exposing species to dangerous temperatures driving widespread population and geographical contractions. However, little is known about how these risks of thermal exposure will expand across species’ existing geographical ranges over time as climate change continues. Here, using geographical data for approximately 36,000 marine and terrestrial species and climate projections to 2100, we show that the area of each species’ geographical range at risk of thermal exposure will expand abruptly. On average, more than 50% of the increase in exposure projected for a species will occur in a single decade. This abruptness is partly due to the rapid pace of future projected warming but also because the greater area available at the warm end of thermal gradients constrains species to disproportionately occupy sites close to their upper thermal limit. These geographical constraints on the structure of species ranges operate both on land and in the ocean and mean that, even in the absence of amplifying ecological feedbacks, thermally sensitive species may be inherently vulnerable to sudden warming-driven collapse. With higher levels of warming, the number of species passing these thermal thresholds, and at risk of abrupt and widespread thermal exposure, increases, doubling from less than 15% to more than 30% between 1.5 °C and 2.5 °C of global warming. These results indicate that climate threats to thousands of species are expected to expand abruptly in the coming decades, thereby highlighting the urgency of mitigation and adaptation actions.
... Climate extremes, noted to be a necessity for the balance of the Earth's atmosphere, have become more frequent and intensified in their destructive behaviour due to global climate change (Stewart et al. 2021). Climate extremes, such as droughts and floods, potentially alter carbon (C) and nitrogen (N) cycling in terrestrial ecosystems at profoundly different timescales (Xu et al. 2009;Bai et al. 2015a, b;Choi et al. 2020). ...
... Climate extremes, such as droughts and floods, potentially alter carbon (C) and nitrogen (N) cycling in terrestrial ecosystems at profoundly different timescales (Xu et al. 2009;Bai et al. 2015a, b;Choi et al. 2020). Hence, increasing environmental stress exists within forest ecosystems, decreasing plant and soil health (Stewart et al. 2021). Extreme events, such as heatwaves, floods and bushfires, can be short in duration but can have long-lasting impacts upon ecosystem function and services (Li et al. , 2020a(Li et al. , 2021aPeguero et al. 2021;Stewart et al. 2021), shaping the abundance and distribution of plant communities (Girardin 2009: Li et al. 2022a. ...
... Hence, increasing environmental stress exists within forest ecosystems, decreasing plant and soil health (Stewart et al. 2021). Extreme events, such as heatwaves, floods and bushfires, can be short in duration but can have long-lasting impacts upon ecosystem function and services (Li et al. , 2020a(Li et al. , 2021aPeguero et al. 2021;Stewart et al. 2021), shaping the abundance and distribution of plant communities (Girardin 2009: Li et al. 2022a. Increasing temperatures and heatwaves lead to increasing intensity and frequency of droughts, which can cause a warmer and drier environment, resulting in increases in bushfires and lighting frequency (Girardin 2009;Li et al. 2021a). ...
Purpose
Climate extremes, such as droughts and floods, have become intensified and more frequent due to intensifying climate change. Increased atmospheric carbon dioxide (CO2) and warming-induced water limitation, as well as climate extremes, may alter carbon (C) and nitrogen (N) cycling in forest ecosystems. This provides a brief review of stable nitrogen isotopic composition (δ¹⁵N) in tree ring in relation to climate extremes and bushfires in context of N availability and losses in forest ecosystems.
Material and methods
Tree rings were extracted from four Pinus sylvestris and four Larix gmelinii sample trees, located in a boreal plantation forest of Mohe City, Heilongjiang Province, China. Tree rings were measured to obtain mean annual basal area increment (BAI), while tree ring δ¹⁵N and total N concentrations were measured on mass spectrometer at 3-year intervals. The tree ring δ¹⁵N data were related to possible climate extremes and bushfires. A brief review of the relevant literature was also undertaken to support our preliminary research findings.
Results and discussion
Globally, increasing atmospheric CO2 concentration and water limitations have led to a warmer-drier climate. This has also been associated with increases of climate extremes such as drought and floods as well as bushfires. These extremes have been recorded with detrimental effects on plant and soil structures within forest ecosystems and play an important role in regulating N availability and losses in forest ecosystems. Studies of N deposition within forest ecosystems using soil and plant δ¹⁵N also showed that N losses under various climate extremes can occur through direct changes in N cycling, such as increasing soil nitrification and denitrification or leaching. It is highlighted that tree rings δ¹⁵N has the potential to fingerprint the intensity and frequency of climate extremes and bushfires in the forest ecosystems, but more such tree ring δ¹⁵N research needs to be done in diversified forest ecosystems to confirm the potential of using tree ring δ¹⁵N for quantifying the frequency and intensity of climate extremes and bushfires at both regional and global scale.
Conclusion
The variation and trend of δ¹⁵N in the soil–plant-climate systems are closely linked to the N cycling in forest ecosystems, and tree ring δ¹⁵N has the great potential to fingerprint both intensity and frequency of climate extremes such as drought and floods as well as bushfires.
