Annual Precipitation Research Articles

Discrepancies in precipitation changes over the Southwest River Basin of China based on ISIMIP3b

Selecting appropriate global climate models (GCMs) is crucial for minimizing uncertainty in regional climate projections under future scenarios. Previous studies have predominantly assessed the modeling capability of GCMs for regional precipitation climatology and its long-term patterns based on annual and seasonal precipitation data. Building upon these, we primally evaluated the performance of five GCMs from phase 3b of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) in simulating precipitation concentration and its variations in the Southwest River Basin (SWRB) of China using the precipitation concentration index (PCI). The results indicate that: (1) The 5 GCMs generally capture the spatial distribution of annual average precipitation in the SWRB but significantly overestimate its magnitude, with a maximum regional average deviation of 207.80 mm. Furthermore, all models tend to overestimate the overall drying trend in the SWRB and show limited capability in simulating interdecadal variations of annual precipitation. (2) While the 5 GCMs reasonably simulate the spatial distribution of annual average PCI in the SWRB, they tend to overestimate its values, with a maximum regional average deviation of 1.54. Additionally, their simulation performance in capturing PCI trends and interdecadal variations is also limited. (3) The 5 GCMs tend to overestimate seasonal precipitation in the SWRB, with the best simulation performance for the distribution of autumn precipitation, followed by spring and summer, and the poorest for winter. Significant differences exist in the simulation performance of the models for seasonal precipitation proportions, which result in discrepancies in the models’ representation of PCI. Moreover, the models’ poor simulation performance of PCI trends is partly due to their inadequate modeling of trends in seasonal precipitation proportions. The findings will contribute to laying the foundation for meteorological hydrological research and water resource management in the SWRB.

Spatial pattern and landscape change prediction of blowouts in sandy grassland

Blowouts are a common type of wind-eroded landform found in sandy and desertified areas. They also represent a major degradative surface process affecting grassland ecosystems. Blowouts exacerbate changes in surface morphology through their effects on other surface phenomena including vegetation. In this paper, Xilingol League sandy grassland blowouts are taken as the research object, and the U.S. Keyhole satellite data and China’s Gaofen-1 satellite data are used as the data source, and the blowouts are extracted based on the 3 S technology for a total of six periods of high-resolution remote sensing image data in the study area from 1962 to 2023. The Landscape Pattern Index method and Fuzzy Land Use Simulation (FLUS) modelling applied to changes over the last six decades provided spatial evolution parameters for predicting future blowout distributions. Results showed that blowouts affecting the Xilingol grassland area increased by 16.81% over the past 60 years. The patch density (PD) increased by 0.9 per hectare. The mean proximity index (PROX_MN) and mean Euclidean nearest neighbour distance (ENN_MN) showed a tendency to decrease and then increase indicating initial expansion and then merging of adjacent blowouts to create the present landscape. The FLUS model used ten factors to predict changes in blowout distributions from 2023 to 2033. Factors included digital elevation model (DEM), slope, aspect, normalized difference vegetation index (NDVI), mean annual temperature, mean annual precipitation, population density, real GDP, distance to water, and distance to impervious surfaces. It was found that grassland area decreased by 6217.12 hm2 and blowout area decreased by 102.91 hm2. Results of this study can expand understanding of blowout morphodynamics in ecologically sensitive areas.

Enhancing sustainable development through Spatiotemporal analysis of Ramsar wetland sites in South Asia

The ecological significance of wetlands makes it imperative to study changes in their inundation extent and propose necessary conservation measures. Monitoring wetland dynamics and implementing strategies to protect these essential ecosystems is crucial for maintaining the balance of natural systems. This study used pre-processed Landsat imagery (1991–2020) to generate yearly composites and produce inundation maps based on an automated Short-Wave Infrared thresholding technique within the Google Earth Engine platform. The analysis was executed on individual wetlands to describe their typical condition owing to regional climatic and geographical circumstances. The Mann-Kendall test was used to understand the trends in the change of inundation extent. The thresholding method achieved an overall accuracy of 89.0 %, with average dry and wet Producer's accuracies of 90.6 % and 86.6 %, respectively. The accuracy was higher for open water lakes compared to wetlands with complex vegetation dynamics. The trend analysis revealed that 46 sites follow an increasing trend, while the remaining 43 sites were found to be decreasing. Among these 43, 12 sites were found to be significantly decreasing, with the Upper Ganga River showing a maximum decrease of about 59 % in the inundation extent. Factors such as elevation, precipitation, temperature, and climate type were found to influence the trends in wetland inundation. Wetlands at high altitudes (>4000 m) and those receiving less than 500 mm of annual precipitation were more likely to exhibit decreasing trends. Coastal wetlands showed varying trends, with five increasing and three significantly increasing. The findings of this study provide valuable insights into the relationship between sustainable development and wetland conservation, supporting the Ramsar Convention's goals and the UN's Sustainable Development Goals. The individualized analysis of Ramsar sites enables the development of localized management strategies, climate change adaptation, and informed policy-making, ultimately contributing to the sustainable use of these critical ecosystems in South Asia.

Mapping critical soil moisture thresholds of water stress for global grasslands

The critical soil moisture threshold (SMth) of plant water stress distinguishes whether vegetation is in an energy-limited or water-limited regime. Accurate quantification of SMth for grasslands holds significant implications for drought monitoring and efficient grassland management. However, our understanding of SMth within global grasslands remains limited. In this study, we investigated the relationship between SMth and environmental factors and mapped the global SMth for grasslands based on the estimated SMth across FLUXNET sites. Firstly, SMth was identified and estimated for 18 distinct grassland sites. Then, the factors significantly affecting SMth were investigated and the global SMth for grasslands was predicted using an empirical linear model. Our results showed that SMth was significantly positively correlated with mean annual soil moisture (SM), mean annual precipitation (PRE), and maximum annual LAI (LAImax), while negatively correlated with vapor pressure deficit (VPD) and shortwave radiation (RAD). These factors collectively constrain SMth well, with the coefficient of determination of 0.79. The estimated mean SMth for global grasslands from 2000 to 2021 is 27.8%, with a range from 1.3% to 55.2%. The SMth values are lower in the northern hemisphere than that in the southern hemisphere. The highest values of SMth, exceeding 40.0%, are mainly distributed in Brazil, Peru, Southern Europe, New Zealand and the Tibetan Plateau. In contrast, the lowest values, failing below 20.0%, are mainly distributed in Northern Canada, Greenland, Central African Savannah and Kazakhstan. The SMth is markedly lower in the arid region than that in the tropical and temperate regions. The quantified SMth in this study could provide a direct way to determine whether and to what extent grasslands are subjected to water stress, which would greatly facilitate the study of drought or water stress effects on vegetation growth for grassland ecosystems.

Hydrological response to climate change in Baro basin, Ethiopia, using representative concentration pathway scenarios

Droughts and floods are common in the Baro basin and climate change may exacerbate them. This study aimed to investigate the hydrological response to climate change’s impact in the Baro River basin. Four climate models namely, Hadley Centre Global Environmental Model, version 2 (HadGEM2-ES), Max Planck Institute Earth System Model—Low Resolution (MPI-ESM-LR), Coupled Model Version 5, Medium Resolution (CM5A-MR) and European Community Earth System Model (EC-Earth) dynamically downscaled outputs were obtained from Africa coordinated regional downscaling experiment program. The four climate models were evaluated using a suite of statistical measures such as bias, Root Mean Squared Error, and Coefficient of Variation. The bias of the simulated rainfall varies between − 4.20% and − 25.39% suggesting underestimation. The performance of the models differs subject to the performance measures used for evaluation. Before being used in the climate impact analysis, the climate model data was heavily skewed and needed correction. In terms of bias, HadGEM2-ES performed the worst while EC-Earth performed the best. MPI-ESM-LR was the worst performer in terms of RMSE and CM5A-MR was the best. Changes in the hydrological response to climate change were compared to the baseline scenario (1971–2000) under the Representative Concentration Pathway Scenarios (RCP 4.5) for the medium term (2041–2070). The GCM predictions for the RCP 4.5 scenarios suggested that, in the medium period (2041–2070) the maximum temperature in the Baro River basin will probably rise by 2.1 °C for MPI-ESM-LR and 2.49 °C for CM5A-MR, while the minimum temperature would likely climb by 1.7 °C to EC-Earth and 2.8 °C for HadGEM2-ES. Annual rainfall is expected to fall by 7.02% for CM5A-MR and 17.01% for HadGEM2-ES, while annual evapotranspiration potential is likely to rise. Except from March to May CM5A-MR consistently generated the greatest amount of streamflow change, while MPI-ESM-LR consistently generated the highest magnitude of streamflow change. The annual streamflow reduction is consistent with the annual precipitation reduction and increased annual potential evapotranspiration. Generally, climate change is predicted to have a significant impact on the hydrological response in the Baro River basin under the RCP 4.5 scenario.

Modern Abies, Picea, and Tsuga pollen distribution along the elevation gradient in East Asia

Sub-alpine dark coniferous forests (SCFs) exhibit distinct latitudinal and longitudinal elevation distributions in East Asia. The SCF genera Abies, Picea, and Tsuga produce distinctive pollen and have specific elevation and climate requirements, allowing for the reconstruction of paleo-climatic and paleo-elevational changes from fossil pollen sequences. However, the relationship between SCF elevational distribution and the percentage of coniferous pollen has not been elucidated at the continental scale. In this study, we determined the relationship between Abies, Picea, and Tsuga pollen percentages and SCF elevation distributions in East Asia using an integrated pollen dataset comprising 4863 modern samples. The total percentage of these pollen types showed bimodal patterns with elevation and unimodal patterns with climate. Maximum pollen percentages occurred at elevations of 0–1000 and 2000–4600 m, mean annual temperatures of −5–10 ℃, and mean annual precipitation values of 100–1500 mm. The elevation with the highest proportion of Abies + Picea + Tsuga pollen increased with decreasing latitude: from 500 m (>43°N) to 2300 m (37–43°N), to 3500 m (30–37°N), and to 4000 m (18–30°N). Elevation also exhibited non-monotonic variations with longitude, first increasing from 2500 m (<93°E) to 3500 m (93–102°E), and then decreased to 2500 m (102–113°E) and 500 m (>113°E). The spatial patterns of Abies, Picea, and Tsuga pollen abundance were closely correlated with modern SCF distributions, which are largely modulated by climate and elevation. This study lays the foundation for reconstructing paleo-climate and paleo-elevation variations across East Asia.

Leaf habit drives leaf nutrient resorption globally alongside nutrient availability and climate

Abstract. Nutrient resorption from senescing leaves can significantly affect ecosystem nutrient cycling, making it an essential process to better understand long-term plant productivity under environmental change that affects the balance between nutrient availability and demand. Although it is known that nutrient resorption rates vary strongly between different species and across environmental gradients, the underlying driving factors are insufficiently quantified. Here, we present an analysis of globally distributed observations of leaf nutrient resorption to investigate the factors driving resorption efficiencies for nitrogen (NRE) and phosphorus (PRE). Our results show that leaf structure and habit, together with indicators of nutrient availability, are the two most important factors driving spatial variation in NRE. Overall, we find higher NRE in deciduous plants (65.2 % ± 12.4 %, n=400) than in evergreen plants (57.9 % ± 11.4 %, n=551), likely associated with a higher share of metabolic N in leaves of deciduous plants. Tropical regions show the lowest resorption for N (NRE: 52.4 % ± 12.1 %), and tundra ecosystems in polar regions show the highest (NRE: 69.6 % ± 12.8 %). At the same time, the PRE is lowest in temperate regions (57.8 % ± 13.6 %) and highest in boreal regions (67.3 % ± 13.6 %). Soil clay content, N and P atmospheric deposition (globally available proxies for soil fertility), and mean annual precipitation (MAP) play an important role in this pattern. The statistical relationships developed in this analysis indicate the important role of leaf habit and type for nutrient cycling and guide improved representations of plant-internal nutrient recycling and nutrient conservation strategies in vegetation models.

Response of black pine (Pinus nigra) in southwestern Anatolia to climate change

Global climate change is one of the most critical challenges facing natural ecosystems. As sedentary organisms, plant communities are especially vulnerable, with climate change significantly impacting their development, productivity, and distribution. This study focuses on modelling and mapping the potential distribution of black pine (Pinus nigra) within the Antalya Regional Forest Directorate under the SSP1 2.6 climate scenario for the years 2040, 2060, 2080, and 2100. The MaxEnt modelling method, combined with the HadGEM3-GC31-LL climate model from WorldClim, was used to assess the impact of climate change on black pine. The current distribution model results showed “good” predictive performance, with AUC values of 0.855 for training data and 0.851 for testing data. Key variables influencing the model included precipitation during the wettest quarter, annual precipitation, maximum temperature of the warmest month, and elevation. Projections indicate that the black pine’s distribution will shrink by 2040, become increasingly fragmented by 2060, and decline further by 2080, with near-total disappearance by 2100. In conclusion, this study highlights the urgent need for adaptive management strategies to address the effects of climate change on black pine forests.

The implications of climate change on freshwater resources in the arid and semiarid Mediterranean environments using hydrological modeling, GIS tools, and remote sensing.

Precipitation partitioning in arid and semiarid environments is not well understood due to scanty precipitation, its temporal distribution, and the lack/absence of adequate measurements of the hydrometeorological components. Simulation methods have the potential to bridge the data gap, thereby providing a window to estimate the water balance components. The present investigation evaluates the water balance components of a typical watershed situated in the southeastern Mediterranean for the period 1979 through 2019 using daily meteorological data and a grid spacing of 250 m. Generated runoff results were commensurate with corresponding values obtained using the SWAT model. Computed groundwater recharge is also compatible with recharge values calculated using the chloride mass balance method. Results show that average runoff and groundwater recharge for the entire period was ⁓24 mm a-1 and 19 mm a-1, giving a precipitation ratio of 9.5% and 7.5%, respectively. Substantial interannual variability in the water balance components was observed during the study period which reflected the significant precipitation fluctuations typifying the Eastern Mediterranean. Results show that the period extending from 1998/1999 through 2018/2019 witnessed an 18% drop in annual precipitation, while surface runoff and groundwater recharge experienced a reduction of ⁓34% and ⁓67%, respectively. Although groundwater recharge is a complex function of numerous meteorological and geological factors, the NDVI can provide an excellent indicator of groundwater recharge in marginal Mediterranean environments. This is highly beneficial in areas where climate records are scanty or absent. The presented results emphasize the significant impacts of global warming and aridification on the future availability of water resources in the semiarid marginal climates in the Eastern Mediterranean and point out clearly that water resources in this area will become scarcer, leading to multiple security threats at national and regional levels.

A multiscale analysis of factors influencing Setophaga striata (Blackpoll Warbler) occupancy and abundance during the nonbreeding season in eastern Colombia

Abstract Setophaga striata (Blackpoll Warbler), one of the few boreal-breeding migratory birds that migrates to the Orinoco and Amazon regions, is experiencing steep population declines. However, knowledge of the species’ distribution and habitat use during the nonbreeding season is limited. Here, we explore how stationary nonbreeding season (December to April) occupancy probabilities vary across regional and landscape scales, and with vegetation structure for S. striata in eastern Colombia. By running single-species, single-season hierarchical occupancy models and N-mixture models, we evaluated how regional (annual precipitation, nonbreeding season precipitation, driest month, elevation, and net primary productivity), landscape (habitat type and % forest in the landscape), and vegetation structure variables influenced occupancy by S. striata. In the regional analysis, occupancy was positively influenced by stationary nonbreeding precipitation and net primary productivity, and was predicted to peak at elevations between 500 and 1,000 m. At the landscape scale, occupancy and abundance were higher in agroforestry systems (in order of magnitude: shade-grown cacao, citrus plantations and silvopastures) than in forested habitats. In relation to vegetation structure, occupancy was negatively correlated with a principal component containing shrub density, canopy height, and canopy cover. Within the Orinoco region, a spatial prediction based on our results supported high occupancy rates in moister areas along and close to the Andean foothills and where the Orinoco grasslands transition into Amazonian forests. Our results highlight the importance of landscapes containing agroforestry systems as stationary nonbreeding habitats for S. striata in Colombia’s Orinoco region and the importance of promoting agroforestry systems, like shade-grown cacao, in areas with higher nonbreeding season precipitation and net primary productivity values in order to increase habitat availability for the species.

Phylogeny, historical biogeography and climate niche differentiation in extant species of Ceratophryidae (Anura, Hyloidea) frogs in South America

Ceratophryidae is a family of frogs containing twelve extant species distributed in South America. Several studies have been carried out concerning the systematics, morphology, karyotypes, and behaviour within this monophyletic family. However, little is known about the historical biogeography and the divergence in time of this group. Here, we present an updated phylogeny, along with a calibrated chronogram, to analyse the historical biogeographical pattern and climate niche differentiation among extant species of Ceratophryidae (Anura: Hyloidea) frogs in South America. A phylogeny based on morphological and genetic data was obtained from 256 morphological characters, six mitochondrial and eight nuclear genes for up to a total of 8428 characters in the homological matrix. Our results indicate that the genus Ceratophrys is sister to the clade Chacophrys + Lepidobatrachus. The divergence of the crown group of Ceratophryidae is estimated to have occurred 19.2 Ma at the beginning of the Miocene, with recent cladogenetic events related to the late Miocene (10.18–13.70 Ma) and the Pliocene (~5.3–2.6 Ma). Moreover, the Cerrado region is estimated to be the ancestral area of the family, as well for the genera Chacophrys and Lepidobatrachus. In addition, temperature seasonality and annual precipitation play a major role in the niche differentiation of extant species within Ceratophryidae. In conclusion, our data suggest multiple dispersal and vicariance events originating from the Cerrado region in the early Miocene, and recognize the role of the environment in the differentiation of the ecological niches among extant species of this family in South America. Ceratophryidae is hypothesized to have originated in the semi-arid Cerrado region in the early Miocene (~19.2 million years ago), from where species have diversified by independent dispersal and vicariance events across other South American regions. Ceratophrys frogs are phylogenetically recovered as the sister taxon to the clade comprising Chacophrys and Lepidobatrachus. Three lineages of Lepidobatrachus and four lineages from Ceratophrys diverged in the Pliocene, around 5.3 to 2.6 million years ago. Niche differentiation among extant species of Ceratophryidae appears to reflect roles for temperature seasonality and annual precipitation.

Precipitation and diameter affect wood decomposition both directly and indirectly via deadwood traits and position

Woody plants are important components of dryland ecosystems. Our understanding of wood decomposition in drylands, an important component of biogeochemical cycling, is poor compared to that in mesic ecosystems. To uncovering the complex interactive effects of the different key drivers, we studied the effects of precipitation, position (aboveground and belowground), wood size and litter quality of plant species (four to five local species and one widespread woody species) on woody litter decomposition rates along a precipitation gradient from 37 to 369 mm, spanning five dryland sites. Wood dry matter content (DMC) was a critical negative predictor of wood decomposition in water-limited ecosystems. Thicker woody litter had lower decomposition rates (k values) directly because of smaller relative surface exposure, and indirectly through higher wood DMC or lower bark mass ratio (bark mass divided by wood mass for a given branch length). Mean annual precipitation (MAP) increased the k values both directly, and indirectly by decreasing the wood DMC and increasing the bark mass ratio due to species turnover. The k values of buried woody litter were mostly two to three times higher than litter on the soil surface, but not different at the extremely arid site. A steeper slope of the relationship between overall woody litter quality (particularly wood DMC) or annual precipitation and k values was observed belowground than aboveground, as related to the higher moisture belowground than aboveground. These findings highlight the complex interactions among climate (precipitation), litter position, size and quality on wood decomposition in drylands, thereby helping to improve our mechanistic understanding of dryland woody litter decomposition. We conclude that wood decomposition at the regional and local scales will influence biogeochemical cycling in drylands under future climate change through both direct effects of moisture and indirect effects of litter quality characteristics.

Potential Changes in Distribution of Major Conifers and Their Seed Mass across Siberia by the Mid-Twenty-First Century in a Warming Climate

Research highlights: At the turn of the 21st century, there were more forest territories found disturbed by both natural processes (climate change, wildfires, insect outbreaks, permafrost thawing, etc.) and anthropogenic interferences (air pollution, clearcuts, etc.). Seed collecting, then growing seedlings in forest nurseries, and then planting seedlings over lost forest areas are the forestry measures needed to restore the forest after disturbances. Goals were to construct bioclimatic models of ranges and seed mass of major Siberian conifers (Siberian pine (Pinus sibirica Du Tour), Siberian fir (Abies sibirica Ledeb.), Siberian spruce (Picea obovata Ledeb.), Siberian larches (Larix sibirica Ledeb., L. gmelini (Rupr) Rupr, and L. cajanderi Mayr.) and Pinus sylvestris L.) and predict their potential change in a warming climate by the mid-century. Methods: Multi-year seed mass data were derived from the literature, seed station data, and were collected in the field. Climate data (January and July data and annual precipitation) were derived from published Russian reference books and websites on climate. Bioclimatic indices (growing degree-days &gt; 5 C, negative degree-days &lt; 0 C, and annual moisture index) were calculated from January and July temperatures and annual precipitation for both contemporary and the 2050s (2040–2060) climates using the general circulation model INM-CM5-0 and two climate change scenarios, ssp126 and ssp585, from CMIP6. Our bioclimatic range models (envelope and MaxEnt models) and regression seed mass models for major conifers were built based on these bioclimatic indices. Additionally, their ranges were limited by the permafrost border, which divided the forest area into the permafrost-free zone, where five conifers are able to grow, and the permafrost zone, where only one conifer, Dahurian larch, is able to survive. Results: Under warmed climates, the ranges of all Siberian conifers would expand 1.5-fold due to the decrease in the permafrost zone, except Dahurian larch, which would lose 5–20% of its coverage due to permafrost retreat. Conifers shifting northward would be slower than predicted only by warmed climates because permafrost would thaw slower than climates would warm. Scots pine may expand by up to 60%, covering dryer lands in the south. Future climates were found to favor seed mass increase for major Siberian conifers and for heavier seed to shift northward. Our major conifers differ by the type of seed dispersal mode: zoochoric, animal (Siberian pine) and anemochoric, and wind-dispersed (other five trees). The seed masses of the five anemochoric conifers varied within the range of 1.5–15 g of 1000 seeds, which is about 40–50-fold less than that of zoochoric Siberian pine. Site climate explained about 28–65% of the seed mass variation for the five anemochoric trees and only 11% for Siberian pine (zoochoric tree). This finding needs additional research to explain the reasons. Conclusions: Warmed climates would favor the expansion of the ranges of major Siberian conifers and their seed mass to be heavier, which would support the high-quality seed production for forest well-being and its restoration in Siberia.

PreciDBPN: A customized deep learning approach for hourly precipitation downscaling in eastern China

Long-term series of high-resolution gridded precipitation datasets are essential for hydrological and meteorological research. Producing high-resolution precipitation data from regional models demands substantial computational resources and labor. Global Reanalyses offer long-term coverage and effectively capture annual and seasonal precipitation patterns. However, they have inadequate resolution and frequently have difficulties depicting extreme conditions. This study proposes an efficient and accurate approach for generating long-term series of high spatial and temporal resolution precipitation. It is achieved by leveraging deep learning techniques to integrate the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) global climate reanalysis (ERA5, 0.25°, hourly) data with high-resolution precipitation fusion datasets. Considering the heavy-tailed distribution of precipitation, we developed the PreciDBPN model structure, which combines a classification network with a super-resolution network and incorporates physically relevant indices into the model's input. We trained and evaluated the PreciDBPN and baseline models in eastern China using the China Meteorological Administration Land Data Assimilation System (CLDAS) precipitation dataset (0.0625°, hourly, 2017–2022). When compared to baseline methods and ERA5, our model excels in multiple metrics and provides a more precise representation of relative rainfall frequency. Independent verification was performed using station observations during the period of 2010–2015 when CLDAS data were unavailable. During this verification, the PreciDBPN demonstrated exceptional performance and greater robustness compared to the baseline models. Because our method can efficiently downscale precipitation and bias-correct reanalysis data using minimal computational resources, it can be used to generate high-resolution precipitation datasets (0.0625°, hourly) from 1979 to 2022 while correcting for heavy precipitation underestimations in reanalysis data.

Interannual Variability in Seed Germination Response to Heat Shock in Cistus ladanifer

Mediterranean climates, characterised by hot and dry summers, have predictable fire regimes, and many species with physical seed dormancy (PY) thrive after wildfires. While it is well known that PY is released after heat shock in these species, intraspecific variation in seed response to heat is less understood. This research explores, for the first time, the variability in the traits of Cistus ladanifer seeds from the same central Spain population over eight years. It examines seed germination and viability under different heat shocks and the relationships among seed traits and climatic variables. While the response to heat shock remained constant over the years studied, achieving the highest germination percentages after heat shock at 100 °C, seed germination varied between years, and environmental conditions affected seed traits. Seed moisture content was negatively correlated with the maximum summer temperatures, and seed viability was positively related to annual precipitation. Germination at 100 °C was lower in warmer years as more seeds did not break their PY. In conclusion, despite the fact that PY appears to be genetically determined, it also depends on the environmental conditions experienced by the mother plant. This interannual phenotypic variability may help Cistus ladanifer to cope with the increasingly unpredictable conditions imposed by climate change.

Precipitation and Soil Nitrogen as Key Drivers of Species and Phylogenetic Diversity Across Growth Forms in Picea purpurea Forests of the Eastern Qinghai–Tibet Plateau

ABSTRACTPicea purpurea forests are a fundamental part of the coniferous forests of the Qinghai–Tibet Plateau. These forests support an extremely rich diversity of organisms while providing crucial ecological functions. Despite their importance, the species and phylogenetic diversity (PD) of these forests remain understudied. The extent to which different plant growth forms in the forest are influenced by the environment varies according to differences in the evolutionary history and characteristics of these taxa. Here, we investigate the variations in all, woody, and herbaceous plant species diversity (SD) and PD in the eastern Qinghai–Tibet Plateau's Picea purpurea forests, along with the associated environmental factors influencing these patterns. Our results show that both SD and PD exhibit similar patterns across all, woody, and herbaceous plants. Notably, mean annual precipitation, total nitrogen, and altitude were identified as the primary factors accounting for the majority of variance in SD and PD within plant communities. Specifically, we found positive correlations between SD and PD with soil total nitrogen content, while negative correlations were observed with mean annual precipitation and altitude. Furthermore, we find that the influence of environmental variables on all plants was found to be more pronounced compared to woody and especially herbaceous plants in terms of both SD and PD. Environmental factors had a direct effect on SD and PD in all woody and herbaceous plants. However, the strength of these effects varied. Importantly, our results indicate that environmental factors influence SD independently of PD. Our findings suggest that precipitation and total soil nitrogen were the most influential environmental factors affecting plant diversity across different growth forms in Picea purpurea communities. However, inferring SD from PD remains a challenging task. These findings of our study will provide guidance for forest biodiversity conservation and sustainable forest management in the Qinghai–Tibet Plateau.

Variations on the chemical compositions of chestnut fruits collected at different locations

Chestnut is an essential food source in many countries. Nutritional quality and potential health benefits of Anatolian chestnut trees (Castanea sativa Mill.) have led to increased concern and interest in chestnut production. However, knowledge of the factors that influence the chemical content of chestnut fruits still needs to be improved. Thus, the chemical compositions were evaluated for Anatolian chestnut fruits collected at 14 different locations in northern Türkiye, which is one of the biggest chestnut producers in the world. The effects of latitude, longitude, altitude, aspect, mean annual temperature (°C) (TMA), and mean annual precipitation (mm) (PMA) of the study locations on the chemical compositions of chestnut fruits were monitored. The effects of these parameters on several chestnut characteristics were examined using a mixed-effects multiple regression model. Latitude, longitude, TMA, and PMA were correlated with the mean concentrations of sucrose, free amino acid, glycine betaine, nitrogen (N) (%), and total carbon (C) (%) of the chestnut samples. The moisture content of the fruits was affected by longitude. The antioxidant and mineral content of the chestnut samples also varied by location. These findings may be helpful in site selection, production, and conservation of chestnut cultivars.

Phenotypic Diversity and Seed Germination of Elaeagnus angustifolia L. in Relation to the Geographical Environment in Gansu Province, China

Elaeagnus angustifolia L. is a highly adaptable urban ornamental plant, playing a key role in dry land and saline-alkali protective forests. The diverse geographical and climatic conditions in Gansu Province have resulted in variations in its distribution and growth. This study assesses the phenotypic diversity of fruits and seeds, and the seed germination characteristics of 82 E. angustifolia plants from nine populations in Gansu Province, exploring their relationship with geographical and climatic factors. We measured 12 phenotypic traits and five germination indices. This study included germination tests under standard conditions, statistical analysis of phenotypic differences, and Pearson and Spearman correlation analyses to examine relationships between traits and geo-climatic factors. Principal component and cluster analyses were also performed to identify key traits and classify populations. The findings were as follows: (1) Significant differences were observed in phenotypic traits and germination characteristics among populations. Single fruit weight showed the highest variation (27.56%), while seed transverse diameter had the lowest (8.76%). The Lanzhou population exhibited the greatest variability (14.27%), while Linze had the lowest (6.29%). (2) A gradient change pattern in traits was observed, primarily influenced by longitude and a combination of geographical and climatic factors. Seed germination was positively correlated with altitude, annual precipitation, and relative humidity, but negatively affected by latitude and traits such as fruit weight. (3) Principal component analysis identified germination rate, germination index, seed shape index, and fruit shape index as primary factors, contributing 27.4%, 20.6%, and 19.9% to the variation, respectively. Cluster analysis grouped the 82 plants into four clusters, not strictly based on geographical distance, suggesting influence from factors such as genotype or environmental conditions. In conclusion, this study lays a foundation for understanding the genetic mechanisms behind the phenotypic diversity and germination characteristics of E. angustifolia. It offers insights into how geo-climatic factors influence these traits, providing valuable information for the species’ conservation, cultivation, and management.

Melanism in Polymorphic Terrestrial Snakes: A Meta‐Analysis and Systematic Review

ABSTRACTBackground and AimColour polymorphic populations constitute excellent model systems for testing ecological and evolutionary hypotheses, as alternate colourations are associated with differences in various biological, behavioural and life‐history traits. Melanism is the most common and most obvious form of polymorphism. In reptiles in general (and snakes in particular), thermal melanism has been a popular hypothesis used to explain the appearance of black individuals. It suggests that a trade‐off exists between superior thermoregulation and reduced protection through the loss of crypsis. Surprisingly, despite the growing body of literature available, to date, there are only two qualitative reviews on the evolutionary significance of melanism in reptiles and no quantitative synthesis. We conducted the first systematic review and meta‐analysis summarising the current knowledge on melanism in polymorphic terrestrial snakes and synthesised the evidence for an adaptive advantage of the melanistic morph.LocationNorthern Hemisphere.TaxonPolymorphic terrestrial snakes.ResultsMean prevalence of melanism is 31% with no significant differences between species. Annual precipitation was a significant moderator of melanism prevalence. Our results revealed no significant differences in odds ratios of melanism between sexes or in mean body size.Main ConclusionsEnvironmental plasticity can be considered the primary cause of melanism, possibly as a result of seasonal climatic variations, a result corroborated by the formal meta‐analysis conducted. Conclusions from the meta‐analysis are that melanism in snakes follows Gloger's rule, as is the case in birds and mammals, and as opposed to the thermal melanism hypothesis. Further, our findings do not lend support for other predictions from the thermal melanism hypothesis, such as skewed frequency of melanistics in favour of males or females, or larger body sizes in black individuals. Our results hold implications for the future diversity of animal populations, as climate change is predicted to decrease the degree of colour variation.

Response of Hydrothermal Conditions to the Saturation Values of Forest Aboveground Biomass Estimation by Remote Sensing in Yunnan Province, China

Identifying the key climate variables affecting optical saturation values (OSVs) in forest aboveground biomass (AGB) estimation using optical remote sensing is crucial for analyzing OSV changes. This can improve AGB estimation accuracy by addressing the uncertainties associated with optical saturation. In this study, Pinus yunnanensis forests and Landsat 8 OLI imagery from Yunnan were used as case studies to explain this issue. The spherical model was applied to determine the OSVs using specific spectral bands (Blue, Green, Red, Near-Infrared (NIR), and Short-Wave Infrared Band 2 (SWIR2)) derived from Landsat 8 OLI imagery. Canonical correlation analysis (CCA) uncovered the intricate relationships between climatic variables and OSV variations. The results reveal the following: (1) All Landsat 8 OLI spectral bands showed a negative correlation with the Pinus yunnanensis forest AGB, with OSVs ranging from 104.42 t/ha to 209.11 t/ha, peaking in the southwestern region and declining to the lowest levels in the southeastern region. (2) CCA effectively explained 93.2% of the OSV variations, identifying annual mean temperature (AMT) as the most influential climatic factor. Additionally, the mean temperature of the wettest quarter (MTQ) and annual precipitation (ANP) were significant secondary determinants, with higher OSV values observed in warmer, more humid areas. These findings offer important insights into climate-driven OSV variations, reducing uncertainty in forest AGB estimation and enhancing the precision of AGB estimations in future research.