Biodiversity hotspots, defined as sites with the highest species diversity or as the most threatened and diverse sites, have been widely used in multiple disciplines to identify the priority areas for conservation (Reid, 1998; Ceballos and Ehrlich, 2006; Jha and Bawa, 2006; Willis et al., 2007; Davies, 2010). Based on this definition, hotspots are usually described as the concentration areas with rare species, threatened species, and 70% loss of primary vegetation (Myers et al., 2000). Most of Earth’s biodiversity is found in hotspots, and these hotspots provide a refuge or suitable habitat for vascular plants, mammals, amphibians, insects and others (Habel et al., 2019; Kidane et al., 2019; Trew and Maclean, 2021). Currently, 36 biogeographical regions are highlighted as global conservation priorities owing to their exceptional endemism, and there is a great threat to vegetation integrity (Hrdina and Romportl, 2017). The annual average cost of the global network of conservation zones is estimated to be US$ 27.5 billion, representing the largest investment in protection funds (Gössling, 2002; Mittermeier et al., 2011). Further determining priority conservation zones on different geographic scales for species considering hotspots helps determine the concentration of resources and reallocation (Jepson and Canney, 2001; Trew and Maclean, 2021). However, few studies have discussed the spatial suitability of species in biodiversity hotspots. Evaluating the distribution suitability of species in hotspots is important for biodiversity conservation. For instance, the potential distribution map regarding wild strawberry and Ageratina adenophora was obtained by two studies (Yang et al., 2020; Changjun et al., 2021), and they both demonstrated the importance of exploring the distribution in hotspots. Farashi and Shariati (2017) studied Iran biodiversity hotspots and used a niche model and setting amounts of buffers for mammal, bird, and reptile species. Exploring the habitat suitability for some species and groups in the context of biodiversity hotspots is conducive to the implementation of targeted measures and the further conservation of biodiversity.

Insects, a neglected group, contribute to many functions and services in the natural ecosystem (Noriega et al., 2018; Elizalde et al., 2020; Noriega et al., 2020). Some of their contributions, such as pollination, pest control, and nutrient cycling, are of high value (Potts et al., 2016; Dainese et al., 2019; Uhler et al., 2021). For decades, increasing evidence has indicated that insect assemblages are undergoing significant changes in biodiversity owing to a suit of anthropogenic stress and climate change, especially in hotspots (Fattorini, 2011; Cardoso et al., 2020; Halsch et al., 2021; Moir, 2021; Outhwaite et al., 2022). This is attributable to the fact that substantial extinction pressure is put on insect populations by the fragmentation of biodiversity hotspots (Fonseca, 2009; Stork, 2010; Sullivan and Ozman-Sullivan, 2021). Hochkirch (2016) stated that we must preserve invertebrate biodiversity and pay more attention to the insect crisis. Thus, the protection of biodiversity hotspots will facilitate the reproduction and survival of insect taxa (Samways, 2007; Stork and Habel, 2014). Beetles, also known as Coleoptera, is the most diverse and species-rich insect group, and more than 380,000 species have been described worldwide (Zhang et al., 2018). Most beetles must rely on forests to survive, indicating that the increasing fragmentation of forest habitats will place enormous pressure on beetles. In addition to climate change, the alternation of natural landscapes by humans is a critical cause of insect biodiversity loss, especially for beetles. We focus on this group not only because it is the group with the largest number of species, but also because it has a high value for ecosystem services. For example, dung beetles perform functions such as nutrient cycling, bioturbation, secondary seed dispersal, and play an important role in increasing primary productivity and suppressing parasites in livestock (Nichols et al., 2008). Additionally, some beetles, such as ground beetles, are seen as bioindicators of the evaluation of environmental pollution and the recovery processes in postindustrial areas in accordance with their extreme sensitivity to ecological parameters, such as water quality and soil degradation (Elliott, 2008; Ghannem et al., 2018). Therefore, the critical role of beetles in ecological functions and ecosystems suggests that more attention should be given to beetle conservation. Understanding species distribution helps guide protection; however, there have been few studies on the distribution of beetles on the macro scale, which has fascinated many scholars. Consequently, exploring the spatial dynamics of the potential suitability distribution for beetles on several time scales may not only facilitate beetle biodiversity conservation, but also may be conducive to mitigating biodiversity degradation in hotspots.

For decades, the human footprint has spread all over the world, posing a huge threat to biodiversity, and thousands of species have lost their homes. As a means of determining global conservation priorities, exploring the spatial dynamics of beetles in hotspots is conducive to the conservation of biodiversity. Recently, the species distribution model (SDM) has been widely used to predict the potential geographic distribution of species, including the maximum entropy (MaxEnt) model, rule set prediction (GARP), ecological niche factor analysis (ENFA), and random forest (RF) (Pulliam, 2000; Farashi et al., 2013; Sheridan, 2013; Noriega et al., 2020; Yang et al., 2022). Among these, MaxEnt is preferred due to its impressive advantages, such as ease of operation, good performance, short run time, and relatively accurate results (Phillips and Dudík, 2008; Merow et al., 2013). Kong et al. (2021) established a climate distribution model under four climate change scenarios and revealed that isolated, fragmented giant panda populations were more vulnerable than other populations to extinction risk. Chowdhury et al. (2021) found that approximately 15% of butterflies may be at elevated extinction risk in the tropics, and most migratory butterflies face strong seasonal variation in habitat suitability by using MaxEnt to simulate the seasonal spatial dynamics of butterfly migration. To identify a stable refugia for relict plant species, Tang et al. (2018) mapped the distribution patterns for relict species in East Asia to identify suitable regions and obtained a long-term refuge combined with an abundance map. We also utilized this modeling approach to simulate the spatially suitable distribution for beetles in biodiversity hotspots.

Here, we develop current niche models for beetles and identify the priority suitable habitat under decades scales combined with hotspots, which allows us to observe the characteristics of spatial changes over the past decades. The objectives of this study include the following: (1) to simulate the integrated spatial suitability of beetles; (2) to identify the priority suitable habitat and hotspots for beetles at five scales; and (3) to evaluate the congruence between the suitable habitat of beetles and biodiversity hotspots.

To identify the level of complexity warranted, quantitative evaluation constitutes a significant component of distribution modeling, and the selection of optimal models was based on the results of evaluating various levels of complexity, resulting in different parameter combinations for different species under different times and spaces (Warren and Seifert, 2011; Radosavljevic and Anderson, 2014; Cobos et al., 2019; Kass et al., 2021). In our study, the complexity of the MaxEnt model became a critical part of obtaining a suitable distribution of Coleoptera in the context of 1970 to 2020, with temperature and precipitation as important driving factors. We determined different parameter combinations for beetles to simulate the comprehensive distribution under current climate changes. Unsurprisingly, model performance was effectively improved, as reflected in the model evaluation metrics (AUC≥0.85) and the agreement between the potential and actual distribution of beetles. Ultimately, we coupled current biodiversity hotspots with potential distributions to model the spatial priorities of beetles, and the consistency between them was assessed. This study also revealed the extinction risk of beetles in every biodiversity hotspot and the spatial dynamics of changes. Due to the high human interference of hotspots, we paid particular attention to some regions whose extinction risk in local habitat was correspondingly higher.

Our study indicated that ≤30% of the suitable zones in every ten-year period fell within the biodiversity hotspots, while the majority of suitable habitat were outside the hotspots, which did not mean that these suitable regions were not ecologically significant. In contrast, a higher suitability may occur in some other regions, but more concentrated manifestations were found in biodiversity hotspot areas because the delineation of hotspots contains more ecological significance (Cincotta et al., 2000; Marchese, 2015; Grande et al., 2020). Not only are these regions especially rich in endemic species and particularly threatened by human interference, but the largest sum was assigned to a single protection project (Norman, 2003). We clearly observed that most of Earth’s biodiversity is found in hotspots, and over 150,000 endemic plant species and approximately 13,000 endemic terrestrial vertebrates are sheltered (Bellard et al., 2014; Habel et al., 2019). However, the survival of insects and the richness of biodiversity go hand in hand, and thousands of modern insect extinctions are estimated to have occurred, which are the consequences of silent habitat loss and endemic biodiversity extinction (Dunn, 2005; Fonseca, 2009). The island biogeography theory proposed by Janzen (1968) states that any reduction in a plant species will result in a decrease in the richness of insect fauna. Direct conservation efforts have not been focused on insects. Therefore, we simulated the spatial distribution dynamics for Coleoptera, the largest order of insects, to explore the laws of changes and propose conservation recommendations. The results of this study indicated that the integrated suitability of beetles outside or in hotspots have similar dynamic changes. As the focus of distribution, Southern Europe and North America had a corresponding stability, while South America and Africa experienced a higher extinction risk, which may be attributed to climate changes, land use, and extensive growth of agriculture in recent decades (Higgins, 2007; Griffiths et al., 2010; Perrings and Halkos, 2015).

Although the overall distribution of suitable habitat in hotspots for beetles was relatively severe, these areas also demonstrated potential for beetle conservation and biodiversity restoration. Our results revealed that the potential areas for biodiversity improvement were 2.76×10⁷ km², 2.03×10⁷ km², 2.14×10⁷ km², 1.66×10⁷ km², 1.65×10⁷ km², and 2.16×10⁷ km² for A, B, C, D, E, and Total, respectively. In particular, approximately 49.08% (1.38×10⁷ km²) of fragmented habitat will strengthen forest restoration to increase carrying capacity. Thus, corresponding conservation and management measures should be implemented in some critical countries, including Spain, Turkey, Morocco, Italy, America, and Brazil. Natural recovery and reduction of human disturbance in these regions are significant measures, while a certain level of forest management monitoring should be implemented. For zones with a small but very concentrated distribution of suitable habitat, legislation should be strengthened to facilitate administration, and the further expansion of anthropogenic land must be reduced. Forest areas in these regions will continue to expand, diverse species may be reintroduced, and biodiversity will be improved to accommodate more populations in the long term. China, Chile, South Africa, Australia, and Japan are important countries to prioritize, and cross-border protection is a considerable initiative such as China, which will enhance connectivity between different suitable areas. For other scattered regions, implementing protection planning measures is a huge challenge as a result of fragmented suitability habitat, and many countries are involved. We must remind these countries, such as Mexico, Colombia, Feru, Bolivia, Ecuador, Iran, Kenya, and Tanrania, that attention should be given and that the fragmented suitable regions identified in this study will provide a useful reference for their conservation work.

Additionally, the Mediterranean Basin, Indo-Burma, Irano-Anatolian, and other excellent regions are optimistic. Local habitat restoration of forests and improvement of habitat connectivity for beetles can reduce the extinction risk and increase the population size. Most of beetles have difficulty traveling long distances (Ribak et al., 2013; Chen and Jackson, 2017; Javal et al., 2018). The beetle’s flight capacity is affected by environmental factors such as temperature, precipitation, elevation, and wind, so a significant influence produced by climate change on beetle dispersal and communication (Atkins, 1961; Evenden et al., 2014; Jones et al., 2019; Wijerathna and Evenden, 2020). This is also an important reason why the beetle’s suitable habitat is threatened. The restriction of dispersal and movement of insects can act at the individual to local ecosystem level and then affect the balance of the ecosystem (Loxdale and Lushai, 1999; Hore and Banerjee, 2017; Misso et al., 2017). Consequently, the improvement of fragmented habitat and local connectivity is imperative. Apparently, some conservation work is being carried out in an orderly manner, such as the construction of artificial log pyramids, the stumps colonized by a large tree transplanter, and a large-scale reintroduction of insects in Denmark (Tochtermann, 1987; Ebert, 2011; Méndez and Thomaes, 2021). Such protection measures specific to individual species are important for rare species and should be combined with measures such as afforestation and land use reduction to restore beetle habitat. All strategies, including increasing afforestation activities, reducing anthropogenic interference, and implementing other improvement measures, should be further implemented in different regions in combination with local management policies (Duffus et al., 2023). In addition, we recommend that the corresponding process of conservation work should consider the potential suitability habitat for species, which can indicate the direction and focus of future work.

According to the estimation areas for suitable regions in every biodiversity hotspot, the Cerrado, coastal forest of Eastern Africa, and others that experienced substantial expansion and contraction can formulate corresponding restoration measures combined with local forest distribution and biodiversity loss. Our results provide an important reference for their spatial dynamics and focus. As the first global study on the decadal spatial distribution of beetles, the dynamics of each biodiversity hotspot were expressed clearly. A detailed understanding of decade dynamics is crucial to evaluating the influence of climate change and anthropogenic threats to the suitable habitat of beetles, and we hope our study can provide useful references and recommendations for biodiversity conservation. In addition, some deficiencies exist for this study due to data limitations such as not every insect is adequately documented, substantial occurrence records from this database is significantly increasing from year to year, and the records keeping varies from region to region. All these limitations will affect the credibility and robustness of the model. Thus, our future work will focus on solving these challenges and collecting more accurate data, making our results more reliable.

The original contributions presented in the study are publicly available. This data can be found here: https://datadryad.org/stash/share/gEt_wy0OztunonK733IACHX7FB54AJ_areUhv5Zm19c.

This study does not contain any studies with human participants or animals performed by any of the authors.

PH: Writing – original draft, Writing – review & editing. MB: Data curation, Formal Analysis, Funding acquisition, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – review & editing. LL: Formal Analysis, Funding acquisition, Investigation, Project administration, Resources, Software, Validation, Visualization, Writing – review & editing. YL: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Project administration, Resources, Software, Validation, Visualization, Writing – review & editing. JL: Data curation, Formal Analysis, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing. ZY: Conceptualization, Formal Analysis, Funding acquisition, Investigation, Project administration, Resources, Software, Validation, Visualization, Writing – review & editing.