Global Change Research Research Articles

A meta‐analysis of the effects of climate change‐related abiotic factors on aboveground and belowground plant‐associated microbes

The abiotic environment exerts strong effects on plant‐associated microbes, shaping their interactions with plants and resulting ecosystem processes. However, these abiotic effects on plant–microbe interactions are often highly specific and contingent on the abiotic driver or microbial group, requiring synthesis work describing general patterns and from this generate hypotheses and guide mechanistic work. To address this, we conducted a meta‐analysis of the effects of climate change‐related abiotic factors, namely warming, drought, and eCO2, on plant‐associated microbes distinguishing by microbial taxonomic or biological group (bacteria, fungi or virus) and the plant part where microbes are found or associated with (phyllosphere or rhizosphere). We found abiotic driver‐specific patterns, whereby drought significantly reduced microbial abundance, whereas warming and eCO2 had no significant effects. In addition, these abiotic effects were contingent on the microbial taxonomic group, with fungi being negatively affected by drought but positively affected by warming (eCO2 enrichment had no effect), whereas bacteria and viruses were not significantly affected by any factor. Likewise, rhizospheric microbes were negatively affected by drought but positively affected by warming (eCO2 enrichment had no effect), whereas phyllospheric microbes were not significantly affected by any factor. Collectively, these findings point to important implications for global change research by highlighting contrasting effects of climate change‐related abiotic drivers on plant‐associated microbes and the contingency of such effects on microbe life histories and the nature of their interactions with plants.

Tree growth and survival are more sensitive to high rainfall than drought in an aseasonal forest in Malaysia

Global change research has largely focused on the effects of drought on forest dynamics while the importance of excessive rainfall that can cause waterlogged soils has largely been assessed in riparian zones or seasonally flooded sites. However, increased rainfall may also cause decreased growth and survival of tree species in lowland aseasonal tropical forests due to increased risk from potentially more extensive and frequent waterlogged soils. We used a Bayesian modelling approach on a tree dynamics dataset from 2004 to 2017 to test the concomitant effects of rainfall excess and deficit and dry period length on tree growth and survival across a network of experimentally planted trees in a primary aseasonal forest in Malaysia. Growth declined in 48% of the species and survival decreased in 92% of the species during periods of high rainfall while as little as 4% of species had decreased growth or survival with drought and long dry periods. Climate change is projected to cause more frequent and severe rainfall deficit and excess, and our results suggest increased rainfall may have stronger negative effects on aseasonal tropical forests than that of severe drought.

Research on Landsat 8 land surface temperature retrieval and spatial–temporal migration capabilities based on random forest model

Land surface temperature (LST) plays a crucial role in characterizing land surface processes and the energy balance. Accurate monitoring of spatial–temporal variations in LST holds great significance for global and regional climate change research. However, with the increasing of multi-source remote sensing data, it has become a challenging task to construct an LST model that reduces dependence on auxiliary data (such as land surface emissivity (LSE) and atmospheric water vapor content (WVC) synchronized with satellite observations. This study proposed an LST retrieval model based on random forest model (RFLSTR). The results of 10-fold cross-validation showed that the RFLSTR model had high modelling accuracy, the coefficient of determination (R2) was 0.99, and the root mean square error (RMSE) and mean absolute error (MAE) were lower than 2 K. Landsat 8 images from the Beijing area and South Korea, were utilized to assess the spatial–temporal migration performance of the RFLSTR model. Additionally, Landsat 9 images from South Korea were employed to analyse the sensor migration performance of the RFLSTR model. In conclusion, the findings highlight that the proposed RFLSTR model achieve high retrieval accuracy without relying on auxiliary data (such as LSE and WVC) synchronized with satellite observations. Moreover, the RFLSTR model exhibits robust spatial–temporal capabilities, enhancing the efficiency of LST retrieval and facilitating the utilization of satellite data.

“Maybe you need to do something about it”: challenges in global environmental change research with and within local communities

AbstractResearch on issues such as adapting to rapid environmental change should include indigenous and local people in developing more robust and inclusive diagnoses and responses. Various studies indicate that such projects may face challenges. Researchers touch on these in papers where they reflect on their own work, but to a lesser extent in their empirical papers. Based on interviews with, and articles by, a varied sample of 15 researchers who work with local or indigenous peoples around the globe, I identified the challenges they face and how they deal with them. Thematic analysis of interview transcripts revealed eight themes: (1) external pressure, (2) engaging local people, (3) relevance of projects, (4) prior negative experiences, (5) cultural, historical, and geographical differences, (6) language challenges, (7) payment for participation, and (8) diverging epistemic cultures. Respondents’ statements in all themes contain reflections displaying care, consideration, or responsibility for the projects and the local people they involve. This links the challenges with everyday ethics. Analysis of scientific papers written by the respondents showed that they hardly write about the challenges they face, whereby neither local participants nor other readers of these texts are actively informed by and engaged in critical-reflective discussions about the challenges arising during the research and the strategies used to deal with them. The research community has a responsibility to remedy this shortcoming: in their papers, authors should discuss the main challenges faced and develop, describe, and promulgate strategies for dealing with them.

GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method

Abstract. Land-cover change has been identified as an important cause or driving force of global climate change and is a significant research topic. Over the past few decades, global land-cover mapping has progressed; however, long-time-series global land-cover-change monitoring data are still sparse, especially those at 30 m resolution. In this study, we describe GLC_FCS30D, a novel global 30 m land-cover dynamics monitoring dataset containing 35 land-cover subcategories and covering the period 1985–2022 in 26 time steps (maps were updated every 5 years before 2000 and annually after 2000). GLC_FCS30D has been developed using continuous change detection and all available Landsat imagery based on the Google Earth Engine platform. Specifically, we first take advantage of the continuous change-detection model and the full time series of Landsat observations to capture the time points of changed pixels and identify the temporally stable areas. Then, we apply a spatiotemporal refinement method to derive the globally distributed and high-confidence training samples from these temporally stable areas. Next, local adaptive classification models are used to update the land-cover information for the changed pixels, and a temporal-consistency optimization algorithm is adopted to improve their temporal stability and suppress some false changes. Further, the GLC_FCS30D product is validated using 84 526 globally distributed validation samples from 2020. It achieves an overall accuracy of 80.88 % (±0.27 %) for the basic classification system (10 major land-cover types) and 73.04 % (±0.30 %) for the LCCS (Land Cover Classification System) level-1 validation system (17 LCCS land-cover types). Meanwhile, two third-party time-series datasets used for validation from the United States and Europe Union are also collected for analyzing accuracy variations, and the results show that GLC_FCS30D offers significant stability in terms of variation across the accuracy time series and achieves mean accuracies of 79.50 % (±0.50 %) and 81.91 % (±0.09 %) over the two regions. Lastly, we draw conclusions about the global land-cover-change information from the GLC_FCS30D dataset; namely, that forest and cropland variations have dominated global land-cover change over past 37 years, the net loss of forests reached about 2.5 million km2, and the net gain in cropland area is approximately 1.3 million km2. Therefore, the novel dataset GLC_FCS30D is an accurate land-cover-dynamics time-series monitoring product that benefits from its diverse classification system, high spatial resolution, and long time span (1985–2022); thus, it will effectively support global climate change research and promote sustainable development analysis. The GLC_FCS30D dataset is available via https://doi.org/10.5281/zenodo.8239305 (Liu et al., 2023).

Research progress on the synergies between heat waves and canopy urban heat island and their driving factors

Under the background of global warming and accelerating urbanization, the interaction between heat waves (HWs) and canopy urban heat island (CUHI) has become one of the focuses in the field of global climate change research. This paper comprehensively reviewed and summarized the research process on the synergies of HWs and CUHI and their influencing mechanism. The coupling effect between HWs and CUHI remains debated, which may be related to the use of different standards to define heat wave events. The spatiotemporal differences in the synergies between HWs and CUHI was also influenced by climate background and local circulation. For instance, scholars have reached different conclusions regarding the stronger synergistic effect between daytime and nighttime in cities with different climate backgrounds. In addition, the modulation of urban morphological structure to the synergies between HWs and CUHI cannot be ignored. In the future, it is necessary to adopt different definitions of HWs to systematically study the formation mechanism of urban excess warming from different climatic backgrounds, local circulation conditions, and urban morphologies.

Hydroclimate Changes Based on Testate Amoebae in the Greater Khingan Mountains’ Peatland (NE China) during the Last Millennium

The driving force of climate change in the monsoon margin is complex, making it a key area for regional and global climate change research. Palaeohydrological studies in the monsoon margin have increased the resolution of research in the long term, transitioning from qualitative to quantitative studies to comprehend climate change processes, patterns, and mechanisms. Testate amoebae (TA) in peat sediments are used as a proxy indicator organism for quantitative reconstruction of palaeohydrology. Thus, their community changes are directly related to precipitation, and widely used to reconstruct the patterns of summer precipitation globally. We investigated TA species and reconstructed palaeohydrological changes in the Greater Khingan Mountains’ Hongtu (HT) peatland, located in the East Asian Summer Monsoon (EASM) margin. The result showed that the most abundant TA species were Assulina muscorum (12.4 ± 5.0%) and Nebela tincta (8.9 ± 4.9%) in the HT peat core. The increase in dry indicator species (e.g., A. muscorum and Alabasta militaris) indicated a drying pattern in the HT peatland since 150 cal yr BP. Principal component analysis (PCA) explained 47.6% of the variation in the selected TA assemblages. During 400 to 250 cal yr BP, PCA axis 1 scores ranged from 0.2 to −1.3 (reflecting a drier climate), associating with the Little Ice Age. The paleohydrology of the northern part of the Greater Khingan Mountains was mainly controlled by the EASM, which was associated with changes in North Atlantic Sea surface temperature and solar radiative forcing. The apparent drying pattern may be the result of the gradual intensification of anthropogenic activities and the increase in EASM intensity.

Analysis of the evolution of water culture and water security in the Weihe River Basin over a 100 year-period

The significance of water culture in addressing water crises and ensuring water security has garnered considerable attention, emerging as a focal point in global change and water science research. Water culture is a societal adaptation to changes in hydrological systems. However, this needs to be acknowledged within contemporary discourse on water security governance. This study utilized historical policy document data from many sources, including local municipal records from Shaanxi and Gansu, and water conservancy records. It aimed to identify the significant nodes and stages of policy transformation in the Weihe River Basin (WRB) during the last century (1949–2020). This study employed a content analysis method to elucidate the evolutionary patterns of water culture in the study region during the previous century. Drawing on the co-evolution framework, our investigation delved into the reciprocal relationship between changes in water culture and the evolution of water security in the WRB. Our findings indicated that water culture transformation in the WRB has undergone four significant stages: the Disaster-Resistant Hydraulic (1949–1966), Irrigation Hydraulic (1967–1998), Resources Hydraulic (1999–2010), and Ecological Hydraulic (2011–2020) phases. Water security assessment showed that policy attention varied across the different stages. The disaster-resistant hydraulic phase primarily addressed water-related disaster concerns, whereas the irrigation hydraulic phase emphasized the scarcity of water resources. The resource hydraulic phase focused on ensuring the security of the water environment, while the ecological hydraulic phase placed emphasis on safeguarding water sustainability. Moreover, we found that prevailing water policies prioritize resolving isolated issues; however, water security is a multifaceted systemic matter that requires a comprehensive approach. This study has the potential to offer policy makers a more comprehensive and systematic perspective, enabling them to enhance their understanding of the underlying nature of the problems. Additionally, this study can assist in developing future water security policies.

A comprehensive approach to evaluate coastal dune evolution in Haiyang, China

Coastal dunes record the evolutionary process of coastal dynamic geomorphological systems, and provide valuable information on climate change, sea level changes, environmental evolution. These dunes are essential for global change research. In view of the dynamic changes in coastal dunes caused by extreme weather, coastal erosion and human activities, we propose a comprehensive evaluation method for coastal dune evolution, which monitors Haiyang Ten Thousand Meters Beach of China from three perspectives: point, line, and surface. This method integrates LiDAR, GNSS, and RS technologies. The research results indicate that between 2016 and 2018, 68% of the GNSS point measurements in 22 survey profiles of coastal dunes were eroded along the foreshore. During 2011-2020, the coastline based on the RS data basically remained stable; only the estuarine district underwent significant changes, and the overall average change rate was 1.32 m/a. The overall morphological evolution of coastal dunes obtained by LiDAR in 2018 was relatively stable, but there was a weak erosion trend in the foreshores of the coastal dunes. This study is beneficial for providing precise targets for remediating and restoring eroded coastal areas in the future. Furthermore, it can provide technical support and informational information for ecological environment protection, coastal erosion prevention and environmental evolution in the Haiyang Ten Thousand Meters Beach Marine Nature Reserve.

Fifth National Climate Assessment Reveals Urgent Action Needed to Reduce Greenhouse Gas Emissions

The Fifth National Climate Assessment (NCA5) was released in November 2023 by the U.S. Global Change Research Program. The Assessment evaluates the impacts of a changing climate across 10 US regions and a wide range of biodiversity and other interests, including water, forests and ecosystems, coasts and oceans, agriculture and rural communities, the built environment, energy and transportation, health and air quality, and economic and social systems. The Assessment is the fifth such report released by the US government since 2000, using science‐based data by more than a dozen US agencies and approximately 750 scientists tracking the impacts of climate change, and peer‐reviewed by the National Academies of Sciences, Engineering and Medicine (NASEM).1 The details outlined within the Assessment are not optimistic. In fact, the extensively peer‐reviewed report further quantifies the need to take immediate actions to reduce greenhouse gas (GHG) emissions into the atmosphere. Immediate actions will require both increased mitigation measures to reduce GHG emissions and adaptation measures as we attempt to live with the impacts of a changing climate.

The spatial variation of hydrological conditions and their impact on wetland vegetation in connected floodplain wetlands: Dongting Lake Basin.

Wetland vegetation plays a crucial role in wetland conservation policy formulation and global climate change research. This study analyzed remotely sensed images of West Dongting Lake (DTL) Wetland from 1994 to 2020. This wetland is one of the most important wetlands in the world. At the pixel scale, we applied the histogram comparison approach, the range variability analysis (RVA) method, and the structural equation model (SEM) to quantify spatial changes in the hydrological conditions of wetland lakes and the ecological effects of environmental factors (precipitation, temperature, nutrients, water coverage) on vegetation. We propose a climate (C) - hydrological status (S) - vegetation response (R) (CSR) framework to elucidate the propagation relationships between climate, hydrology, and wetland vegetation conditions. The study found that the hydrological degradation promotes the succession of vegetation into the lake, and the distribution is concentrated in the northern Yangtze River inflow area. And the extent of hydrological changes in the West DTL region reached 34.5% during the flood period. In addition, the post-dam period showed a high degree of hydro-ecological failure, accounting for 65% of the total. Within the wetland area, there was a significant negative correlation between water coverage nutrient levels and bare vegetation within the lake area. Nutrient levels were also significantly negatively correlated with wetland vegetation conditions. Rainfall and temperature influence wetland vegetation by affecting the condition of the water body. This research provides valuable insights into managing wetland water resources and ecological restoration under the influence of climate change and human activities and provides a basis for decision-making.

Hybrid Global Annual 1-km IGBP Land Cover Maps for the Period 2000–2020

Land cover products provide critical information for monitoring and analyzing land surface changes. However, notable disagreement and incompatible classification systems among existing land cover products bring challenges in using them. Here, we developed a hierarchical International Geosphere-Biosphere Programme (IGBP) classification system and integrated four widely used land cover products (i.e., MODIS-IGBP, ESA-CCI, GlobeLand30, and GLC_FCS30) based on their accuracy against a collection of global reference samples. We generated a hybrid global annual land cover product (HYBMAP) with ~1 km (1/120°, 30″) spatial resolution from 2000 to 2020. The HYBMAP integrates information from the four products of high- and medium-resolution and reduces the disagreement between them by up to 20.1%. The overall accuracy of the HYBMAP is 75.5%, which is higher than the best of the four products (MODIS-IGBP, 70.9%). HYBMAP also integrates the temporal change information from the four products and identifies a faster growth of built-up lands. The HYBMAP provides more consistent and reliable global land cover time series data for global change research. It is free to access at https://doi.org/10.5281/zenodo.10488191 .

Practical Exploration of Eco-Geological Survey Mapping in Qinghai–Tibet Plateau: Framework, Standard and Preliminary Cost Estimation

It is a common responsibility of all countries to protect the ecological environment and promote sustainable development. Eco-geology, which provides a basic guarantee for the rational utilization of natural resources, ecological protection and restoration, has gradually become a new hot spot of geological survey institutions in various countries. Eco-geological survey in the Qinghai–Tibet Plateau plays an important role in regional ecological protection and global change research. Setting up workable budgets symbolizes the competence of geological survey organizations in fulfilling their responsibilities, and unreliable cost estimates can cause economic and political complications. The unclear scope definition and scarcity of project information available at early stages make it hard to generate reliable preliminary cost estimates. Hence, based on historical data and the practical experience of scientists who have been engaged in eco-geological survey in the Qinghai–Tibet Plateau for a long time, this research aimed to develop a cost estimation model using statistical learning methods for geological survey organizations to forecast preliminary costs during the early stages of an eco-geological survey project to fulfill different cost control and managerial functions. This research makes full use of modern remote sensing technology and reasonably arranges the input of ground survey, drilling, geophysical exploration and other workloads, supplemented by the existing ecological monitoring station data. It comprehensively sorts out the work means and workload of field and office work needed to complete the map work, and it puts forward a consistent index system and preliminary cost calculation framework. On this basis, based on the principle of matching quantity and price, a reasonable budget standard or market price is selected to calculate the budget estimate of a single map sheet, and then, through the regional adjustment coefficient, the budget estimate of a map sheet covering the whole Qinghai–Tibet Plateau is extended and calculated. The budget estimate will provide effective support for the declaration of eco-geological survey projects in the Qinghai–Tibet Plateau and the calculation of the scale of project funds so as to ensure the smooth development of eco-geological surveying in the region.

Mammal communities of primeval forests as sentinels of global change.

Understanding the drivers and consequences of global environmental change is crucial to inform predictions of effects on ecosystems. We used the mammal community of Białowieża Forest, the last lowland near-primeval forest in temperate Europe, as a sentinel of global change. We analyzed changes in stable carbon (δ13 C) and nitrogen (δ15 N) isotope values of hair in 687 specimens from 50 mammal species across seven decades (1946-2011). We classified mammals into four taxonomic-dietary groups (herbivores, carnivores, insectivores, and bats). We found a significant negative trend in hair δ15 N for the mammal community, particularly strong for herbivores. This trend is consistent with temporal patterns in nitrogen deposition from (15 N depleted) industrial fertilizers and fossil fuel emissions. It is also in line with global-scale declines in δ15 N reported in forests and other unfertilized, non-urban terrestrial ecosystems and with local decreases in N foliar concentrations. The global depletion of 13 C content in atmospheric CO2 due to fossil fuel burning (Suess effect) was detected in all groups. After correcting for this effect, the hair δ13 C trend became non-significant for both community and groups, except for bats, which showed a strong decline in δ13 C. This could be related to an increase in the relative abundance of freshwater insects taken by bats or increased use of methane-derived carbon in food webs used by bats. This work is the first broad-scale and long-term mammal isotope ecology study in a near-primeval forest in temperate Europe. Mammal communities from natural forests represent a unique benchmark in global change research; investigating their isotopic temporal variation can help identify patterns and early detections of ecosystem changes and provide more comprehensive and integrative assessments than single species approaches.

A Cloud Water Path-Based Model for Cloudy-Sky Downward Longwave Radiation Estimation from FY-4A Data

Clouds are a critical factor in regulating the climate system, and estimating cloudy-sky Surface Downward Longwave Radiation (SDLR) from satellite data is significant for global climate change research. The models based on cloud water path (CWP) are less affected by cloud parameter uncertainties and have superior accuracy in SDLR satellite estimation when compared to those empirical and parameterized models relying mainly on cloud fraction or cloud-base temperature. However, existing CWP-based models tend to overestimate the low SDLR values and underestimate the larger SDLR. This study found that this phenomenon was caused by the fact that the models do not account for the varying relationships between cloud radiative effects and key parameters under different Liquid Water Path (LWP) and Precipitable Water Vapor (PWV) ranges. Based upon this observation, this study utilized Fengyun-4A (FY-4A) cloud parameters and ERA5 data as data sources to develop a new CWP-based model where the model coefficients depend on the cloud phase and cloud water path range. The accuracy of the new model’s estimated SDLR is 20.8 W/m2 for cloudy pixels, with accuracies of 19.4 W/m2 and 23.5 W/m2 for overcast and partly cloudy conditions, respectively. In contrast, the accuracy of the old CWP-based model was 22.4, 21.2, and 24.8 W/m2, respectively. The underestimation and overestimation present in the old CWP-based model are effectively corrected by the new model. The new model exhibited higher accuracy under various station locations, cloud cover scenarios, and cloud phase conditions compared to the old one. Comparatively, the new model showcased its most remarkable improvements in situations involving overcast conditions, water clouds with low PWV and low LWP values, ice clouds with large PWV, and conditions with PWV ≥ 5 cm. Over a temporal scale, the new model effectively captured the seasonal variations in SDLR.

An Optimized Framework for Precipitable Water Vapor Mapping Using TS-InSAR and GNSS

Observations of precipitable water vapor (PWV) in the atmosphere play a crucial role in weather forecasting and global climate change research. Spaceborne Interferometric Synthetic Aperture Radar (InSAR), as a widely used modern geodetic technique, offers several advantages to the mapping of PWV, including all-weather capability, high accuracy, high resolution, and spatial continuity. In the process of PWV retrieval by using InSAR, accurately extracting the tropospheric wet delay phase and obtaining a high-precision tropospheric water vapor conversion factor are critical steps. Furthermore, the observations of InSAR are spatio-temporal differential results and the conversion of differential PWV (InSAR ΔPWV) into non-difference PWV (InSAR PWV) is a difficulty. In this study, the city of Jinan, Shandong Province, China is selected as the experimental area, and Sentinel-1A data in 2020 is used for mapping InSAR ΔPWV. The method of small baseline subset of interferometry (SBAS) is adopted in the data processing for improving the coherence of the interferograms. We extract the atmosphere phase delay from the interferograms by using SRTM-DEM and POD data. In order to evaluate the calculation of hydrostatic delay by using the ERA5 data, we compared it with the hydrostatic delay calculated by the Saastamoinen model. To obtain a more accurate water vapor conversion factor, the value of the weighted average temperature Tm was calculated by the path integral of the ERA5. In addition, GNSS PWV is used to calibrate InSAR PWV. This study demonstrates a robust consistency between InSAR PWV and GNSS PWV, with a correlation coefficient of 0.96 and a root-mean-square error (RMSE) of 1.62 mm. In conclusion, our method ensures the reliability of mapping PWV by using Sentinel-1A interferograms and GNSS observations.

Analysis of the spatiotemporal changes in global land cover from 2001 to 2020

Land cover changes have far-reaching effects on climate change and the evolution of ecological environments, making them important components of global change research. Based on MODIS land cover data (MCD12Q1), statistical parameters such as land cover dynamic degree, transition probability, and transition matrix were employed to analyse the spatiotemporal characteristics of global land cover changes from 2001 to 2020. The results indicated that land cover exhibits a latitudinal distribution in mid-latitude regions and a longitudinal distribution in high and low-latitude regions. During the study period, the areas of evergreen needleleaf forests, deciduous needleleaf forests, deciduous broadleaf forests, closed shrublands, and permanent wetlands exhibited fluctuating changes. Evergreen broadleaf forests and barren lands have decreased annually, whereas mixed forests, woody savannas, grasslands, urban and built-up areas, and cropland/natural vegetation mosaics have increased annually. In terms of the dynamic degree, the most significant changes occurred in deciduous broadleaf forests, closed shrublands, permanent wetlands, and cropland/natural vegetation mosaics. Additionally, there were significant variations in the types and regions of land cover changes and transitions. Evergreen needleleaf forests transitioned into grassland types, and the conversion between grassland types was the main transition from mid- to high- latitude regions. In tropical areas, evergreen broadleaf forests, open shrublands, and croplands have shifted towards grassland types as primary transitions. These findings provide significant implications for the in-depth exploration of land-atmosphere interactions, climate change, and numerical models.

Overcoming barriers to enable convergence research by integrating ecological and climate sciences: the NCAR–NEON system Version 1

Abstract. Global change research demands a convergence among academic disciplines to understand complex changes in Earth system function. Limitations related to data usability and computing infrastructure, however, present barriers to effective use of the research tools needed for this cross-disciplinary collaboration. To address these barriers, we created a computational platform that pairs meteorological data and site-level ecosystem characterizations from the National Ecological Observatory Network (NEON) with the Community Terrestrial System Model (CTSM) that is developed with university partners at the National Center for Atmospheric Research (NCAR). This NCAR–NEON system features a simplified user interface that facilitates access to and use of NEON observations and NCAR models. We present preliminary results that compare observed NEON fluxes with CTSM simulations and describe how the collaboration between NCAR and NEON that can be used by the global change research community improves both the data and model. Beyond datasets and computing, the NCAR–NEON system includes tutorials and visualization tools that facilitate interaction with observational and model datasets and further enable opportunities for teaching and research. By expanding access to data, models, and computing, cyberinfrastructure tools like the NCAR–NEON system will accelerate integration across ecology and climate science disciplines to advance understanding in Earth system science and global change.

Landscape-Scale Long-Term Drought Prevalence Mapping for Small Municipalities Adaptation, the Czech Republic Case Study

Drought is a phenomenon that is strengthening with the progress of climate change. Many fields of human activities such as agriculture, forestry, ecology, economy, water supply, or energy production are affected. Municipalities are one of the most important actors, because final adaptation often takes place at this level. However, planning measures is challenging for small municipalities, with adaptation capacity being lower than in big cities. A model working with data from the Global Change research Institute CzechGlobe and the Czech national drought monitor Intersucho allows for information to be obtained at the landscape scale about drought, and their utilization for small municipalities is introduced. In addition to detailed maps for the years 1991–2014, the model enables long-term prediction of drought prevalence for the years 2021–2040 and 2041–2060. GIS-integrated Random Forest regression and twelve climate, topography, and land use/land cover variables were involved in the model construction. The tuned model could explain 70% of reference data variability, and was used for drought prevalence mapping in 20 m spatial detail. Utilisation of overlay and visualisation tools and consultation of actual spatial planning maps helped create maps for spatial decision-making support in precautionary measure and landscape management within the municipalities.

Modelling thermal sensitivity in the full phenological distribution: A new approach applied to the spring arboreal caterpillar peak

Abstract Advances in spring phenology are among the clearest biological responses to climate warming. There has been much interest in how climate impacts on phenology because the timings of key events have implications for species interactions, nutrient cycling and ecosystem services. To date most work has focused on only one aspect of population phenology, the effects of temperature on the average timing. In comparison, effects of temperature on the abundance of individuals and their seasonal spread are understudied, despite their potential to have profound impacts on species interactions. Here we develop a new method that directly estimates the effect of spring temperatures on the timing, height and width of the phenological distribution and apply it to temperate forest caterpillars, a guild that has been the focus of much research on phenology and trophic mismatch. We find that warmer spring conditions advance the timing of the phenological distribution of abundance by −4.96 days °C−1 and increase its height by 34% °C−1 but have no significant effect on the duration of the distribution. An increase in the maximum density of arboreal caterpillars with rising temperatures has implications for understanding climate impacts on forest food chains, both in terms of herbivory pressure and the resources available to secondary consumers. The new method we have developed allows the thermal sensitivity in the full phenological distribution to be modelled directly from raw data, providing a flexible approach that has broad applicability within global change research. Read the free Plain Language Summary for this article on the Journal blog.