Seasonal Temperature Research Articles

Baltic Sea surface temperature analysis 2022: a study of marine heatwaves and overall high seasonal temperatures

Abstract. In 2022, large parts of the Baltic Sea surface experienced the third-warmest to the warmest temperatures over the summer and autumn months since 1997. Warm temperature anomalies can lead to marine heatwaves (MHWs), which are discrete periods of anomalous high temperatures relative to the usual local conditions. Here, we describe the overall sea surface temperature (SST) conditions observed in the Baltic Sea in 2022 and provide a spatiotemporal description of surface MHW events based on remote sensing, reanalysis, and in situ station data. The most MHWs, locally up to seven MHW events, were detected in the western Baltic Sea and the Inner Danish Straits, where maximum MHW intensities reached values of up to 4.6 °C above the climatological mean. The northern Baltic Proper and the Gulf of Bothnia were impacted mainly by two MHWs at maximum intensities of 7.3 and 9.6 °C, respectively. Our results also reveal that MHWs in the upper layer occur at a different period than at the bottom layers and are likely driven by different mechanisms. Reanalysis data from two exemplary stations, “Lighthouse Kiel (LT Kiel)” and “Northern Baltic”, show a significant increase in MHW occurrences of +0.73 MHW events per decade at LT Kiel and of +0.64 MHW events per decade at Northern Baltic between 1993 and 2022. Moreover, we discuss the expected future increased occurrence of MHWs based on a statistical analysis at both locations.

Germination responses to changing rainfall timing reveal potential climate vulnerability in a clade of wildflowers.

The seasonal timing of life history transitions is often critical to fitness, and many organisms rely upon environmental cues to match life cycle events with favorable conditions. In plants, the timing of seed germination is mediated by seasonal cues such as rainfall and temperature. Variation in cue responses among species can reflect evolutionary processes and adaptation to local climate and can affect vulnerability to changing conditions. Indeed, climate change is altering the timing of precipitation, and germination responses to such change can have consequences for individual fitness, population dynamics, and species distributions. Here, we assessed responses to the seasonal timing of germination-triggering rains for eleven species spanning the Streptanthus/Caulanthus clade (Brassicaceae). To do so, we experimentally manipulated the onset date of rainfall events, measured effects on germination fraction, and evaluated whether responses were constrained by evolutionary relationships across the phylogeny. We then explored the possible consequences of these responses to contemporary shifts in precipitation timing. Germination fractions decreased with later onset of rains and cooler temperatures for all but three Caulanthus species. Species' germination responses to the timing of rainfall and seasonal temperatures were phylogenetically constrained, with Caulanthus species appearing less responsive. Further, four species are likely already experiencing significant decreases in germination fractions with observed climate change, which has shifted the timing of rainfall towards the cooler, winter months in California. Overall, our findings emphasize the sensitivity of germination to seasonal conditions, underscore the importance of interacting environmental cues, and highlight vulnerability to shifting precipitation patterns with climate change, particularly in more northern, mesic species.

Tree carbon stock and seasonal influence on soil properties in shivpuri-nagarjun national park, nepal

The carbon stock stored within the biomass of tree species is vital in the forest ecosystem as it contributes significantly to the carbon balance. In addition, the physicochemical properties of soil play a critical role, in influencing overall ecosystem health. This study has analyzed the carbon stock and influence of seasonal change on soil physicochemical properties along soil depths in the Shivpuri Nagarjun National Park (SNNP), Nepal. The above-ground biomass carbon stock was found to be 227.09 t/ha and below-ground stock was 45.42 t/ha. Tree species Castanopsis tribuloides exhibited the highest values of above and below-ground tree carbon stock. The soil of the study site was sandy loam and slightly acidic. High temperature and moisture in the monsoon season were followed by an increased bulk density during the pre-monsoon with deeper soil layers. The sand, silt, and clay contents did not differ significantly across the seasons and depths. The key soil nutrients, like carbon, total nitrogen, phosphorus, and potassium were high during the monsoon season at the topsoil layer, which gradually declined with increasing depth in all seasons. The study highlights that the total tree carbon stock in the study site is 272.51 t/ha, with significant seasonal and depth-related variations in soil attributes. The monsoon season, characterized by maximum soil moisture and higher concentrations of essential soil components, is crucial in influencing soil physicochemical properties and offers important insights for forest conservation and management. Bangladesh J. Bot. 53(3): 567-576, 2024 (September)

Morphological and Germination Characteristics of Alhagi maurorum Boiss. and Salsola richteri Kar. Seeds Distributed in the Karakum Desert of Turkmenistan

The Karakum Desert is the largest desert in Turkmenistan and covers a significant part of Central Asia. This desert is home to plant species that can adapt to hot, dry, and barren conditions. During the summer months, the Karakum Desert can get extremely hot, with temperatures reaching up to 50 °C, while in winter, it can drop to -20 °C. Therefore, the desert conditions significant seasonal temperature differences. In winter, rainfall is very low, snow rarely falls, and quickly melts. Afghan winds have an impact on the desert vegetation. The desert vegetation mainly consists of short grasses and woody shrubs. Despite the scarcity of rainfall and high temperatures during the summer months, steppe plants have generally been able to adapt to the harsh conditions of the desert. There are also species that have adapted to the desert climate, such as Alhagi maurorum Boiss., Haloxylon persicum Bunge, Haloxylon aphyllum (Minkw.) Iljin), Solanum nigrum L., and Salsola richteri Kar. These plants are highly valuable in terms of nutrition for animals and are used as winter animal feed in rural areas. In this study, the seed and germination characteristics of Alhagi maurorum Boiss. and Salsola richteri Kar, which are tree and shrub-like plants that can adapt to Karakum Desert conditions, were examined. In laboratory study, the morphological characteristics of the seeds were determined, and vitality and germination tests were conducted. Information was obtained about the germination adaptation of these plants in desert ecosystems. As a result of the study, it was determined that S. richteri had a very low rate of viable seeds and no germination, while the germination process of Alhagi maurorum could take a considerably long time.

Space-time cluster analysis and maximum entropy modeling of Peste des petits ruminants (PPR) in Türkiye.

Peste des petits ruminants (PPR) is an economically important highly serious transboundary disease that mainly occurs in small ruminants such as sheep and goats. The aim of this study was to identify the probability of risk and and space-time clusters of Peste des Petits Ruminants (PPR) in Türkiye. The occurrence of PPR in Türkiye from 2017 to 2019 was investigated in this study using spatial analysis based on geographic information system (GIS). Between these dates, it was determined that 337 outbreaks and 18,467 cases. The highest number of outbreaks were detected in the Central Anatolia region. It was determined that PPR is seen more intensely in sheep compared to goats in Türkiye. In this study, 34 environmental variables (19 bioclimatic, 12 precipitation, altitude and small livestock density variables) were used to explore the environmental influences on PPR outbreak by maximum entropy modeling (Maxent). The clusters of PPR in Türkiye were identified using the retrospective space-time scan data that were computed using the space-time permutation model. A PPR prediction model was created using data on PPR outbreaks combination with environmental variables. Nineteen significant (p < 0.001) space-time clusters were determined. It was discovered that the variables altitude, sheep density, precipitation in june, and average temperature in the warmest season made important contributions to the model and the PPR outbreak may be strongly related with these variables. In this study, PPR in Türkiye has been characterized significantly spatio-temporal and enviromental factors. In this context, the disease pattern and obtained these findings will contribute to policymakers in the prevention and control of the disease.

Grass leaf structural and stomatal trait responses to climate gradients assessed over the 20th century and across the Great Plains, USA.

Abstract. Using herbarium specimens spanning 133 years and field-collected measurements, we assessed intraspecific trait (leaf structural and stomatal) variability from grass species in the Great Plains of North America. We focused on two widespread, closely related grasses from the tribe Paniceae: Dichanthelium oligosanthes subsp. scribnerianum (C3) and Panicum virgatum (C4). Thirty-one specimens per taxon were sampled from local herbaria from the years 1887 to 2013 to assess trait responses across time to changes in atmospheric [CO2] and growing season precipitation and temperature. In 2021 and 2022, the species were measured from eight grasslands sites to explore how traits vary spatially across natural continental precipitation and temperature gradients. Δ13C increased with atmospheric [CO2] for D. oligosanthes but decreased for P. virgatum, likely linked to increases in precipitation in the study region over the past century. Notably, this is the first record of decreasing Δ13C over time for a C4 species illustrating 13C linkages to climate. As atmospheric [CO2] increased, C:N increased and δ15N decreased for both species and %N decreased for D. oligosanthes. Across a large precipitation gradient, D. oligosanthes leaf traits were more responsive to changes in precipitation than those of P. virgatum. In contrast, only two traits of P. virgatum responded to increases in temperature across a gradient: specific leaf area (increase) and leaf dry matter content (decrease). The only shared significant trend between species was increased C:N with precipitation. Our work demonstrates that these closely related grass species with different photosynthetic pathways exhibited various trait responses across temporal and spatial scales, illustrating the key role of scale of inquiry for forecasting leaf trait responses to future environmental change.

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.

Biotic and abiotic factors associated with genome size evolution in oaks.

The evolutionary processes that underlie variation in plant genome size have been much debated. Abiotic factors are thought to have played an important role, with negative and positive correlations between genome size and seasonal or stressful climatic conditions being reported in several systems. In turn, variation in genome size may influence plant traits which affect interactions with other organisms, such as herbivores. The mechanisms underlying evolutionary linkages between plant genome size and biotic and abiotic factors nonetheless remain poorly understod. To address this gap, we conducted phylogenetically controlled analyses testing for associations between genome size, climatic variables, plant traits (defenses and nutrients), and herbivory across 29 oak (Quercus) species. Genome size is significantly associated with both temperature and precipitation seasonality, whereby oak species growing in climates with lower and less variable temperatures but more variable rainfall had larger genomes. In addition, we found a negative association between genome size and leaf nutrient concentration (found to be the main predictor of herbivory), which in turn led to an indirect effect on herbivory. A follow-up test suggested that the association between genome size and leaf nutrients influencing herbivory was mediated by variation in plant growth, whereby species with larger genomes have slower growth rates, which in turn are correlated with lower nutrients. Collectively, these findings reveal novel associations between plant genome size and biotic and abiotic factors that may influence life history evolution and ecological dynamics in this widespread tree genus.

Effects of climate change and species distribution modeling of Loxosceles (Araneae: Sicariidae) from Central Mexico

With 40 of the 149 described species, Mexico harbors the highest diversity of the spider genus Loxosceles. However,knowledge about these spiders’ distribution patterns in a climate change (CC) context is poorly known. In this study,the distributions of 4 species from Central Mexico, Loxosceles malintzi, L. misteca, L. tenochtitlan and L. zapoteca, were estimated and evaluated based on species distribution modeling (SDM) and the possible effects of CC. Two future scenarios were simulated (years 2050 and 2080) to show possible increases or reductions in species distributions. The most important variables that influence the distribution of the species were: isothermality, seasonality of temperature, and precipitation. In the CC scenarios, some species showed a possible increase, specifically, Loxosceles malintzi with an increase in its distribution of 79% by 2050 and 66% by 2080, whereas L. misteca was projected to increase its distribution by 28% for 2050 and 38% for 2080. However, a decrease in the distribution of L. tenochtitlan by 51% for 2050 and 38% for 2080 was projected, as well as a 45% decrease by 2050 and a 40% decrease by 2080 for L. zapoteca.

Modeling the Effects of Temperature and Limiting Nutrients on the Competition of an Invasive Floating Plant, Pontederia crassipes, with Submersed Vegetation in a Shallow Lake.

The potential for a non-native plant species to invade a new habitat depends on broadscale factors such as climate, local factors such as nutrient availability, and the biotic community of the habitat into which the plant species is introduced. We developed a spatially explicit model to assess the risk of expansion of a floating invasive aquatic plant species (FAV), the water hyacinth (Pontederia crassipes), an invader in the United States, beyond its present range. Our model used known data on growth rates and competition with a native submersed aquatic macrophyte (SAV). In particular, the model simulated an invasion into a habitat with a mean annual temperature different from its own growth optimum, in which we also simulated seasonal fluctuations in temperature. Twenty different nutrient concentrations and eight different temperature scenarios, with different mean annual amplitudes of seasonal temperature variation around the mean of the invaded habitat, were simulated. In each case, the ability of the water hyacinth to invade and either exclude or coexist with the native vegetation was determined. As the temperature pattern was changed from tropical towards increasingly cooler temperate levels, the competitive advantage shifted from the tropical FAV to the more temperate SAV, with a wide range in which coexistence occurred. High nutrient concentrations allowed the coexistence of FAV, even at cooler annual temperatures. But even at the highest nutrient concentrations in the model, the FAV was unlikely to persist under the current climates of latitudes in the Southeastern United States above that of Northern Alabama. This result may have some implications for where control efforts need to be concentrated.

Causal network linking honey bee (Apis mellifera) winter mortality to temperature variations and Varroa mite density

Winter season is a critical time for honey bees (Apis mellifera) colonies when individual mortalities may lead to total colony losses or diminish productivity in subsequent seasons. A deeper understanding of the causes and consequences of winter mortality is required. In this study, we analyzed winter (November–March) individual bee mortality in an apiary in Central Europe from 1991 to 2023. We observed consistency in mortality times among years, but also some systematic departures from the shared trend. We distinguished four clusters of year-specific mortality trajectories. However, we found no statistically significant differences in means of spring (March–May), autumn (October), winter (November–March) temperatures, or autumn Varroa destructor density among clusters. Nevertheless, our insights into the dynamics of individual bee mortality may be important for determining critical moments during wintering when implementing additional protective measures could prove beneficial. Hypothesis-driven path analysis indicated causal links in our study system, including both direct and indirect influences. The density of V. destructor in autumn was positively related to temperature, especially in the preceding spring, but to a lesser extent also in autumn. Increased winter mortality was related to lower winter temperatures and a higher mite infestation in autumn. We found no significant effects of individual winter mortality on honey harvests in subsequent seasons. Honey harvest was determined by bee abundance in spring, and the latter, unexpectedly, was not related to winter mortality. Our study adds to accumulating evidence of the major role of weather and climatic conditions in the resilience of honey bee colonies and improves our understanding of mortality processes. We highlighted the importance of causative factors, especially seasonal temperatures and V. destructor density, and their potential as predictive indicators of individual winter mortality, bee colony fate, and honey productivity.

Reconstructing the biological invasion of noxious invasive weed Parthenium hysterophorus and invasion risk assessment in China.

Invasive alien plants (IAPs) present a severe threat to native ecosystems and biodiversity. Comprehending the potential distribution patterns of these plant invaders and their responses to climate change is essential. Parthenium hysterophorus, native to the Americas, has become an aggressively invasive species since its introduction to China in the 1930s. This study aims to collect and reconstruct the historical occurrence and invasion of P. hysterophorus. Using the optimal MaxEnt model, the potential geographical distributions of P. hysterophorus were predicted based on screened species occurrences and environmental variables under the current and three future scenarios in the 2030s, 2050s, and 2070s (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5), and the invasion risk of P. hysterophorus in Chinese cities, croplands, forests, and grasslands was assessed. The results show that: (1) The species initially invaded highly suitable areas and further spread to regions with non-analogous climate conditions. (2) Under the current climatic conditions, the overall potential distribution of P. hysterophorus is characterized by more in the southeast and less in the northwest. Climate variables, including mean annual temperature (bio1), precipitation in the wettest month (bio13), isothermality (bio3), and temperature seasonality (bio4), are the primary factors influencing its distribution. (3) The potential distribution of P. hysterophorus will expand further under future climate scenarios, particularly toward higher latitudes. (4) Forests and crop lands are the areas with the most serious potential invasion risk of P. hysterophorus. Therefore, we suggest that the government should strengthen the monitoring and management of P. hysterophorus to prevent its spread and protect agro-ecosystems and human habitats. Depending on the potential risk areas, measures such as quarantine, removal, and publicity should be taken to mitigate the threat of P. hysterophorus invasion and to raise awareness of P. hysterophorus invasion prevention.

Unraveling the distribution pattern and driving forces of soil microorganisms under geographic barriers.

The Altai Mountains (ALE) and the Greater Khingan Mountains (GKM) in northern China are forest regions dominated by coniferous trees. These geographically isolated regions provide an ideal setting for studying microbial biogeographic patterns. In this study, we employed high-throughput techniques to obtain DNA sequences of soil myxomycetes, bacteria, and fungi and explored the mechanisms underlying the assembly of both local and cross-regional microbial communities in relation to environmental factors. Our investigation revealed that the environmental heterogeneity in ALE and GKM significantly affected the succession and assembly of soil bacterial communities at cross-regional scales. Specifically, the optimal environmental factors affecting bacterial Bray-Curtis similarity were elevation and temperature seasonality. The spatial factors and climate change impact on bacterial communities under the geographical barriers surpassed that of local soil microenvironments. The assembly pattern of bacterial communities transitions from local drift to cross-regional heterogeneous selection. Environmental factors had a relatively weak influence on myxomycetes and fungi. Both soil myxomycetes and fungi faced considerable dispersal limitation at local and cross-regional scales, ultimately leading to weak geographical distribution patterns.IMPORTANCEThe impact of environmental selection and dispersal on the soil microbial spatial distribution is a key concern in microbial biogeography, particularly in large-scale geographical patterns. However, our current understanding remains limited. Our study found that soil bacteria displayed a distinct cross-regional geographical distribution pattern, primarily influenced by environmental selection. Conversely, the cross-regional geographical distribution patterns of soil myxomycetes and fungi were relatively weak. Their composition exhibited a weak association with the environment at local and cross-regional scales, with assembly primarily driven by dispersal limitation.

Anticipating the potential distribution of Fasciola spp. in Gilan province of Iran: Insights from MaxEnt and climate change scenarios

Fasciolosis, a parasitic disease affecting humans and animals, is uniquely influenced by climatic and environmental factors. Gilan province in northern Iran is recognized as a high-endemic area for this parasite. This study aims to assess the prevalence of fasciolosis in Gilan province during the current period and forecast the distribution pattern of the parasite in future periods by analyzing climatic variables and identifying the most critical factors impacting Fasciola. To evaluate the present status of fasciolosis in Gilan, we collected 189 sheep fecal samples from different parts of the province and quantified eggs per gram of feces in each sample. Meteorological and environmental data were obtained and clipped to the study area. A total of 19 presence points were used to model the habitat suitability of Fasciola spp. through the maximum entropy (MaxEnt) algorithm, with jackknife analysis to determine variable importance. To project the potential distribution of Fasciola spp. in Gilan province under future scenarios, we employed MaxEnt using current (1970–2000) and projected climatic data based on three representative concentration pathway scenarios (RCP 2.6, RCP 4.5, and RCP 8.5) to predict habitat suitability in 2030, 2050, and 2070.The results of this study indicate the proportion of Fasciola spp. infection was highest in Talesh (46.37 %) and Langarud (45.7 %), while Rudsar (0 %) and Shaft (16.25 %) exhibited the lowest infection rates in Gilan province. MaxEnt modeling highlighted the significance of bioclimatic variables, particularly those associated with vegetation and temperature, such as temperature seasonality (Bio4) and normalized difference vegetation index (NDVI). The ecological niche modeling illustrated that the highest potential distribution for Fasciola in Gilan province is concentrated in the north-western and central regions, exhibiting an 80–100 % potential. However, projections for the future indicate a decrease to less than 20 % suitability for most of the province under all three scenarios until 2070. This study provides valuable insights into the dynamic relationship between climatic variables and Fasciola distribution, enabling better preparedness and control strategies for this trematode in Gilan province and other regions with similar climates.

Seasonal acclimation of photosynthetic thermal tolerances in six woody tropical species along a thermal gradient

Abstract Extreme heat events are becoming increasingly common, and the short‐term acclimation of photosynthesis will have a large impact on plant performance. Trees in lowland tropical forests, which are hypothesized to have limited abilities to tolerate rising temperatures, may need to rely on short‐term acclimation of their more plastic traits, like photosynthetic thermal tolerance, to persist in the face of increasingly variable climates. Here, we investigated seasonal acclimation of thermal tolerances in plant species of the moist Amazon. Specifically, we measured the photosynthetic thermal tolerances of six common woody Amazonian species at the beginning and at the end of the dry season to determine the species' abilities to acclimate to intra‐annual changes to climate. In addition, we used the natural thermal gradient present at our research site to test the acclimation of individual plants to maximum air temperatures not currently observed elsewhere in the moist lowland Amazon (up to ~43°C). Between seasons, there were significant overall increases in the thermal tolerances of three species (i.e. higher thermal tolerances in the hotter dry season), suggesting that leaf megathermy is prominent in these species. Also, three species acclimated their thermal tolerances to microsite‐level differences in seasonal temperature maxima, suggesting closer fidelity between leaf and air temperatures (i.e. limited homeothermy) for these species. Our results show that some woody species from the moist Amazon can acclimate their thermal tolerances over short time‐scales, although acclimation is likely insufficient to overcome thermal stress during extreme temperature events. Some species may therefore be more sensitive to heatwaves than others, which could impact survival and composition of tropical lowland forests into the future. Read the free Plain Language Summary for this article on the Journal blog.

Spatial pattern and ecological adaptation of heterostylous and homostylous species of Primula in China

Abstract Floral syndrome is one of the key components of plant pollination syndromes, affecting variety of evolutionary and ecological processes in angiosperms. The evolutionary transition from self-incompatible heterostyly to self-compatible homostyly occurred repeatedly in angiosperm families. Although the evolution of heterostyly and homostyly has been deeply studied, our understanding on their differences in ecological strategies is still lacking. In this work, using the floral syndrome and distributions of the Primula in China we compared the spatial pattern of floral syndrome frequency and its climatic determinants. Our results reveal that distylous and homostylous Primula have similar primary centers of species diversity in southwest China, while distylous species have larger range size than homostylous ones. Temperature seasonality is the dominant climate factor of these geographic patterns, but its effect is much stronger in distylous than in homostylous Primula. Distylous species have larger flower size and number, and fruit size than homostylous ones. Climate, especially temperature seasonality mainly influenced species range size via its effects on floral syndrome. Our study suggests that homostyly is likely derived from heterostylous ancestors in similar geographical context, and larger reproductive investment in floral phenotype may provide compensatory mechanisms for obligate out-breeding heterostyly. Future investigations regarding the evolutionary history and tolerance or resistance to environmental change between distyly and homostyly may greatly advance our understanding of their spatial pattern and adaptative differences.

Global Distribution Prediction of Cyrtotrachelus buqueti Guer (Coleoptera: Curculionidae) Insights from the Optimised MaxEnt Model.

Cyrtotrachelus buqueti Guer is a major pest affecting bamboo forests economically, causing significant damage to bamboo forests in Sichuan Province, China. To understand how C. buqueti responds to future climate conditions, an optimized Maximum Entropy Model (Maxent) was used to simulate the potential global distribution patterns of C. buqueti under current climate conditions and three different future climate scenarios and to analyze the dominant factors influencing its distribution. The results indicate that Bio18 (precipitation of the warmest quarter), Bio04 (temperature seasonality), Bio06 (minimum temperature of the coldest month), and Bio02 (mean diurnal temperature range) are the main environmental factors affecting the distribution of this species. The global area of high-suitability habitats for C. buqueti is 9.00 × 104 km2, primarily distributed in China. Under three different future climate scenarios, there are varying degrees of expansion in both the total suitable habitat and the medium-suitability areas for C. buqueti. Under the SSP5-8.5 scenario, the medium-suitability area of the species increases the most, reaching 9.83 × 104 km2. Additionally, these findings can serve as a reference for developing and implementing control strategies, assisting relevant authorities in more effectively managing and controlling this pest, and mitigating its potential threats to bamboo forest ecosystems and economies.

Thermal and morphometric correlates of the extremely low rate of energy use in a wild frugivorous primate, the Mayotte lemur

Primates spend on average half as much energy as other placental mammals while expressing a wide range of lifestyles. However, little is known about how primates adapt their rate of energy use in the context of natural environmental variations. Using doubly labelled water, behavioral and accelerometric methods, we measured the total energy expenditure (TEE) and body composition of a population of Eulemur fulvus (N = 12) living in an agroforest in Mayotte. We show that the TEE of this medium-sized cathemeral primate is one of the lowest recorded to date in eutherians. Regression models show that individual variation in the rate of energy use is predicted by fat-free mass, body size, thigh thickness and maximum temperature. TEE is positively correlated with increasing temperature, suggesting that thermoregulation is an important component of the energy budget of this frugivorous species. Mass-specific TEE is only 10% lower than that of a closely related species previously studied in a gallery forest, consistent with the assertion that TEE varies within narrow physiological limits. As lemur communities include many species with unique thermoregulatory adaptations, circadian and/or seasonal temperature variations may have constituted a major selective pressure on the evolution of lemur metabolic strategies.

Modeling the Impacts of Climate Change on Potential Distribution of Betula luminifera H. Winkler in China Using MaxEnt

Betula luminifera H. Winkler, a fast-growing broad-leaved tree species native to China’s subtropical regions, possesses significant ecological and economic value. The species’ adaptability and ornamental characteristics make it a crucial component of forest ecosystems. However, the impacts of global climate change on its geographical distribution are not well understood, necessitating research to predict its potential distribution shifts under future climate scenarios. Our aims were to forecast the impact of climate change on the potential suitable distribution of B. luminifera across China using the MaxEnt model, which is recognized for its high predictive accuracy and low sample data requirement. Geographical coordinate data of B. luminifera distribution points were collected from various databases and verified for redundancy. Nineteen bioclimatic variables were selected and screened for correlation to avoid overfitting in the model. The MaxEnt model was optimized using the ENMeval package, and the model accuracy was evaluated using the Akaike Information Criterion Correction (delta.AICc), Training Omission Rate (OR10), and Area Under the Curve (AUC). The potential distribution of B. luminifera was predicted under current and future climate scenarios based on the Shared Socio-economic Pathways (SSPs). The optimized MaxEnt model demonstrated high predictive accuracy with an AUC value of 0.9. The dominant environmental variables influencing the distribution of B. luminifera were annual precipitation, minimum temperature of the coldest month, and standard deviation of temperature seasonality. The potential suitable habitat area and its geographical location were predicted to change significantly under different future climate scenarios, with complex dynamics of habitat expansion and contraction. The distribution centroid of B. luminifera was also predicted to migrate, indicating a response to changing climatic conditions. Our findings underscore the importance of model optimization in enhancing predictive accuracy and provide valuable insights for the development of conservation strategies and forest management plans to address the challenges posed by climate change.

222 Validation of Brix for predicting sugar concentration of alfalfa and orchardgrass

Abstract The objective of this study was to evaluate the accuracy of Brix in predicting sugar concentrations in fresh alfalfa (Medicago sativa L.; ALF) and orchardgrass (Dactylis glomerata L.; OG) forages to be used as an inexpensive and rapid field-level assessment of relative energy in forages. In a 2-yr study, fresh forages samples from ALF and OG monoculture pastures in central Pennsylvania, U.S. were collected once monthly from May to September. Samples were immediately evaluated for Brix values with a hand-held digital refractometer, and the remaining biomass was frozen immediately with liquid N to halt cellular respiration. Samples were lyophilized and analyzed for individual sugars and wet chemistry nutritive analyses. Brix values were correlated with wet chemistry analyses using the PROC CORR procedure in SAS, with significance established at P &amp;lt; 0.05. Brix was positively correlated (P &amp;lt; 0.05) with total and individual sugars in ALF during late spring and late summer (0.49 to 0.93), but correlations were non-existent (P &amp;gt; 0.05) or negative (-0.55 to -0.73; P &amp;lt; 0.05) in mid-summer. Brix values had moderate to strong negative correlations (P &amp;lt; 0.05) to NDF and ADF in ALF (-0.57 to -0.71). Conversely, Brix values did not correlate (P &amp;gt; 0.05) to any notable sugar parameters in OG beyond the first sampling date (0.60 to 0.74; P &amp;lt; 0.05). Brix was not correlated (P &amp;gt; 0.05) to NDF and ADF in OG. In summary, Brix values did not consistently predict sugar concentrations in fresh ALF and OG forages. Because Brix measures dissolved solids in solution (not just sugars), Brix readings collected from crushed ALF or OG samples may be confounded by fibrous fractions found in the solution as well as decreased sugar concentrations compared with fruit crops. Brix accuracy may also be dependent on seasonal temperature patterns, plant growth stage, and daily weather patterns. Other solutions should be investigated that rapidly assess sugar profiles and nutritive values of fresh forages.