Future temperature extremes threaten land vertebrates.

The frequency, duration, and intensity of extreme thermal events are increasing and are projected to further increase by the end of the century1,2. Despite the considerable consequences of temperature extremes on biological systems3-8, we do not know which species and locations are most exposed worldwide. Here we provide a global assessment of land vertebrates' exposures to future extreme thermal events. We use daily maximum temperature data from 1950 to 2099 to quantify future exposure to high frequency, duration, and intensity of extreme thermal events to land vertebrates. Under a high greenhouse gas emission scenario (Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5); 4.4 °C warmer world), 41.0% of all land vertebrates (31.1% mammals, 25.8% birds, 55.5% amphibians and 51.0% reptiles) will be exposed to extreme thermal events beyond their historical levels in at least half their distribution by 2099. Under intermediate-high (SSP3-7.0; 3.6 °C warmer world) and intermediate (SSP2-4.5; 2.7 °C warmer world) emission scenarios, estimates for all vertebrates are 28.8% and 15.1%, respectively. Importantly, a low-emission future (SSP1-2.6, 1.8 °C warmer world) will greatly reduce the overall exposure of vertebrates (6.1% of species) and can fully prevent exposure in many species assemblages. Mid-latitude assemblages (desert, shrubland, and grassland biomes), rather than tropics9,10, will face the most severe exposure to future extreme thermal events. By 2099, under SSP5-8.5, on average 3,773 species of land vertebrates (11.2%) will face extreme thermal events for more than half a year period. Overall, future extreme thermal events will force many species and assemblages into constant severe thermal stress. Deep greenhouse gas emissions cuts are urgently needed to limit species' exposure to thermal extremes.

A global reptile assessment highlights shared conservation needs of tetrapods.

Comprehensive assessments of species' extinction risks have documented the extinction crisis1 and underpinned strategies for reducing those risks2. Global assessments reveal that, among tetrapods, 40.7% of amphibians, 25.4% of mammals and 13.6% of birds are threatened with extinction3. Because global assessments have been lacking, reptiles have been omitted from conservation-prioritization analyses that encompass other tetrapods4-7. Reptiles are unusually diverse in arid regions, suggesting that they may have different conservation needs6. Here we provide a comprehensive extinction-risk assessment of reptiles and show that at least 1,829 out of 10,196 species (21.1%) are threatened-confirming a previous extrapolation8 and representing 15.6 billion years of phylogenetic diversity. Reptiles are threatened by the same major factors that threaten other tetrapods-agriculture, logging, urban development and invasive species-although the threat posed by climate change remains uncertain. Reptiles inhabiting forests, where these threats are strongest, are more threatened than those in arid habitats, contrary to our prediction. Birds, mammals and amphibians are unexpectedly good surrogates for the conservation of reptiles, although threatened reptiles with the smallest ranges tend to be isolated from other threatened tetrapods. Although some reptiles-including most species of crocodiles and turtles-require urgent, targeted action to prevent extinctions, efforts to protect other tetrapods, such as habitat preservation and control of trade and invasive species, will probably also benefit many reptiles.

The global biomass of wild mammals.

Wild mammals are icons of conservation efforts, yet there is no rigorous estimate available for their overall global biomass. Biomass as a metric allows us to compare species with very different body sizes, and can serve as an indicator of wild mammal presence, trends, and impacts, on a global scale. Here, we compiled estimates of the total abundance (i.e., the number of individuals) of several hundred mammal species from the available data, and used these to build a model that infers the total biomass of terrestrial mammal species for which the global abundance is unknown. We present a detailed assessment, arriving at a total wet biomass of ≈20 million tonnes (Mt) for all terrestrial wild mammals (95% CI 13-38 Mt), i.e., ≈3 kg per person on earth. The primary contributors to the biomass of wild land mammals are large herbivores such as the white-tailed deer, wild boar, and African elephant. We find that even-hoofed mammals (artiodactyls, such as deer and boars) represent about half of the combined mass of terrestrial wild mammals. In addition, we estimated the total biomass of wild marine mammals at ≈40 Mt (95% CI 20-80 Mt), with baleen whales comprising more than half of this mass. In order to put wild mammal biomass into perspective, we additionally estimate the biomass of the remaining members of the class Mammalia. The total mammal biomass is overwhelmingly dominated by livestock (≈630 Mt) and humans (≈390 Mt). This work is a provisional census of wild mammal biomass on Earth and can serve as a benchmark for human impacts.

Automated assessment reveals that the extinction risk of reptiles is widely underestimated across space and phylogeny.

The Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), is a crucial tool for conservation decision-making. However, despite substantial effort, numerous species remain unassessed or have insufficient data available to be assigned a Red List extinction risk category. Moreover, the Red Listing process is subject to various sources of uncertainty and bias. The development of robust automated assessment methods could serve as an efficient and highly useful tool to accelerate the assessment process and offer provisional assessments. Here, we aimed to (1) present a machine learning-based automated extinction risk assessment method that can be used on less known species; (2) offer provisional assessments for all reptiles-the only major tetrapod group without a comprehensive Red List assessment; and (3) evaluate potential effects of human decision biases on the outcome of assessments. We use the method presented here to assess 4,369 reptile species that are currently unassessed or classified as Data Deficient by the IUCN. The models used in our predictions were 90% accurate in classifying species as threatened/nonthreatened, and 84% accurate in predicting specific extinction risk categories. Unassessed and Data Deficient reptiles were considerably more likely to be threatened than assessed species, adding to mounting evidence that these species warrant more conservation attention. The overall proportion of threatened species greatly increased when we included our provisional assessments. Assessor identities strongly affected prediction outcomes, suggesting that assessor effects need to be carefully considered in extinction risk assessments. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap for other less known taxa.

A protocol for harvesting biodiversity data from Facebook.

The expanding use of community science platforms has led to an exponential increase in biodiversity data in global repositories. Yet, understanding of species distributions remains patchy. Biodiversity data from social media can potentially reduce the global biodiversity knowledge gap. However, practical guidelines and standardized methods for harvesting such data are nonexistent. Following data privacy and protection safeguards, we devised a standardized method for extracting species distribution records from Facebook groups that allow access to their data. It involves 3 steps: group selection, data extraction, and georeferencing the record location. We present how to structure keywords, search for species photographs, and georeference localities for such records. We further highlight some challenges users might face when extracting species distribution data from Facebook and suggest solutions. Following our proposed framework, we present a case study on Bangladesh's biodiversity-a tropical megadiverse South Asian country. We scraped nearly 45,000 unique georeferenced records across 967 species and found a median of 27 records per species. About 12% of the distribution data were for threatened species, representing 27% of all species. We also obtained data for 56 DataDeficient species for Bangladesh. If carefully harvested, social media data can significantly reduce global biodiversity knowledge gaps. Consequently, developing an automated tool to extract and interpret social media biodiversity data is a research priority.

Un protocolo para recolectar datos sobre biodiversidad en Facebook Resumen El uso creciente de plataformas de ciencia comunitaria ha causado un incremento exponencial de los datos sobre biodiversidad en los repositorios mundiales. Sin embargo, el conocimiento sobre la distribución de las especies todavía está incompleto. Los datos sobre biodiversidad obtenidos de las redes sociales tienen el potencial para disminuir el vacío de conocimiento sobre la biodiversidad mundial. No obstante, no existe una guía práctica o un método estandarizado para recolectar dichos datos. Seguimos los protocolos de privacidad y protección de datos para diseñar un método estandarizado para extraer registros de la distribución de especies de grupos en Facebook que permiten el acceso a sus datos. El método consta de tres pasos: selección del grupo, extracción de datos y georreferenciación de la localidad registrada. También planteamos cómo estructurar las palabras clave, buscar fotografías de especies y georreferenciar las localidades de dichos registros. Además, resaltamos algunos retos que los usuarios pueden enfrentar al extraer los datos de distribución de Facebook y sugerimos algunas soluciones. Aplicamos nuestro marco de trabajo propuesto a un estudio de caso de la biodiversidad en Bangladesh, un país tropical megadiverso en el sureste de Asia. Reunimos casi 45,000 registros georreferenciados únicos para 967 especies y encontramos una media de 27 registros por especie. Casi el 12% de los datos de distribución correspondió a especies amenazadas, que representaban el 27% de todas las especies. También obtuvimos datos para 56 especies deficientes de datos en Bangladesh. Si los datos de las redes sociales se recolectan con cuidado, éstos pueden reducir de forma significativa el vacío de conocimiento para la biodiversidad mundial. Como consecuencia, es una prioridad para la investigación el desarrollo de una herramienta automatizada para extraer e interpretar los datos sobre biodiversidad de las redes sociales.

Using social media records to inform conservation planning.

Citizen science plays a crucial role in helping monitor biodiversity and inform conservation. With the widespread use of smartphones, many people share biodiversity information on social media, but this information is still not widely used in conservation. Focusing on Bangladesh, a tropical megadiverse and mega-populated country, we examined the importance of social media records in conservation decision-making. We collated species distribution records for birds and butterflies from Facebook and Global Biodiversity Information Facility (GBIF), grouped them into GBIF-only and combined GBIF and Facebook data, and investigated the differences in identifying critical conservation areas. Adding Facebook data to GBIF data improved the accuracy of systematic conservation planning assessments by identifying additional important conservation areas in the northwest, southeast, and central parts of Bangladesh, extending priority conservation areas by 4,000-10,000 km2 . Community efforts are needed to drive the implementation of the ambitious Kunming-Montreal Global Biodiversity Framework targets, especially in megadiverse tropical countries with a lack of reliable and up-to-date species distribution data. We highlight that conservation planning can be enhanced by including available data gathered from social media platforms.

Registros de las redes sociales para guiar la planeación de la conservación Resumen La ciencia ciudadana es importante para monitorear la biodiversidad e informar la conservación. Con el creciente uso de los teléfonos inteligentes, muchas personas comparten información de la biodiversidad en redes sociales, pero todavía no se usa ampliamente en la conservación. Analizamos la importancia de los registros de las redes sociales para las decisiones de conservación enfocados en Bangladesh, un país tropical megadiverso y mega poblado. Cotejamos los registros de distribución de especies de aves y mariposas en Facebook y Global Biodiversity Information Facility (GBIF), las agrupamos en datos sólo de GBIF o datos combinados de Facebook y GBIF e investigamos las diferencias en la identificación de las áreas de conservación críticas. La combinación de los datos de Facebook con los de GBIF mejoró la precisión de las evaluaciones de la planeación de la conservación sistemática al identificar otras áreas importantes de conservación en el noroeste, sureste y centro de Bangladesh, extendiendo así las áreas prioritarias de conservación en unos 4,000-10,000 km2 . Se requieren esfuerzos comunitarios para impulsar la implementación de los objetivos ambiciosos del Marco Global de Biodiversidad Kunming-Montreal, especialmente en países tropicales que carecen de datos confiables y actuales sobre la distribución de las especies. Destacamos que la planeación de la conservación puede mejorarse si se incluye información tomada de las redes sociales.

Expanding conservation culturomics and iEcology from terrestrial to aquatic realms.

The ongoing digital revolution in the age of big data is opening new research opportunities. Culturomics and iEcology, two emerging research areas based on the analysis of online data resources, can provide novel scientific insights and inform conservation and management efforts. To date, culturomics and iEcology have been applied primarily in the terrestrial realm. Here, we advocate for expanding such applications to the aquatic realm by providing a brief overview of these new approaches and outlining key areas in which culturomics and iEcology are likely to have the highest impact, including the management of protected areas; fisheries; flagship species identification; detection and distribution of threatened, rare, and alien species; assessment of ecosystem status and anthropogenic impacts; and social impact assessment. When deployed in the right context with awareness of potential biases, culturomics and iEcology are ripe for rapid development as low-cost research approaches based on data available from digital sources, with increasingly diverse applications for aquatic ecosystems.

Evaluating global interest in biodiversity and conservation.

The first target of the Convention for Biological Diversity (Aichi target 1) was to increase public awareness of the values of biodiversity and actions needed to conserve it-a key prerequisite for other conservation targets. Monitoring success in achieving this target at a global scale has been difficult; however, increased digitization of human life in recent decades has made it easier to measure people's interests at an unprecedented scale and allows for a more comprehensive evaluation of Aichi target 1 than previously attempted. We used Google search volume data for over a thousand search terms related to different aspects of biodiversity and conservation to evaluate global interest in biodiversity and its conservation. We also investigated the correlation of interest in biodiversity and conservation across countries to variables related to biodiversity, economy, demography, research, education, internet use, and presence of environmental organizations. From 2013 to 2020, global searches for biodiversity components increased, driven mostly by searches for charismatic fauna (59% of searches were for mammal species). Searches for conservation actions, driven mostly by searches for national parks, decreased since 2019, likely due to the COVID-19 pandemic. Economic inequality was negatively correlated with interest in biodiversity and conservation, whereas purchasing power was indirectly positively correlated with higher levels of education and research. Our results suggest partial success toward achieving Aichi target 1 in that interest in biodiversity increased widely, but not for conservation. We suggest that increased outreach and education efforts aimed at neglected aspects of biodiversity and conservation are still needed. Popular topics in biodiversity and conservation could be leveraged to increase awareness of other topics with attention to local socioeconomic contexts.

Evaluación del interés mundial en la biodiversidad y la conservación Resumen La primera meta del Convenio sobre la Diversidad Biológica (Meta 1 de Aichi) era aumentar la conciencia pública sobre los valores de la biodiversidad y las acciones necesarias para conservarla, un requisito previo clave para otras metas de conservación. Ha sido difícil monitorear el éxito en la obtención de esta meta a escala mundial; sin embargo, la creciente digitalización de la vida humana en las últimas décadas ha facilitado la medición de los intereses de la gente a una escala sin precedentes y permite una evaluación más exhaustiva de la Meta 1 de Aichi que la que se había intentado previamente. Utilizamos datos sobre el volumen de búsquedas en Google de más de mil términos relacionados con distintos aspectos de la biodiversidad y la conservación para evaluar el interés mundial en la biodiversidad y su conservación. También investigamos la correlación del interés por la biodiversidad y la conservación en los distintos países con variables relacionadas a la biodiversidad, la economía, la demografía, la investigación, la educación, el uso del internet y la presencia de organizaciones ambientalistas. Las búsquedas mundiales sobre los componentes de la biodiversidad aumentaron de 2013 a 2020, impulsadas sobre todo por búsquedas de especies carismática (el 59% de las búsquedas correspondían a especies de mamíferos). Las búsquedas de acciones de conservación, impulsadas principalmente por búsquedas de parques nacionales, han disminuido desde 2019, probablemente debido a la pandemia de COVID-19. La desigualdad económica se correlacionó negativamente con el interés en la biodiversidad y la conservación, mientras que el poder adquisitivo se correlacionó indirectamente de manera positiva con niveles más altos de educación e investigación. Nuestros resultados sugieren un éxito parcial en la obtención de la Meta 1 de Aichi en el sentido de que aumentó ampliamente el interés por la biodiversidad, pero no por la conservación. Sugerimos que se necesitan mayores esfuerzos de divulgación y educación dirigidos a aspectos desatendidos de la biodiversidad y la conservación. Los temas populares de biodiversidad y conservación podrían aprovecharse para aumentar la conciencia sobre otros temas si se presta atención a los contextos socioeconómicos locales.

A season for all things: Phenological imprints in Wikipedia usage and their relevance to conservation.

Phenology plays an important role in many human-nature interactions, but these seasonal patterns are often overlooked in conservation. Here, we provide the first broad exploration of seasonal patterns of interest in nature across many species and cultures. Using data from Wikipedia, a large online encyclopedia, we analyzed 2.33 billion pageviews to articles for 31,751 species across 245 languages. We show that seasonality plays an important role in how and when people interact with plants and animals online. In total, over 25% of species in our data set exhibited a seasonal pattern in at least one of their language-edition pages, and seasonality is significantly more prevalent in pages for plants and animals than it is in a random selection of Wikipedia articles. Pageview seasonality varies across taxonomic clades in ways that reflect observable patterns in phenology, with groups such as insects and flowering plants having higher seasonality than mammals. Differences between Wikipedia language editions are significant; pages in languages spoken at higher latitudes exhibit greater seasonality overall, and species seldom show the same pattern across multiple language editions. These results have relevance to conservation policy formulation and to improving our understanding of what drives human interest in biodiversity.

Combining culturomic sources to uncover trends in popularity and seasonal interest in plants.

Culturomic tools enable the exploration of trends in human-nature interactions, although they entail inherent biases and necessitate careful validation. Furthermore, people may engage with nature across different culturomic data sets differently. We evaluated people's digital interest and engagement with plant species based on Wikipedia and Google data and explored the conservation implications of these temporal interest patterns. As a case study, we explored the digital footprints of the most popular plant species in Israel. We analyzed 4 years of daily page views from Hebrew Wikipedia and 10 years of daily Google search volume in Israel. We modeled popularity of plant species in these 2 data sets based on a suite of plant attributes. We further explored the seasonal trends of people's interest in each species. We found differences in how people interacted digitally with plants in Wikipedia and Google. Overall, in Google, searches for species that have utility to humans were more common, whereas in Wikipedia, plants that serve as cultural emblems received more attention. Furthermore, in Google, popular species attracted more attention over time, opposite to the trend in Wikipedia. In Google, interest in species with short bloom duration exhibited more pronounced seasonal patterns, whereas in Wikipedia, seasonality of interest increased as bloom duration increased. Together, our results suggest that people's digital interactions with nature may be inherently different depending on the sources explored, which may affect use of this information for conservation. Although culturomics holds much promise, better understanding of its underpinnings is important when translating insights into conservation actions.

Combinación de las Fuentes de Culturomia para Descubrir las Tendencias en la Popularidad y el Interés Estacional por las Plantas Resumen Las herramientas utilizadas por la culturomia permiten la exploración de las tendencias en las interacciones humano-naturaleza, aunque conllevan sesgos inherentes y necesitan de una verificación minuciosa. Además de lo anterior, las personas pueden vincularse de maneras diversas con la naturaleza a través de diferentes conjuntos de datos de culturomia. Evaluamos el interés y el vínculo digitales de las personas con algunas especies de plantas con base en información de Wikipedia y Google y exploramos las implicaciones para la conservación de estos patrones de interés temporal. Como estudio de caso, exploramos las huellas digitales de las especies de plantas más populares en Israel. Analizamos la información recolectada a lo largo de cuatro años sobre las vistas diarias por página en la Wikipedia Hebrea y la información de diez años del volumen de búsqueda en Google en Israel. Modelamos la popularidad de las especies de plantas en estos dos conjuntos de datos con base en una serie de atributos botánicos. Adicionado a esto, exploramos las tendencias estacionales del interés de las personas en cada especie. Encontramos diferencias en cómo las personas interactuaron digitalmente con las plantas en Wikipedia y en Google. En general, en las búsquedas de Google para especies que tienen utilidad para los humanos fueron más comunes, mientras que en Wikipedia las plantas que fungen como emblemas culturales recibieron más atención. Además, en Google, las especies populares atrajeron más atención conforme pasaba el tiempo, contrario a las tendencias en Wikipedia. En Google, las especies con una duración corta de florecimiento exhibieron patrones estacionales más pronunciados, mientras que en Wikipedia la estacionalidad del interés incrementó conforme incrementa la duración del florecimiento. En conjunto, nuestros resultados sugieren que las interacciones digitales de las personas con la naturaleza pueden ser inherentemente diferentes dependiendo de las fuentes que se exploren, lo cual puede afectar al uso de esta información para la conservación. Aunque la culturomia parece prometer mucho, un mejor entendimiento de sus sustentos es importante cuando se quieran transformar los conocimientos en acciones de conservación.

Using Wikipedia to measure public interest in biodiversity and conservation.

The recent growth of online big data offers opportunities for rapid and inexpensive measurement of public interest. Conservation culturomics is an emerging research area that uses online data to study human-nature relationships for conservation. Methods for conservation culturomics, though promising, are still being developed and refined. We considered the potential of Wikipedia, the online encyclopedia, as a resource for conservation culturomics and outlined methods for using Wikipedia data in conservation. Wikipedia's large size, widespread use, underlying data structure, and open access to both its content and usage analytics make it well suited to conservation culturomics research. Limitations of Wikipedia data include the lack of location information associated with some metadata and limited information on the motivations of many users. Seven methodological steps to consider when using Wikipedia data in conservation include metadata selection, temporality, taxonomy, language representation, Wikipedia geography, physical and biological geography, and comparative metrics. Each of these methodological decisions can affect measures of online interest. As a case study, we explored these themes by analyzing 757 million Wikipedia page views associated with the Wikipedia pages for 10,099 species of birds across 251 Wikipedia language editions. We found that Wikipedia data have the potential to generate insight for conservation and are particularly useful for quantifying patterns of public interest at large scales.

La Wikipedia como Instrumento de Medición del Interés Público por la Biodiversidad y la Conservación Resumen El crecimiento reciente de los datos masivos en línea ofrece oportunidades para la medición rápida y asequible del interés público. La culturomia de la conservación es un área emergente de investigación que utiliza la información en línea para estudiar las relaciones entre el humano y la naturaleza y usarlas para la conservación. Los métodos de conservación basados en culturomia, aunque prometedores, todavía están siendo desarrollados y refinados. Consideramos el potencial de Wikipedia, la enciclopedia en línea, como recurso para la culturomia de la conservación y los métodos para usar sus datos en la conservación. El gran tamaño de Wikipedia, su uso extenso, estructura subyacente de datos y acceso abierto tanto a su contenido como a sus análisis de uso hacen que sea muy adecuada para usarse en la investigación de culturomia de la conservación. Las limitantes de usar la información de Wikipedia incluyen la falta de ubicación de la información asociada con algunos metadatos y la información limitada sobre los motivos de muchos usuarios. Hay siete pasos metodológicos a considerar cuando se usa la información de Wikipedia para la conservación: la selección de metadatos, temporalidad, taxonomía, representación del idioma, geografía de la Wikipedia, geografía física y biológica y medidas comparativas. Cada una de estas decisiones metodológicas puede afectar a las medidas del interés en línea. Como estudio de caso, exploramos estos temas analizando 757 millones de vistas de páginas en Wikipedia para las páginas sobre 10, 099 especies de aves a través de 251 ediciones de Wikipedia en idiomas diferentes. Encontramos que la información de Wikipedia fue particularmente útil para cuantificar los patrones de interés público a grandes escalas y tiene el potencial para generar conocimiento para la conservación.

Digital data sources and methods for conservation culturomics.

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human-nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human-nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human-nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.

Fuentes de Información Digital y Métodos para la Culturomia de la Conservación Resumen La continua pérdida de biodiversidad es el resultado principal del comportamiento humano insostenible. Por esto, el éxito a largo plazo de la conservación de la biodiversidad depende de una comprensión exhaustiva de las interacciones humano-naturaleza. Dichas interacciones son ubicuas pero varían enormemente en el tiempo y el espacio, lo que dificulta su monitoreo eficiente a escalas espaciales amplias. Sin embargo, la Era de la Información también nos proporciona nuevas oportunidades para comprender de mejor manera las interacciones humano-naturaleza pues muchos aspectos de la vida diaria quedan registrados en una variedad de formatos digitales. El campo emergente de la culturomia de la conservación busca aprovechar los recursos y los métodos digitales para estudiar las interacciones humano-naturaleza y así proporcionar nuevas herramientas para el estudio de la conservación a escalas temporales y espaciales relevantes. No obstante, las dificultades técnicas asociadas con la identificación, acceso y análisis de la información relevante obstaculizan la adopción más amplia de los métodos de la culturomia. Para ayudar a superar estas barreras proponemos un marco de trabajo de investigación de culturomia de la conservación que aborde la obtención de datos, el análisis y los sesgos inherentes. Entre las principales fuentes de datos sobre culturomia se incluyen las páginas web, las redes sociales y otras plataformas digitales a partir de las cuales se pueden obtener medidas del contenido y la participación. Normalmente se busca obtener datos crudos a partir de este tipo de plataformas, pero esto requiere que se tengan en consideración las vías de acceso, el almacenaje y la preparación de la información para su posterior análisis. Los métodos para el análisis de datos incluyen analísis de redes para explorar las conexiones entre los temas, el análisis de series de tiempo para los datos temporales y el modelado espacial para resaltar los patrones espaciales. Los desafíos sobresalientes asociados a la investigación en culturomia incluyen temas de interdisciplinariedad, ética, sesgos de datos y validación. La orientación práctica que ofrecemos ayudará a los investigadores y practicantes de la conservación a identificar y obtener los datos necesarios. También les ayudará a realizar análisis apropiados para responder a sus preguntas específicas, facilitando así la adopción más amplia de las estrategias de culturomia para su aplicación en la conservación.

iNaturalist insights illuminate COVID-19 effects on large mammals in urban centers.

Restricted human activity during the COVID-19 pandemic raised global attention to the presence of wildlife in cities. Here, we analyzed iNaturalist observations of prominent wildlife species around North-American urban centers, before and during the COVID-19 pandemic outbreak. We suggest that the popular notion of 'wildlife reclaiming cities' may have been exaggerated. We found that while pumas ventured deeper into urban habitats during the COVID-19 pandemic, bears, bobcats, coyotes, and moose did not. Species differential behavioral responses may highlight their evolutionary history cohabiting human habitats. Nevertheless, our results highlight the importance of urban nature for people during the pandemic. Our insights could help manage urban wildlife, better plan greenspaces, and promote positive nature engagements.

Reduced human activity in shallow reefs during the COVID-19 pandemic increases fish evenness.

The COVID-19 pandemic provides a rare opportunity to examine effects of people on natural systems and processes. Here, we collected fish diversity data from coral reefs at the Israeli Gulf of Aqaba during and after the COVID-19 lockdown. We examined beach entrances to the reef, nearby shallow reefs and deeper areas exposed mostly to divers. We found that the lockdown elicited a behavioral response that resulted in elevated species richness at designated reef entrances, predominantly influenced by increased evenness without changes to total abundances. This effect was observed both at the local scale and when several beach entrances were aggregated together. Consequently, non-extractive human activities may have substantial short-term impacts on fish diversity. Our insights could help designate guidelines to manage visitor impacts on coral reefs and aid in their prolonged persistence.

Global COVID-19 lockdown highlights humans as both threats and custodians of the environment.

The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundreds of reports of unusual species observations from around the world suggest that animals quickly responded to the reductions in human presence. However, negative effects of lockdown on conservation also emerged, as confinement resulted in some park officials being unable to perform conservation, restoration and enforcement tasks, resulting in local increases in illegal activities such as hunting. Overall, there is a complex mixture of positive and negative effects of the pandemic lockdown on nature, all of which have the potential to lead to cascading responses which in turn impact wildlife and nature conservation. While the net effect of the lockdown will need to be assessed over years as data becomes available and persistent effects emerge, immediate responses were detected across the world. Thus, initial qualitative and quantitative data arising from this serendipitous global quasi-experimental perturbation highlights the dual role that humans play in threatening and protecting species and ecosystems. Pathways to favorably tilt this delicate balance include reducing impacts and increasing conservation effectiveness.

The association between patient-therapist MATRIX congruence and treatment outcome.

Objective: The present study aimed to examine the association between patient-therapist micro-level congruence/incongruence ratio and psychotherapeutic outcome. Method: Nine good- and nine poor-outcome psychodynamic treatments (segregated by comparing pre- and post-treatment BDI-II) were analyzed (N = 18) moment by moment using the MATRIX (total number of MATRIX codes analyzed = 11,125). MATRIX congruence was defined as similar adjacent MATRIX codes. Results: the congruence/incongruence ratio tended to increase as the treatment progressed only in good-outcome treatments. Conclusion: Progression of MATRIX codes' congruence/incongruence ratio is associated with good outcome of psychotherapy.

Using machine learning to disentangle homonyms in large text corpora.

Systematic reviews are an increasingly popular decision-making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine-learning methods to handle and screen big data for relevant information in conservation science.