Philippa Kaur

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Systematic palaeontologyOrder Hemiptera Linnaeus, 1758Suborder Sternorrhyncha Amyot et Audinet-Serville, 1843Superfamily Protopsyllidioidea Carpenter, 1931Family Postopsyllidiidae Hakim, Azar et Huang, 2019Genus Megalophthallidion Drohojowska et Szwedo, gen. nov.LSID urn:lsid:zoobank.org:act:A6F71390-9B8E-4A19-8F30-C2A024B6EFB1Type speciesMegalophthallidion burmapateron Drohojowska et Szwedo, sp. nov.; by present designation and monotypy.EtymologyGeneric name is derived from Classic Greek megas (μέγας)—large, ophthalmos (ὀφθαλμός)—an eye and Greek form of generic name Psyllidium. Gender: masculine.Type localityNorthern Myanmar: state of Kachin, Noije bum 2001 Summit Site amber mine in the Hukawng Valley, SW of Maingkhwan.Type stratumLowermost Cenomanian, Upper Cretaceous (‘mid-Cretaceous’).DiagnosisHead capsule with 12 stiff setae on tubercles (18 setae in Postopsyllidium); fore wing without pterostigma (tiny pterostigma, widening of ScP + RA present in Postopsyllidium); vein CuP not thickened distally (distinctly thickened distally in Postopsyllidium); profemur with a row of ventral (ventrolateral) setae (two rows in Postopsyllidium).Megalophthallidion burmapateron Drohojowska et Szwedo, sp. nov.LSID urn:lsid:zoobank.org:act:F3F971F4-AE04-4F41-98B0-9A0A04470625.(Figs. 1A–F, 2A–I).Figure 1Megalophthallidion burmapteron gen. et sp. nov., holotype (MAIG 6687), imago. (A) Photo of body, ventral side; (B) photo of right antennae and (C) drawing of antenna; (D) drawing of body, dorsal side; (E) drawing of thorax structure with sclerites marked: red—pronotum; orange—mesopraescutum; yellow—mesoscutum; light green—mesoscutellum, dark green—mesopostnotum; light blue—metascutum; dark blue—metascutellum; violet—metapostnotum; (F) photo of thorax dorsal side. Scale bars: 0.5 mm (A), 0.2 mm (B–D), 0.1 mm (F).Full size imageFigure 2Megalophthallidion burmapteron gen. et sp. nov., holotype (MAIG 6687), imago. (A) Photo of right fore wing; (B) photo of right wings; (C) photo of antenna and proleg; (D) photo of proleg and mesoleg, and (E) photo of femur of proleg, and (F) photo of right metatarsus and left mesotarsus in the background, and (G) photo of right mesotarsus of mesoleg, and (H) Photo of tarsi; (I) photo of male genital block. Scale bars: 0.5 mm (A–D), 0.2 mm (B,E,F,H), 0.1 mm (G,I).Full size imageMaterialHolotype, number MAIG 6687 (BUB 96), deposited in Museum of Amber Inclusions (MAIG), University of Gdańsk, Poland. Imago, a complete and well-preserved male. Piece of amber 8 × 6 × 3 mm, cut from larger lump, polished flat on both sides.Type localityNorthern Myanmar: state of Kachin, Noije bum 2001 Summit Site amber mine in the Hukawng Valley, SW of Maingkhwan.Type stratumLowermost Cenomanian, Upper Cretaceous (‘mid-Cretaceous’).DiagnosisAs for the genus with the following additions: three ocelli distinct, antennomere IX the longest, about as long as pedicel, antennomeres III–VII and XI of similar length, antennomere XII the shortest, subconically tapered in apical portion. Paramere lobate, ventral margin with acute, small process, apical and dorsal margins rounded. Aedeagus geniculately bent at base, directed dorsally, tapered apicad.DescriptionMale (Figs. 1A–F, 2A–I). Head with compound eyes distinctly wider than pronotum (Fig. 1D–F). Compound eyes subglobular, protruding laterally. Vertex short in midline, about 2.5 times as wide as posterior margin and as long in middle; trapezoidal, anterior margin slightly arched, lateral margins diverging posteriad, posterior margin shallowly arched, disc of vertex with distinct setae on large tubercles: four setae at posterior margin, two at anterior angles of compound eyes, two medial, over the median ocellus. Three ocelli present, median ocellus distinct, visible from above, lateral ocelli near anterior angles of compound eyes. Frons about as wide as long in midline, two rows of setae on tubercles, upper row at level of median ocellus, lower one, below half of compound eye height. Clypeus, elongate, triangular, in lower portion roof-like; two setae on tubercles near upper margin. Genae very narrow. Rostrum reaching slightly beyond mesocoxae, apical segment slightly shorter than subapical one, darker. Antennae bases placed at lower margin of compound eyes; antennal fovea elevated; scapus shorter than pedicel, cylindrical; pedicel cylindrical; antennomeres IIIrd–VIIth and XIth of similar length, VIIIth slightly longer than VIIth, as long as Xth antennomere, IXth the longest, XIIth the shortest, tapered apically; rhinaria absent.Thorax (Fig. 1D–F): pronotum quadrangular, about as long as mesothorax; pronotum with anterior and posterior margins parallel, merely arcuate, disc with transverse groove in the median portion, lateral margins slightly arcuate, two distinct setae on tubercles in anterolateral angle, two setae on tubercles anterior margin at distance1/3 to median line, three distinct setae on tubercles in posterolateral angles. Mesopraescutum subtriangular, with apex widely rounded, about 0.4 times as wide as pronotum, about 0.4 times as long as wide, delicately separated from mesoscutum. Mesoscutum as wide as pronotum at widest point, distinctly narrowed medially, anterior angles rounded, anterolateral margin sigmoid, lateral angle acute, posterior angles wide, posterior margin V-shape incised, posterolateral areas of mesoscutum disc declivent posteriorly; disc with two setae on tubercles, at 1/3 of mesoscutum width. Mesoscutellum about as long as wide, diamond-shape, anterior and lateral angles acute, posterior angle rounded. Mesopostnotum in form of transverse band, slightly widened in median portion. Metascutum narrower than mesoscutum, anterior angles widely rounded, lateral angles acute, anterolateral margin concave, posterior margin arcuate, with deep median arcuate incision. The suture between metascutum and metascutellum weakly visible, metascutellum subtriangular, longer than wide at base.Parapteron with three distinct setae.Fore wing (Fig. 2A,B) membranous, narrow, elongate, about 3.5 times as long as wide, widest at 2/3 of length. Anterior margin merely arcuate, slightly bent at very base, anteroapical angle widely arcuate, apex rounded, posteroapical angle widely arcuate, tornus arcuate, claval margin straight, with incision between terminals of Pcu (claval apex) and A1. Stem ScP + R + MP + CuA slightly arcuate, very short stalk ScP + R + MP + CuA leaving basal cell, stem ScP + R oblique, straight, forked in basal half of fore wing length, branch ScP + RA, oblique, reaching anterior margin slightly distally of half of fore wing length, slightly distally of ending of CuA2 branch; branch RP slightly arcuate, a little more curved in basal section, reaching margin at anteroapical angle; stalk MP + CuA slightly shorter than basal cell; stem MP almost straight, forked in apical half of fore wing, at about 2/3 of fore wing length, with three terminals reaching margin between apex and posteroapical angle; stem CuA shorter than branches CuA1 and CuA2, about half as long as branch CuA1; claval vein CuP weak at base, not thickened distally; claval vein Pcu straight, claval vein A1 straight. Basal cell present, subtriangular, about twice as long as wide, basal veinlet cua-cup oblique, no other veinlets present; cell r (radial) very long, longer than half of fore wing length; cell m (medial) the shortest, shorter than cell cu (areola postica). Margins of fore wing with fringe of long setae, starting on costal margin near base of fore wing, ending at level of middle of cell cu; longitudinal veins with distinct, scarcely but evenly dispersed, movable setae; terminal section of CuP with two setae; costal margin with row of short, densely distributed setae, apical margin, tornus and claval margin with rows of scaly setae.Hind wing (Fig. 2B) membranous, shorter than fore wing, 3.23 times as long as wide. Costal margin bent at base, then almost straight up to the level of ScP + RA end and wing coupling lobe, then straight to anteroapical angle, anteroapical angle widely arcuate, apex arcuate, posteroapical angle arcuate, tornus straight, claval margin merely arcuate, posteroclaval angle angulate; stem ScP + R + MP bent at base, then straight, stem ScP + R short, branch ScP + RA short, about as long as stem ScP + R, branch RP arcuate basally than straight, reaching apex; stem MP arcuate, forked slightly distad CuA1 terminus level, branch MP1+2 slightly arcuate, reaching margin at posteroapical angle, branch MP3+4 straight, reaching tornus; stem CuA slightly bent at base, then straight, forked slightly distad ScP + R forking, branch CuA1 arcuate, branch CuA2 short, straight, slightly oblique, reaching tornus; claval vein CuP weak, visible only at base, claval vein Pcu slightly arcuate; wing coupling apparatus (fold) with a few short setae.Legs slender, relatively long, profemora armed (Fig. 2C–H). Procoxa as long as profemur, narrow, flattened. Protrochanter scaphoid, elongate, with long apical and subapical setae. Profemur flattened laterally, about as long as protibia, ventrally armed with four large setae on elevated plinths; dorsal margin with row of short, decumbent setae. Protibia narrow, rounded in cross section, covered with short setae, a few longer setae in distal portion. Protarsus—single, long tarsomere, plantar surface with row of semi-erect setae; tarsal claws long, straight, directed ventrally, no arolium nor empodium.Mesocoxa elongate, narrow, slightly flattened. Mesotrochanter scaphoid. Mesofemur slender, flattened laterally, dorsal margin with short setae. Mesotibia subequal to mesofemur, slender, covered with setae, two apical setae slightly thicker and longer. Mesotarsus with three tarsomeres, basimesotarsomere the longest, shorter than cumulative length of mid- and apical mesotarsomere, plantar margins with setae, two apical setae slightly longer and thicker; midmesotarsomere the shortest, 1/3 of basimesotarsomere length, a few setae on plantar surface; apical tarsomere shorter than basimesotarsomere, twice as long as midmesotarsomere, plantar surface with a few, scarcely dispersed setae, tarsal claws long, narrow, directed ventrally, no arolium nor empodium.Metacoxa conical, narrow. Metatrochanter scaphoid, elongate. Metafemur slender, laterally flattened, longer than mesofemur, dorsal margin with row of short setae. Metatibia, long, slender, 1.6 times as long as metafemur, with suberect setae of different size, two larger and longer and two shorter setae subapical setae. Metatarsus slightly less than half of metatibia length, with three tarsomeres, basimetatarsomere the longest, more than twice as long as apical metatarsomere, 1.5 times as long as combined length of mid- and apical metatarsomere, plantar surface with scarce decumbent setae; mid metatarsomere the shortest, 1/4 of basimetatarsomere length, plantar surface with a few setae, two apical ones slightly thicker; apical metatarsomere about 0.4 of basimetatarsomere length, with scarcely dispersed setae on along plantar surface; tarsal claws, long, slender, other pretarsal structures absent.Abdomen (Fig. 1F) narrowly attached to thorax, tergite segment shorter, 2nd tergite distinctly longer, 3rd to 8th tergites of similar length; pygofer narrowing apicad, ventral margin strongly elongated posteriorly; anal tube short, directed posterodorsad, anal style shorter than anal tube. Paramere lobate, ventral margin with acute, small process, apical and dorsal margins rounded. Aedeagus (Fig. 2I) geniculately bent at base, directed dorsad, tapered apicad.Female. Unknown.Megalophthallidion sp. (5th instar nymph)(Figs. 3A–D, 4A–F)Figure 3Megalophthallidion sp. (MAIG 6688), nymph. (A) Photo of body, dorsal side and (B) drawing of body dorsal side; (C) photo of body dorsal side and (D) drawing of body ventral side. Scale bars: 0.5 mm (A–D).Full size imageFigure 4Megalophthallidion sp. (MAIG 6688), nymph. Photo of clypeus and (B) drawing of clypeus; (C) photo of proleg, and (D) photo of mesoleg, and (E) photo of metaleg; (F) photo of posterior part of abdomen ventral side. Scale bars: 0.1 mm (A–F).Full size imageMaterialNymph, 5th instar, MAIG 6688 (BUB 1799), deposited in Museum of Amber Inclusions (MAIG), University of Gdańsk, Poland. Piece of amber 13 × 6 × 2 mm, cut from larger lump, polished flat on one side, more convex on the other.Diagnostic charactersThe nymph of Megalophthallidion gen. nov. is similar in general body shape to the only known fossil protopsyllidioidean nymph described from Lower Cretaceous Lebanese amber—Talaya batraba Drohojowska et Szwedo, 2013. The nymph of Talaya batraba is 2nd or 3rd instar, therefore some features are difficult to compare with this last instar nymph of Megalophthallidion gen. nov. The morphological states observed in those two specimens are: head covered with strongly expanded disc and expanded disc of pronotum, however shapes and ratios of these structures differ; compound eyes on ventral side of head, shifted laterad (ommatidia on cones in T. batraba, while ventroposterior expansions are present in Megalophthallidion gen. nov.); compound eyes visible from above as short, stout cones in fissure between posterior margin of disc (hypertrophied vertex) and anterior margin of pronotum (compound eyes (?) are visible on dorsal side of Permian Aleuronympha bibulla Riek, 1974); in Megalophthallidion gen. nov. rostrum reached mesocoxa, while in Talaya batraba distinctly exceeds length of the body; abdomen with 9 segments; tergites of abdominal segments 5th–9th expanded posterolaterad in form of fan-like expansion; 9th abdominal segment short, placed ventral; anal tube short, cylindrical, epiproct (?) globular.DescriptionNymph, 5th instar (Figs. 3A–D, 4A–F). Body oval shaped, dorso-ventrally flattened, 1.5 times longer than wide with segmentation visible; on the ventral side slightly concave. Length of body c. 1.56 mm long, outline, in dorsal view, maximum width of body 0.94 mm; length of head and pronotum (cephaloprothorax) c. 0.46 mm in midline, width c. 0.83 mm; cumulative length of mesonotum + metanotum c. 0.25 mm; abdomen c. 0.8 mm long. Dorsal side (Fig. 3A,B) with distinct median line (ecdysial line), not reaching anterior or posterior margin of the body, the line distinctly roof-like in abdominal portion. Anterior margin of head (cephaloprothorax) disc arcuate, lateral angles rounded; anterior margin of pronotum arcuate, lateral margins arcuately diverging posteriad, posterior margin distinctly arcuate, anterior angles widely rounded, posterior angles acutely rounded, disc elevated, convex, lateral portions declivitous; the fissure between posterior margin of head disc and anterior margin of pronotum narrow, widened medially, with stalked compound eyes popping out.Head partly separated from prothorax, wide in ventral view. Bases of antennae protruding anterolaterally, wide, anterior margin arcuate, with a small lump extending anteriorly connecting margin with vertex expansion. Suture separating anteclypeus and postclypeus visible in ventral aspect (Fig. 4A,B). Postclypeus about three times as long as wide, oval, slightly swollen, without any setae; weak traces of salivary pump muscle attachments visible. Anteclypeus about as long as postclypeus, widened in upper section below clypeal suture, convex, carinately elevated in lower section, with sides distinctly declivitous, clypellus long, carinately elevated. Lora (mandibulary plates) distinct, separated from anteclypeus by shallow suture, with upper angles at half of postclypeus length, lower angles at half of anteclypeus length, about as wide as half of postclypeus width. Maxillary plates narrow. Genal portion of head enlarged, medial portion arcuately convex; lateral sections narrowing laterally, terminally encircling bases of compound eyes. Antennae short (Fig. 3C,D), placed in front of genal portion. Antennal flagellum indistinctly subdivided into four segments. Rostrum (Fig. 4A,B) three-segmented, 0.2 mm long, with apex reaching apex of mesocoxae; apical segment about 2.5 times as long as subapical one.No lateral sclerites on meso- and metathorax, only one plus one large medial sclerite on both meso- and metathorax. Mesothoracic and metathoracic wing pads distinct, wide, subtriangular, with posterior apices directed posteriorly; lateral portions of mesothoracic wing pads arcuate. Fore wing pad 0.6 mm long, with small, straight humeral lobe, forming a right angle, not protruding anteriorly. Mesothoracic tergites slightly larger than metathoracic segments (respectively c. 0.14 mm and c. 0.12 mm long in midline, 0.26 mm and 0.27 mm in lateral lines); mesothoracic tergum with distinct median elevation (low double crest with ecdysial line in between), slightly wider than long in midline, anterior margin arcuate, lateral margins straight, subparallel, posterior margin concave. Metathoracic wing pad apex slightly exceeding mesothoracic wing pad. Metathoracic tergum wider than long, slightly shorter than mesothoracic tergum, with distinct elevation in the middle.Legs relatively long (Figs. 3C,D, 4C–E). Coxae of legs placed near the median axis of the body. Prolegs: procoxal pit with margins elevated, procoxa conical (c. 0.1 mm long), protrochanter scaphoid, about as long as procoxa, profemur c. 0.13 mm long, slightly flattened laterally, merely thickened, protibia longer than profemur, c. 0.23 mm long; tarsus shorter than protibia, basiprotarsomere about as long as apical protarsomere, the latter with distinct tarsal claws, and wide arolium. Mesoleg similar to proleg, mesocoxa conical (c. 0.1 mm long), mesotrochanter scaphoid, mesofemur (c. 0.13 mm) slightly flattened laterally, mesotibia slightly longer than mesofemur (c. 0.18 mm), mesotarsus slightly shorter than mesotibia, three-segmented, basimesotarsomere the longest (c. 0.07 mm), about as long as combined length of mid- and apical mesotarsomeres (c. 0.04 mm respectively), arolium wide, tarsal claws distinct. Metaleg: metacoxa conical (c. 0.1 mm), metatrochanter scaphoid, about as long as metacoxa (c. 0.12 mm). Metafemur (c. 0.17 mm) slightly more thickened than pro- and mesofemur, metatibia slightly longer (0.19 mm) than pro- and mesotibiae. Metatarsus three-segmented: basimetatarsomere about as long (0.08 mm) as combined length of mid- and apical metatarsomeres (0.04 mm respectively), arolium lobate, wide, tarsal claws distinct, widely spread.Abdomen (Fig. 3A–D) 9-segmented, narrow at base, widening fan-shape posteriorly, 1st segment visible from above, segmentation visible, abdominal terga 5th–9th expanded posterolaterally. Tergites carinately elevated in the middle, separated by ecdysial line. 1st sternite visible in ventral view, sternites 2nd–4th fused medially, sternites 5th–9th separated; 9th abdominal segment short (Fig. 4F), placed ventrally, under tergal expansion; anal tube short, cylindrical, epiproct (?) globular. More

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Nearly two years into the United Nations Decade of Ocean Science, research, including some featured in this month’s issue, shows that there is still a wealth of scientific secrets to uncover in the ocean depths.
In many ways, considering the ocean as a single unit is overly broad. The global ocean covers 71% of the planet’s surface, reaches down to depths of over 10 kilometres, includes about 1.35 billion cubic kilometres of water and houses an approximated 2.2 million eukaryotic species. There are distinct regions, with distinct physical properties, and, in turn, there are distinct species. Yet, the world’s oceans do have a level of physical and thematic connectivity.
Credit: Daria Zaseda / DigitalVision Vectors / GettyPhysically, a large part of the connection is related to the presence of large rotating ocean currents that transfer heat across latitudes and contribute to ocean mixing (thermohaline circulation). Some of these currents are warming at alarming rates — up to three times faster than the rest of the ocean, leading to questions about the underlying mechanisms of the warming and expectations for change.Focusing on western boundary currents (WBCs) in the Southern Hemisphere, in an Article in this issue of Nature Climate Change, Li and colleagues answer a long-debated question on the mechanisms of change, showing that temperature-gradient-related instabilities, rather than flow-speed-related instabilities are behind the shifts. In another Article, focusing on the global future changes of eddies (including eddy-rich WBCs), Beech and colleagues report the development of a flexible method that maximizes local model resolution while minimizing computational costs, to reveal the long-term geographical specificities and nonlinear temperature increases expected to 2100 (see also the News and Views article by Yang on these papers).A recent paper1 has demonstrated the important role of large ocean currents in defining plankton biogeography and dynamics, and WBC warming has previously been linked to impacts such as fishery collapses. The tight link between physical processes and biological responses is an underscoring theme of climate change ecology, but is perhaps more apparent in the open ocean, where physical processes can be easily (if imperfectly) linked to primary productivity using remotely sensed phytoplankton pigment absorption, and where life is generally less impacted by geographical, political or disturbance-based boundaries compared with land and freshwater systems. These aspects may facilitate modelling of current and future communities, while also allowing broader assumptions to be made about biological movement and connectivity.Despite these benefits, understanding ocean change comes with its own difficulties. Biological sampling, while easy enough in the surface waters, becomes increasingly difficult at depth. Although future habitats for various organisms have been projected on the basis of their thermal limits in the ocean, these predictions often still rely on temperatures at the surface of the sea. Addressing this, Santana-Falcón and colleagues report in an Article the global mapping of ocean temperature changes to depths of 1,000 metres, and reveal the complex depth-dependent changes in thermal upper and lower bounds that marine organisms will soon be subjected to. In another Article, Ariza and colleagues neatly address the issue of directly monitoring deep-ocean change by compiling a large database of sound-based observations, and subsequently classifying the ocean’s ‘echobiomes’, defined as sound-scattering communities with comparable structural and functional properties (see also the accompanying News and Views article by Hazen). Sound-based methods are also increasingly being used on land2, and represent an exciting tool for monitoring change, particularly in hard-to-reach places such as deep forests, high mountaintops or underground. While the sound reflection method used in the study by Ariza and colleagues has limits in its ability to identify organisms at the individual or species levels, it does provide a community-level focus on change, which remains much needed in the field of global change ecology.At the other end of the spatial spectrum, research by Lee and colleagues reported in an Article also in this issue dives deep into the DNA of a keystone ocean organism (a copepod), to understand the mechanisms that may allow longer-term adaptation to warming and pH stress. The work reveals remarkable adaptation over just a few short generations, which is linked to epigenetic changes. As climate change impacts continue to escalate, the ability of organisms to invoke both shorter- and longer-term adaptations has become an increasingly relevant area of research. Epigenetics has previously been reported as a quick-response method to cope with environmental stress, and may be particularly relevant in defining the adaptation of short-lived animals such as insects and the resilience of the communities they uphold.The five research pieces linked to the oceans in this issue reveal just some of the diversity of topics, methods and scales relevant to understanding global change. Also increasingly relevant are works on ocean conservation3 and on the social and economic impacts of ocean change4,5. Like climate change science, the topic of ocean change is less of a field, and more of a cross-disciplinary theme. More

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MaterialsWe collected from the literature and available databases a dataset of radiocarbon dates from Europe (West of 60°E and North of 37°N) either obtained from remains of the four analyzed species or from archaeological layers where they have been observed. However, we only considered observations dated between 7500 and 47,000 cal BP: their scarcity before this period may bias the GAMs, and after it, domesticated cattle, pigs and (later) horses arrived in Europe, making it difficult to differentiate them from their wild forms.We excluded any record fitting one or more of the following conditions: unreliable; not in accord with the expected chronology of their archaeological layer; without a reported standard error; available only as terminus ante/post quem.All dates were calibrated with OxCal5 version 4.4 using the IntCal20 curve51, and we further excluded any record for which calibration resulted in an error, resulting in the number of points presented in Table 1 as “Original dataset” (available at the link https://doi.org/10.6084/m9.figshare.20510364).Table 1 Number of observations for each species.Full size tableSDMs based on GAMs need presence/background data, not frequencies; moreover, multiple observations (i.e., presence in different archaeological layers) from the same site and time slice are likely to introduce stronger sample biases linked to chrono-geographically differential sampling efforts. For this reason, we collapsed our observations by keeping only one point per grid cell per time slice for each species, leaving the number of observations reported in Table 1 as “Collapsed datasets”, used for all the analyses presented in this work.To perform all analyses, we used the R package pastclim v. 1.042 to couple each observation from the collapsed datasets to paleoclimatic reconstructions published in8 by setting dataset = “Beyer2020”. These are based on the Hadley CM3 model, include 14 different bioclimatic variables at a spatial resolution of 0.5°, and are available for the whole world every 1000 years until 22 kya and every 2000 years before that date (referred to in the manuscript as “time slices”). Specifically, each observation was associated with the relevant bioclimatic reconstruction based on its average age and spatial coordinates.As already mentioned, the four species analyzed show different preferences regarding temperature, habitat, and altitude. Therefore, for the Species Distribution Modelling, we choose five environmental variables that should be able to capture such differences: two measures of temperature (BIO5, maximum temperature of the warmest month, and BIO6, minimum temperature of the coldest month); two variables to help capture habitat differentiation (BIO12, total annual precipitation, and Net Primary Productivity, NPP), and one measure of topography (rugosity42).High collinearity can be problematic in SDMs; we confirmed that all our variables had a correlation below 0.7, a threshold commonly adopted for this kind of analysis52,53.Whilst the GAMs predicted all time points; we visualized our results by creating an average estimate for the following periods: pre-LGM (from the beginning of the time range analyzed, i.e., 47 kya to 27 kya), LGM (from 27 to 18 kya), Late Glacial (from 18 to 11.7 kya), Holocene (from 11.7 kya to the end of the time range analyzed, i.e., 7.5 kya).MethodsWe generated 25 sets of background points for each species to adequately represent the existing climatic space in our SDMs. Each set was generated by sampling, for each observation, 50 random locations matched by time. This resulted in n = 25 datasets (“repetitions”) of background points and presences (observations) for each species, which we used to repeat our analyses to account for the stochastic sampling of the background. For each dataset, we used GAMs to fit two possible models: a “constant niche” model, which included only the environmental variables as covariates, and a “changing niche” model, that also included interactions of each environmental variable with time (fitted as tensor products).In GAMs, the effect of a given continuous predictor on the response variable (in our case, the logit transformed probability of a presence) is represented by a smooth function; this smooth function can be linear or non-linear and can become highly complex in shape depending on the number of knots selected by the GAM fitting algorithm. The interaction between two covariates is modelled by tensor products54; this approach is equivalent to an interaction term in a linear model but with the added complexity of the smooth function. In our models, we confine tensor products to the interaction between an environmental variable and time; a simple way to think about such a tensor product is that it allows the smooth representation of the relationship between the variable and the probability of a presence to change progressively over time.GAMs were fitted using the mgcv package in R54 using thin plate regression splines (TPNR; bs = “tp”, default in mgcv) for environmental variables and their tensor products with time in the “niche changing” models. The GAM algorithm automatically selects the complexity of the smooth most appropriate to the data that are being fitted; as GAM can have issues with overfitting, we added an additional penalty against overly complex smooths (gamma = 1.4) and used Restricted Maximum Likelihood (REML = TRUE), as recommended by54. It is possible that even with these settings, the complexity of the smooth is not sufficient; we used mgcv::gam.check() to check this, and increased the basis dimension of the smooth, k, to make sure that k-1 was larger than the estimated degrees of freedom (edf). We found the best maximum thresholds for k to be 16 for bio06 and 10 for all other variables.We checked for non-linear correlation among variables using the mgcv::collinearity function and checked the values of estimated concurvity. All estimates were below the threshold of 0.8 in all models, runs and variables except for a few instances for time (Supplementary Figs. 5–8). We consider this not to be worrying: this is most likely a result of sample bias, and GAM is known to be robust to correlation/concurvity55,56.We verified the model assumptions by inspecting the residuals using the R package DHARMa57. Standard tests for deviations from the expected distribution and dispersion were non-significant for all repetitions for all species, as were the tests for outliers. Furthermore, we tested for spatial autocorrelation among residuals by computing Moran’s I; all tests were either non-significant or, when significance was detected, the estimate of Moran’s I was very close to zero, revealing a trivial deviation from the assumptions which should not impact the results (Supplementary Tables 1–4).We performed model choice (Supplementary Tables 5–8) by comparing the constant- and changing-niche models for each combination of species and repetition using the Akaike Information Criterion (AIC). AIC strongly supported the changing-niche model in all species and repetitions, an inference supported by the higher Nagelkerke R2 and expected deviance for those models than for the constant-niche ones (Supplementary Tables 5–8).The model fit for each of the changing niche GAMs was evaluated with the Boyce Continuous Index25,26, designed to be used with presence-only data58,59. We set a threshold of Pearson’s correlation coefficient  >  0.8 to define acceptable models25 (Supplementary Table 9).The relative importance of each environmental variable was quantified for all the models above the BCI threshold of 0.8 in two different ways. Firstly, we computed the total deviance explained by each variable by simply fitting a GAM with only that variable. We then estimated the unique deviance explained by each variable by comparing the full model with one for which that variable was excluded (i.e., we computed the explained deviance lost by dropping that predictor). The difference between the two values represents the deviance explained by a variable which can also be accounted for by other variables (i.e., the deviance in common with other variables).To achieve more robust predictions60, we averaged in two different ensembles the repetitions for the changing niche GAMs with BCI  > 0.8: by mean and median. This step is intended to reduce the weight of models that are highly sensitive to the random sampling of the background60. Then, for each species, we selected the ensemble (either based on mean or median) with the higher BCI as the most supported and used it to perform all further analyses.The effect of different variables through time was visualized by plotting the interactions of the GAMs. For each model with a BCI  > 0.8, we used the R package gratia27 to generate a surface with time as the x-axis, the environmental variable as the y-axis, and the effect size as the z-axis (visualized as colour shades). We then plotted the mean surface for each species, which captures the signal consistent across all randomized background sets.To visualize the prediction for each species, we then transformed the predicted probabilities of occurrence from the ensemble into binary presence/absences by using the threshold needed to get a minimum predicted area encompassing 99% of our presences (function ecospat.mpa() from the ecospat R package61). The binary predictions were then visualized using the mean over the time steps within each major climatic period.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

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