Climate Interactions Research Articles

Fuel layer specific pollutant emission factors for fire prone forest ecosystems of the western U.S. and Canada.

Wildland fires are a major source of gases and aerosols, and the production, dispersion, and transformation of fire emissions have significant ambient air quality impacts and climate interactions. The increase in wildfire area burned and severity across the United States and Canada in recent decades has led to increased interest in expanding the use of prescribed fires as a forest management tool. While the primary goal of prescribed fire use is to limit the loss of life and property and ecosystem damage by constraining the growth and severity of future wildfires, a potential additional benefit of prescribed fire - reduction in the adverse impacts of smoke production and greenhouse gas (GHG) emissions - has recently gained the interest of land management agencies and policy makers in the United States and other nations. The evaluation of prescribed fire/wildfire scenarios and the potential mitigation of adverse impacts on air quality and GHGs requires fuel layer specific pollutant emission factors (EFs) for fire prone forest ecosystems. Our study addresses this need with laboratory experiments measuring EFs for carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), ethyne (C2H2), formaldehyde (H2CO), formic acid (CH2O2), hydrogen cyanide (HCN), fine particulate matter (PM2.5), nitric oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and total reduced sulfur (TRS) for the burning of individual fuel components from three forest ecosystems which account for a large share of wildfire burned area and emissions in the western United States and Canada - Douglas fir, ponderosa pine, and black spruce/jack pine.

Simulation of ecosystem fluxes with the SCOPE model: Sensitivity to parametrization and evaluation with flux tower observations

Accurate estimates of carbon, water and energy fluxes between the Earth surface and the atmosphere are crucial for enhancing our understanding of ecosystem–climate interactions. Such estimates can be made by combining remote sensing derived land surface parameters with climate reanalysis data. We analysed to what degree generic (plant functional type (PFT)-independent) satellite-derived vegetation properties and climate reanalysis data can explain land surface fluxes and to what extent the PFT-specific information extends the flux simulations. For this purpose, we used the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) model, which combines radiative transfer in plant leaves and vegetation canopies with photosynthesis and energy balance in a single model representation of the vegetation. We evaluated the performance of SCOPE in simulating fluxes by comparison to 63 eddy covariance sites representing 10 PFTs. We varied the sources of maximum carboxylation capacity (Vcmax25) and BallBerrySlope values (default vs literature), the seasonality of Vcmax25 and the meteorological forcing (locally measured and climate reanalysis). The average performance of daily flux in terms of root-mean-square error (RMSE) was 2.3 ± 0.8 μmol CO2 m−2 s−1 (R2= 0.74 ± 0.12) for gross primary productivity (GPP), 24 ± 8 W m−2 (R2= 0.68 ± 0.16) for latent heat flux (λE) and 50 ± 15 W m−2 (R20.47±0.17) for sensible heat flux (H). The inter-site variability of the annual accumulated GPP flux was captured well with seasonally varying PFT-specific Vcmax25 (R2= 0.74, RMSE = 308 g C m−2 yr−1 and bias = −68 g C m−2 yr−1). The annual accumulated evapotranspiration (ET) was overestimated (R2= 0.31, RMSE = 101 mm yr−1 and bias = 37 mm yr−1), mainly in the ecosystems with subtropical Mediterranean climate, for which the soil resistance to evaporation from porous space (rss) had to be constrained from soil moisture content (SMC) or land surface temperature (LST). Overall, the study demonstrates that SCOPE model can simulate ecosystem flux with high accuracy without site-specific calibration of its parameters.

Single- and multi-year ENSO events controlled by pantropical climate interactions

To better understand the diverse temporal evolutions of observed El Niño‒Southern Oscillation (ENSO) events, which are characterized as single- or multi-year, this study examines similar events in a 2200-year-long integration of Community Earth System Model, version 1. Results show that selective activation of inter- and intra-basin climate interactions (together, pantropical climate interactions) controls ENSO’s evolution pattern. When ENSO preferentially activates inter-basin interactions with tropical Indian and/or Atlantic Oceans, it introduces negative feedbacks into the ENSO phase, resulting in single-year evolution. When ENSO preferentially activates intra-basin interactions with subtropical North Pacific, it causes positive feedbacks, producing multi-year evolution. Three key factors (developing-season intensity, pre-onset Pacific condition, and maximum zonal location) and their thresholds, which determine whether inter- or intra-basin interactions are activated and whether an event will become a single- or multi-year event, are identified. These findings offer a way to predict ENSO’s evolution pattern by incorporating the controlling role of pantropical climate interactions.

Changes in root chemical diversity along an elevation gradient of Changbai Mountain, China.

Root chemical traits play a critical role in plant resource use strategies and ecosystem nutrient cycling; however, the chemical diversity of multiple elements of fine root and community chemical assembly belowground are poorly understood. Here, we measured 13 elements (C, N, K, Ca, Mg, S, P, Al, Fe, Na, Mn, Zn, and Cu) in the fine roots of 204 plant species along elevational transect from 540 to 2357 m of Changbai Mountain, China to explore the variation, diversity, and community assembly of root chemical traits. At the species level, the concentrations of macronutrients (N, K, Ca, Mg, S, and P) decreased, whereas the trace metals (Fe, Mn, and Zn) increased with elevation. Root chemical traits at the community level systematically shifted along elevational gradients showing a pattern similar to that at the species level, which were mainly influenced by climate and soil rather than species diversity. In general, the interactions of climate and soil were the main drivers of root chemical assembly for woody layers, whereas soil factors played significant role for root chemical assembly for herb layer. The chemical assembly of rock-derived element P was mainly driven by soil factors. Meanwhile, root chemical diversities were mainly regulated by species diversity, the interactions of climate and soil, and soil factors in the tree, shrub, and herb layers, respectively. A better understanding of plant root chemical diversity and community chemical assembly will help to reveal the role of chemical traits in ecosystem functioning.

Seeing roots from space: aboveground fingerprints of root depth in vegetation sensitivity to climate in dry biomes

With predicted climate change, drylands are set to get warmer and drier, increasing water stress for the vegetation in these regions. Plant sensitivity to drier periods and drought events will largely depend on trait strategies to access and store water, often linked to the root system. However, understanding the role of below-ground traits in enhancing ecological resilience to these climate changes remains poorly understood. We present the results of a study in southern Africa where we analysed the relationship between root depth and the vegetation sensitivity index (VSI) (after Seddon and Macias-Fauria et al 2016 Nature 531 229–32). VSI demonstrates remotely-sensed aboveground vegetation responses to climate variability; thus our study compares aboveground vegetation responses to belowground root traits. Results showed a significant negative relationship between root depth and vegetation sensitivity. Deeper roots provided greater resistance to climate variability as shown by lower sensitivity and higher temporal autocorrelation in vegetation greenness (as measured by the enhanced vegetation index). Additionally, we demonstrated a link between deeper roots and depth to groundwater, further suggesting that it is the ability of deeper roots to enable access to groundwater that provides ecological resistance to climate variability. Our results therefore provide important empirical evidence that the ability to access deeper water resources during times of lower water availability through deeper roots, is a key trait for dryland vegetation in the face of future climate change. We also show that belowground traits in drylands leave a fingerprint on aboveground, remotely-sensed plant–climate interactions, an important finding to aid in scaling up data-scarce belowground research.

The effects of fire, climate, and species composition on longleaf pine stand structure and growth rates across diverse natural communities in Florida

The longleaf pine (Pinus palustris) savanna is an endangered ecosystem within a global biodiversity hotspot. However, most studies of longleaf habitats have not considered their distinct structure and function among unique communities, which are critical for developing appropriate management strategies. We aim to assess how differences in climate, fire, and species composition interact and relate to longleaf pine densities and growth rates in distinct communities. We surveyed longleaf pine stand structure (density by size and age classes) and estimated growth rates using 516 tree cores across 5 community types (69 plots, each ≤ 160 m2). Surveys covered the range of longleaf pine in Florida, USA, including the southernmost extent of the species range, and included all communities where longleaf are dominant (sandhill, upland pine, and mesic, wet, and scrubby flatwoods). We used an NMDS ordination to classify communities by species composition. We used linear mixed-effects models to examine the effect of community type on longleaf pine density and growth rates and then used recursive partitioning and regression tree analyses to identify how climate, fire, and species composition affect density and growth rates. We found that stand structure and species composition were different across communities, with upland pine being the most species rich and having the highest density of mature trees, whereas growth rates were not statistically different across communities. Across communities, unique interactions between climate, fire, and species composition, resulted in differences in stand structure and growth rates. In general, tree and grass stage densities were best predicted by species composition and fire rather than by climate, whereas growth rates were best predicted by climate. Having included the southernmost extent of longleafs range we show that longleaf growth rates increased with higher temperatures, but this effect is reversed in dry conditions. Our results suggest that longleaf growth rates across its range will be more sensitive to current and future climate change than longleaf population density. Furthermore, while controlling competition from hardwoods has been a focus of longleaf restoration, our results suggest that species that facilitate longleaf establishment may be equally important in restoring and managing these habitats. Managers should design and apply regional and community specific plans that take into account relationships between fire and associated species composition under a changing climate, which will influence strand structure and tree growth differently in different communities.

Calibration, validation and application of the SWAT model to determine the hydrological benefit of wetland rehabilitation in KwaZulu-Natal, South Africa

In South Africa, with highly variable and intense land-use practices, coupled with limited soil fertility and water resources, there has been a long history of encroachment of arable lands (sugarcane and timber plantations) into surrounding wetlands. Although wetland delineation within the timber and sugar sectors is well-defined in policy, and existing and proposed legislation, there are significant areas of non-compliance. The spatially-explicit Soil Water Assessment Tool (SWAT) was adopted to investigate the interactions of climate, land-use and soil on the water-use of natural and encroached wetlands. This paper documents the calibration, validation and application of the SWAT model on Quaternary Catchment (QC) U20G, which is a 498 km2 catchment that forms part of the uMngeni River basin. The SWAT-CUP parameter sensitivity and optimization model was tested with daily observed streamflow data for this catchment. Parameters were modified using the sequential uncertainty fitting (SUFI-2) analysis routine to calibrate the model. The simulated flow had a close fit to the observed flow with a regression coefficient (r2) of 0.87 and a Nash-Sutcliffe (NS) coefficient of 0.8. Through the buffer scenario analysis, the model showed that if the wetland and a 20-m buffer were to be returned to a natural state, there could be a 16% increase in the annual streamflow contribution, with an upper limit of a 60% increase in some hydrologic response units (HRUs). Thus there would be a hydrological gain if wetlands and sensitive buffer areas were to be cleared of commercial timber species and sugarcane.

Subalpine woody vegetation in the Eastern Carpathians after release from agropastoral pressure

The subalpine vegetation in the Eastern Carpathians has been under agropastoral influence as a high-mountain open pasture for about five centuries. Today, the subalpine zone released by human intervention is growing as thickets. In this study, we use a numerical model of tree crowns (CHM, Canopy Height Model) based on laser scanning (LiDAR) and a high-resolution digital terrain model (DTM) to delineate the subalpine thicket distribution. Anselin ‘Local Moran's I’ statistic was used to find hot and cold spots in vegetation cover. We used a logistic generalized linear model (GLM) and Principal Component Analysis (PCA) to set for the historical, climatic and terrain conditions candidates as the predictors of the present-day distribution of vegetation hot spots. We use variance partitioning to assess the interaction of climate and terrain variables. The resulting model suggests key environmental controls that underlie the vegetation pattern. Namely, snow in terrain depressions protects woody vegetation against abrasion and winter drought and increased insolation reduces the site humidity in the summer on S-E exposure hampering re-vegetation. In addition, the increasing distance from the treeline declines the rate of secondary succession. In all, the spatial model predicts the 35% coverage by thickets as a theoretical maximum of available climatic-terrain niches. The results suggest that the growth of the subalpine thicket, in the face of growing global temperature, may be restricted due to the limited number of niches available.

Impact of Indian Ocean Dipole Events on Phytoplankton Size Classes Distribution in the Arabian Sea

Changes in the environmental condition associated with climatic events could potentially influence the PSC dynamics of the regional marine ecosystem. The Indian Ocean dipole (IOD) is one of the critical ocean–atmosphere interactions that affects the climate of the Arabian Sea, and it could be a potential factor influencing the regional PSC distribution. However, the relationship between PSC and IOD remains unclear and less explored. In this study, using the in-situ database acquired from the Arabian Sea, we reparametrized the three−component abundance−based phytoplankton size class model and applied it to reconstructed satellite−derived chlorophyll−a concentration to extract the fractional contribution of phytoplankton size classes to chlorophyll−a concentration. Further, we investigated the influence of IOD on the changes in the biological–physical properties in the Arabian Sea. The results showed that the biological–physical processes in the Arabian Sea are interlinked and the changes in the IOD mode control the physical variables like sea surface temperature (SST), sea surface height (SSH), and mixed layer depth (MLD), which influence the specific PSC abundance. Unprecedented changes in the PSC distribution and physical properties were observed during the extreme positive and negative IOD events, which clearly indicated the potential role of IOD in altering the PSC distribution in the Arabian Sea. This study highlights the impact of extreme climate events on PSC distribution and the need for a better understanding of the associated physical–biological–climate interactions.

Assessing temporal variability of lake turbidity and trophic state of European lakes using open data repositories

Water turbidity is one of the more important water quality parameters that is strictly linked with the productivity of the lake and is commonly used as an indicator of the trophic state. However, limited field data availability across wide geographic gradients may hinder the conduction of large scale longitudinal studies. In this study, time series of lake turbidity and trophic state index (TSI) between 2002 and 2012 were obtained from the Copernicus Lake Water products to create a large longitudinal dataset of lake variables for 22 European lakes. The dataset was combined with estimates of nutrient concentrations and surface water temperature obtained from the Hydrological Predictions for the Environment (HYPE) and ERA5-Land data repositories, that were used as environmental predictors. Hence, the validity of the lake water quality parameters was tested by a) exploring their spatial and temporal variability and b) identifying associations with the environmental predictors. For this purpose, seasonal Mann-Kendall tests were applied to find significant inter-annual trends of turbidity and TSI for each lake, and generalized additive models (GAMs) were employed to identify the main parameters that shape their temporal dynamics. Although we did not find significant inter-annual changes, our findings highlighted the strong influence of seasonality and surface water temperature in defining the temporal variability patterns in most of the lakes. In addition, the importance of nutrients varied among lakes as several lakes exhibited narrow nutrient gradients reflecting relatively stable nutrient conditions during the examined period. Other lake intrinsic factors, such as local climate and biotic interactions, are important drivers of shaping turbidity and nutrient dynamics. This study highlighted the usefulness of combining lake data from large repositories in conducting large scale spatial studies as a valuable asset for future lake research and management purposes.

Ecological Policies Dominated the Ecological Restoration over the Core Regions of Kubuqi Desert in Recent Decades

Climate change and human activities significantly affected environmental changes in drylands. However, the relative roles remain unclear regarding these factors’ effects on environment changes in drylands. Herein, we analyzed vegetation change trends using remote-sensing datasets to determine the interactions of vegetation, climate, and anthropogenic activities in an arid region of China, Kubuqi Desert. Our study showed that 67.64% of the pixels of fractional vegetation coverage (FVC) increased in 2020 in comparison with those of 1986. The FVC exhibited a significant greening trend (0.0011/yr, p < 0.05) in 1986–2020 as a whole. This greening trend revealed two distinct periods separated by a turning point in 2001. There was no clear trend of FVC before 2001, and then there was a dramatically greening trend since 2001 in most regions of the study area. The increasing rate (0.0036/yr) in the later period was three times higher than the entire period. The accelerated increasing trend was due to the variable compound effects of climate and human activities. The correlation between FVC and precipitation was mainly positive, which outweighs the significantly negative correlation between vegetation and temperature. However, both climatic factors cannot well explain the trends of vegetation dynamics, implying a possible role for human activities. Generally, climate change and anthropogenic activities contributed 42.15% and 57.85% to the overall vegetation variations in 1986–2020. Specifically, the relative role of the two factors was vastly different in two distinct periods. Climate change led the dominant roles (58.68%) in the vegetation variations in 1986–2001, while anthropogenic activities dominated (86.79%) in driving vegetation recovery in the period after 2001. Due to the massive ecological conservation programs such as the Grain for Green Project launched in 2001, substantial deserts have been transformed into grasslands and forests. This analysis highlights the ecological policies largely responsible for vegetation restoration and provides references for ecological protection and sustainable development in eco-fragile ecosystems.

The Antarctic contribution to 21st-century sea-level rise predicted by the UK Earth System Model with an interactive ice sheet

Abstract. The Antarctic Ice Sheet will play a crucial role in the evolution of global mean sea level as the climate warms. An interactively coupled climate and ice sheet model is needed to understand the impacts of ice–climate feedbacks during this evolution. Here we use a two-way coupling between the UK Earth System Model and the BISICLES (Berkeley Ice Sheet Initiative for Climate at Extreme Scales) dynamic ice sheet model to investigate Antarctic ice–climate interactions under two climate change scenarios. We perform ensembles of SSP1–1.9 and SSP5–8.5 (Shared Socioeconomic Pathway) scenario simulations to 2100, which we believe are the first such simulations with a climate model that include two-way coupling of atmosphere and ocean models to dynamic models of the Greenland and Antarctic ice sheets. We focus our analysis on the latter. In SSP1–1.9 simulations, ice shelf basal melting and grounded ice mass loss from the Antarctic Ice Sheet are generally lower than present rates during the entire simulation period. In contrast, the responses to SSP5–8.5 forcing are strong. By the end of the 21st century, these simulations feature order-of-magnitude increases in basal melting of the Ross and Filchner–Ronne ice shelves, caused by intrusions of masses of warm ocean water. Due to the slow response of ice sheet drawdown, this strong melting does not cause a substantial increase in ice discharge during the simulations. The surface mass balance in SSP5–8.5 simulations shows a pattern of strong decrease on ice shelves, caused by increased melting, and strong increase on grounded ice, caused by increased snowfall. Despite strong surface and basal melting of the ice shelves, increased snowfall dominates the mass budget of the grounded ice, leading to an ensemble mean Antarctic contribution to global mean sea level of a fall of 22 mm by 2100 in the SSP5–8.5 scenario. We hypothesise that this signal would revert to sea-level rise on longer timescales, caused by the ice sheet dynamic response to ice shelf thinning. These results demonstrate the need for fully coupled ice–climate models in reducing the substantial uncertainty in sea-level rise from the Antarctic Ice Sheet.

Snail trails on PV modules in Brazil’s tropical climate: Detection, chemical Properties, bubble formation, and performance effects

This case study examines relationships among crystalline-Si cell microcracks, the formation of snail trails, the chemical processes involved, and resulting power loss of the modules under operating conditions in the tropical climate of Brazil. Snail-trail discolorations are imaged by ultraviolet fluorescence and are correlated with the electrical losses of the underlying microcracks by electroluminescence. Complementary microanalytical-techniques are used to compare the chemistry/composition of the encapsulant, contacts, and cell surface regions above and separated from snail trails. The formation of Ag-nanoparticles that react with oxygen, CO2, moisture, and the organic encapsulant result in the formation Ag-compounds (i.e., Ag2CO3. AgO2) accounting for the snail-trail discoloration. Bubble formation along the Ag-fingers are reported. Additionally, evolution of bubble trails along the microcracks is observed for the first time, and the resulting chemical interactions are identified. The processes are discussed in terms of the materials, condition of the backsheets, and local environmental and climate interactions. The modules are shown to exhibit additional power-loss at the higher operating temperatures (>50–60 °C) beyond that expected from the maximum-power temperature coefficient. This is attributed to the opening of the microcracks, with Pmax returning to near its original value upon cooling with observed to healing of the microcrack regions.

Contrasting mass absorption efficiency of carbonaceous aerosols between PM1 and PM2.5 in urban Beijing

Carbonaceous aerosol, mainly comprising elemental carbon (EC) and organic carbon (OC), plays an important role in aerosol–climate interaction owing to its light-absorbing feature. The radiative forcing of carbonaceous aerosol is largely determined by its mass absorption efficiency (MAE). To depict the MAE of carbonaceous aerosol and its variations with aerosol size and chemical composition, light absorption coefficients and the main chemical composition of PM1 and PM2.5 were comparably measured in a winter field campaign in urban Beijing. On average, aerosol absorption by PM1 at 880 nm wavelength contributes to approximately half of aerosol absorption by PM2.5, mainly because aerosol absorption at this wavelength was dominated by EC and nearly half of the total EC mass in PM2.5 existed in PM1. The average MAE of EC at 880 nm (MAEEC,880nm) was 3.9 ± 0.7 m2 g−1 for PM2.5, lower than that for PM1 (4.4 ± 0.8 m2 g−1) likely because of the larger EC cores and lower coating degrees of EC particles in PM1–2.5. Variation in MAEEC,880nm was related to the bulk mass fractions of nitrate in PM1 and PM2.5, implying the important impact of secondary nitrate formation on the modification of EC mixing states and enhancing EC absorption efficiency in Beijing. Absorption by OC took up about 40% of the absorption coefficients for PM1 and PM2.5 at 370 nm. The mean MAE of OC at 370 nm (MAEOC,370nm) was 2.4 ± 0.9 m2 g−1 for PM1, higher than that of for PM2.5 (1.9 ± 0.6 m2 g−1). The high value of MAEOC,370nm might be associated with regionally transported aerosols during clean and polluted periods. Enlarged particle sizes might have considerably weakened MAEOC,370nm for PM2.5 while exerting negligible impact on MAEOC,370nm for PM1.

Fire–climate interactions through the aerosol radiative effect in a global chemistry–climate–vegetation model

Abstract. Fire emissions influence radiation, climate, and ecosystems through aerosol radiative effects. These can drive rapid atmospheric and land surface adjustments which feed back to affect fire emissions. However, the magnitude of such feedback remains unclear on the global scale. Here, we quantify the impacts of fire aerosols on radiative forcing and the fast atmospheric response through direct, indirect, and albedo effects based on the two-way simulations using a well-established chemistry–climate–vegetation model. Globally, fire emissions cause a reduction of 0.565 ± 0.166 W m−2 in net radiation at the top of the atmosphere with dominant contributions by the aerosol indirect effect (AIE). Consequently, terrestrial surface air temperature decreases by 0.061 ± 0.165 ∘C with coolings of >0.25 ∘C over the eastern Amazon, the western US, and boreal Asia. Both the aerosol direct effect (ADE) and AIE contribute to such cooling, while the aerosol albedo effect (AAE) exerts an offset warming, especially at high latitudes. Land precipitation decreases by 0.180 ± 0.966 mm per month (1.78 % ± 9.56 %) mainly due to the inhibition in central Africa by AIE. Such a rainfall deficit further reduces regional leaf area index (LAI) and lightning ignitions, leading to changes in fire emissions. Globally, fire emissions reduce by 2 %–3 % because of the fire-induced fast responses in humidity, lightning, and LAI. The fire aerosol radiative effects may cause larger perturbations to climate systems with likely more fires under global warming.

Second-Entry Burns Reduce Mid-Canopy Fuels and Create Resilient Forest Structure in Yosemite National Park, California

Understanding the patterns and underlying drivers of forest structure is critical for managing landscape processes and multiple resource management. Merging several landscape-scale datasets, including long-term fire histories, airborne LiDAR, and downscaled topo-climatic data, we assessed complex ecological questions regarding the interactions of forest structure, climate, and fire in the Yosemite National Park, a protected area historically dominated by frequent fire and largely free of the impacts of commercial industrial logging. We found that forest structure broadly corresponded with forest types arranged across elevation-driven climatic gradients and that repeated burning shifts forest structure towards conditions that are consistent with increased resilience, biodiversity, and ecosystem health and function. Specifically, across all forest types, tree density and mid-canopy strata cover was significantly reduced compared to overstory canopy and the indices of forest health improved after two fires, but no additional change occurred with subsequent burns. This study provides valuable information for managers who seek to refine prescriptions based on an enhanced understanding of fire-mediated changes in ladder fuels and tree density and those seeking to define the number of treatments needed to mitigate severe fire risk and enhance resiliency to repeated fires. In addition, our study highlights the utility of large-landscape LiDAR acquisitions for supporting fire, forest, and wildlife management prioritization and wildfire risk assessments for numerous valued resources.

Short-term paleogeographic reorganizations and climate events shaped diversification of North American freshwater gastropods over deep time

What controls species diversity and diversification is one of the major questions in evolutionary biology and paleontology. Previous studies have addressed this issue based on various plant and animal groups, geographic regions, and time intervals. However, as most previous research focused on terrestrial or marine ecosystems, our understanding of the controls on diversification of biota (and particularly invertebrates) in freshwater environments in deep time is still limited. Here, we infer diversification rates of North American freshwater gastropods from the Late Triassic to the Pleistocene and explore potential links between shifts in speciation and extinction and major changes in paleogeography, climate, and biotic interactions. We found that variation in the speciation rate is best explained by changes in continental fragmentation, with rate shifts coinciding with major paleogeographic reorganizations in the Mesozoic, in particular the retreat of the Sundance Sea and subsequent development of the Bighorn wetland and the advance of the Western Interior Seaway. Climatic events in the Cenozoic (Middle Eocene Climate Optimum, Miocene Climate Optimum) variably coincide with shifts in speciation and extinction as well, but no significant long-term association could be detected. Similarly, no influence of diversity dependence was found across the entire time frame of ~ 214 Myr. Our results indicate that short-term climatic events and paleogeographic changes are relevant to the diversification of continental freshwater biota, while long-term trends have limited effect.

Elevation affects the ecological stoichiometry of Qinghai spruce in the Qilian Mountains of northwest China.

Environmental heterogeneity in temperature, moisture, and soil fertility caused by elevation gradients can affect the trade-offs in the survival strategies of tree species. There is uncertainty about the allocation of resources to different tissues of trees in response to the elevation gradient with respect to carbon (C), nitrogen (N), and phosphorus (P). Here, the C, N, and P content of leaves, branches, trunks, and thick and fine roots of Picea crassifolia (Qinghai spruce) and their stoichiometric changes across three different elevations were investigated in the Qilian Mountains. We found that N:P of Qinghai spruce was <14 in all tissues at most elevations, indicating that Qinghai spruce was more susceptible to N limitation. Meanwhile, the N content and N:P of Qinghai spruce each were significantly negatively correlated with temperature (p < 0.05), and its P content was lower at high elevation. The contribution of soil–climate interactions on the elevation gradient to each tissue type was 34.02% (leaves), 16.84% (branches), 67.78% (trunks), 34.74% (thick roots), and 49.84% (fine roots), indicating that interacting climate and soil factors on the elevation gradient predominately drove the C, N, and P content and stoichiometry variation in each tissue type of Qinghai spruce trees. The results of this study clarify that the elevation gradient regulates the elemental content and resource allocation in Qinghai spruce, providing basic data and an important timely reference for future forest management in the regions where coniferous trees grows. These findings also help improve our understanding of elevational patterns of forest ecosystem stoichiometry in arid and semiarid regions.

Simulating long-term phosphorus, nitrogen, and carbon dynamics to advance nutrient assessment in dryland cropping

Soil chemical fertility has steadily declined in tropical and subtropical agriculture with depleted stocks of phosphorus (P), nitrogen (N), and carbon (C). Assessing the dynamics of these elements and their interactions on crop productivity in dryland cropping are complex because climate often dictates crop nutrient response. This results in under- or over- fertilising crops, suboptimal crop yield, and fertiliser inefficiency. The Agricultural Productions Systems sIMulator (APSIM) model accounts for C x N x climate interactions, but simulation of P dynamics is constrained by a dearth of suitable data. To address this problem, we used a novel approach to simulate P, N, and C dynamics at a 35-year long-term field trial, where a broad range of N (0, 40, 80, 120 kg ha −1 ) and P (0, 10, 20 kg ha −1 ) fertiliser rates were consistently applied. We parameterised the soil P model with quantified adsorption isotherms and by assuming correspondence between conceptual soil P pools and Hedley fractionation pools. Soil N and C dynamics were parameterised with measured organic N, C, and charcoal content to estimate organic matter decay coefficients, pool sizes, and C:N ratios. APSIM accounted for variation in mean N export (94%), crop yield (88%), and P export (62%) across the 12 treatments, and reproduced interannual variation in N × P effects for crop yield and N export, where crop response was strongly mediated by N supply and water availability. APSIM also identified the long-term depletion or accumulation of soil P, N, and C in most treatments. P fractionation and isotherm measurements are labour intensive but worthwhile, and future efforts should work to consolidate a database for different soil types. Better informed P modelling will provide insights into the effects of climate variability on soil fertility and crop productivity, and guide management practices to deliver better fertiliser efficiency and maintain soil organic C. • Assessing the effects of soil fertility decline on crop productivity is complex due to climate × N × P interactions. • APSIM was parameterised with long-term soil P fractionation, and organic C and N data. • Across 12 treatments, APSIM explained 94% of N export, 88% crop yield, and 62% P export. • APSIM reproduced interannual treatments effects which were strongly mediated by N and water supply. • Long-term simulation showed N and P addition reduced the loss of soil organic C.

Long-Term Changes of Land Use and Land Cover in the Yangtze River Basin from 1990–2020 Landsat Data

Economic development and climate change drive the land use and land cover (LULC) change globally. Annual robust maps of LULC are critical for studying climate change and land–climate interaction. However, the current existing methods for optimizing and expanding the publicly available China land cover data set (CLCD) are limited. In this article, 30-m annual LULC changes are obtained from 1990 to 2020 in the Yangtze River basin (YRB). The results show an overall accuracy rate of 82.66% and better performances on Geo-Wiki test samples when compared to similar products. Based on our 30-m annual LULC data set, the drastic LULC changes are found in YRB over a 30-year period, where impervious surface area more than tripled, cropland area decreased by 6.12%, and water area decreased by 6.09%. In addition, through the geographically and temporally weighted regression method, a fitting model with a goodness of fit of 0.91 well reveals that human activity plays a driving role in the LULC change of YRB.