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Assessing seasonal demographic covariation to understand environmental-change impacts on a hibernating mammal

Natural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development, reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneous, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.

Data from: Strong survival selection on seasonal migration versus residence induced by extreme climatic events

1. Elucidating the full eco-evolutionary consequences of climate change requires quantifying the impact of extreme climatic events (ECEs) on selective landscapes of key phenotypic traits that mediate responses to changing environments. Episodes of strong ECE-induced selection could directly alter population composition, and potentially drive micro-evolution. However, to date, few studies have quantified ECE-induced selection on key traits, meaning that immediate and longer-term eco-evolutionary implications cannot yet be considered. 2. One widely-expressed trait that allows individuals to respond to changing seasonal environments, and directly shapes spatio-seasonal population dynamics, is seasonal migration versus residence. Many populations show considerable among-individual phenotypic variation, resulting in 'partial migration'. However, variation in the magnitude of direct survival selection on migration versus residence has not been rigorously quantified, and empirical evidence of whether seasonal ECEs induce, intensify, weaken or reverse such selection is lacking. 3. We designed full-annual-cycle multi-state capture-recapture models that allow estimation of seasonal survival probabilities of migrants and residents from spatio-temporally heterogeneous individual resightings. We fitted these models to nine years of geographically extensive year-round resighting data from partially migratory European shags (Phalacrocorax aristotelis). We thereby quantified seasonal and annual survival selection on migration versus residence across benign and historically extreme non-breeding season (winter) conditions, and tested whether selection differed between females and males. 4. We show that two of four observed ECEs, defined as severe winter storms causing overall low survival, were associated with very strong seasonal survival selection against residence. These episodes dwarfed the weak selection or neutrality evident otherwise, and hence caused selection through overall annual survival. The ECE that caused highest overall mortality and strongest selection also caused sex-biased mortality, but there was little overall evidence of sex-biased selection on migration versus residence. 5. Our results imply that seasonal ECEs and associated mortality can substantially shape the landscape of survival selection on migration versus residence. Such ECE-induced phenotypic selection will directly alter migrant and resident frequencies, and thereby alter immediate spatio-seasonal population dynamics. Given underlying additive genetic variation, such ECEs could potentially cause micro-evolutionary changes in seasonal migration, and thereby cause complex eco-evolutionary population responses to changing seasonal environments.

opencc-by-4.0Dec 2020View details →

Timing of drought in the growing season

Experimental setup: For the experiment we established six grasses in monoculture that are commonly used in agricultural practice in August 2013 on 168 plots (3 × 5 m). This timing is following best practice and guarantees full establishment of the sward (including vernalisation during winter) and full productivity in the following year. The six grasses established were Lolium perenne L. early flowering (LPe; cultivar ‘Artesia’), Lolium perenne L. late flowering (LPl; cultivar ‘Elgon’), Dactylis glomerata L. early flowering (DGe; cultivar ‘Barexcel’), Dactylis glomerata L. late flowering (DGl; cultivar ‘Beluga’), Lolium multiflorum Lam. var italicum Beck (LM; cultivar ‘Midas’), and Poa pratensis L. (PP; cultivar ‘Lato’). Phosphorous, potassium and manganese were applied following national fertilization recommendations for intensely managed grasslands at the beginning of each growing season (39 kg P/ha, 228 kg K/ha, 35 kg Mg/ha). In addition, all plots received the same amount of mineral N fertilizer as ammonium-nitrate (280 kg N/ha, divided into six applications per year). The solid N fertilizer was applied at the beginning of the growing season (80 kg N/ha) and after each of the first five cuts (40 kg N/ha each time). Each of the six grasses was subject to four treatments: one rain-fed control and three seasonal drought treatments (spring, summer, fall). A drought treatment lasted for ten weeks. Drought was simulated using rainout shelters that excluded rainfall completely on the treatment plots. The rainout shelters were tunnel-shaped and consisted of steel frames (3 × 5.5 m, height: 140 cm) that were covered with transparent and UV radiation transmissible greenhouse foil (Lumisol clear, 200 my, Hortuna AG, Winikon, Switzerland). To allow air circulation, shelters were open on both opposing short ends and had ventilation openings of 35 cm height over the entire length at the top and the bottom at both long sides. Rain-fed controls were subject to the natural precipitation regime. However, when soil water potential sank below -0.5 MPa due to naturally dry conditions, control plots were additionally watered with 20 mm of water (300 l per plot). Watering happened once on June 16th and 17th 2014 and three times in 2015 (7.7., 14.7., 11.8.). Relative humidity and air temperature were measured hourly at the field site using VP-3 humidity, temperature and vapor pressure sensors (Decagon Devices, Inc., Pullman, WA, USA). Measurements were conducted in control and treatment plots under the rainout shelters. Information on precipitation and evapotranspiration was provided by the national meteorological service stations that were in close proximity of our research site (average of the two surrounding meteorological stations Zurich Affoltern in 1.4 km distance and Zurich Kloten in 4.5 km distance). Soil water potential was measured in 10 cm depth on an hourly basis using 32 MPS-2 dielectric water potential sensors (Decagon Devices, Inc., Pullman, WA, USA). The soil water potential sensors were evenly distributed over the field and treatments. Daily means of all measurements were calculated per treatment, but across grasses since no grass-specific alterations in soil water potential were expected or measured. Aboveground biomass was harvested six times per year at a five-week interval in 2014 and 2015, and once in spring 2016. The harvests were synchronized with the drought treatments and occurred five and ten weeks after the installation of the shelters on a respective treatment. For the harvest, aboveground biomass was cut at 7 cm height above the ground and harvested from a central strip (5 × 1.5 m) of the plot using an experimental plot harvester (Hege 212, Wintersteiger AG, Ried/I., Austria). The fresh weight of the total harvest of a plot was determined with an integrated balance directly on the plot harvester. Dry biomass production was determined by assessing dry weight – fresh weight ratios of the harvested biomass. For this a biomass subsample was collected for each plot and the fresh and dry weight (dried at 60°C for 48 h) were determined. Belowground biomass of four grasses (DGe, DGl, LPe and LPl) was harvested six times per year, at the end of each drought period and six to eight weeks after drought release, from the respective treatment and control plots using a manual soil auger with a diameter of 7 cm. For each plot samples of the upper 14 cm soil were taken from two different spots (one sample directly from a tussock and one from in between tussocks) and pooled as one sample per plot. All samples were washed using a sieve with a mesh size of 0.5 cm × 0.5 cm and weighed after drying (at 60°C for 72 h). In order to allow the comparison of grassland productivity in the different treatments across the two years we standardized the productivity that occurred in between two harvest periods (i.e. during five weeks) for growth related temperature effects and calculated temperature-weighted growth rates for each of the six grasses (DMYTsum). For this purpose, we determined temperature sums of daily mean air temperature above a base temperature of 5°C (Tsum) for each growth period (i.e. 5 weeks prior to harvest in the unsheltered control as well as the sheltered treatment plots). Dry matter yield (DMY) of a given harvest was then divided by the temperature sum of the corresponding time period to obtain temperature-weighted growth rates (henceforth referred to simple as growth rate): DMYTsum = DMY(g/m2)/Tsum(°C). To determine the absolute change of growth (ACG) of a drought treatment on aboveground growth rate we calculated the difference between temperature-weighted growth rates in a drought treatment (drt) and the corresponding control (ctr): ACG = DMYTsum(drt)-DMYTsum(ctr). To determine the relative change of growth (RCG) due to drought, we calculated percentage change of temperature-weighted growth rates: RCG = 100×(DMYTsum(drt)/DMYTsum(ctr)-1). Annual aboveground NPP as an average of the different grasses was determined by adding up the dry matter yields of the six harvests of a growing season. These data were not temperature-corrected (DMY).   Used Instruments: <ul> <li>VP-3 humidity, temperature and vapor pressure sensors (Decagon Devices, Inc., Pullman, WA, USA)</li> <li>MPS-2 dielectric water potential sensors (Decagon Devices, Inc., Pullman, WA, USA) experimental plot harvester (Hege 212, Wintersteiger AG, Ried/I., Austria)</li> <li>manual soil auger with a diameter of 7 cm</li> </ul>   Data List of parameters measured or described: <ul> <li>soil water potential</li> <li>air temperature</li> <li>vapor pressure deficit</li> <li>precipitation</li> <li>phenological stage (seperated into vegetative and generative)</li> <li>fresh weight</li> <li>dry weight</li> <li>δ13C of plant material</li> <li>nitrogen content of harvested plant material</li> <li>digestible organic matter of plant harvested material</li> <li>crude protein content of plant harvested material</li> <li>crude ash content of plant harvested material</li> </ul> Measuring periods (date, daytime): The data was collected from March 12th 2014 until May 3rd 2016 Column descriptions and units: <ul> <li>Plot: plot number</li> <li>Cultivar: short key for tested cultivar monoculture <ul> <li>LPf: Lolium perenne L. 'Artesia' (early-flowering cultivar)</li> <li>LPs: Lolium perenne L. 'Elgon' (early-flowering cultivar)</li> <li>DGf: Dactylis glomerata L. 'Barexcel' (early-flowering cultivar)</li> <li>DGs: Dactylis glomerata L. 'Beluga' (early-flowering cultivar)</li> <li>LM: Lolium multiflorum Lam. var italicum Beck 'Midas'</li> <li>PP: Poa pratensis L. 'Lato'</li> <li>TR: Trifolium repens L. 'Bombus'</li> </ul> </li> <li>Treatment: short key for the implemented kind of seasonal drought; <ul> <li>F: spring drought</li> <li>S: summer drought</li> <li>H: autumn drought, K: control</li> </ul> </li> <li>Serie: type of serie (A or B)</li> <li>Rep: number of replication in the experiment</li> <li>Row: number of row in the field: 1-5</li> <li>Bock: position of plots in the field: block 1 is on the westernmost site of the field, block 7 on the easternmost site</li> <li>Recovery: short key for: <ul> <li>C - control</li> <li>bT - before treatment conditions</li> <li>T - treatment conditions;</li> <li>R - recovery conditions (after treatment)</li> </ul> </li> <li>Harvest: number of harvest</li> <li>Date: date of harvest</li> <li>DOY: date of harvest as day of year</li> <li>FWplot: fresh weight per plot (kg/plot)</li> <li>FWha: fresh weight (kg/ha)</li> <li>percentageDW: percentage dry weight (%)</li> <li>DW: dry weight (kg/ha)</li> <li>Growthdays: number of days in growing period between two harvests</li> <li>DWdays: rate of growth (calculated by: DW (kg/ha)/Growthdays) (kg/ha/day)</li> <li>ATsum: sum of daily air temperature averages above 5°C from previous harvest until current harvest (°C)</li> <li>RadSum: sum of daily radiation averages from previous harvest until current harvest (W/m2); Daily radiation averages as a mean of MeteoSwiss stations Zürich-Affoltern and Zürich-Kloten; RadSum of current treatment reduced by 10%, because of radiation-reducing effect of rainout shelters (see Hortuna AG)</li> <li>VPDsum: sum of daily vapour pressure deficit (VPD) averages (derived from daily air temperature and daily relative humidity) from previous harvest until current harvest (kPa)</li> <li>RainSum: sum of daily rainfall data from previous harvest until current harvest (mm); Daily rainfall data as a mean of MeteoSwiss stations Zürich-Affoltern and Zürich-Kloten; manual watering events added to control plots; RainSum of current treatment set to 0, because of rainout shelters excluding the rain</li> <li>SWP: soil water potential (MPa)</li> <li>medianSWP10: median of daily mean soil water potential in 10cm depth from previous harvest until current harvest (MPa)</li> <li>cumSWP10: cumulative soil water potential in 10cm depth from previous harvest until current harvest (MPa)</li> <li>SWPdays10: number of days within the growing period (between two harvests) with a soil water potential in 10 cm depth of or below -1.5MPa</li> <li>medianSWP30: median of daily mean soil water potential in 30cm depth from previous harvest until current harvest (MPa)</li> <li>cumSWP30: cumulative soil water potential in 30cm depth from previous harvest until current harvest (MPa)</li> <li>SWPdays30: number of days within the growing period (between two harvests) with a soil water potential in 30 cm depth of or below -1.5MPa</li> <li>Phen: phenological stage right before harvest/at garvest date (0: vegetative; 1: generative)</li> <li>IsoC: drift corrected δ13C value (&permil;)</li> <li>IsoN: drift corrected δ15N value (&permil;)</li> <li>N: nitrogen concentration (g/kg DW)</li> <li>VOS: digestibale organic matter (g/kg DW)</li> <li>RP: crude protein (g/kg DW)</li> <li>RA: crude ash (g/kg DW)</li> <li>Nc: critical plant nitrogen concentration, corresponding to the observed crop mass (DW); calculated after Lemaire 1997: Diagnosis of nitrogen uptake in crops</li> <li>NNI: nitrogen nutrition index (N/Nc); Ratio of actual plant nitrogen concentration and critial plant nitrogen concentration; see Lemaire 1997: Diagnosis of nitrogen uptake in crops</li> </ul> List of archived files: <ul> <li>Biomass: <ul> <li>181004_Biomass_2014</li> <li>181004_Biomass_2015</li> <li>181004_Biomass_2016</li> <li>181004_RootBiomass_2014</li> </ul> </li> <li>Phenology: <ul> <li>181004_Phenology_2014</li> <li>181004_Phenology_2015</li> </ul> </li> <li>Physiology: <ul> <li>181004_Isotopes_201415</li> <li>181004_PlantWaterPotential</li> <li>181004_PredawnPlantWaterPotential</li> <li>181004_StomatalConductance</li> </ul> </li> <li>Soil Moisture: <ul> <li>181004_Soil sensors_daily mean_2014</li> <li>181004_Soil sensors_daily mean_2015</li> </ul> </li> </ul>

opencc-by-4.0Oct 2020View details →

Seasonality in Holocene Temperature Reconstructions in Southwestern China

Reconstructions of global surface temperature, dominated by records from the northern extratropics, show an apparent Holocene cooling trend after the early Holocene Climatic Optimum. However, model simulations suggest a global warming Holocene tendency. This “Holocene temperature conundrum” may be caused by the seasonal bias of paleotemperature proxies. Here we report a quantitative Holocene record with ~100-year resolution based on branched glycerol dialkyl glycerol tetraethers (brGDGTs) from an alpine lake in southwestern China. Our reconstructed Holocene temperature record displays a steady long-term trend without distinct cooling or warming changes. Based on the temperature values and their evolution over time, our reconstruction is interpreted to present temperature changes in ice-free seasons from March to November. Unlike the often-documented Holocene cooling of regional summer temperatures driven by boreal summer insolation, this observed trend in our reconstructed temperatures is probably caused by slightly decreasing local ice-free season insolation and somewhat compensated by increasing atmospheric greenhouse gas concentrations. Our results demonstrate that the climatic drivers of ice-free season and summer temperature changes could be different and highlight the significance of elucidating the seasonality of proxies before using them for paleoclimate reconstructions.

Supplementary material 1 from: Guedes GHS, Salgado FLK, Uehara W, de Pavia Ferreira DL, Araújo FG (2020) The recapture of Leptopanchax opalescens (Aplocheiloidei: Rivulidae), a critically endangered seasonal killifish: habitat and aspects of population structure. Zoologia 37: 1-8. https://doi.org/10.3897/zoologia.37.e54982

Figure S1. Photographic records of Leptopanchax opalescens in an aquarium after three hours of capture (Photos 1–3), and record of a male specimen with more exuberant color immediately after capture in its natural habitat (Photos 4–5). Date: March 19th, 2020; Coordinates: 22°42.35'S, 43°41.59'W.

Breeding season length predicts duet coordination and consistency in Neotropical wrens (Troglodytidae)

Many animals produce coordinated signals, but few are more striking than the elaborate male-female vocal duets produced by some tropical songbirds. Yet, little is known about the factors driving the extreme levels of vocal coordination between mated pairs in these taxa. We examined evolutionary patterns of duet coordination and their potential evolutionary drivers in Neotropical wrens (Troglodytidae), a songbird family well-known for highly coordinated duets. Across 23 wren species we show that the degree of coordination and precision with which pairs combine their songs into duets varies by species. This includes some species that alternate their song phrases with exceptional coordination to produce rapidly alternating duets that are highly consistent across renditions. These highly coordinated, consistent duets evolved independently in multiple wren species. Duet coordination and consistency are greatest in species with especially long breeding seasons, but neither duet coordination nor consistency are correlated with clutch size, conspecific abundance, or vegetation density. These results suggest that tightly coordinated duets play an important role in mediating breeding behaviour, possibly by signalling commitment or coalition of the pair to mates and other conspecifics.

Fitness consequences of seasonally different life histories? A match-mismatch experiment

To survive and reproduce successfully, animals have to find the optimal time of breeding. Species living in non-tropical environments often adjust their reproduction plastically according to seasonal changes of the environment. Information about the prevailing season can be transmitted in utero, leading to adaptation of the offspring to the prevailing season. After birth, animals acquire additional personal information about the environment which allows them to adjust their reproductive investment. Here, we tested in a full-factorial match-mismatch experiment the influence of reproductive adjustments according to maternal and personal information. We bred wild cavies (Cavia aperea), a precocial rodent, either into increasing (spring) or decreasing (autumn) photoperiod and subsequently, after weaning, transferred female offspring to the matching or mismatching season. We measured growth, specific metabolic rate (sRMR) and reproductive events across six months. Although sRMR was elevated for females primed for good (spring) conditions when transferred to the mismatching autumn condition, we found no maternal effects on reproduction. Females adjusted their reproductive decisions according to the season they personally experienced, thereby implying a potentially high level of plasticity. Females reproducing in spring started reproduction earlier with a lower reproductive effort than females reproducing in autumn but ultimately, the two groups did not differ in survival, growth or reproduction. These data suggest important developmental plasticity, highlight the use of personal information acquired after weaning over early information provided until weaning and point out the potential value of multiple cues such as food abundance and quality and temperature besides photoperiod.

Data from: Genetic diversity of the rain tree (Albizia saman) in Colombian seasonally dry tropical forest for informing conservation and restoration interventions

Albizia saman is a multipurpose tree species of seasonally dry tropical forests (SDTFs) of Mesoamerica and northern South America typically cultivated in silvopastoral and other agroforestry systems around the world, a trend that is bound to increase in light of multimillion hectare commitments for forest and landscape restoration. The effective conservation and sustainable use of A. saman requires detailed knowledge of its genetic diversity across its native distribution range of which surprisingly little is known to date. We assessed the genetic diversity and structure of A.saman across twelve representative locations of SDTF in Colombia, and how they may have been shaped by past climatic changes and human influence. We found four different genetic groups which may be the result of differentiation due to isolation of populations in pre-glacial times. The current distribution and mixture of genetic groups across STDF fragments we observed might be the result of range expansion of SDTFs during the last glacial period followed by range contraction during the Holocene and human-influenced movement of germplasm associated with cattle ranching. Despite the fragmented state of the presumed natural A. saman stands we sampled we did not find any signs of inbreeding, suggesting that gene flow is not jeopardized in humanized landscapes. However, further research is needed to assess potential deleterious effects of fragmentation on progeny. Climate change is not expected to seriously threaten the in situ persistence of A. saman populations and might present opportunities for future range expansion. However, the sourcing of germplasm for tree planting activities needs to be aligned with the genetic affinity of reference populations across the distribution of Colombian SDTFs. We identify priority source populations for in situ conservation based on their high genetic diversity, lack or limited signs of admixture and/or genetic uniqueness.

Data from: Differing impacts of two major plant invaders on urban plant-dwelling spiders (Araneae) during flowering season

The dataset contains spider (Araneae) specimen numbers collected from flowering invasive American goldenrod (Solidago canadensis/gigantea) and invasive Himalayan balsam (Impatiens glandulifera) stands occuring naturally in urban areas of the city of Karlsruhe, Germany. Corresponding plots with native ruderalized vegetation in direct vicinity of each invaded plot were used as a comparison plot, resulting in a fully paired design for each plant invader study. An additional column represents potential non-araneae prey items collected together with the spiders from each stand. Spider specimens were determined to the family level as well as classified into web builders and hunters without a web.

opencc-by-4.0Jan 2021View details →

Linking Seasonal-to-Interannual Variability of Intermediate Currents in the Southwest Tropical Pacific to Wind Forcing and ENSO

This dataset contains zonal velocity data observed by the mooring at 142E/0,142E,1S,141.4E/1.7S. It is supplementary of the paper "Linking Seasonal-to-Interannual Variability of Intermediate Currents in the Southwest Tropical Pacific to Wind Forcing and ENSO" published by the Geophysical Research Letters (https://doi.org/10.1029/2021GL092440). Please let me know if you need any more information.

opencc-zeroJan 2021View details →

Habitat loss on seasonal migratory range imperils an endangered ungulate

<ol> <li>Endangered species policies and their associated recovery documents and management actions do not always sufficiently address the importance of migratory behavior and seasonal ranges for imperiled populations.</li> <li>Using a telemetry location dataset spanning 1981 – 2018, we tested for changes in prevalence of migratory tactics (resident, migrant) over time, switching between tactics, shifts in seasonal space-use including migration corridors, and survival consequences of migrant and resident tactics for 237 adult female endangered woodland mountain caribou in one population in western Canada.</li> <li>Over more than three decades, the proportion of individuals displaying annual migration to the low elevation forested winter range declined from nearly 100% to 38%. Correspondingly, there was a strong switch away from being migrant to being year-round residents at high elevation.</li> <li>These behavioral changes corresponded to abandonment of low elevation winter ranges in association with increasing levels of anthropogenic land uses, including forestry and oil and gas developments. Furthermore, there were no identifiable migration corridors to target for migratory route protection.</li> <li>These shifts translated to lower survival rates, particularly for caribou demonstrating resident tactics, consistent with recent declines of the caribou population. That migrants switched to residency in their largely undisturbed summer range, despite lower survival, indicates maladaptive habitat selection consistent with recent patterns of mountain caribou extirpations.</li> <li>Globally, endangered species policies and their associated recovery plans and management actions often do not explicitly consider the challenge of protecting migratory species. Effective conservation of migratory species requires protecting critical habitats needed for the entire life history of the species, including all seasonal ranges and migratory habitat.</li> </ol>

opencc-zeroJan 2021View details →

Endangered predators and endangered prey: seasonal diet of Southern Resident killer whales

Understanding diet is critical for conservation of endangered predators. The Southern Resident killer whales (SRKW) (Orcinus orca) are an endangered population occurring primarily in the west coast and inland waters of Washington and British Columbia. Insufficient prey has been identified as a factor limiting their recovery, so a clear understanding of the whales' seasonal diet is a high conservation priority. Previous studies have shown that their summer diet in inland waters consists primarily of Chinook salmon (Oncorhynchus tshawytscha), despite this species' rarity compared to some other salmonids. During other times of year, when ranging patterns include the U.S. and Canadian west coast and the northern and southern portions of the Salish Sea, their diet is largely unknown. To address this data gap, we collected feces and prey remains from October to May 2004-2017 in both the Salish Sea and U.S. west coast waters. Using visual and genetic species identification for prey remains and genetic approaches for fecal samples, we characterized the diet of the SRKWs in fall, winter, and spring. Chinook salmon were identified as an important prey item year-round, averaging ~50% of their diet in the fall, increasing to 70-80% in the late winter/early spring, and returning to nearly 100% in the late spring. Other salmon species and non-salmonid fishes, also made substantial dietary contributions. The relatively high species diversity in winter suggested a possible lack of Chinook salmon, probably due to seasonally lower densities, based on their proclivity to selectively consume this species in other seasons. A wide diversity of Chinook salmon stocks were consumed, many of which are also at risk. Although west coast samples consisted of 14 stocks, four rivers systems accounted for 90% of the samples, predominantly the Columbia River. Increasing the abundance of Chinook salmon stocks that inhabit the whales' winter range may be an effective conservation strategy for this population.

opencc-zeroJan 2021View details →

Genomic architecture of a genetically assimilated seasonal color pattern

Developmental plasticity allows genomes to encode multiple distinct phenotypes that can be differentially manifested in response to environmental cues. Alternative plastic phenotypes can be selected through a process called genetic assimilation; although the mechanisms are still poorly understood. We assimilated a seasonal wing color phenotype in a naturally plastic population of butterflies, and characterized three responsible genes. Combined with endocrine assays, and chromatin accessibility and conformation analyses, we found that the transition of wing coloration from an environmentally determined trait to a predominantly genetic trait occurred through selection for regulatory alleles of downstream wing patterning genes. This mode of genetic evolution is likely favored by selection because it allows tissue- and trait-specific tuning of reaction norms without affecting core cue detection or transduction mechanisms.

FIGURE 6 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 6. Type locality of Nothobranchius elucens; Uganda: upper Nile drainage: ephemeral swamp in the Aringa system. Photographed on 6 June 2017.

FIGURE 4 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 4. Nothobranchius elucens, female, about 25 mm SL, live; Uganda: upper Nile drainage: ephemeral swamp in the Aringa system, about 2.6 km south of Madi Opei town. Photographed after two weeks in captivity.

FIGURE 7. Nothobranchius taiti, MRAC 2018.015.P.0002 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 7. Nothobranchius taiti, MRAC 2018.015.P.0002, paratype, male, 35.3 mm SL, live; Uganda: upper Nile drainage: Lake Kyoga basin: ephemeral swamp of the Apapi River system. Photographed after 2 weeks in captivity.

FIGURE 1 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 1. Comparative morphometry in males of Nothobranchius elucens (blue triangles) and N. taiti (green squares). Score plot of principal component analysis on the best subset of morphometric characters; first vs. second principal components.

FIGURE 2. Nothobranchius elucens, MRAC 2020.007.P.0001 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 2. Nothobranchius elucens, MRAC 2020.007.P.0001, holotype, male, 31.9 mm SL; Uganda: upper Nile drainage: ephemeral swamp in the Aringa system, about 2.6 km south of Madi Opei town.

FIGURE 3. Nothobranchius elucens, MRAC 2020.007.P.0008 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 3. Nothobranchius elucens, MRAC 2020.007.P.0008, paratype, male, 35.7 mm SL, live; Uganda: upper Nile drainage: ephemeral swamp in the Aringa system, about 2.6 km south of Madi Opei town. Photographed after one month in captivity.

FIGURE 5 in Nothobranchius elucens, a new species of seasonal killifish from the upper Nile drainage in Uganda (Cyprinodontiformes: Nothobranchiidae)

FIGURE 5. Map of Uganda, showing the type locality of Nothobranchius elucens (blue triangle) and N. taiti (green squares). Map prepared by Brian Watters.