There is pressing need to anticipate the impacts of climate change on species and their functional contributions to ecosystem processes. Our objective is to evaluate the potential bee response to climate change considering (1) response traits—body size, nest site, and sociality; (2) contributions to ecosystem services (effect trait)—crop pollination; and (3) bees’ size of current occurrence area. We analyzed 216 species occurring at the Carajás National Forest (Eastern Amazon, Pará, Brazil), using two different algorithms and geographically explicit data. We modeled the current occurrence area of bees and projected their range shift under future climate change scenarios through species distribution modeling. We then tested the relationship of potential loss of occurrence area with bee traits and current occurrence area. Our projections show that 95% of bee species will face a decline in their total occurrence area, and only 15 to 4% will find climatically suitable habitats in Carajás. The results indicate an overall reduction in suitable areas for all traits analyzed. Bees presenting medium and restricted geographic distributions, as well as vital crop pollinators, will experience significantly higher losses in occurrence area. The potentially remaining species will be the wide-range habitat generalists, and the decline in crop-pollinator species will probably pose negative impact on pollination service. The north of Pará presented the greatest future climatic suitability and can be considered for conservation purposes. These findings emphasize the detrimental effects on biodiversity and agricultural production by climate change and provide data to support conservation planning.

Pollination may be severely affected by the decreasing size and increasing isolation of habitat patches. However, most studies that have considered the effects of these two variables on plant-pollinator interactions have been carried out in areas that have undergone anthropogenic fragmentation, and little is known about their effects in natural habitats. The Carajás National Forest and Campos Ferruginosos National Park are two protected areas in the eastern Amazon where one can find isolated ferruginous outcrops characterized by iron-rich soil and herbaceous-shrub vegetation surrounded by Amazon forest. These patches of canga provide an opportunity to analyze plant-pollinator interactions in naturally fragmented areas. Our objective was to test whether the size and isolation of naturally isolated outcrops located in Carajás affect plant-pollinator interactions by using pollination syndromes and interaction networks. We determined the pollination syndromes of 771 plant species that occurred in eleven canga patches and performed field work to analyze plant-pollinator networks in nine canga patches. The structure of the plant-pollinator networks was not affected by the size or isolation of the canga patches. Generalist species were present in all canga areas, indicating that they are important in maintaining the plant communities in isolated canga patches. The lack of significance related to the distance between canga patches suggests that the forest does not prevent pollinator movement between canga patches.

Anthropogenic-induced climate change has already altered the conditions to which species have adapted locally, and consequently, shifts of occurrence areas have been previously reported (Chen et al. 2011). Anticipating the results of climate change is urgent, and using these results efficiently to guide decision-making can help to build strategies to protect species from those changes. Therefore, our objective is to propose the use of climate change impact assessments, obtained through species distribution models (SDMs), to guide decision making. The emphasis will be on data that could help determine the potentially vulnerable species and the priority areas, which could act as climate refuges, as well as wildlife corridors. SDMs are based on species occurrence points, available mainly from biological collections and observations (Franklin 2010). When combined with geospatially explicit layers of abiotic or biotic data (e. g. temperature, precipitation, land use), which defines the ecological requirements of species under study, it can generate species distribution models. These models are projected in the form of maps indicating areas where the species can find the most suitable habitats and, therefore, where one can most likely find them. To support public policies decision, the generation of robust and reliable model is an important factor. A minimum number of six occurrence points is a mandatory requirement, with non-overlapping area as a filter criteria. Unfortunatelly, in Brasil, as well as in Latin America in general, this type of data is scarce. Thus, with SDMs, four types of decision making information data regarding priority species and areas could be obtained (Fig. 1). Size of potential occurrence areas: species that have a small area of occurrence are potentially vulnerable, since they present endemism, usually living in restricted environmental conditions. In this case, any small change in environmental conditions can result in the extinction of the impacted species. Thus, this region needs to be protected. Difference between current and future area: species presenting the most significant reduction in potential areas should be prioritized by decision-makers. This measurement could be used as an indication of vulnerability. Even species that have no predicted area reduction or an increase could be prioritized in management programs due to its role in the complex interaction networks of ecosystem services, such as pollinators, seed dispersers or disease control. These species could be more resilient to network interaction changes due climate, and possibly are better able to provide their services in the extreme unfavorable climate scenarios. Areas that maintain higher species diversity in future scenarios: their protection could be prioritized in restoration and conservation programs. Especially in cases involving multiple species, those areas could be considered as climate refuges by decision-makers. Additionally, for the reconstruction and use of SDM published in peer-reviewed journals, it is necessary that all pieces of information about models, its generation, ensemble methods, data cleaning and data quality criteria applied should be available. The availability of the four above mentioned types of information can help on decision-making strategies aiming the protection of priority species and areas. In conclusion, SDMs present essential information about the present and future impacts of projected climate change and their derived data could be preserved using a standard controlled vocabulary.

Ecosystem services provided by biodiversity are associated with supporting life on the planet. Climate change has negatively impacted biodiversity, altering the phenology and geographical distribution of species and the interaction between them. In megadiverse areas, such as tropical forests, studies of species interactions that consider all the species of flora and fauna are not feasible due to our limited knowledge of biodiversity and the necessity of extensive and costly fieldwork. Instead, Species Distribution Modelling (SDM) techniques can be used, together with other species information (e.g., pollination syndrome) as a proxy for these interactions to estimate spatial patterns of potential distribution dynamics. In this study, we modeled our process steps to obtain the estimated future climate shifts and identification of climatically stable areas over time. These areas may represent climatic refuges and future actions to increase the connectivity between them are strategies that could help mitigate potential future damage for biodiversity conservation. Our resulting evaluation data processing flow originated from our group process analysis applied to the Carajás region (Brazil) in which we identified the probable losses of nectarivorous bat species (pollinators), on the order of 66% (Costa et al. 2018); nectarivorous birds, on the order of 60% (Miranda et al. 2019); and bees, on the order of 85% (Giannini et al. 2020) until 2050. Our process, described using the Business Process Model and Notation (BPMN) is represented in Fig. 1. Our group is preparing a data paper with all of our generated data and programs/libraries to be released as soon as possible.

Natural history collections are of extreme importance as they safeguard data from both spatial and temporal sources. Biological collections store the biodiversity information of the majority of the world´s ecosystems, including data from extinct and threatened species. Worldwide, interactions betweens species perform important functions that contribute to the maintenance of the environment. The use of biodiversity by human society generates the so called Ecosystems Services (Nature’s Contributions to People), which may act at a local or even a global scale, as is the case with crop pollination services. Bees are the most important pollinator group and are responsible for the pollination of approximately 80% of Angiosperms and 75% of the crops worldwide. Bee pollinator decline has raised concern globally, the loss and degradation of habitat being one of the causes, with detrimental impacts on food production and biodiversity. In this context, we suggest incorporating and providing spatially explicit plant-pollinator interaction data into natural history collections databases. Plant-pollinator interaction traits (morphological, biochemical, physiological, structural, phenological or behavioural characteristics of organisms that influence performance or fitness) can firstly be identified through pollination syndromes by using floral traits such as size, shape, color, odor and the reward. Bee body size (estimated usually by intertegular distance) and tongue length are important traits that can be used to evaluate bee-flower compatibility and also to estimate an average flight range for each bee species through the landscape. Since interaction is context dependent, data on functional traits could be associated with spatial references, such as geographic coordinates, altitude and land use where species were collected. Such information is usually available in data repositories delivered by collections. Thus, the association of species identification, functional traits and occurrences can act as an important tool for understanding local ecosystem processes, to forecast impacts based on land use and climate change and also for assisting decision making processes for nature conservation. Online databases must also be linked to a Digital Object Identifier (DOI), as is the case for data plubications, so that the work of providing the data can be properly acknowledged and cited in the literature.