Ecology

We asked whether the mating of male and female fruit flies would be affected by the presence of parasitoid wasps. We placed a pair of D. melanogaster flies in a small Petri dish, either with or without parasitoid wasps (Fig. 1a). In an initial experiment we used the wasp Leptopilina boulardi, which specializes on D. melanogaster and on closely related fly species14.Fig. 1: Exposure of Drosophila to wasps accelerates sexual behavior.a Courtship arena containing a male and virgin female fly with (left) and without (right) two wasps, one male and one female. b Copulation latency of D. melanogaster. p  More

Now that China has finally updated its List of Wildlife under Special State Protection, a more nimble and responsive approach is needed to aid conservation. The list should be reviewed every year, as well as subjected to the planned five-yearly updates. Species can quickly become endangered in times of rapid development.The latest additions are the first in more than 30 years (see go.nature.com/2q7sfga). During that time, China has changed profoundly, but the list of protected species has not kept pace. This lag has been disastrous for some animals that were not given the protection they needed.At least 33 species became extinct in China and many more are critically endangered (Y. Xie & W. Sung Integr. Zool. 2, 26–35; 2007; Z. Jiang et al. Biodivers. Sci. 24, 500–551; 2016).An independent government committee should be created to oversee amendments. When making decisions, it could refer to appendices of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) and the ‘red lists’ of threatened species curated by the Chinese Academy of Sciences and the International Union for Conservation of Nature (IUCN). These steps would build on the more forceful approach to managing wildlife that China has taken since the start of the COVID-19 pandemic. More

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For each case study area, a search query was executed (Table 1). Query terms were based on the hashtags of the geographical name of the study areas; therefore, the post download was related to the name of the study area (e.g., Galapagos), with all downloaded posts including this name as query. Query search was limited to English, the most common language amongst tourists. This might have overlooked posts where the name of the place was in a different language. For most marine areas, this was considered irrelevant as the name of the place is not translated to other languages (e.g., Tayrona, Vamizi, Skomer). In some of the cases, the name of the place could appear in a variety of languages (e.g., Great Barrier Reef), however, the use of non-English place hashtags as queries generally retrieved a significantly lower number of posts (e.g., Gran Barrera de Coral in Spanish with 1900 posts, or Grand Barrière de Corail in French with 14 posts, while Great Barrier Reef had over 10,000 posts). In the specific case of Easter Island, we observed that the use of three particular queries was linked to a high number of posts: Easter Island and the local name Rapanui had over 10,000 posts each, and Isla de Pascua in Spanish had 8700 posts. In this case, three separate posts’ downloads were performed, and data were merged for subsequent analysis. The above, rather than a limitation of the methodological approach, demonstrates its flexibility to adapt to different data acquisition requirements.To illustrate the most relevant information contained as part of the posts downloaded for each of the 14 areas, we selected the 150 most frequent hashtags from each dataset in order to create the network graph and represent the dominant discourse in relation to the area in question. Network graphs were delineated using eigenvector, betweenness and edge betweenness as centrality measures. Eigenvector centrality measure (hereafter Eigenvector) allows identifying those hashtags that are frequently posted with other hashtags also frequently posted, and it can be interpreted as the pairs or groups of features more frequently related to the case study by the users. Betweenness centrality (hereafter betweenness) and edge betweenness centrality (hereafter edge betweenness) provide information about clusters of hashtags that describe users’ experiences or perceptions and that connect (by means of a hashtag) to other clusters representing other types of experiences or perceptions. These high betweenness hashtags structure the general discourse about an area and their removal would fragment the network and disconnect distant concepts. Therefore, hashtags and links with high betweenness can show the discourse parallel or additional to the main discourse and their relations, allowing to identify less frequent activities or perceptions but that are equally important to understand the network as a whole.Network centrality measuresResults indicated that network graphs captured information on distinct types of ecosystem services, for example, those based on wildlife and nature, heritage, or beach tourism. In areas such as Galapagos, central hashtags were nature, wildlife, photography, travel and adventure, evidencing a preference for wildlife and nature-based tourism. In this area, betweenness evidenced the connections between the most frequent hashtags group with other peripheric hashtags and provided a complete picture on the discourse of Galapagos’ visitors (Fig. 2). As such, nature and wildlife-based travel and photography is related with natural science concepts like evolution and endemism, and specific biotic and abiotic components like crabs and waves, altogether related with positive feelings (i.e., happy). Other areas emerging for their wildlife and nature were Skomer nature reserve, characterised by the hashtags birds (including the species Puffin), nature and wildlife photography; and Península Valdés, characterized by many locality names and by fauna, with the frequently posted hashtags’ wildlife, whales and nature funnelling most connections to other less frequent hashtags (e.g., wind, hiking, relax) and providing a full picture of the social perception on nature recreation activities, iconic fauna and positive feelings. Three networks, Sandwich Harbour, Glacier Bay and Macquarie Island also included popular hashtags related with nature, wildlife and photography; however, most hashtags had low betweenness and edge betweenness limiting the diversity of the posts (all network graphs are available at the Figshare repository, https://doi.org/10.6084/m9.figshare.13325627.v2).Figure 2Example of network graphs in Galapagos case study. In plot (A) node size represents the Eigenvector centrality and edges represent normalized strength (weighted degree). In plot (B) node size represents normalized Betweenness centrality and edges represent normalized Edge betweenness.Full size imageRegarding cultural heritage, Easter Island was characterised by popular hashtags related with Easter Island stone statues (moais) and with travel; and edge betweenness evidenced a diversity of peripherical nodes that describe other cultural elements, like design, music and food, and evidence social preferences for different cultural elements of the island, beyond the moais. Other areas reflected cultural identity by the frequent post of local names (e.g., Ytrehvaler), words related with the country’s identity (e.g., Isole Egadi) and positive feelings about this identity (e.g., Tawharanui). In Tayrona National Park network, the full discourse identified cultural identity like Kogui (indigenous culture) linked with the popular posts related with nature and summer holidays. Similarly, in Tawharanui and Isole Egadi, beach, nature and summer where the most frequent posts that, in some cases, where connected with places and activities. In these cases, and particularly in Isole Egadi and Ytrehvaler, edge betweenness allows to identify connections between places and activities, wildlife or natural structures, providing relevant information for area management and conservation.A group of areas were appreciated by their underwater ecosystems. For Great Barrier Reef, popular hashtags were related with the coral reef: ocean, diving, underwater photography, travel, nature, coral and reef; whereas betweenness highlighted a set of hashtags related with conservation: science, sustainability, save the reef, 4 ocean (Fig. 3) and evidenced the presence of a conservationist discourse in the social media. In Toguean Island network, the frequent hashtags beach, wonderful and charming are connected to peripherical hashtags related with the sea (e.g., sea life, diving), while in Vamizi, popular hashtags were related with high-income tourism, private island, travel, luxury travel, and were connected to less frequent hashtags linked to the sea, including recreational fisheries. These last two examples illustrate differences in the benefits, and beneficiaries, provided by two popular touristic destinations.Figure 3Example of network graphs in Great Barrier Reef case study. In plot (A) node size represents the Eigenvector centrality and edges represent normalized strength (weighted degree). In plot (B) node size represents normalized Betweenness centrality and edges represent normalized Edge betweenness.Full size imageNetwork communitiesThe division of hashtags in communities allows for a more detailed exploration of the words included in the 150 most frequent hashtags selection, independently of their centrality measures, and allowed a categorisation of hashtags within cultural ecosystem services classes in each area (Table 2). Hashtags were grouped in 3 to 5 communities, with some communities relatively constant across case studies, e.g., aesthetics, wildlife and nature appreciation (Fig. 4) (all other network graphs are available at the Figshare repository, https://doi.org/10.6084/m9.figshare.13325627.v2).Table 2 Cultural Ecosystem Services’ types (CES) depicted from the community analysis (Fast Greedy algorithm). The order of the CES class does not imply a priority rank.Full size tableFigure 4Communities assessed through Fast-Greedy algorithm for the case studies Glacier Bay (A) and Tayrona (C). The node size represents the normalized Eigenvector and the colour represents the community. The colour and width of the edges represents the normalized edge strength (weighted degree).Full size imageIn some of the areas, the communities were diverse in hashtag composition, for example, in Galapagos, wildlife (and related words) was distinctive of several communities, but other communities were characterised by different concepts: beach, holidays, happiness, snorkelling and diving. In Easter Island, the hashtags related with the stone statues and cultural heritage characterise one community, while the other communities include a diversity of hashtags classified under adventure, nature, underwater recreational activities; therefore, it widens the information provided by the centrality metrics. Tayrona (Fig. 4) is also a diverse network with one community characterised by hashtags like beach, summer, happiness (wellbeing), but other communities contain a diversity of hashtags like forest, hiking, indigenous and wildlife (classified in recreational, cultural heritage, nature and aesthetics; Table 2).In some areas, the communities were not so diverse, but provided additional information on the posts. For example, in MacQuarie Island the communities highlighted iconic fauna, including several penguin species, and biodiversity conservation. In several areas, network communities informed of the iconic fauna and specific places: puffins and other bird species in Skomer; southern right whale, sealions and penguins in Península Valdés; glaciers and mountains in Glacier bay (Fig. 4); desert and dunes in Sandwich harbour. Finally, Ytrehvaler is a network characterised by many local names (in Norwegian), evidencing a national tourism, and hashtags related with scenery.Merged network of the 14 case studiesThe merged network highlighted several hashtags that act as bridges between communities of hashtags (Fig. 5). Nature, travel, photo and travel photography are key to structure the global network. However, several low eigenvector hashtags connect smaller groups: sunset and island connect the subgroups from Easter Island, Isole Egadi and Vamizi.Figure 5Global network graph including the fourteen case studies where the node size represents the Eigenvector centrality. The coloured clusters arrange the case studies to facilitate the visual identification of areas connected in the network.Full size imageFrom the hashtag travel photography diverges a branch that connects 7 areas through adventure; a small group of hashtags deriving from this node represent Sandwich harbour and Vamizi, connected through Africa. The hashtag ocean, connected to adventure, relates Great Barrier Reef with Tawharanui, and to wanderlust (a German expression for the desire to explore the world) that connects Península Valdés, Skomer and Macquairie Island. These three areas and Tayrona are also connected through the central hashtag travel photography, and Skomer and Macquairie Island through wildlife photography. The hashtag adventure is also connected to a group of hashtags from Galapagos that also derive to the high eigenvector hashtag nature.The hashtag nature is key to include the fragile sub-network Ytrehvaler, and also derives to other high eigenvector hashtag, travel, that in turn, connects to the small sub-network from Glacier bay. Photo, a central hashtag related with travel, connects to paradise, that is key to integrate Toguean Island, a few hashtags from Tayrona related with the Caribbean and beach, and a group of hashtags from Peninsula Valdez related with whale watching. Some other small hashtags, that are connected to high eigenvector hashtags but are not included in any particular area are shared by many of the areas, e.g., sun, relax, landscape photography, nature lovers, sunset, sky. More

Vegetation history of the Acıgöl areaOur palynological analyses of 72 regularly spaced samples show a diversified vegetal landscape alternately wooded and open, in response to orbitally driven climatic cyclicity. However, arboreal pollen values remain almost constantly below 50% of the Pollen Sum (PS) (average 27.5%, median 22.8%), which corresponds to an overall open landscape (Fig. 3). Among herbaceous plants, the dominant taxa are steppics such as Artemisia, heliophilous and halophilous taxa including Calystegia, several Compositae, Convolvulus, Linum, Plantago ssp., Poaceae and Chenopodiaceae that could develop on the saline shores of Acıgöl lake during evaporitic periods. Forests are composed of a mixture of conifers, Mediterranean Pinus, Abies, Cedrus, Cupressaceae and Picea, associated with broadleaved trees dominated by Mediterranean oaks, i.e. deciduous and evergreen Quercus, with some Olea. Riverine trees such as Alnus, Salix, Populus, Tamarix, Juglans and Platanus have also been identified. Few Tertiary or megathermic relictual taxa (Carya, Liquidambar, Parrotia, Pterocarya fraxinifolia, Taxodiaceae, Tsuga, Zelkova) were identified so far in the pollen assemblages, mostly before 2.2 Ma, due to climatic cooling17,18 since the end of Tertiary which led to a decline in global biodiversity19,20.Figure 3Simplified pollen and NPP diagram in percentages of Acıgöl, core 3, based on the age model of Demory et al. [1]. Equidistant scale. Values are in percentages calculated on a pollen sum without Non-Pollen Palynomorphs (NPP), Ferns, Bryophytes and Algae. The beige rectangle corresponds to the date of the presence of Homo erectus at Kocabaş (Lebatard et al. [4]).Full size imageThe vast freshwater stretch of Acıgöl, located in a predominantly arid limestone hills environment, seems to have been a crucial resource for the mammalian fauna, which probably concentrated around the site in search of water and pastures. Indeed, low percentages of arboreal pollen imply that the landscape remained open throughout the sequence and suggest a marked grazing pressure by herbivores in addition to climatic factors21,22,23.Coprophilous fungi spores, cereals and other ancestors of cultivated plantsCoprophilous fungi spores are excellent indicators of herbivorous mega-mammal herds since they grow exclusively on dung deposited by these animals24. At Acıgöl, a wide variety of coprophilous fungi spores has been identified throughout the pollen record including: Sporormiella sp., Podospora sp., Delitschia sp., Sordaria sp. and Valsaria variospora (Figs. 3, 4). They provide evidence for a continuous presence of large herbivorous mammals around the lake throughout Quaternary.Figure 4Coprophilous fungi spores of Acıgöl, core 3. Equidistant scale. Age model is from Demory et al. [1]. In red: coprophilous fungi taxa..Full size imagePollens of Poaceae, such as Secale (rye) and Cerealia-type, have been identified throughout the sequence (Figs. 3, 5). Unexpectedly, they present the same morphological characteristics as that of modern cereal grains25,26, namely an average size of ≥ 40 µm and a large pore + annulus (≥ 8 µm). As by definition cereals are cultivated plants, we will call the corresponding plants “proto-cereals” to highlight that their pollen are identical to those of cereals. This resemblance can be seen clearly in Fig. 5, where we have brought together fossil cereals from Acιgöl (Fig. 5, photos 1–7), from Roman time (Fig. 5, photo 8), not modified by modern agricultural practices, and from the current wheat field of the Lauragais agricultural plain, Gardouch, France (Fig. 5, photo 9). Cerealia-type frequencies reach a maximum of 9% of the PS around 2.2 Ma and can be as abundant as wild Poaceae pollen (Fig. 3). The Cerealia/Poaceae ratio shows that 24.66% of all Poaceae are proto-cereals from 2.0 to 2.3 Ma (Supplementary Table 1). Such high proto-cereal rates are almost never reached in pollen records, even in recent periods and in the presence of agriculture, because of the very low pollen dispersal capacity of cereals27. A lowering of frequencies down to 2–4% range is recorded in younger periods (Fig. 3), as well as a step like decrease of the Cerealia/Poaceae ratio (Fig. 6). This change may be related to the Middle-Pleistocene Transition (MPT) cooling and to the mega-mammal fauna change from a Villafranchian to a Galerian type28. MPT and faunal changes occurred around 0.9–1.0 Ma, while a decrease in our proto-cereal starts around 1.5 Ma, however signs of cooling and amplified climatic cycles predate the MPT28.Figure 5Pollen grain of Cerealia and Triticum sp. from Acıgöl (ACI), core 3 (photos 1–7), the Roman site of La Verrerie, Arles, France (photo 8) and Gardouch, France, current wheat field (photo 9). Photographies with a photonic (photo 1 – 4 and 8) and a confocal microscope (photos 5-7 and 9). 1) sample ACI 239 m, age: 0.871 Ma. 2) sample ACI 435.50 m, age: 1.709 Ma. 3) sample ACI 532.44 m, age: 2.122 Ma. 4) sample ACI 509.50 m, age: 2.026 Ma. 5) sample ACI 552.57 m, age 2.206. 6) sample ACI 552.57 m, age: 2.206 Ma. 7) sample ACI 429.50 m, age: 1.681 Ma. 8) sample La Verrerie 1455, age: 50-70 BC (Roman). 9) current pollen of Triticum sp., age: 2000 AD. L: maximal length (µm).Full size imageFigure 6Cerealia/Poaceae ratio in %, % cultivated tree ancestors and % Olea of Acıgöl, core 3.Full size imageThe histogram of wild Poaceae and proto-cereal pollen size (Fig. 7a) shows that there are a number of pollen populations modes around 30, 37.5, 45–50, supporting the idea that the larger grain sizes cannot be interpreted as a tail of ‘anomalous’ wild Poaceae pollen. Moreover, comparison with the present-day pollen rain recorded in moss pollsters, sampled around the lake of Acıgöl (Fig. 7b and Supplementary Table 2), show that the large pollen size mode (≥ 40 µm) is nowadays nearly absent (0–0.97% of the PS, Cerealia/Poaceae ratio of 4.52%, Supplementary Tables 3 and 4), even in biotopes with wild Poaceae considered to be ancestors of cereals (Aegilops, sample 2a, cereal rate: 0.97% of the PS) or with cereals such as Hordeum (sample 3a, b and 4, cereal rate 0.31, 0.00, 0.33 of the PS respectively, Supplementary Tables 2 and 3).Figure 7a) Pollen size of wild Poaceae and proto-cereal of Acıgöl, core 3. The measurements were made on the 10 samples with the highest cereal pollen content. A total of 991 grains of pollen were measured. b) Current pollen rain at the Acıgöl lake and surroundings. 8 moss samples were collected and 354 measurements of the longest axis of the wild Poaceae and cereal pollen grain were made.Full size imageOur interpretation is that proto-cereals recorded throughout the Acıgöl sequence derive from wild Poaceae. Their emergence and predominance may have been favoured by the impact of large herbivore herds attracted to Acıgöl lake shores, and through genetic drift. Through the process of trampling, nitrogen enrichment of soils and browsing, large mammal herds could have altered the genotype of proto-cereals naturally present in Acıgöl and thus, favoured the emergence of modern cereals. For genetic reasons, the descendants of these proto-cereals are not represented today among cultivated Poaceae because domestication bottlenecks eliminate genetic variation29.Is there a relationship between the size of proto-cereal pollen and climate? To our knowledge, the genetic literature does not show any relationship between the increase in pollen size and temperature. However, there does seem to be a relationship with atmospheric drought30,31 which is said to have favoured the appearance of polyploidy in certain species of Poaceae. It cannot be excluded that climate has had an influence on the proto-cereal genome, but only the interaction between herds of large herbivores and proto-cereal steppes can explain why proto-cereal pollen has never been found in such abundance elsewhere in Pleistocene pollen records.The ancestors of cultivated trees (Olea sp., Juglans sp., Castanea sp., Corylus sp., Prunus t.), typical of the modern Mediterranean agriculture, are also present in the Acıgöl sequence (Fig. 3 and Supplementary Table 5). Their amount increases after 1.5 Ma, mainly due to Olea (Fig. 6). Other potentially edible plants such as Ephedra, Hippophae, all the Compositae and the Fagaceae have been identified in the pollen assemblages. They correspond to 54.4% of plants identified in the pollen assemblages. Among these plants, there are 72% grasses and 28% trees and, among edible organs, 51% are vegetables and 20% are seeds (Supplementary Fig. 1a,b). These results testify to the potential wealth of accessible food resources that human and animal populations could feed on. Interestingly, studies carried out in Spain on the present-day consumption of wild plants lead to results close to those obtained at Acıgöl, with 87% grasses and 13% trees32.In recent years, new biological and archaeological data obtained from sites with human occupation have improved our knowledge of the beginnings of agriculture and the modalities of its implementation. In the Levant, the Ohalo II site highlights the presence of proto-cereal seeds, and flint tools to harvest, as early as 23,000 years before the present33. Further north, on the archaeological site of Gesher Benot Ya’aqov, proto-cereal seeds (oats, Avena) as well as pollen from cereals and trees currently cultivated, were identified over a period ranging from 750,000 to 820,000 years34,35. Moreover, recent genetic data indicate that the emergence of agriculture did not occur at a single location at the onset of the Neolithic (e.g. the “Fertile Crescent” hypothesis) but is, on the contrary, an evolutionary and multi-regional long-term phenomenon36,37,38. Alternatively, or simultaneously, are the hominins also partly responsible by having developed episodes of a form of transitory “proto-agriculture”? We already know that this domestication process was discontinuous with shutdown and restart phases37,39. Acheulean lithic tools, characterised by symmetrically shaped bifaces, testify to the rather advanced cognitive capacities of early Pleistocene populations that may have visited the lakeshore of Acıgöl5. Hominin populations may also have benefited from this opportunity to diversify their food regime with easily harvested and nutrient-rich wild plants (Supplementary Table 5), as it is the case today for hunter-gatherer populations in Africa and elsewhere in the world. More

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