In 2021, more than 28.4 million people were estimated to reside within the Legal Amazon area in Brazil. Since 1970, the resident population in the region has quadrupled. The Legal Amazon in Brazil extends across nine Brazilian states, with the the largest area located in the state of Amazonas.

Forest fires are a serious problem for the preservation of the Tropical Forests. Understanding the frequency of forest fires in a time series can help to take action to prevent them. Brazil has the largest rainforest on the planet that is the Amazon rainforest.

Content This dataset report of the number of forest fires in Brazil divided by states. The series comprises the period of approximately 10 years (1998 to 2017). The data were obtained from the official website of the Brazilian government.

Acknowledgements We thank the brazilian system of forest information

Inspiration With this data, it is possible to assess the evolution of fires over the years as well as the regions where they were concentrated. The legal Amazon comprises the states of Acre, Amapá, Pará, Amazonas, Rondonia, Roraima, and part of Mato Grosso, Tocantins, and Maranhão.

Context

This is a small subset of dataset of Book reviews from Amazon Kindle Store category.

Content

5-core dataset of product reviews from Amazon Kindle Store category from May 1996 - July 2014. Contains total of 982619 entries. Each reviewer has at least 5 reviews and each product has at least 5 reviews in this dataset. Columns - asin - ID of the product, like B000FA64PK -helpful - helpfulness rating of the review - example: 2/3. -overall - rating of the product. -reviewText - text of the review (heading). -reviewTime - time of the review (raw). -reviewerID - ID of the reviewer, like A3SPTOKDG7WBLN -reviewerName - name of the reviewer. -summary - summary of the review (description). -unixReviewTime - unix timestamp.

Which file to use?

There are two files one is preprocessed ready for sentiment analysis and other is unprocessed to you basically have to process the dataset and then perform sentiment analysis

Acknowledgements

This dataset is taken from Amazon product data, Julian McAuley, UCSD website. http://jmcauley.ucsd.edu/data/amazon/

License to the data files belong to them.

Inspiration

-Sentiment analysis on reviews. -Understanding how people rate usefulness of a review/ What factors influence helpfulness of a review. -Fake reviews/ outliers. -Best rated product IDs, or similarity between products based on reviews alone (not the best idea ikr). -Any other interesting analysis

From 2004 to 2024, the net revenue of Amazon e-commerce and service sales has increased tremendously. In the fiscal year ending December 31, the multinational e-commerce company's net revenue was almost 638 billion U.S. dollars, up from 575 billion U.S. dollars in 2023.Amazon.com, a U.S. e-commerce company originally founded in 1994, is the world’s largest online retailer of books, clothing, electronics, music, and many more goods. As of 2024, the company generates the majority of it's net revenues through online retail product sales, followed by third-party retail seller services, cloud computing services, and retail subscription services including Amazon Prime. From seller to digital environment Through Amazon, consumers are able to purchase goods at a rather discounted price from both small and large companies as well as from other users. Both new and used goods are sold on the website. Due to the wide variety of goods available at prices which often undercut local brick-and-mortar retail offerings, Amazon has dominated the retailer market. As of 2024, Amazon’s brand worth amounts to over 185 billion U.S. dollars, topping the likes of companies such as Walmart, Ikea, as well as digital competitors Alibaba and eBay. One of Amazon's first forays into the world of hardware was its e-reader Kindle, one of the most popular e-book readers worldwide. More recently, Amazon has also released several series of own-branded products and a voice-controlled virtual assistant, Alexa. Headquartered in North America Due to its location, Amazon offers more services in North America than worldwide. As a result, the majority of the company’s net revenue in 2023 was actually earned in the United States, Canada, and Mexico. In 2023, approximately 353 billion U.S. dollars was earned in North America compared to only roughly 131 billion U.S. dollars internationally.

In March 2024, Amazon.com had approximately 2.2 billion combined web visits, up from 2.1 billion visits in February. In the fourth quarter of 2024, Amazon’s net income amounted to approximately 20 billion U.S. dollars. Online retail in the United States Online retail in the United States is constantly growing. In the third quarter of 2023, e-commerce sales accounted for 15.6 percent of retail sales in the United States. During that quarter, U.S. retail e-commerce sales amounted to over 284 billion U.S. dollars. Amazon is the leading online store in the country, in terms of e-commerce net sales. Amazon.com generated around 130 billion U.S. dollars in online sales in 2022. Walmart ranked as the second-biggest online store, with revenues of 52 billion U.S. dollars. The king of Black Friday In 2023, Amazon ranked as U.S. shoppers' favorite place to go shopping during Black Friday, even surpassing in-store purchasing. Nearly six out of ten consumers chose Amazon as the number one place to go find the best Black Friday deals. Similar findings can be observed in the United Kingdom (UK), where Amazon is also ranked as the preferred Black Friday destination.

The biodiversity in the vegetation, the animals, the ecosystems are here in our Amazon. Today, Brazil and Bolivia are suffering a great forest fire that affects all people around the world.

Context

Dataset of Amazon Reviews for Electronics Category.

Content

5-core dataset of product reviews from Amazon Electronics category from May 1996 - July 2014. Contains total of 1689188 entries. Each reviewer has at least 5 reviews and each product has at least 5 reviews in this dataset.

Columns are: asin - ID of the product, like B000FA64PK helpful - helpfulness rating of the review - example: 2/3. overall - rating of the product. reviewText - text of the review (heading). reviewTime - time of the review (raw). reviewerID - ID of the reviewer, like A3SPTOKDG7WBLN reviewerName - name of the reviewer. summary - summary of the review (description). unixReviewTime - unix timestamp.

Acknowledgements

This dataset is taken from Amazon product data, Julian McAuley, UCSD website. http://jmcauley.ucsd.edu/data/amazon/

License to the data files belongs to them.

Inspiration

• Sentiment analysis on reviews.
• Understanding how people rate the usefulness of a review/ What factors influence helphelpfulness of a review.
• Fake reviews/ outliers.
• Any other interesting analysis.

Approximately 20% of the Brazilian Amazon has now been deforested, and the Amazon is currently experiencing the highest rates of deforestation in a decade, leading to large-scale land-use changes. Roads have consistently been implicated as drivers of ongoing Amazon deforestation and may act as corridors to facilitate species invasions. Long-term data, however, are necessary to determine how ecological succession alters avian communities following deforestation and whether established roads lead to a constant influx of new species.

We used data across nearly 40 years from a large-scale deforestation experiment in the central Amazon to examine the avian colonization process in a spatial and temporal framework, considering the role that roads may play in facilitating colonization.

Since 1979, 139 species that are not part of the original forest avifauna have been recorded, including more secondary forest species than expected based on the regional species pool. Among the 35 species considered to have colonized and become established, a disproportionate number were secondary forest birds (63%), almost all of which first appeared during the 1980s. These new residents comprise about 13% of the current community of permanent residents.

Widespread generalists associated with secondary forest colonized quickly following deforestation, with few new species added after the first decade, despite a stable road connection. Few species associated with riverine forest or specialized habitats colonized, despite road connection to their preferred source habitat. Colonizing species remained restricted to anthropogenic habitats and did not infiltrate old-growth forests nor displace forest birds.

Deforestation and expansion of road networks into terra firme rainforest will continue to create degraded anthropogenic habitat. Even so, the initial pulse of colonization by non-primary forest bird species was not the beginning of a protracted series of invasions in this study, and the process appears to be reversible by forest succession.

Methods We generated the avian regional species pool (n=725 species) for the Biological Dynamics of Forest Fragments Project (BDFFP; 2°20′ S, 60°W), ~80 km north of Manaus, Amazonas, Brazil. To do so, we used a few simple criteria: 1) the species must have been previously recorded in the Amazon (total ~1300 species), 2) for terra firme species, we only included birds that are known from the Guiana area of endemism, and 3) we imposed distance cutoffs of ~500 km from the BDFFP for resident species and ~1000 km for migratory species. We then curated the resulting list by hand to ensure that the final list matched current knowledge. These criteria necessarily mean that all species that have already been detected from the BDFFP are included.

To this list, we added three additional columns. The "BDFFP list" column denotes all species that have been recorded at the BDFFP between 1979 and 2017 (n=407 species; see Rutt et al., 2017). Another column includes a list of the birds that are part of the "core forest avifauna" at the project (n=268 species), or those species that are regularly found in primary terra firme forest. Terra firme species are only designated as part of the core avifauna if they reached a relative abundance of rare, uncommon, or common during one of the last two avifaunal inventories (Cohn-Haft et al., 1997; Rutt et al., 2017). Finally, the last column categorizes each species by habitat according to the Parker et al. (1996) databases. When appropriate, we used the first (primary) habitat type that was listed therein; however, we made adjustments if the primary code suggested the species occurred in habitat not found in the central Amazon (e.g., montane forest, temperate grassland). In those cases, we accepted secondary or tertiary habitat codes. We then collapsed these 22 categories (21 distinct habitats plus ‘Edge’) for the regional species pool into a more manageable seven that adequately captured habitat diversity in the immediate vicinity of the BDFFP: aquatic, primary forest, riverine, secondary forest, white sand, palm, and grassland/pasture (see Appendix 1 in the paper).

Taxonomy follows the South American Classification Committee (J. V. Remsen, Jr. et al., 2018). See the Methods section of the paper for further details.

References

Cohn-Haft, M., Whittaker, A., & Stouffer, P. C. (1997). A new look at the "species-poor" central Amazon: the avifauna north of Manaus, Brazil. Ornithological Monographs, 48, 205-235.

Parker, T. A., Stotz, D. F., & Fitzpatrick, J. W. (1996). Ecological and distributional databases. In D. F. Stotz, J. W. Fitzpatrick, T. A. Parker, & D. Moskovits (Eds.), Neotropical Birds: Ecology and Conservation (pp. 113-407). Chicago, IL: University of Chicago Press.

Remsen, J. V., Jr., Cadena, C. D., Jaramillo, A., Nores, M., Pacheco, J. F., Pérez-Emán, J., . . . Zimmer, K. J. (2018). A classification of the bird species of South America. American Ornithologists' Union. http://www.museum.lsu.edu/~Remsen/SACCBaseline.htm

Rutt, C. L., Jirinec, V., Johnson, E. I., Cohn-Haft, M., Vargas, C. F., & Stouffer, P. C. (2017). Twenty years later: an update to the birds of the Biological Dynamics of Forest Fragments Project, Amazonas, Brazil. Revista Brasileira de Ornitologia, 25(4), 259-278.

This data set is composed of 8 folders for the surveys of 2002 and 2003, 2004-2010. Each folder contains the unprocessed ACCESS dataset + the surveys used each year. The processed, clean datasets are available in several public repositories and have been made available several journal publications as well.

General aims, purposes and background of the collection. The project aimed to improve the capability of researchers to conduct socio-economic analysis in the buffer zone of the Cordilliera Azul National Park in Peru. This is a designated ‘protected area’ of rainforest, defined around a natural valley at the Western edge of the Amazon rainforest, and thus containing high and unique natural biodiversity. The Western edge of the park is a forest-frontier buffer zone, with a population of around 250,000, crossing a number of different local authority areas , with a number of towns and connected by all-season roads. The Eastern edge of the park has various indigenous areas in the vicinity, and is largely continuous forest to the border of Brazil and beyond. Rising levels of deforestation within the buffer zone prompt a need to better consider the nexus of conservation, livelihoods (well-being) and trade (in timber and agricultural commodities). This data set has been assembled as an index of relevant secondary data sources from across different government departments in order to help researchers explore this nexus.

The index includes: 27 sets of agricultural data, 4 sets of livelihood data incl. census data and locations of indigenous groups, and 3 sets of deforestation data, plus geodata for the four local authorities bordering the park: Huanuco, Loreto, San Martín, Ucayali.

This project supports sustainable economic development and welfare in farming communities in the Western edge of the Peruvian Amazon, by assisting a non-governmental organisation (NGO) in Peru called CIMA (Centro de Conservación, Investigación y Manejo de Areas Naturales) to analyse and manage its socio-economic and geospatial data. Through analysis of extensive secondary data on farmer households and agricultural supply chains, alongside geospatial data providing evidence of patterns of deforestation in the landscape, the project aims to gain a better understanding of current practices, challenges, and opportunities for improving agricultural sustainability in the region. It will examine the data needed to inform and monitor the levels of sustainable rural livelihoods and forest conservation in the landscape, and seek to understand how sustainable agriculture (e.g. Fair Trade and organic certifications; agroforestry schemes) can be incentivised and promoted. Importantly, the project will develop standardised processes for data analysis to help support CIMA's objectives for improving the quality of life of local communities while conserving forests.

As CIMA is required to report on how its conservation work benefits local people, the project will support the development of a data management approach that is based on community needs and wants, and helps to develop a holistic approach to understanding the links between livelihoods, supply chains, and deforestation. The proposed project will involve collection, cleaning and consolidation of the NGO-held data, and develop a platform on which the data can be stored and easily accessed by CIMA in the long-term. This will support the NGO in project monitoring and evaluation duties, and reporting to funding agencies, impact investors and against policy frameworks such as the UN Sustainable Development Goals and the UN Convention on Biological Diversity. Following the principles of mutual learning and transparency, all data and analysis will be shared by all members of the project team, and regular online meetings will be held between the research team and CIMA, to ensure that the data platform is developed with the input of users and to ensure that the project meets CIMA's needs. The project is based on a strong relationship between the research team and the local partners, CIMA, who have successfully worked together on a preliminary ESRC IAA fund.

The research term at the University of Sussex will organise a series of three participatory workshops (project inception; capacity building; outputs and impact workshops) in Peru, with the project's beneficiaries and stakeholders, including local and national government agencies. This will help to ensure that the project is supportive of Peru's national vision for sustainable development and that the project can inform sub-national and national policy in Peru. Furthermore, the project has important implications for a large international community of practice (including business, civil society, funding agencies, governments) working on the intersection of forests, supply chains and local livelihoods; which demands a strong evidence base for action. The research team is interdisciplinary in nature, bringing together environmental scientists, human geographers, sustainable supply chain and performance indicator experts. Outcomes of the research will then also inform those various academic communities, leading to better understanding of the influences between rural development, agricultural commodity production, including for export to global...

For more than three decades UCSUR has documented the status of older adults in the County along multiple life domains. Every decade we issue a comprehensive report on aging in Allegheny County and this report represents our most recent effort. It documents important shifts in the demographic profile of the population in the last three decades, characterizes the current status of the elderly in multiple life domains, and looks ahead to the future of aging in the County. This report is unique in that we examine not only those aged 65 and older, but also the next generation old persons, the Baby Boomers. Collaborators on this project include the Allegheny County Area Agency on Aging, the United Way of Allegheny County, and the Aging Institute of UPMC Senior Services and the University of Pittsburgh.

The purpose of this report is to provide a comprehensive analysis of aging in Allegheny County. To this end, we integrate survey data collected from a representative sample of older county residents with secondary data available from Federal, State, and County agencies to characterize older individuals on multiple dimensions, including demographic change and population projections, income, work and retirement, neighborhoods and housing, health, senior service use, transportation, volunteering, happiness and life satisfaction, among others. Since baby boomers represent the future of aging in the County we include data for those aged 55-64 as well as those aged 65 and older.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

Conservationists often assume that connection with and caring about nature's wellbeing is strongly linked to ecological knowledge. Existing evidence on the link between ecological knowledge and psychological nature connection is mixed, geographically limited to countries in the Global North, and does not scrutinize potential differences in determinants of ecological knowledge and nature connection.

We investigate the relationship between psychological nature connection and ecological knowledge of local bird species and assess their associations with potential drivers, including access to, contact with, and reliance on nature and socio-demographic characteristics. Our study is carried among a novel participant population of colonist farmers living along a major deforestation frontier in the Brazilian Amazon.

Our study context has high conservation relevance and provides an ideal setting to assess the extent to which conservation psychology's insights from the Global North hold true elsewhere. Tropical farm-forest frontiers suffer from intense habitat and biodiversity loss, and farmers with migrant origins are important yet rarely studied conservation stakeholders. Importantly, farmer's experiences of nature are likely to vary considerably due to the wide range of socio-demographic, economic, geographic, and cultural diversity.

Interviewees scored highly on two indices of nature connection, but scores were higher among older people and those with greater contact with nature. Bird identification knowledge was generally low to moderate, and higher among men and younger people. Species more frequently recognised were regionally common, larger-bodied, or associated with non-forest habitats. 5. Ecological knowledge of birds and nature connection were not correlated, and they did not have any predictors in common. Our results indicate that colonist farmers are capable of forming strong connections with nature, even if they rarely possess detailed knowledge of local forest biodiversity. Considering the complex and apparently context-dependent relationship between knowing and caring about nature, it is unwise to assume that changing one would automatically affect the other.

Abstract Rural communities that were founded based on land occupation in the Amazon usually have a wide knowledge about the use of medicinal plants. Studies carried out in this context reveal a vast heterogeneity in terms of knowledge and use of medicinal plants. They also describe the influence these communities have on plant diversity and the cultural aspects associated with their use. This paper shows the dynamics of knowledge and use of medicinal plants in the Paulo Fonteles Rural Settlement, established in 2006 in the Mosqueiro District, Belém Municipality, Pará state, Brazilian Amazon. Data was collected through semi-structured interviews and participatory workshops and analyzed qualitatively and quantitatively. Medicinal plants are crucial resources for farmers before and after land occupation. A total of 140 ethnospecies were recorded, of which 119 were identified; They belong to 58 botanical families. 60 species are native to Brazil. Out of those, 21 belong to the phytogeographic domain restricted to Amazonia. 59 species were introduced the region. The local knowledge of medicinal plants is well spread among informants of different age and sex groups. People from other regions in Brazil reported significantly more medicinal plants than those native to the state of Pará. Among the 140 plants mentioned, 110 refer to species whose uses have been maintained over time by informants. The socio-cultural heterogeneity and the dynamic livelihood of the farmers has been crucial for the improvement of their knowledge and the increase of the diversity of the local flora.

Local people's perceptions of cultivated and wild agrobiodiversity, as well as their management of hybridization are still understudied in Amazonia. Here we analyze domesticated treegourd (Crescentia cujete), whose versatile fruits have technological, symbolic and medicinal uses. A wild relative (C. amazonica) of the cultivated species grows spontaneously in Amazonian flooded forests. We demonstrated, using whole chloroplast sequences and nuclear microsatellites, that the two species are strongly differentiated. Nonetheless, they hybridize readily throughout Amazonia and the proportions of admixture correlate with fruit size variation of cultivated trees. New morphotypes arise from hybridization, and are recognized by people and named as local varieties. Small hybrid fruits are used to make the important symbolic rattle (maracá), suggesting that management of hybrid trees is an ancient human practice in Amazonia. Effective conservation of Amazonian agrobiodiversity needs to incorporate this interaction between wild and cultivated populations that is managed by smallholder families. Beyond treegourd, our study clearly shows that hybridization plays an important role in tree crop phenotypic diversification, and that the integration of molecular analyses and farmers'perceptions of diversity help disentangle crop domestication history.

Dataset Card for First Impressions V2

The first impressions data set, comprises 10000 clips (average duration 15s) extracted from more than 3,000 different YouTube high-definition (HD) videos of people facing and speaking in English to a camera. The videos are split into training, validation and test sets with a 3:1:1 ratio. People in videos show different gender, age, nationality, and ethnicity. Videos are labeled with personality traits variables. Amazon Mechanical Turk (AMT) was… See the full description on the dataset page: https://huggingface.co/datasets/yeray142/first-impressions-v2.

ConQA is a dataset created using the intersection between VisualGenome and MS-COCO. The goal of this dataset is to provide a new benchmark for text to image retrieval using short and less descriptive queries than the commonly use captions from MS-COCO or Flicker. ConQA consists of 80 queries divided into 50 conceptual and 30 descriptive queries. A descriptive query mentions some of the objects in the image, for instance, people chopping vegetables. While, a conceptual query does not mention objects or only refers to objects in a general context, e.g., working class life.

Dataset generation For the dataset generation, we followed a 3 step workflow: filtering images, generating queries and seeding relevant, and crowd-sourcing extended annotations.

Filtering images The first step is focused on filtering images that have meaningful scene graphs and captions. To filter the images, we used the following procedure:

The image should have one or more captions. Hence, we discarded the YFCC images with no caption, obtaining images from the MS-COCO subset of Visual Genome. The image should describe a complex scene with multiple objects. We filtered all the scene graphs that did not contain any edges. images pass this filter. The relationships should be verbs and not contain nouns or pronouns. To detect this, we generated sentences for each edge as a concatenation of the words on the labels of the nodes and the relationship and applied Part of Speech tagging. We performed the POS Tagging using the model en_core_web_sm provided by SpaCy. We filter all scene graphs that contain an edge not tagged as a verb or that the tag is not in an ad-hoc list of allowed non-verb keywords. The allowed keywords are top, front, end, side, edge, middle, rear, part, bottom, under, next, left, right, center, background, back, and parallel. We allowed these keywords as they represent positional relationships between objects. After filtering, we obtain images.

Generating Queries To generate ConQA, the dataset authors worked in three pairs and acted as annotators to manually design the queries, namely 50 conceptual and 30 descriptive queries. After that, we proceeded to use the model "ViT-B/32" from CLIP to find relevant images. For conceptual queries, it was challenging to find relevant images directly, so alternative proxy queries were used to identify an initial set of relevant images. These images are the seed for finding other relevant images that were annotated through Amazon Mechanical Turk.

Annotation crowdsourcing Having the initial relevant set defined by the dataset authors, we expanded the relevant candidates by looking into the top-100 visually closest images according to a pre-trained ResNet152 model for each query. As a result, we increase the number of potentially relevant images to analyze without adding human bias to the task.

After selecting the images to annotate, we set up a set of Human Intelligence Tasks (HITs) on Amazon Mechanical Turk. Each task consisted of a query and 5 potentially relevant images. Then, the workers were instructed to determine whether each image is relevant for the given query. If they were not sure, they could alternatively mark the image as “Unsure”. To reduce presentation bias, we randomize the order of images and the options. Additionally, we include validation tasks with control images to ensure a minimum quality in the annotation process, so workers failing 70% or more of validation queries were excluded.

Infrastructure development and overfishing in the Amazon make it imperative to define adequate scales for the ecosystem-based management of commercial fisheries and the wetlands on which they depend. We mapped fisheries and fish ecology data from Brazil, Peru, Bolivia and Colombia to an explicit GIS framework of river and mainstem basins. Migratory species account for more than 80% of the known maximum catches of commercial fisheries across the Amazon. Of these migratory species, we nominated six long-distance migratory fish taxa as flagship species to define the two main commercial fishery regions. The migrations of at least one goliath catfish species define a large-scale longitudinal link joining the Andes, Amazon Lowlands and Amazon River estuary. Migratory characiforms demonstrate interbasin wetland connectivity between nutrient-rich and nutrient-poor rivers over at least 2 million km2, or about one-third of the Amazon Basin. We show that flooded forest area is the most important wetland variable explaining regional variations in migratory characiform biomass as indicated by maximum annual fishery catches. The management of Amazon fisheries will require transnational cooperation and a paradigm shift from local community management alone to a more integrated approach that considers both rural and urban consumers and challenges, and the realistic life histories of migratory species.

South America and especially the Amazon basin is known to be home to some of the most isolated human groups in the world. Here we report on a study of mitochondrial DNA (mtDNA) in the Waorani from Ecuador, probably the most warlike human population known to date. Seeking to look in more depth at the characterization of the genetic diversity of this Native American tribe, molecular markers from the X and Y chromosomes were also analyzed. Only three different mitochondrial DNA haplotypes were detected among the Waorani sample. One of them, assigned to Native American haplogroup A2, accounted for more than 94% of the total diversity of the maternal gene pool. Our results for sex chromosome molecular markers failed to find direct kinship between individuals and further emphasized the low genetic diversity of the mtDNA found. Bearing in mind the results obtained for both the analysis of the mtDNA control region and complete mitochondrial genomes, we suggest the existence of a "Waorani-specific" mtDNA lineage. According to current knowledge on the phylogeny of haplogroup A2, we propose that this lineage could be designated as subhaplogroup A2s. Its wide predominance among the Waorani people might have been conditioned by severe genetic drift episodes resulting from founding events, long-term isolation, and a traditionally small population size most likely associated with the striking ethnography of this Amazonian community. In all, the Waorani constitute a fine example of how genetic imprint may mirror ethnopsychology and sociocultural features in human populations.

We have already crossed seven planetary boundaries related to the Earth's stability and resilience. The two most critical boundaries we have crossed are Climate Change and Biosphere Integrity (1). The anthropogenic climate change is amplifying the frequency and intensity of global heatwaves and air pollution events (2), significantly impacting both human health and the environment. Since the Industrial Revolution, Brazil has become the fourth largest global emitter of CO2, releasing 113 gigatons (Gt) of CO2, of which 97 Gt (86%) originate from land use and forests (3). Brazilian Amazon released more carbon than it absorbed over past 10 years. From 2010 through 2019, Brazil’s Amazon basin gave off 16.6bn tonnes of CO2, while drawing down only 13.9bn tonnes (4). In addition, researchers have observed thousands of fires in the brazilian Amazon every year, with especially intense activity during the dry months of July through November (5). Despite all these facts and numerous instances of damage, the surroundings of Manaus, the capital city of the Brazilian Amazon, have once again been suffering from excessive heat and heavy smoke. In the summer of 2023 in several cities of the brazilian Amazon, the air quality index for PM2.5 particulate matter consistently exceeded 150 μg/m3, which is considered unhealthy (151-200 μg/m3), very harmful (201-300 μg/m3), or even hazardous (above 300 μg/m3) to health. This was the case on October 11, 2023, when in Manaus city, the PM2.5 level of 414.6 μg/m3 was recorded. Almost every day in September and October 2023, Manaus citizens have been waking up and going to bed with a lot of smoke, except for when it rains. The population has been left in the dark regarding the locations of the wildfires as well as whether those responsible are being severely punished according to the law. This underscores the urgent need for science-informed climate action, particularly in the Brazilian Amazon region, where uncontrolled deforestation and burning prevail. Unfortunately, the local population lacks timely and accurate information about the primary sources contributing to these issues. As mentioned above, in October 2023, Manaus city, faced an unprecedented heatwave and dangerous air quality due to widespread regional fires. This escalating problem in the Amazon region is exacerbated by the absence of precise data on the locations of key burning epicenters. This study has four phases to reach the following goals: Goal 1: to identify and share information on high-intensity fire zones within a 300km radius of Manaus during August to October 2023, the peak of the Amazon summer; Goal 2: to offer recommendations to policymakers and decision-makers. Phase 1: 1.1 Formulation of the problem; 1.2 Definition of the main goals Phase 2: Literature Review 2.1. Planet's boundaries and tipping point; 2.2. Climate Change and CO2 Emissions; 2.3. Brazil's CO2 Emissions; 2.4. Amazon Deforestation and Burning; 2.5. Climate Change effects in Amazon: floods, droughts, heat, and smoke; 2.6. How to classify Fire Intensity based on Fire Radiative Potency (FRP) (6, 7, 8, 9, 10, 11) Phase 3: 3.1 Collection of Data; 3.2 Analysis of Data Phase 4: 4.1 Publish articles in newspaper-Portuguese; 4.2 Translate articles to English; 4.3 Create the Dataset; 4.4 Create and update the Digital Platform; 4.5 Share information to society; 4.6 Evaluate readers feedback It was colleced and analyzed nearly 70,000 active fires and thermal anomalies records from NASA FIRMS satellites (12) using geospatial techniques (13, 14, 15), Google´s Maps or Earth Engine tools (16,17,18), and GPS coordinate services . It is crucial to identify and transparently communicate the most active burning areas during this severe heatwave and air pollution event, particularly when conveyed in a language accessible to the general public. This involves weekly publication of information in the Jornal do Comércio do Amazonas (in Portuguese) and translating and sharing it in English on digital platforms such as Personal webpage, LinkedIn, Facebook and Harvard Dataverse. Moreover, this information can guide policymakers and decision-makers in directing fire prevention and control resources to the most vulnerable regions in the upcoming years. Main References: (1) Rockström, J., Gupta, J., Qin, D. et al. Safe and just Earth system boundaries. Nature 619, 102–111 (2023). https://doi.org/10.1038/s41586-023-06083-8 (2) IPCC, 2022: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. doi:10.1017/9781009325844. (3) Evans S. (2021). Analysis: which countries are historically responsible for climate change? Carbon Brief, UK. (accessed 11 March 2022) (4) Qin, Y., Xiao, X., Wigneron, JP. et al. Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon. Nat. Clim. Chang. 11, 442–448 (2021)....

This dataset includes information on macroinvertebrate abundance (broad taxonomic groups) and land-use history for 85 study sites of the eastern Amazon (in the states of Maranhão and Pará). The sampling took place annually between 2010 and 2016, at the end of the rainy season (April to August). The climate of the region is rainy tropical, with mean annual temperature of 27 ° C and annual rainfall of 2100-2300 mm. The most common types of soils are Oxisols and Argisols. The study sites were covered by ombrophilous forests both primary and at different successional stages.

Macrofauna sampling followed the Tropical Soil Biology and Fertility protocol (Anderson and Ingram 1993). At each study site, 3 to 8 samples were collected at each 20 m along a linear transect or two perpendicular linear transects in a cross shape. Each sample contained the litter and the top 10 cm of soil of 25 × 25 cm squares. All invertebrates larger than 2 mm were sorted by hand from samples and classified into broad taxonomic groups.

Land-use history was obtained from the interpretation of Landsat time series imagery. At each study site, we identified past events of forest clearing through the visualization of Landsat 4, 5, 7 and 8 images (available at http://earthexplorer.usgs.gov) acquired between 1984 and 2016. Clearing events were detected from changes in forest patterns identified in true color image composites (combining red, green and blue bands) and images classified with the normalized difference vegetation index (NDVI). The number images used varied with year and location due to availability and cloud cover, but all sites were covered by at least one image per year. Overall, we analyzed 1508 images. The moment of forest clearance was not always observed but could always be dated with year-level accurately inferred from vegetation contrasts of sequential images. Field estimates of forest regeneration age and interviews of local people were used to validate satellite imagery interpretation.