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Simple Summary: Bumblebee species are crucial pollinators for both crops and natural ecosystems. Managing diversity and securing the services they provide requires sufficient data to manage these systems effectively. In this study, seventeen environmental factors were selected to understand their contribution to shaping species assemblages and to provide baseline information for understanding drivers of community assembly. The study focused on Gansu Province because it has some of the highest richness of bumblebees within China, and China represents a major data gap for bee distribution data. Net primary productivity followed by water vapor pressure were top-ranked drivers of species distributions. The results enhance our understanding of the importance of environmental factors in shaping bumblebee community assemblages. Understanding the influence of factors responsible for shaping community assemblage is crucial for biodiversity management and conservation. Gansu is one of the richest regions for bumblebee species in the world. We explored the distribution data of 52 bumblebee species collected in Gansu and its surroundings between 2002 and 2022, predicting habitat suitability based on 17 environmental variables using MaxEnt. The factors influencing community assemblage were assessed using canonical correspondence analysis. Net primary productivity, water vapor pressure, temperature seasonality, annual precipitation, and precipitation seasonality were some of the most influential drivers of species distributions. Based on Ward's agglomerative cluster analysis, four biogeographic zones are described: the Southern humid zone, the Western Qilian snow mountain zone, the Eastern Loess plateau zone, and the Western dry mountain zone. In the clusters of grid cells based on beta diversity values, the Southern humid zone comprised 42.5% of the grid cells, followed by the Eastern Loess plateau zone (32.5%), the Western dry mountain zone (20%), and the Western Qilian snow mountain zone (5%). Almost all the environmental factors showed a significant contribution to the assemblages of bumblebees of different groups. Our findings highlight the need for better data to understand species biogeography and diversity patterns, and they provide key baseline data for refining conservation strategies. [ABSTRACT FROM AUTHOR]

With the recent launch of the Kunming-Montreal global biodiversity framework (GBF), and the associated monitoring framework, understanding the framework and data needed to support it is crucial. Unfortunately, whilst the monitoring framework was meant to provide key data to monitor progress towards goals and targets, most indicators are too unclear for detection or marking progress. The most common datasets for this task, such as the IUCN redlist of species, have major spatial inaccuracies, and lack the temporal resolution to track progress, whilst point-based datasets lack data from many regions, in addition to species coverage. Utilising existing data will require the careful use of existing data, such as the use of inventories and projecting richness patterns, or filling data gaps before developing species-level models and assessments. As high-resolution data fall outside the scope of explicit indicators within the monitoring framework, using essential biodiversity variables within GEOBON (which are noted in the prelude of the monitoring framework) as a vehicle for data aggregation provides a mechanism for collating the necessary high-resolution data. Ultimately developing effective targets for conservation will require better species data, for which National Biodiversity Strategic Action Plans (NBSAPs) and novel mechanisms for data mobilisation will be necessary. Furthermore, capitalising on climate targets and climate biodiversity synergies within the GBF provides an additional means for developing meaningful targets, trying to develop urgently needed data to monitor biodiversity trends, prioritising meaningful tasks, and tracking our progress towards biodiversity targets. [ABSTRACT FROM AUTHOR]

The draft post-2020 Global Biodiversity Framework asks CBD parties to conserve at least 30% of the planet by 2030 'through a well-connected and effective system of protected areas ... with the focus on areas particularly important for biodiversity'. We use Thailand as a case study for the ability of a densely populated, hyper diverse, tropical, middle-income country to meet this target at a national level. Existing protected areas (PAs) total 24.3% of Thailand's land area. Adding forest on government land adjacent to existing PAs, plus unprotected areas of Ramsar sites, raises this to 29.5%. To assess the importance for biodiversity, we used modeled distributions of birds and mammals plus, as proxies for other biodiversity components, elevation, bioclimate, forest type, and WWF ecoregion. All modeled species occur in the current PA system but <30% meet representation targets. Expansion of the system increases the proportion of mammals and birds adequately protected and increases the protection for underrepresented bioclimatic zones and forest types. The expanded system remains fragmented and underrepresents key habitats, but opportunities for increasing protection of these are limited. It is also still vulnerable to climate change, although projected impacts are reduced. Additional protection is needed for wetland and coastal habitats, and limestone karsts. [ABSTRACT FROM AUTHOR]

Protected areas are the backbone of biodiversity conservation but vulnerable to climate change. Thailand has a large and well-planned protected area system, covering most remaining natural vegetation. A statistically derived global environmental stratification (GEnS) was used to predict changes in bioclimatic conditions across the protected area system for 2050 and 2070, based on projections from three CMIP5 earth system models and two representative concentration pathways (RCPs). Five bioclimatic zones were identified composed of 28 strata. Substantial spatial reorganization of bioclimates is projected in the next 50 years, even under RCP2.6, while under RCP8.5 the average upward shift for all zones by 2070 is 328–483 m and the coolest zone disappears with two models. Overall, 7.9–31.0% of Thailand's land area will change zone by 2070, and 31.7–90.2% will change stratum. The consequences for biodiversity are less clear, particularly in the lowlands where the existing vegetation mosaic is determined largely by factors other than climate. Increasing connectivity of protected areas along temperature and rainfall gradients would allow species to migrate in response to climate change, but this will be difficult in much of Thailand. For isolated protected areas and species that cannot move fast enough, more active, species-specific interventions may be necessary. [ABSTRACT FROM AUTHOR]