Loss, resilience and recovery of kelp forests in a region of rapid ocean warming.

BACKGROUND AND AIMS: Changes in kelp abundances on regional scales have been highly variable over the past half-century owing to strong effects of local and regional drivers. Here, we assess patterns and dominant environmental variables causing spatial and interspecific variability in kelp persistence and resilience to change in Nova Scotia over the past 40 years. METHODS: We conducted a survey of macrophyte abundance at 251 sites spanning the Atlantic coast of Nova Scotia from 2019 to 2022. We use this dataset to describe spatial variability in kelp species abundances, compare species occurrences to surveys conducted in 1982 and assess changes in kelp abundance over the past 22 years. We then relate spatial and temporal patterns in abundance and resilience to environmental metrics. KEY RESULTS: Our results show losses of sea urchins and the cold-tolerant kelp species Alaria esculenta, Saccorhiza dermatodea and Agarum clathratum in Nova Scotia since 1982 in favour of the more warm-tolerant kelps Saccharina latissima and Laminaria digitata. Kelp abundances have increased slightly since 2000, and Saccharina latissima and L. digitata are widely abundant in the region today. The highest kelp cover occurs on wave-exposed shores and at sites where temperatures have remained below thresholds for growth (21 °C) and mortality (23 °C). Moreover, kelp has recovered from turf dominance following losses at some sites during a warm period from 2010 to 2012. CONCLUSIONS: Our results indicate that dramatic changes in kelp community composition and a loss of sea urchin herbivory as a dominant driver of change in the system have occurred in Nova Scotia over the past 40 years. However, a broad-scale shift to turf-dominance has not occurred, as predicted, and our results suggest that resilience and persistence are still a feature of kelp forests in the region despite rapid warming over the past several decades.

Estimates of Crop Yield Anomalies for 2022 in Ukraine Based on Copernicus Sentinel-1, Sentinel-3 Satellite Data, and ERA-5 Agrometeorological Indicators.

The study explores the feasibility of adapting the EOStat crop monitoring system, originally designed for monitoring crop growth conditions in Poland, to fulfill the requirements of a similar system in Ukraine. The system utilizes satellite data and agrometeorological information provided by the Copernicus program, which offers these resources free of charge. To predict crop yields, the system uses several factors, such as vegetation condition indices obtained from Sentinel-3 Ocean and Land Color Instrument (OLCI) optical and Sea and Land Surface Temperature Radiometer (SLSTR). It also incorporates climate information, including air temperature, total precipitation, surface radiation, and soil moisture. To identify the best predictors for each administrative unit, the study utilizes a recursive feature elimination method and employs the Extreme Gradient Boosting regressor, a machine learning algorithm, to forecast crop yields. The analysis indicates a noticeable decrease in crop losses in 2022 in certain regions of Ukraine, compared to the previous year (2021) and the 5-year average (2017-2021), specifically for winter crops and maize. Considering the reduction in yield, it is estimated that the decline in production of winter crops in 2022 was up to 20%, while for maize, it was up to 50% compared to the decline in production.

Global warming is projected to lead to increased freshwater growth potential and changes in pace of life in Atlantic salmon Salmo salar.

Global warming has been implicated in widespread demographic changes in Atlantic salmon Salmo salar populations, but projections of life-history responses to future climate change are lacking. Here, we first exploit multiple decades of climate and biological data from the Burrishoole catchment in the west of Ireland to model statistical relationships between atmospheric variables, water temperature, and freshwater growth of juvenile Atlantic salmon. We then use this information to project potential changes in juvenile growth and life-history scheduling under three shared socioeconomic pathway and representative concentration pathway scenarios from 1961 to 2100, based on an ensemble of five climate models. Historical water temperatures were well predicted with a recurrent neural network, using observation-based atmospheric forcing data. Length-at-age was in turn also well predicted by cumulative growing degree days calculated from these water temperatures. Most juveniles in the Burrishoole population migrated to sea as 2-year-old smolts, but our future projections indicate that the system should start producing a greater proportion of 1-year-old smolts, as increasingly more juveniles cross a size-based threshold in their first summer for smoltification the following spring. Those failing to cross the size-based threshold will instead become 2-year-old smolts, but at a larger length relative to 2-year-old smolts observed currently, owing to greater overall freshwater growth opportunity. These changes in age- and size-at-seaward migration could have cascading effects on age- and size-at-maturity and reproductive output. Consequently, the seemingly small changes that our results demonstrate have the potential to cause significant shifts in population dynamics over the full life cycle. This workflow is highly applicable across the range of the Atlantic salmon, as well as to other anadromous species, as it uses openly accessible climate data and a length-at-age model with minimal input requirements, fostering improved general understanding of phenotypic and demographic responses to climate change and management implications.

Assessing temperature-based adaptation limits to climate change of temperate perennial fruit crops.

Temperate perennial fruit and nut trees play varying roles in world food diversity-providing edible oils and micronutrient, energy, and protein dense foods. In addition, perennials reuse significant amounts of biomass each year providing a unique resilience. But they also have a unique sensitivity to seasonal temperatures, requiring a period of dormancy for successful growing season production. This paper takes a global view of five temperate tree fruit crops-apples, cherries, almonds, olives, and grapes-and assesses the effects of future temperature changes on thermal suitability. It uses climate data from five earth system models for two CMIP6 climate scenarios and temperature-related indices of stress to indicate potential future areas where crops cannot be grown and highlight potential new suitable regions. The loss of currently suitable areas and new additions in new locations varies by scenario. In the southern hemisphere (SH), end-century (2081-2100) suitable areas under the SSP 5-8.5 scenario decline by more than 40% compared to a recent historical period (1991-2010). In the northern hemisphere (NH) suitability increases by 20% to almost 60%. With SSP1-2.6, however, the changes are much smaller with SH area declining by about 25% and NH increasing by about 10%. The results suggest substantial restructuring of global production for these crops. Essentially, climate change shifts temperature-suitable locations toward higher latitudes. In the SH, most of the historically suitable areas were already at the southern end of the landmass limiting opportunities for adaptation. If breeding efforts can bring chilling requirements for the major cultivars closer to that currently seen in some cultivars, suitable areas at the end of the century are greater, but higher summer temperatures offset the extent. The high value of fruit crops provides adaptation opportunities such as cultivar selection, canopy cooling using sprinklers, shade netting, and precision irrigation.

Seasonal variability in the effect of temperature on key phenological stages of four table grapes cultivars.

Progressive warming of the grape growing regions has reduced the land capability for sustainable grapevine production and the geographical distribution of grapes. Bud burst, blooming, berry set, veraison, and harvest are the key phenological stages of grapevine, and are crucial for managing vineyard activities. The objective of this study was to evaluate the effect of seasonal temperature variability on the timing of key phenological stages of table grape cultivars in a new emerging viticulture region, i.e., the Pothwar region of Pakistan. Phenological stages of four table grape cultivars were recorded during two consecutive growing seasons at two locations. All phenological stages were attained earlier for the relatively warmer location, i.e., Chakwal. Similarly, the length of the growing season from bud burst to harvest was 15 to 21 days longer for the 2020 growing season than for the 2019 growing season, which corresponds to the inter-annual temperature variability. Moreover, the grapevine cultivars showed a distinct response for each growth phase; cv. Perlette matured earlier while cv. NARC Black was the last to ripen. Despite the large variability in the length of the active growing period from bud burst to harvest, accumulated growing degree days (GDD) varied only in a narrow range, i.e., 1510-1557 for cv. Perlette, 1641-1683 for cv. King's Ruby, 1744-1770 for cv. Sugraone, and 1869-1906 for cv. NARC Black. This implies that seasonal temperature variability using GDD is a better indicator for the phenology of table grape cultivars compared to regular time. It is clear from the results from this study that the variation in phenological responses of table grape cultivars due to temperature differences necessitates genotype and site-specific vineyard management.

Reproductive phenology and behaviour of endangered redside dace (Clinostomus elongatus) in urban streams.

Investigation of the reproductive phenology and spawning behaviour of imperilled species in relation to environmental variability is needed to understand a critical component of species life history. In this study, we used redside dace (Clinostomus elongatus), a freshwater leuciscid listed as Endangered under Canada's Species at Risk Act, to model spawning phenology and make predictions about spawning initiation using historical and climate change projected thermal cues (measured as cumulative growing degree days), and provide an ethological description of spawning behaviour. Logistic regression models applied to 4 years of average daily stream water temperature data and field behavioural observations of the onset of spawning activity indicated a 50% probability of spawning initiation when cumulative growing degree days reached 214°C days and a 95% probability of spawning initiation at 288°C days. Using two climate change scenarios (i.e., a mid-century 1.6°C increase and an end of century 3.6°C increase), spawning initiation was predicted to advance 3 days by the year 2050 and 7 days by the year 2100. Underwater video cameras placed at two sites within an urban stream captured 73 unique spawning events revealing that redside dace spawn in pairs as well as in dense, tightly packed groups (more than 20 individuals). Moreover, there is evidence of redside dace having a polygynandrous mating system, as female redside dace spawned with multiple males in 45.2% of the total spawning events recorded. Taken together, this study provides important insights into redside dace spawning initiation and behaviour, key life-history traits having conservation implications for future reproductive success and, ultimately, population dynamics.

Multi-criteria decision analysis integrated with GIS to determine land suitability for cultivation and best harvest time of vine.

BACKGROUND: In this study, the quality of land suitability for vine cultivation in south-western Iran was evaluated and a land suitability map for vine cultivation was developed using the fuzzy-analytic hierarchy process (AHP). The best harvest time of vines was determined based on the relationship between total soluble solids (TSS) and titratable acidity (TA) with fruit colour (red, green, and blue or RGB) in ten points and also the growing degree-days (GDD) maps from April to December. The relationship between GDD and effective parameters in vine cultivation was determined using principal component analysis (PCA) and Pearson correlation methods. RESULTS: The results illustrated that the maximum temperature and relative humidity (RH) have the greatest effect on vine cultivation and its yield (weight 0.24). The results of the land suitability map showed that central regions have better conditions for growing vines (32%). The measurements of TA and TSS depicted that vines of the northern parts have higher TA and lower TSS and there is a significant relationship between them and fruit colour. The results of GDD maps showed that the harvest time of ruby vine and Gezel-azm is July and August, respectively. Also, the temperature (Tmean , Tmax and Tmin ), wind speed, and GDD were the most important parameters to determine the best location for vine cultivation. CONCLUSION: Determining land suitability for cultivation, the best harvest time, the time of grape ripening, and following the exact time of export and import of vine has a vital role to increase its productivity and services. © 2022 Society of Chemical Industry.

Estimating phenological sensitivity in contemporary vs. historical data sets: Effects of climate resolution and spatial scale.

PREMISE: Phenological sensitivity, or the degree to which a species' phenology shifts in response to warming, is an important parameter for comparing and predicting species' responses to climate change. Phenological sensitivity is often measured using herbarium specimens or local studies in natural populations. These approaches differ widely in spatiotemporal scales, yet few studies explicitly consider effects of the geographic extent and resolution of climate data when comparing phenological sensitivities quantified from different data sets for a given species. METHODS: We compared sensitivity of flowering phenology to growing degree days of the alpine plant Silene acaulis using two data sets: herbarium specimens and a 6 yr observational study in four populations at Niwot Ridge, Colorado, USA. We investigated differences in phenological sensitivity obtained using variable spatial scales and climate data sources. RESULTS: Herbarium specimens underestimated phenological sensitivity compared to observational data, even when herbarium samples were limited geographically or to nearby weather station data. However, when observational data were paired with broader-scale climate data, as is typically used in herbarium data sets, estimates of phenological sensitivity were more similar. CONCLUSIONS: This study highlights the potential for variation in data source, geographic scale, and accuracy of macroclimate data to produce very different estimates of phenological responses to climate change. Accurately predicting phenological shifts would benefit from comparisons between methods that estimate climate variables and phenological sensitivity over a variety of spatial scales.

Effects of climatic and cultivar changes on winter wheat phenology in central Lithuania.

It is essential to understand how climate change and varieties affect crop phenology and yields to adapt to future climate change. The aim of this study was to analyse the phenological development trends of three winter wheat cultivars (1990-2020) to identify the most critical meteorological-climatic factors influencing the development and yield of the cultivars and to investigate the heat requirements for each phenological phase to reveal the potential of the different cultivars to adapt to the warming climate. The observed dates of green-up, the beginning of stem elongation, and the grain development advanced significantly, but the timing of maturity changed insignificantly during the period of 1990-2020. The most marked change was related to the shortening of the period from sowing to green-up. The green-up dates were related to the mean temperature of the period after sowing. The occurrence of stem elongation and grain development dates were negatively correlated with the mean temperature in May. Significant correlations were found between temperature and duration from sowing to green-up and positive from stem elongation to grain development. The change of cultivar led to earlier green-up and grain development dates, but cultivar choise had no influence on sowing, stem elongation, and maturity dates from 1990 to 2020. The newer cultivar Skagen was more successful in exploiting increased thermal resources. The heat requirements remained almost unchanged during the vegetative development period, while the heat amount required during the reproductive period increased by about 15%. These findings demonstrate that the choice of crop cultivars with higher thermal requirements may be an appropriate adaptation mean to achieve higher yields in response to climate change, at least in the middle latitudes.

Climatic suitability projection for deciduous fruit tree cultivation in main producing regions of northern China under climate warming.

China is the largest fruit producer and consumer market in the world. Understanding the growing conditions responses to climate change is the key to predict future site suitability of main cultivation areas for certain deciduous fruit trees. In this study, we used dynamic and growing degree day models driven by downscaled daily temperatures from 22 global climate models to project the effects of climate change on growing conditions for deciduous fruit trees under two representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios over 2 future time periods (represented by central years 2050s and 2085s) in northern China. The results showed a general increase of available winter chill for all sites under RCP4.5 scenario, and the most dramatic increase in chill accumulation could reach up to 36.8% in northeast regions for RCP8.5. However, the forecasted chill will decrease by 6.4% in southeast stations under RCP8.5 by 2085s. Additionally, the increase rate of growing season heat showed spatially consistency, and the most pronounced increase was found in the RCP8.5 by 2085s. For the southwest station, median heat accumulation increased by 20.8% in the 2050s and 37.1% in the 2085s under RCP8.5. Similar increasing range could be found in the northeast station; the median growing season heat increased by 19.8% and 38.8% in the 2050s and 2085s under RCP8.5, respectively. Moreover, the date of last spring frost was expected to advance and the frequency of frost occurrences was projected to decline in the study area compared to the past. Overall, the present study improves understanding regarding site-specific characteristics of climatic suitability for deciduous fruit tree cultivation in main producing regions of northern China. The results could provide growers and decision-makers with theoretical evidence to take adaptive measure to ensure fruit production in future.

Changes in spatio-temporal distribution of AgMERRA-derived agro-climatic indices and agro-climatic zones for wheat crops in the northeast Iran.

This study evaluates the potential of gridded AgMERRA (the Modern-Era Retrospective Analysis for Research and Applications) to estimate aridity index (AI), growing degree days (GDD), and temperature seasonality (TS) for six land stations across northeast Iran. The researcher investigated the spatiotemporal variation of the AgMERRA-derived agro-climatic indices for the entire period 1981-2010 and three 10-year sub-periods for the 347 wheat harvested grid cells (0.25° × 0.25°) and their utility for agro-climate zoning in northeast Iran. Results indicated a good agreement between AgMERRA daily solar radiation, maximum and minimum temperatures, and annual total precipitation with corresponding land observations for the six studied sites. AgMERRA-derived evapotranspiration (ETo), AI, GDD, and TS also exhibited good agreement (R2 and d > 0.7) with the land station-derived indices for most of the locations. Annual analysis of the AI indicated a negative trend for all of the wheat harvested grid cells, but the decrease was significant (p < 0.05) only for 14.70% of grid cells, which were located in the southwest part of the studied region. The magnitude of the significant decreasing trends in annual AI was (-)0.0011 per year. The increase in aridity was due to the concurrent occurrences of positive ETo trends and negative precipitation trends. All of the wheat harvested grid cells showed a significant increasing trend (p < 0.05) for GDD at the rate of 24.10 °C d year-1. The TS series demonstrated an apparent increasing trend for 99.2% of wheat harvested grid cells; however, only 16.9% of them had the significant positive trend (p < 0.05) with the average rate of 0.023 °C year-1. The wheat harvested grid cells with increasing trend for TS were mainly distributed in the arid mountainous southern part of the study area. The 10 years sub-periods revealed that the best conditions in terms of most of the studied agro-climatic indices were found in sub-period 1981-1990 and the north Khorasan had better conditions in all three sub-periods. Based on AI, GDD, and TS, 13 major gridded agro-climatic zones were recognized in northeast Iran.

The influence of thermal cues on the reproductive phenology of Silver Shiner, Notropis photogenis.

Reproductive phenology and the length of the growing season vary in response to interannual environmental variability, with implications for population dynamics of freshwater fishes. Understanding the reproductive phenology of imperilled species in relation to environmental conditions is needed to better evaluate potential responses to changing environmental conditions, estimate future population dynamics and develop comprehensive recovery strategies. We examined Silver Shiner, a species listed as "Threatened" under Canada's Species at Risk Act, during spring 2018 and 2019 to better understand the reproductive phenology of the species at the northern edge of its range in Canada. The initiation of Silver Shiner spawning occurred on the descending limb of the hydrograph and was completed before the onset of the extended period of low summer flow. In addition, both the initiation and cessation of spawning occurred in response to a cumulative growing degree day base 5 (GDD5 ) cue, with logistic regression models indicating a 50% probability the population initiated and ceased spawning when GDD5 reached 68°C•days and 368°C•days, respectively. Logistic regression incorporating GDD5 effectively predicted spawning initiation and cessation, providing useful models for examining the impacts of alterations to the thermal regime on reproductive phenology and improving the ability to evaluate changes in the larval growth period. Furthermore, the models can facilitate the development of real-time estimates of spawning activity, and therefore ensure that disturbance to the species is minimized during the sensitive reproductive period.

Changing climate associated with the range-wide decline of an estuarine finfish.

Southern flounder (Paralichthys lethostigma) are a coastal flatfish species that supports recreational and commercial fisheries but are currently experiencing range-wide declines. To quantify the range-wide declines and investigate the role of climate in these declines, fishery-independent sampling data of age-0 flounder were obtained from 34 estuaries representing four states in the Gulf of Mexico (TX, LA, AL, and FL) and three states in the Southeastern United States Atlantic Ocean (FL, SC, and NC) spanning from 1976 to 2019. Generalized additive models (GAM) were used to estimate age-0 recruitment trends. Spatial and temporal synchrony analyses were then conducted using annual GAM-predicted values to determine if trends were similar between estuaries in close proximity, and if declines occurred at the same time. Because the species is dependent on physical transport (i.e., winds and tides) for recruitment, hourly wind speed, wind direction, water temperature, and air temperature were obtained for estuaries with non-zero sampling totals and long-term data sets. Only six estuaries showed significant relationships between age-0 flounder indices and growing degree days. However, all estuaries with wind data showed significant relationships between age-0 flounder indices and hourly summed wind speed. Southern flounder also have environmental sex determination, meaning warming estuaries could also account for population changes and declines. We document that water temperatures in the same space and time where southern flounder sexually determine are warmer now than even a decade ago, which could masculinize populations and substantially change population demographics. These results illustrate the vulnerability of estuarine finfish populations to climate change and increased climate variability. Understanding how climate acts on southern flounder biology may help managers respond to and prevent fishery collapses.

Snow melt timing acts independently and in conjunction with temperature accumulation to drive subalpine plant phenology.

Organisms use environmental cues to align their phenology-the timing of life events-with sets of abiotic and biotic conditions that favor the successful completion of their life cycle. Climate change has altered the environmental cues organisms use to track climate, leading to shifts in phenology with the potential to affect a variety of ecological processes. Understanding the drivers of phenological shifts is critical to predicting future responses, but disentangling the effects of temperature from precipitation on phenology is often challenging because they tend to covary. We addressed this knowledge gap in a high-elevation environment where phenological shifts are associated with both the timing of spring snow melt and temperature. We factorially crossed early snow melt and passive warming treatments to (1) disentangle the effects of snow melt timing and warming on the phenology of flowering and fruiting and reproductive success in three subalpine plant species (Delphinium nuttallianum, Valeriana edulis, and Potentilla pulcherrima); and (2) assess whether snow melt acts via temperature accumulation or some other aspect of the environment (e.g., soil moisture) to affect phenological events. Both the timing and duration of flowering and fruiting responded to the climate treatments, but the effect of snow melt timing and warming varied among species and phenological stages. The combined effects of the treatments on phenology were always additive, and the snow melt treatment often affected phenology even when the warming treatment did not. Despite marked responses of phenology to climate manipulations, the species showed little change in reproductive success, with only one species producing fewer seeds in response to warming (Delphinium, -56%). We also found that snow melt timing can act both through temperature accumulation and as a distinct cue for phenology, and these effects are not mutually exclusive. Our results show that one environmental cue, here snow melt timing, may act through multiple mechanisms to shift phenology.

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities.

Tundra dominates two-thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community-specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil.

Effects of cultivar and growing degree day accumulations on forage partitioning and nutritive value of common vetch (Vicia sativa L.) on the Tibetan plateau.

BACKGROUND: The use of common vetch in grassland-livestock systems has expanded greatly within recent years, partly because of its value as a high-quality forage crop but also to improve the soil nitrogen availability. In-field estimation of forage yield potential and nutritional characteristics is required for providing management decision to farmers on how to optimize the management and use of common vetch forages. The aim of this work was to study changes in forage partitioning and nutritive value responses of a late-maturing and an early maturing cultivar of common vetch in a two-year study on the Tibetan Plateau. RESULTS: This study provided evidence for differential patterns of forage accumulation for common vetch with contrasting maturity over 2 years. The late-maturing cultivar exhibited greater forage yield and a lower proportion of pods, compared to the early maturing cultivar. There was a tendency towards lower forage nutritive value with the late-maturing cultivar. Regressions of nutritive value parameters of common vetch forages on growing degree days were explained by the cubic (P < 0.001) models, all with high coefficients of determination (R2 ≥ 0.792). CONCLUSION: This study shows that the late-maturing cultivar harvested at end of the pod-filling stage produces high forage yield, increasing the availability of high-quality forage for ruminants, thereby improving the self-sufficiency of farmers, in terms of forage yield and high-concentration protein. For early maturing cultivars, it may be better to harvest at the early flowering stage for better nutritive value and in part to enable a subsequent double crop of oat. © 2020 Society of Chemical Industry.

On quantifying the apparent temperature sensitivity of plant phenology.

Many plant phenological events are sensitive to temperature, leading to changes in the seasonal cycle of ecosystem function as the climate warms. To evaluate the current and future implications of temperature changes for plant phenology, researchers commonly use a metric of temperature sensitivity, which quantifies the change in phenology per degree change in temperature. Here, we examine the temperature sensitivity of phenology, and highlight conditions under which the widely used days-per-degree sensitivity approach is subject to methodological issues that can generate misleading results. We identify several factors, in particular the length of the period over which temperature is integrated, and changes in the statistical characteristics of the integrated temperature, that can affect the estimated apparent sensitivity to temperature. We show how the resulting artifacts can lead to spurious differences in apparent temperature sensitivity and artificial spatial gradients. Such issues are rarely considered in analyses of the temperature sensitivity of phenology. Given the issues identified, we advocate for process-oriented modelling approaches, informed by observations and with fully characterised uncertainties, as a more robust alternative to the simple days-per-degree temperature sensitivity metric. We also suggest approaches to minimise and assess spurious influences in the days-per-degree metric.

Developmental trap or demographic bonanza? Opposing consequences of earlier phenology in a changing climate for a multivoltine butterfly.

A rapidly changing climate has the potential to interfere with the timing of environmental cues that ectothermic organisms rely on to initiate and regulate life history events. Short-lived ectotherms that exhibit plasticity in their life history could increase the number of generations per year under warming climate. If many individuals successfully complete an additional generation, the population experiences an additional opportunity to grow, and a warming climate could lead to a demographic bonanza. However, these plastic responses could become maladaptive in temperate regions, where a warmer climate could trigger a developmental pathway that cannot be completed within the growing season, referred to as a developmental trap. Here we incorporated detailed demography into commonly used photothermal models to evaluate these demographic consequences of phenological shifts due to a warming climate on the formerly widespread, multivoltine butterfly (Pieris oleracea). Using species-specific temperature- and photoperiod-sensitive vital rates, we estimated the number of generations per year and population growth rate over the set of climate conditions experienced during the past 38 years. We predicted that populations in the southern portion of its range have added a fourth generation in recent years, resulting in higher annual population growth rates (demographic bonanzas). We predicted that populations in the Northeast United States have experienced developmental traps, where increases in the thermal window initially caused mortality of the final generation and reduced growth rates. These populations may recover if more growing degree days are added to the year. Our framework for incorporating detailed demography into commonly used photothermal models demonstrates the importance of using both demography and phenology to predict consequences of phenological shifts.

Detecting flowering phenology in oil seed rape parcels with Sentinel-1 and -2 time series.

A novel methodology is proposed to robustly map oil seed rape (OSR) flowering phenology from time series generated from the Copernicus Sentinel-1 (S1) and Sentinel-2 (S2) sensors. The time series are averaged at parcel level, initially for a set of 229 reference parcels for which multiple phenological observations on OSR flowering have been collected from April 21 to May 19, 2018. The set of OSR parcels is extended to a regional sample of 32,355 OSR parcels derived from a regional S2 classification. The study area comprises the northern Brandenburg and Mecklenburg-Vorpommern (N) and the southern Bavaria (S) regions in Germany. A method was developed to automatically compute peak flowering at parcel level from the S2 time signature of the Normalized Difference Yellow Index (NDYI) and from the local minimum in S1 VV polarized backscattering coefficients. Peak flowering was determined at a temporal accuracy of 1 to 4 days. A systematic flowering delay of 1 day was observed in the S1 detection compared to S2. Peak flowering differed by 12 days between the N and S. Considerable local variation was observed in the N-S parcel-level flowering gradient. Additional in-situ phenology observations at 70 Deutscher Wetterdienst (DWD) stations confirm the spatial and temporal consistency between S1 and S2 signatures and flowering phenology across both regions. Conditions during flowering strongly determine OSR yield, therefore, the capacity to continuously characterize spatially the timing of key flowering dates across large areas is key. To illustrate this, expected flowering dates were simulated assuming a single OSR variety with a 425 growing degree days (GDD) requirement to reach flowering. This GDD requirement was calculated based on parcel-level peak flowering dates and temperatures accumulated from 25-km gridded meteorological data. The correlation between simulated and S2 observed peak flowering dates still equaled 0.84 and 0.54 for the N and S respectively. These Sentinel-based parcel-level flowering parameters can be combined with weather data to support in-season predictions of OSR yield, area, and production. Our approach identified the unique temporal signatures of S1 and S2 associated with OSR flowering and can now be applied to monitor OSR phenology for parcels across the globe.

Evaluation of forewarning models for mustard aphids in different agro-climatic zones of India.

Mustard aphid, Lipaphis erysimi (Kaltenbach), is the most serious pest of Rapeseed-Mustard which is known to be responsible for a tremendous loss in yield and oil content, under various agro-climatic conditions of India. Information support on aphid occurrence and intensity is necessary for effective management by the farmers in the mustard-growing belt. In this study, an effort is made to develop forewarning model using the field data on aphid for 12 consecutive rabi seasons from 2003-2004 to 2014-2015 under different agro-climatic locations in India. Three main components of aphid-related stages were identified for which necessary forewarnings were needed to be issued: (1) severity, (2) the time of reaching the economic threshold level (ETL) for decision-making on pesticide application, and (3) time of occurrence of peak population. To address these, three different models were developed/used and validated using incident field dataset. Those field observations when the infestation level were below severe category (< 60) during rising phase of the aphid population were found to indicate highest R sqr. (0.82) for the model-I during validation. When model-II was used, 11 out of 14 locations (78.57%) stood validated. The assumptions made in model-III also got validated when humidity thermal ratio (HTR) of the week of peak population ranged between 1.5 and 4 (lowest among the weeks considered), and population reached severe category. The models showed better results during real-time validation in seasons 2016-2017 and 2017-2018, thus suggesting that these three models can be used to ascertain the severity, week of ETL, and week of peak aphid population for Brassica juncea varieties all over the mustard belt in India and can be operationalized spatially to forewarn against the aphid pest population in future under Gramin Krishi Mausam Sewa (GKMS) scheme.