BUSCADOR RECOLECTA

[Usage Notes] GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms, Excel format This database includes thermal tolerance metrics for 2,133 species of multicellular algae, plants, fungi, and animals in 43 classes, 203 orders and 525 families from both aquatic, and terrestrial realms, extracted from published studies. Abbreviated citations are included in the 'REF_min' and 'REF_max' variable in the data file. For full citations, please see the attached workbook, "References_1_09_2017.xlsx". The data are available in both Excel and CSV formats in the Dryad Digital Repository (doi:10.5061/dryad.1cv08). Updates to the data and metadata will be curated through the iDiv data portal (https://idata.idiv.de/). For example, in the future we plan to include interspecific variation in the dataset, to provide multiple estimates of thermal tolerance limits for a given species where estimates determined using the best possible methods will be more highly ranked. GlobalTherm_upload_10_11_17.xlsx References_1_09_2017.xlsx GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms, CSV format This database includes thermal tolerance metrics for 2,133 species of multicellular algae, plants, fungi, and animals in 43 classes, 203 orders and 525 families from both aquatic, and terrestrial realms, extracted from published studies. Abbreviated citations are included in the 'REF_min' and 'REF_max' variable in the data file. For full citations, please see the attached workbook, "References_1_09_2017.xlsx". The data are available in both Excel and CSV formats in the Dryad Digital Repository (doi:10.5061/dryad.1cv08). Updates to the data and metadata will be curated through the iDiv data portal (https://idata.idiv.de/). For example, in the future we plan to include interspecific variation in the dataset, to provide multiple estimates of thermal tolerance limits for a given species where estimates determined using the best possible methods will be more highly ranked. GlobalTherm_upload_02_11_17.csv References_1_09_2017.xlsx, How climate affects species distributions is a longstanding question receiving renewed interest owing to the need to predict the impacts of global warming on biodiversity. Is climate change forcing species to live near their critical thermal limits? Are these limits likely to change through natural selection? These and other important questions can be addressed with models relating geographical distributions of species with climate data, but inferences made with these models are highly contingent on non-climatic factors such as biotic interactions. Improved understanding of climate change effects on species will require extensive analysis of thermal physiological traits, but such data are scarce and scattered. To overcome current limitations, we created the GlobTherm database. The database contains experimentally derived species’ thermal tolerance data currently comprising over 2,000 species of terrestrial, freshwater, intertidal and marine multicellular algae, pl ants, fungi, and animals. The GlobTherm database will be maintained and curated by iDiv with the aim of expanding it, and enable further investigations on the effects of climate on the distribution of life on Earth., Peer reviewed

[Methods] Author contributions: Monasterio, Beukema and Gómes lead field (lizard sampling) and lab (estimation of thermal limits and measurement of body weights) work, and Monasterio and Araújo designed experiments. Herrando-Pérez conceived the idea of the two research manuscripts (Functional Ecology, Journal of Animal Ecology) and submitted the data to Dryad. Funding: MBA partly funded through CGL2011-26852 project of the Spanish Ministry of Economy and Competitiveness. Field and experimental work funded by IC&DT 1/SAESCTN/ALENT-07-0224-FEDER-001755 project led by MBA. Acknowledgements: We thank the Biological Station of “El Ventorrillo” for hosting the field team and for providing the thermal experimental facilities essential for this research. We also thank Tim Leerschool, Filipe Serrano and Matthijs Hollanders for their support in the field. Collection permits: Samples, experiments and use of experimental animals supported for Portuguese populations by permits 360 to 362/2014/CAPT and 550 to 552/2014/CAPT (Instituto da Conservação da Natureza e das Florestas), and for Spanish populations by permits (autonomous communities in parenthesis hereafter) SGYB/EF/FJRH Re-9H/13 & SGYB/AF/DBP Re-79y131/14 (Andalucía), 2014-500201724/2014/02343 & INAGA/5000201/24/2013/04434 (Aragón), DGMEN/SEN/avp_13_025_aut & DGMEN/SEN/avp_14_020_aut (Castilla La Mancha), P/CYL/101/2013 & EP/CYL/106/2014 (Castilla y León), CN0023/14/ACA1587(14) (Extremadura), 2566/RX131316//clave031/2013 & 2241/RX123724//clave018/2014 (Galicia), and 10/033298.9/13 & 10/013907.9/14 (Madrid). [Usage Notes] Content of dataset: Critical Thermal Maxima (CTmax) and Critical Thermal Minima (CTmax) and body weights of 304 male individuals belonging to 59 populations and 15 species of Iberian lizards (Dryad doi: 10.5061/dryad.1553pc3). Body weight, CTmax and CTmin available for all populations except the Moncayo/Soria/Spain population of Podarcis muralis for which CTmin was not measured. Dataset set used in two research manuscripts: Intraspecific variation in lizard heat tolerance alters estimates of climate impact / Journal of Animal Ecology (doi: 10.1111/1365-2656.12914) and Heat tolerance is more variable than cold tolerance across species of Iberian lizards after controlling for intraspecific variation / Functional Ecology (in press). Versions of dataset: the first version of the dataset contained CTmax data alone (Journal of Animal Ecology), species names, population codes, locality names (with region, country, lat/long), the second version of the dataset (Functional Ecology) contains the latter information along with CTmin and body-weight data while the locality names and lat/long have been refined., The widespread observation that heat tolerance is less variable than cold tolerance (‘cold-tolerance asymmetry’) leads to the prediction that species exposed to temperatures near their thermal maxima should have reduced evolutionary potential for adapting to climate warming. However, the prediction is largely supported by species-level global studies based on single estimates of both physiological metrics per taxon. We ask if cold-tolerance asymmetry holds for Iberian lizards after accounting for intraspecific variation in critical thermal maxima (CTmax) and minima (CTmin). To do so, we quantified CTmax and CTmin for 58 populations of 15 Iberian lizard species (299 individuals). Then, we randomly selected one population from each study species (population sample = 15 CTmax and CTmin values), tested for variance homoscedasticity across species, and repeated the test for thousands of population samples as if we had undertaken the same study thousands of times, each time sampling one different population per species. The ratio of variances in CTmax to CTmin across species varied up to 16-fold depending on the populations chosen. Variance ratios show how much CTmax departs from the cross-species mean compared to CTmin, with a unitary ratio indicating equal variance of both thermal limits. Sampling one population per species was six times more likely to result in the observation of greater CTmax variance (‘heat-tolerance asymmetry’) than cold-tolerance asymmetry. The null hypothesis of equal variance was twice as likely for cases of cold-tolerance asymmetry than for the opposite scenario. Range-wide, population-level studies that quantify heat and cold tolerance of individual species are urgently needed to ascertain the global prevalence of cold-tolerance asymmetry. While broad latitudinal clines of cold tolerance have been strongly supported, heat tolerance might respond to smaller-scale climatic and habitat factors hence go unnoticed in global studies. Studies investigating physiological responses to climate change should incorporate the extent to which thermal traits are characteristic of individuals, populations and/or species., British Ecological Society, Award: 4496-5470. European Union, Award: IC&DT 1/SAESCTN/ALENT-07-0224-FEDER-001755. Spanish Ministry of Economy and Competitiveness, Award: CGL2011-26852., Peer reviewed

Vida de antes. Infancia de la informante. Condiciones duras. Se comía poco, y se dejaban las tajadas para quien hacía los trabajos más duros. Trabajos y herramientas de la siega. Les pagaban poco dinero, usualmente se retribuía en especie (productos de la matanza). Emigración en Bilbao, donde hacían un poco de todo. La vida mejoró en los ’70. Mucha más población que ahora. Mineral: titanio y estaño. Se cultivaban las tierras, algo que ahora no se hace; no se pasaba hambre, pero no se podía elegir comida. La emigración. Al jubilarse, vuelven al pueblo; cuando no pueden valerse, van a una residencia o con los hijos. Trabajaban en las minas, pero sin seguros. Asistencia sanitaria., A vida antes. A infância da informante. Condições difíceis. Comia-se pouco alimento, e as talhadas deixavam-se para os que faziam o trabalho mais duro. Trabalho e ferramentas de ceifa. Recebiam pouco dinheiro, geralmente em espécie (produtos da matança). Emigração para Bilbao, onde fizeram um pouco de tudo. A vida melhorou nos anos 70. Muita mais população do que agora. Mineral: titânio e estanho. A terra era cultivada, algo que não se faz agora; não se passava fome, mas não se podia escolher o alimento. Emigração. Quando se reformam, regressam à aldeia; quando não conseguem desenvolver-se, vão para uma residência ou com os seus filhos. Eles trabalhavam nas minas, mas sem descontos. Cuidados da saúde., Life in the old days. Informant's childhood. Harsh conditions. Little food was eaten, and the slices were left for those who did the hardest work. Work and tools of mowing. They were paid little money, usually in kind (products of the slaughter). Emigration to Bilbao, where they did a bit of everything. Life improved in the '70s. Much more population than now. Mineral: titanium and tin. The land was cultivated, something that is not done now; you didn't starve, but you couldn't choose food. Emigration. When they retire, they return to the village; when they can't help themselves, they go to a residence or with their children. They worked in the mines, but without insurance. Health care.

Pastoreo. La vida de la gente del campo era dura. Construcción en el campo de chozas con rastrojos y arbustos; allí vivía toda la familia. Los contratos de los trabajadores y los arrendamientos se hacían “de San Pedro a San Pedro”. Muchos pagos se hacían en especie. El ganado. Había fundamentalmente ovejas. La raza merina que entró en Australia vino de Herrera. Colectivo de los diferentes animales. El ordeño. Queso. Nombres específicos para cada pastor según el animal. Crías de los animales. La "tosquía" es un trabajo muy duro. El aprovechamiento de la lana, que da un rendimiento muy escaso. Otros animales domésticos: gallinas, conejos. Bestias de carga. El patrón. Venían de fuera. Muchos recibían fincas de la Iglesia o de Franco a cambio de favores. Herrera tiene una “jurisdicción” muy pequeña, la gente de a pie tiene terrenos pequeños, en contraste con los grandes latifundios., A pastagem. A vida das pessoas do campo era difícil. Construção no campo de cabanas com restolho e arbustos; toda a família vivia lá. Os contratos dos trabalhadores e os arrendamentos eram feitos "de San Pedro a San Pedro". Muitos pagamentos eram efetuados em espécie. Gado. Havia principalmente ovelhas. A raça merina que entrou na Austrália veio de Herrera. Colectivo dos diferentes animais. A ordenha. Queijo. Nomes específicos para cada pastor de acordo com o animal. Descendentes de animais. A "tosquía" é um trabalho muito duro. O aproveitamento da lã, que dá um rendimento muito baixo. Outros animais domésticos: galinhas, coelhos. Bestas de carga. O padrão. Vieram de fora. Muitos recebiam fazendas da Igreja ou de Franco em troca de favores. Herrera tem uma "jurisdição" muito pequena, as pessoas humildes têm pequenos lotes de terra, em contraste com os grandes latifúndios., Grazing. The life of the people of the countryside was hard. Construction in the field of huts with stubble and bushes; the whole family lived there. The contracts of the workers and the leases were made "from San Pedro to San Pedro". Many payments were made in kind. Cattle. There were mainly sheep. The Merino race that entered Australia came from Herrera. Collective of the different animals. Milking. Cheese. Specific names for each shepherd according to the animal. Animals' offspring. The "tosquía" is a very hard work. The use of wool, which gives a very low yield. Other domestic animals: chickens, rabbits. Beasts of burden. The master. They came from outside. Many received farms from the Church or from Franco in exchange for favors. Herrera has a very small "jurisdiction", the ordinary people have small plots of land, in contrast to the large estates.

Había gente en condiciones muy duras. Trabajos de las informantes como jornaleras, en el campo o en casas. ¿Qué animales había? Alguna gente tenía vacas para vender leche, pero sobre todo lo que había eran animales para labrar y carretar. Ganado vacuno, ovino y caprino. La tosquía. Preparación del queso. Pastores. Cochino. La matanza., Havia pessoas em condições muito duras. Os informantes trabalhavam como diaristas, nos campos ou nas casas. Que animais estavam lá? Algumas pessoas tinham vacas para vender leite, mas acima de tudo havia animais para lavrar e carregar. Gado, ovelhas e cabras. Tosquia. Preparação do queijo. Pastores. O porco. Matança., There were people in very harsh conditions. The informants worked as day laborers, in the fields or in houses. What animals were there? Some people had cows to sell milk, but most of all there were animals for tilling and carding. Cattle, sheep and goats. Cough. Preparation of cheese. Shepherds. Pigs. Slaughter.

Corrales para animales. Pozos. Mobiliario y utensilios domésticos. Comidas según las partes del día. Poner la mesa. Partes del cuerpo. El médico. Nombres de parentesco. Partes del día [también se pregunta en ferrereño], Currais para animais. Poços. Mobiliário e utensílios domésticos. Refeições de acordo com as partes do dia. Colocar a mesa. Partes do corpo. O médico. Nomes de parentes. Partes do dia [também perguntado em ferrerenho], Corrals for animals. Wells. Furniture and domestic utensils. Meals according to the parts of the day. Setting the table. Body parts. The doctor. Names of relatives. Parts of the day [also asked in Ferrereño]

Relación con Malpica. La frontera estaba cerrada a menudo, era difícil pasar. El barquero. En épocas pasadas se iba a Montalvão, a través de Cedillo. En Portugal había un molino y llevaban para moler. El contrabando. Relaciones con los guardias. Hoy la frontera está abierta, pero hay menos contacto; ayuda que el río sea imposible de cruzar a pie., Relação com Malpica. A fronteira estava muitas vezes fechada, era difícil de atravessar. O barqueiro. Antes, ia-se a Montalvão, através de Cedillo. Em Portugal havia um moinho e eles levavam para moer. Contrabando. Relações com os guardas. Hoje a fronteira está aberta, mas há menos contacto; ajuda a que o rio seja impossível de atravessar a pé., Relationship to Malpica. The border was often closed, it was difficult to cross. The boatman. Once upon a time, people used to go to Montalvão, through Cedillo. In Portugal there was a mill and they took to grind. Smuggling. Relations with the guards. Today the border is open, but there is less contact; it helps that it is impossible to cross the river on foot.

Buenas relaciones con Portugal. Mucho comercio. Contrabando y aduaneros. Ahora pasa mucha droga., Boas relações com Portugal. Muito comércio. Contrabando e alfândega. Agora passam muitas drogas., Good relations with Portugal. Lots of trade. Contraband and customs. Now a lot of drugs go by.

Los informantes enseñan algunos de los objetos tradicionales que almacenan en su casa., Os informantes mostram alguns dos objectos tradicionais que guardam em casa., Informants show some of the traditional objects they store at home.

El ganado (vacas, ovejas, cabras, cerdos). Ferias de ganado. Lana. Lácteos y derivados. La matanza., O gado (vacas, ovelhas, cabras, porcos). Feiras de gado. Lã. Laticínios e derivados. Matança., The cattle (cows, sheep, goats, pigs). Cattle fairs. Wool. Milk and derivatives. The slaughter.