Length Of Season Research Articles

Comparative analysis of global urban land surface phenology between the MODIS and VIIRS products and extraction methods.

The reliability of land surface phenology (LSP) derived from satellite remote sensing is crucial for obtaining accurate estimates of the phenological response of vegetation to future climate change in urban ecosystems. Differences in phenological definition and extraction methodology using remote sensing can generate systemic errors in estimating the phenological temperature sensitivity to predict the biological response of vegetation. Here, we evaluated the start of the season (SOS), the end of the season (EOS), and the growing season length (GSL) between the Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Dynamics (MCD12Q2) and the Suomi National Polar-Orbiting Partnership NASA Visible Infrared Imaging Radiometer Suite (VIIRS) Land Cover Dynamics (VNP22Q2) over 1470 urban clusters worldwide. We found that the availability of valid phenological estimation in urban areas was low across climates, and cities without valid phenological data were mainly distributed in tropical and dry climate zones. The phenological comparison for each urban cluster worldwide revealed significant differences between the two products. For SOS, EOS, and GSL, only a small proportion of urban clusters (6.01%, 3.54%, and 1.50%, respectively) exhibited R2 surpassing 0.5, and approximately 31.63%, 37.37%, and 58.57% showed the RMSD values exceeding two weeks. These results remained consistent and robust across various climates, latitudinal gradients, and valid pixel proportions. We also revealed discrepancies in the inter-annual variability of LSP between the two products. These disparities in phenological metrics directly lead to systematic uncertainties in the measurements of temperature sensitivity. Furthermore, urban phenology disparities primarily arise from the different phenology definitions employed by the two products. Standardizing the definition of phenology metrics extraction from remote sensing data is crucial to the comprehensive understanding of phenological responses to urban environments, which thus provides referencing resources for studying how future environmental changes affect vegetation in natural ecosystems.

Climate variability impact on cotton production in North Cote d’Ivoire

In Cote d’Ivoire, cotton ranks third in exports after cocoa and coffee. Moreover, it constitutes a vital economic resource in Cote d’Ivoire savannah region. Due to climate variability, the cotton sowing period, from May 20 to June 20, is less and less respected. In this context, this study objective was to analyze, in conjunction with cotton production, the wet season length, from 1992-1995 to 2015-2018 in Korhogo region. So, stationarity tests were used as well as two climatographic types, rainfall, potential evapotranspiration (PLv-PET) and PET-Relative Humidity (ETP-RH), reinforced by means comparisons. For this purpose, data were collected from airports aeronautical operation and meteorological development company at Korhogo station. Overall, there was a non-significant downward trend in rainfall from 1990 to 2023. Looking deeply, this reduction trend was 58 days decrease (-27%) in wet season length on 2015-2018 period, compared to an average 214±16 days annual length on 1992-1995. In fact, the wet period has shrunk significantly, from 151±24 to 103±6 days (-32%). At the same time, there was no significant difference in active growing season duration, between periods 1992-1995 and 2015-2018, although 22 days decrease was observed. Indeed, despite the relatively short study's period length, there was shortening wet periods, combined with late rainy seasons start. Consequently, farmers sowed later. These conclusions lead to a suggestion of new cotton variety’s introduction with adapted cycle, as well as new agricultural practice initiations. These include forecasting sowing dates by area and adapting alternative cultivation techniques, which improve soil's useful water reserve.

Ecological and demographic drivers of kin-directed cooperation in a social bird: Insights from a long-term study.

The evolution of sociality is one of the major evolutionary transitions in the history of life and a key step in this transition is the occurrence of kin associations. Yet, the question of what demographic processes and environmental factors generate kin-structured populations and drive kin-directed cooperation remains open. In this review, we synthesise 30 years of studies of the long-tailed tit Aegithalos caudatus, which has a kin-selected cooperative breeding system with redirected help: failed breeders may help to raise offspring of conspecifics, typically relatives, breeding nearby. We describe the use of ecological, demographic, genetic and behavioural approaches to reveal: (a) how kin-structured populations (here 'kin neighbourhoods') arise; (b) why the prevalence of cooperation varies among populations and individuals; and (c) how variation in dispersal and opportunities for cooperation influence individual fitness. The kin neighbourhoods of long-tailed tits arise from three processes. First, natal dispersal is limited and sex-biased so many individuals, especially males, recruit as breeders close to their natal site. Second, neither dispersal nor migration necessarily disrupts kin associations because long-tailed tits often move with close relatives. Third, a small effective population size driven by high nest predation rates enhances within-population relatedness. Together, these processes set the scene for kin-directed helping behaviour by causing spatial clustering of relatives. The prevalence of cooperation within kin neighbourhoods depends on several factors, both at the population-level (annual nest predation rate and length of the breeding season) and individual-level (relatedness, familiarity, sex and condition). However, limited information on prior social association and the reliability of kin discrimination cues hampers our current understanding of individual helping decisions. Finally, variation in dispersal within and between sexes affects the probability of interacting with kin, the likelihood of cooperation, and accrual of the direct and indirect components of inclusive fitness. We use this comprehensive understanding of the factors driving cooperative behaviour in long-tailed tits to highlight gaps in knowledge and suggest future avenues for research in this system, and to make general inferences about the role of dispersal, demography and kinship in social evolution.

Detecting the Phenological Threshold to Assess the Grassland Restoration in the Nanling Mountain Area of China

The dynamics of vegetation changes and phenology serve as key indicators of interannual changes in vegetation productivity. Monitoring the changes in the Nanling grassland ecosystem using the remote sensing vegetation index is crucial for the rational development, utilization, and protection of these grassland resources. Grasslands in the hilly areas of southern China’s middle and low mountains have a high restoration efficiency due to the favorable combination of water and temperature conditions. However, the dynamic adaptation process of grassland restoration under the combined effects of climate change and human activities remains unclear. The aim of this study was to conduct continuous phenological monitoring of the Nanling grassland ecosystem, and evaluate its seasonal characteristics, trends, and the thresholds for grassland changes. The Normalized Difference Phenology Index (NDPI) values of Nanling Mountains’ grasslands from 2000 to 2021 was calculated using MOD09A1 images from the Google Earth Engine (GEE) platform. The Savitzky–Golay filter and Mann–Kendall test were applied for time series smoothing and trend analysis, and growing seasons were extracted annually using Seasonal Trend Decomposition and LOESS. A segmented regression method was then employed to detect the thresholds for grassland ecosystem restoration based on phenology and grassland cover percentage. The results showed that (1) the NDPI values increased significantly (p < 0.01) across all grassland patches, particularly in the southeast, with a notable rise from 2010 to 2014, and following an eastern to western to central trend mutation sequence. (2) the annual lower and upper NDPI thresholds of the grasslands were 0.005~0.167 and 0.572~0.727, which mainly occurred in January–March and June–September, respectively. (3) Most of the time series in the same periods showed increasing trends, with the growing season length varying from 188 to 247 days. (4) The overall potential productivity of the Nanling grassland improved. (5) The restoration of the mountain grasslands was significantly associated with the grassland coverage and mean NDPI values, with a key threshold identified at a mean NDPI value of 0.5 for 2.1% grassland coverage. This study indicates that to ensure the sustainable development and conservation of grassland ecosystems, targeted management strategies should be implemented, particularly in regions where human factors significantly influence grassland productivity fluctuations.

From Mountains to Basins: Asymmetric Ecosystem Vulnerability and Adaptation to Extreme Climate Events in Southwestern China

The increasing frequency of both singular and compound extreme climate events driven by global warming has profoundly impacted terrestrial ecosystems. Using machine learning-based Random Forest algorithms and moving correlation analysis, this study quantifies the impacts of extreme climate indices (ECIs) on two ecological indicators (EIs), the NDVI and GPP, from 1982 to 2019. The results reveal that singular extreme climate events exert a more pronounced influence on ecosystems across Southwestern China (SWC) than compound ones. Specifically, the NDVI and GPP exhibited strong correlations with summer days (SU) and diurnal temperature range (DTR), with SU contributing positively (weight = 0.275 for the GPP and 0.238 for the NDVI) and DTR negatively (weight = 0.107 for the GPP and 0.130 for the NDVI). Regional analyses highlighted distinct spatial patterns: in mid–high-altitude areas (>1 km), including the Hengduan Mountains (HDMs) and Yunnan–Guizhou Plateau (YGP), extreme temperatures and precipitation significantly promoted vegetation growth, with rainfall day index (RDI), frost days (FD), extreme temperature index (ETI), SU, and DTR all having a strong influence (>0.1) on the GPP and NDVI. These areas showed strong adaptability to extreme climate, benefiting overall vegetation health. In contrast, ecosystems in low-altitude areas (<1 km) showed more variable responses. The Guangxi Basin (GXB) exhibited strong resistance to ECIs, with vegetation being almost unaffected by extreme precipitation and benefiting from continuous warming. Only consecutive wet days (CWD) and FD were significantly negatively correlated with EIs (p < 0.05), and their correlation weights were low (weights = 0.043 and 0.013). However, the vegetation in the Sichuan Basin (SCB) is more susceptible to climate extremes, which have particularly strong effects on the NDVI. SU, tropical nights (TR), ETI, and growing season length (GSL), which have positive effects on EIs in mid–high-altitude areas, show extremely significant negative correlations in the SCB (p < 0.001), and their weights account for one-third of the total (weights = 0.15, 0.11, 0.061 and 0.012, respectively). These findings underscore the heterogeneous responses of ecosystems to ECIs and emphasize the need for region-specific strategies in ecosystem management and disaster prevention amid climate change.

Reconstruction of drought and long-rain chronologies since the 17th century in central Japan using intra-annual tree-ring oxygen isotope ratios and documentary records

Abstract. Oxygen isotope ratios (δ18O) of tree-ring cellulose and historical documentary records are widely used to explore the hydroclimatic conditions of the past. In this study, we attempted to reconstruct chronologies of local climate disasters spanning 4 centuries in central Japan using these proxy data. For tree-ring δ18O measurements, we prepared cellulose samples from a long-living cedar tree with continuously broad ring widths. To enhance the temporal resolution, we divided each annual ring into several (mainly six) segments. Analysis of the correlations with observed relative humidity and precipitation data revealed that the intra-ring δ18O variations in the sample tree reflected the hydroclimatic conditions from April to July in each year. Subsequently, we chronologically listed the occurrence of eight types of disasters in the 17th to 19th centuries in the area adjacent to the sample tree according to 20 titles of “Town/City history”, which is a compilation of historical documentary records from the local municipality. By comparison with the intra-ring δ18O data, we found that most of the major droughts and long rains recorded in the historical documents occurred in the Baiu rainy season (typically June–July) or pre-Baiu season, corresponding to the growing season of the sample tree. Based on an analysis of the intra-ring δ18O variation for documentary-based drought and long-rain years, we set thresholds of intra-ring δ18O values to identify and extract drought and long-rain years. Drought and long-rain chronologies obtained by applying these thresholds were temporally continuous, complementing those based on documentary records. They depicted the relationships between the frequency of these climate disasters and the occurrence of major famines and the long-term tendency of length and magnitude of the Baiu rainy season in historical times.

How Do Changes in Grassland Phenology and Its Responses to Extreme Climatic Events in Central Asia?

Extreme climate events have become more frequent under global warming, significantly affecting vegetation phenology and carbon cycles in Central Asia. However, the mediating effects of intensity of compound drought and heat events (CDHEs) and compound moisture and heat events (CMHEs) on grassland phenology and their trends in the relative contributions to grassland phenology over time have remained unclear. Based on the calculation results of grassland phenology and compound events (CEs), this study used trend analysis, partial least squares regression structural equation modeling (PLS-SEM), and ridge regression analysis to investigate the mediating effect and the temporal trend in relative contribution of CEs to grassland phenology in Central Asia, and the magnitude of sensitivity of grassland phenology to CEs. This study revealed that the start of season (SOS) was advanced by 0.4 d·a−1, end of season (EOS) was delayed by 0.5 d·a−1, and length of season (LOS) extended by 0.8 d·a−1 in 1982–2022. The duration of the CDHEs (0−37 days) was greater than that of the CMHEs (0−9 days) in Central Asia. The direct effects of CDHEs and CMHEs on grassland phenology were generally negative, except for the direct positive effect of CDHEs on LOS. The indirect effects of temperature and precipitation on grassland phenology through CDHEs and CMHEs were greater than their direct effects on phenology. The relative contribution of CDHEs to grassland phenology was consistently greater than that of CMHEs, and both the relative contribution curves showed a significant upward trend. The sensitivity of grassland phenology to CDHEs was higher than its sensitivity to CMHEs at 0.79 (SOS), 1.18 (EOS), and 0.72 (LOS). Our results emphasize the mediating effects of CDHEs and CMHEs on grassland phenology. Under the influence of CDHEs and CMHEs, the LOS will further lengthen in the future.

Mercury exposure in an endangered songbird: influence of marsh hydrology and evidence for early breeding impairment.

Songbird reproductive success can decline from consuming mercury-contaminated aquatic insects, but assessments of hydrologic conditions influencing songbird mercury exposure are lacking. We monitored breast feather total mercury (THg) concentrations and reproductive success in the U.S. federally listed endangered Cape Sable Seaside Sparrow (CSSS: Ammospiza maritima mirabilis) over three breeding seasons in the Florida Everglades. We used model comparison to explore the influence of annual hydrologic variation on adult CSSS THg concentrations, and tested mercury effects on individual reproductive success (individuals' mate status, apparent nest success, and total productivity) that were scaled to estimates on population productivity using a demographic model. We identified four hydrologic models that explained annual variation in adult THg concentrations, with the top model showing a negative association between THg concentrations and drought length of the previous breeding season and a positive association between THg concentrations and dry-season water recession rate (model adjusted R2 = 0.82). Adult male mating probability declined by 63% across the range of THg concentrations observed. We found no mercury effect on CSSS nest success or total productivity. However, demographic modeling suggested the reduced mating could produce a 60% decrease in population productivity compared to a scenario with no THg impact. Our results suggest that CSSS mercury exposure is influenced by local hydrologic conditions that can increase early breeding failure (lack of breeding initiation) and potentially limit population productivity. This study is the first to describe CSSS mercury exposure and its potential reproductive costs at the individual and population levels.

Wild Boar Attacks on Hunting Dogs in Czechia: The Length of the Hunting Season Matters.

Hunting dogs are exposed to the risk of injury in driven hunts, an often-used method for managing growing wild boar numbers. This study investigated the impact of increased hunting pressure-both across the hunting season and within individual hunting events-on the risk of wild boar attacks on hunting dogs, i.e., the length of the hunting season (2.68 ± 0.76 months, mean ± standard deviation), the number of driven hunts per season (3.99 ± 0.43), the intervals between hunts (17.85 ± 4.83 days), the number of wild boars harvested per season (14.46 ± 13.10), and the number of participants (23.8 ± 10.69) and dogs (4.56 ± 2.66) involved per hunt. The data were collected via a retrospective questionnaire survey. The information-theoretic approach (IT-AIC) and GLMM were employed to estimate the factors' effects on the number of wild boar attacks on dogs reported in 40 hunting grounds in five consecutive hunting seasons (2.60 ± 5.07 attacks per hunting season in a hunting ground). The number of attacks only increased with the length of the hunting season. The best model did not include other factors, such as shorter intervals between hunts, a higher number of driven hunts, wild boars harvested, or participants. The respondents reported 150 injuries by wild boars during 797 driven hunts. Most injuries were mild (73.8%), with fewer severe (18.8%) and fatal (7.4%) cases. Further investigation into wild boar and hunting dog interactions is necessary for constructing strategies to improve hunting practices and reduce dog injury risks.

Spatial clustering of seasonal sea ice of Hudson Bay, Canada, 1971–2018

ABSTRACT The spatial variation in seasonal sea ice in Hudson Bay is examined using spatial clustering analyses. For the period 1971 to 2018, a time series of sea-ice breakup and freeze-up dates and ice-free season length at thirty-six grid locations is generated from sea-ice charts derived from satellites and other data. These data are analyzed spatially using three different clustering techniques. Overall, the three methods revealed a northeast/southwest axis in sea-ice behavior consistent with a well-documented cyclonic current flow and wind regime in Hudson Bay. The methods did differ in assigning grid locations to clusters with the greatest consistency for breakup behavior and in the northern region of the Bay across all three metrics. The greatest variability occurred with the central sea-ice platform likely the response to only subtle variations among these locations, leading to varying clusters. Missing data especially with freeze-up and ice-free season played a role in the clustering.

Shifting in Rainy Season Features in the Mekong Delta under the Background of Global Climate Change

Background: Shifting in the rainy season features (RSFs) have caused impishly cultivation activities around the world, especially under the impacts of enhancing climate change. In the Mekong Delta, rainfall is a crucial factor that determines crop sowing and harvesting dates. Methods: This study investigated the RSFs, including the rainy season onset date (RSOD), cessation date (RSCD) and length (LRS), in the Mekong Delta from 1995 to 2022. The study aimed to understand the spatial and temporal variability of the rainfall features and their implications across the Mekong Delta. The study utilized rainfall data at gauge stations across the Mekong Delta, covering a period of 30 years. The study employed descriptive statistical methods to analyze the RSFs, including RSOD, RSCD and LRS. Result: The results revealed the spatial and temporal variability of RSFs across the study area. The analysis of RSOD, RSCDand LRS revealed consistent patterns. However, the SD and CV values suggested moderate variability in these features, indicating the need for further investigation into the factors influencing these variations. The findings highlight the importance of considering RSFs for effective rain-fed resource management and planning in the Mekong Delta.

Quantifying phenotypic and genetic variation for cow fertility phenotypes in American Simmental using total herd reporting data.

Reproduction plays a major role in the production efficiency of livestock species. However, cow-centric reproductive traits tend to be lowly heritable and are not expressed until later in an animal's lifetime, making phenotypic selection alone inefficient at generating genetic gain. Genetic progress can be accelerated by focusing selection on the predicted genetic component of reproductive traits using Expected Progeny Differences (EPDs). We used the American Simmental Association's performance and Total Herd Enrollment data, made up of 533,155 calving records from 303,158 females (132,403 cows and 170,755 heifers), 33,732 of which are genotyped, to explore three continuous and two discrete phenotypes focused on quantifying early and sustained fertility in beef cows. We analyzed calving date (cow's calving date relative to the start of the calving season), calving interval (days between calves), first calving interval (calving interval observation between the first and second calving record for a female), heifer pregnancy (did the animal calve as 2-year-old), and discrete early calving (did animal calve in the first 30 days of the calving season) as distinct, but correlated measures of fertility. This dataset provides insight into population-wide trends related to cow attrition, calving season lengths, and phenotypic variation in fertility. We used pedigree and genomic REML to estimate these six phenotypes' genetic, permanent environment, and temporary environmental variance components. Pedigree estimated heritabilities were 0.06 (±0.000011) for calving date, (0.04 ±0.000005) for calving interval, 0.07 (±0.000016) for discrete early calving, 0.05 ±0.000041 for first calving interval, and 0.23 (±0.000099) for heifer pregnancy, consistent with other fertility traits across beef and dairy cattle. The incorporation of genomics increased the heritability estimate for heifer pregnancy (0.24 ±0.000098) and decreased the estimate for first calving interval (0.04 ±0.000029). Positive phenotypic and genetic correlations were found among these phenotypes (rG = 0.01-0.96). These results call for further work in optimizing genetic predictions and exploration of the genetic architecture through genome-wide studies. Whole herd reporting date frameworks represent opportunities for measuring new reproductive phenotypes, but their utility in genetic evaluations will rely on novel trait initiatives and consistent recording that captures more detailed data.

Changes in high-latitude surface energy balance driven by snowpack and vegetation dynamics under warmer climate

Abstract With rapid climate warming, expected changes in snowpack and vegetation will alter the seasonal surface albedo of high-latitude ecosystems. The extent to which these albedo changes may affect surface energy balances and thus soil temperatures is uncertain, but represents a potentially important component of ecosystem feedbacks to climate change. Here, we apply a well-tested process-rich ecosystem model, ecosys, to examine changes in seasonal surface albedo and soil temperature driven by climate-induced snowpack and vegetation changes across Alaska under a warmer twenty-first century climate. Under the Representative Concentration Pathway 8.5 climate change scenario, the modeled changes in surface albedo exhibited large seasonal and spatial variations. We found spring albedo decreases driven by increases in snow-free periods (>20 d) and an extended growing season length that resulted in greater gains in leaf area index (LAI) in most parts of Alaska. In contrast, we modeled increases in summer and winter albedo (despite modeled increases in LAI) across much of the boreal forest due to an increased proportion of aspen, which has a higher leaf albedo than the currently dominant black spruce. Modeled latent heat fluxes generally increase across the twenty-first century, particularly during the spring and summer. Overall, climate warming and changes in surface energy fluxes resulted in a 3.5 ± 0.50 °C increase in spatial- and annual-averaged top 10 cm surface soil temperatures across Alaskan ecosystems by the year 2100, with larger increases in tundra than boreal forest regions. We conclude that under warmer climates, seasonal variations in albedo and surface energy fluxes are particularly pronounced during the spring and summer, driven by changes in snowpack and vegetation dynamics.

Mapping wildfires in Canada with Landsat MSS to extend the National Burned Area Composite (NBAC) time series back to 1972

Background Satellite imaging has improved burned area mapping; however, few studies have taken advantage of the Multi-Spectral Scanner (MSS) in early Landsat satellites, which started acquiring data 10 years earlier than Thematic Mapper (TM). Aims To expand Canada’s National Burned Area Composite (NBAC) annual time series back to 1972 using MSS data and report annual statistics and national trends for 1972–2022. Methods Pre- and post-fire image composites were created using an improved collection of MSS data available from the Google Earth Engine. A Normalized Difference Vegetation Index (NDVI) difference image was adaptively thresholded to extract burned areas, which were then vectorised. To assess accuracy, MSS fire polygons were compared with TM in a year of overlap. Key results Compared with TM, MSS polygons overestimated burned area by 5.6% when the relativised differenced NDVI was used, with significant upward trends for number of fires > 200 ha, fire season length and mean duration of fires. Conclusions MSS is a valuable data source for retrospective mapping of boreal and temperate forest fires where data from finer-resolution sensors are lacking. Implications After the addition of MSS-mapped fires, NBAC is the longest satellite-based time series of annual burned area from individually mapped fires in the world.

Lengthening Atlantic Hurricane Seasons with Earlier Storm Formation Dates Including Implications from 2020

Abstract This paper analyzes the formation dates of the nth storm in a sequence for all named North Atlantic tropical cyclones (TCs) and assesses whether the intraseasonal length of the Atlantic hurricane season has changed temporally. The record-breaking 2020 season, with 30 named storms, set records for the earliest third TC formation (Cristobal) and from the sixth TC (Fay) onward. Analysis of season length from 1851 to 2022 identifies only one statistically significant breakpoint detected in the early 1970s, roughly coinciding with the introduction of satellite observations. Since 1970, we also find a trend toward longer North Atlantic hurricane seasons. The 1971–2022 trend is robust and statistically significant, whether assessed as the number of days between the first and last storm or by the distance between intermediate percentiles (e.g., 10th–90th and 15th–85th). These increases are mainly associated with storms forming earlier in the calendar year and are best described as an upward trend rather than a stepwise shift between eras. Although a simple trend fits better than a stepwise model, improvement falls short of significance, so we do not formally reject the stepwise hypothesis. If, following this hypothesis, the 1950–2022 period is segmented into a high-activity era (HAE1; 1950–69), a low-activity era (LAE; 1970–94), and second high-activity era (HAE2; 1995–2022), the median season length of HAE2 is 12 days longer than in the first HAE, but this difference is not statistically significant (p = 0.58) and could be explained by the substantial difference in the observational network. The median season length in both HAE1 and HAE2 are significantly longer (by 36 and 48 days, respectively) than the intervening LAE.

Evaluation of Summer Season Characteristics and Its Changes in Iraq over the Period (1960-2021)

Anthropogenic climate change has essentially affected the characteristics of the thermal seasons, hence the overall ecosystems, and human health. The characteristics of the thermal seasons in Iraq, and how they change are still unclear. This research has been conducted to: (1) evaluate the spatial characteristics of summer season in Iraq over the period (1960-2021). (2) Estimating changes in the length and timing (onset and end) of summer in Iraq using the Mann-Kendall test (MK) and Sen's slope estimator. The findings indicated that there are significant spatial differences in the average length of the summer season in Iraq. The difference reaching more than 30 days between northern and southern Iraq, It is longer in the south. Results of trend analysis showed that summer season length significantly increases by 3.33 and 6.67 days/decade respectively. Our results reveal that, all over Iraq, the onset of thermal summer season occurs earlier by more than 17 days during (1960-2021). The biggest statistically significant changes in summer advancing were observed in northern and western Iraq. However, the results revealed that the only western Iraq has been recorded advancing at the end of the summer, while the end of the summer at all other parts occurred later.

ГЕНЕТИЧЕСКИЕ РЕСУРСЫ RIBES NIGRUM L. IN SITU и EX SITU В РЕСПУБЛИКЕ БАШКОРТОСТАН

The article presents the results of the evaluation of the Ribes nigrum L. collection at the "Kushnarenkovsky Breeding Center for Fruit and Berry Crops and Grapes" in the Republic of Bashkortostan (RB). The collection includes 24 varieties, 57 hybrids, 62 seedlings of domestic breeding, and 3 wild forms of R. nigrum. The study objects were varieties of R. nigrum bred by the Bashkir Research Institute of Agriculture: Belskaya, Bobrovaya, Valovaya, Iremel, Karaidel, Kushnarenkovskaya, Truzhenitsa, Estafeta, and varieties from other regions of the Russian Federation: Gracia, Chudnoye Mgnovenie, Ocharovanie, Kipiana, Iskushenie, Maly Princ, Tamerlan, Sensei, Pigmei, Suiga, Tikzo, Nilga, Sobolinka. It has been shown that under changing climatic conditions, the Valovaya, Iremel, and Truzhenitsa varieties maintain their berry ripening phenorhythms. The growing season length of R. nigrum varieties in the Republic of Bashkortostan for the period 2015–2023 averaged 188±4.2 days. High adaptation to changing climatic conditions was demonstrated by the Bobrovaya, Iremel, Karaidel, and Kushnarenkovskaya varieties, which possess strong frost and drought resistance. The Valovaya variety has been identified as a reliable source of large-fruit traits. Large-fruited varieties also include Belskaya, Truzhenitsa, and Iremel, with an average berry weight of 2.3 g or more. High yields were observed in the Belskaya (133 c/ha), Iremel (133 c/ha), and Truzhenitsa (148.3 c/ha) varieties. High ascorbic acid content was noted in the Chishma (179.8±17.6 mg/%), Karaidel (151.8±11.3 mg/%), and Iremel (150.1±10.4 mg/%) varieties. The maximum sugar content (13.3%) was recorded in the Estafeta variety in 2012, and a high level of ascorbic acid (340.0 mg/100 g) was noted in the Karaidel variety in 2023. Clonal micropropagation protocols have been developed for the Karaidel, Chishma, and Seyanets Golubki varieties. The rehabilitated R. nigrum regenerants grown under ex vitro conditions retain varietal traits, phenorhythms, and show high productivity. In RB, R. rubrum L. and R. nigrum are found in natural habitats. The latter is widely distributed across 25 administrative districts, in three botanical- geographical zones, which may be of interest for breeding work.

Effects of heat, elevated vapor pressure deficits and growing season length on growth trends of European beech

In recent decades, continued growth decline has been observed in various beech forest regions of Central and Western Europe, especially in the warmer lowlands, which is not necessarily linked to increased mortality. While earlier dendrochronological studies have shown that a deteriorating climatic water balance in the course of climate warming can drive negative growth trends, less is known about the effects of climatic extremes on tree growth, notably heat and rising atmospheric vapor pressure deficits (VPD). Through climate-growth analysis, we analyzed the influence of summer heat duration (frequency of hot days with Tmax > 30°C) and elevated VPD on the basal area increment (BAI) of dominant beech trees in 30 stands across a precipitation gradient in the northern German lowlands. Summer heat (especially in June) and elevated VPD are reducing BAI in a similar manner as does a deteriorated climatic water balance. While growing season length (GSL), derived from thermal thresholds of growth activity, has substantially increased since 1980, BAI has declined in the majority of stands, demonstrating a recent decoupling of tree productivity from GSL. We conclude that heat and elevated VPD most likely are important drivers of the recent beech growth decline in this region, while growing season length has lost its indicative value of beech productivity.

Effects of Porcine Zona Pellucida Immunocontraception on Mare Body Condition and Foaling Season Length in Two Western Wild Horse Populations.

Wildlife managers and the public have expressed considerable interest in the use of contraception to help manage the populations of wild horses and burros (Equus caballus and E. asinus). Field testing has shown that two preparations of the porcine zona pellucida (PZP) vaccine, a simple emulsion (ZonaStat-H) and PZP-22 (which supplements ZonaStat-H with a controlled-release component) effectively prevent pregnancy in individual mares and can substantially reduce population foaling rates. To determine whether some PZP preparations might have secondary effects that harm treated mares or their foals, we examined the effects of PZP-22 vaccinations and the follow-up boosters of either PZP-22 or ZonaStat-H on adult female body condition, foaling season, and foal mortality in two wild horse herds in the western USA, Cedar Mountains Herd Management Area, Utah (CM; 2008-2015), and Sand Wash Basin Herd Management Area, Colorado (SWB; 2008-2014). At both sites in every study year, summer body condition scores improved faster in mares without foals than mares with foals (p < 0.001; CM, n = 234; SWB, n = 172), but PZP treatments did not affect mare body condition apart from their contraceptive effects. Births to mares treated with PZP within the previous three years were delayed and spread out over the foaling season, but foal mortality rates through the first and second year were low, unrelated to date of birth, and virtually identical for the foals of PZP-treated and untreated mothers (all comparisons n.s.; CM, n = 775, SWB, n = 640). Thus, in these two populations, we found no evidence that changes in reproductive timing associated with PZP treatments were harmful to either mares or foals.

Trends and Variability in annual and seasonal rainfall amount and timing in Wereilu district, Northeastern Highlands of Ethiopia

Studying climate change can significantly benefit agricultural practices in a country where many people rely heavily on subsistence farming. To this end, this study aimed to examine trends and variability in rainfall amounts and timing in the climate-vulnerable Wereilu district, northeastern highlands of Ethiopia. The coefficient of variation and standardized rainfall anomaly were employed to analyse rainfall variability, while the Innovative Trend Analysis (ITA) was applied to examine rainfall trends. The findings revealed that Kiremt (main rainy season) exhibited moderate variability, whereas Belg (small rainy season) exhibited high variability. The trend analysis showed significant changes in both seasonal and annual rainfall amounts and their timing. Annual and Kiremt rainfall significantly increased at Wereilu by 55.5 mm and 88.7 mm per decade, respectively, and at Kabie by 16.6 mm and 48.4 mm per decade (p < 0.01). In contrast, Belg rainfall revealed a significant declining trend at both sites. The graphical trend analysis revealed a positive trend for all clusters during Kiremt. In contrast, Belg showed a declining trend across all clusters, with a more pronounced decline in higher values at both sites. Rainfall onset dates significantly shifted towards earlier onset, while rainfall cessation dates showed insignificant late cessation. The length of the rainy season exhibited a positive trend (p < 0.01) at Wereilu and (p < 0.05) at Kabie. Overall, the observed substantial changes in rainfall amounts and timing imply the need for relevant adaptation measures, particularly in the farming system and water sector.