Relative Richness Research Articles

Elevational patterns and drivers of taxonomic and phylogenetic diversity of pteridophytes: A case study from the Himalaya

In recent times of global biodiversity crisis, documenting the distribution patterns of regional biodiversity and unravelling the drivers that shape these patterns has assumed urgent research priority. In mountains, understanding the distribution of biodiversity along elevational gradients is crucial to its conservation, restoration, and sustainable use. In the Himalaya – highest mountain range in the world – although studies focusing on the elevational distribution of higher plants (angiosperms and gymnosperms) are available, however such studies on lower plants such as pteridophytes are largely lacking. To fill this knowledge gap, here we investigate the elevational patterns of taxonomic and phylogenetic diversity of pteridophytes and their bioclimatic drivers in Jammu and Kashmir. We compiled a comprehensive dataset on 225 pteridophyte species of the study region. We divided the elevation gradient in the study region into 43 vertical bands, each with a width of 100 meters. We used regression analysis to assess the relationship of species richness (SR), standardized effect sizes of phylogenetic diversity (PDses), mean pairwise distance (MPDses), and mean nearest taxon distance (MNTDses) with the elevation. Our results revealed a mid-elevational peak in species richness and a half U-shaped curve in phylogenetic structure along the elevational gradient. We found phylogenetic clustering more or less at mid- and high-elevational bands and phylogenetic overdispersion at low-elevation bands. Taxonomic and phylogenetic ꞵ-diversity was mainly governed by species turnover component. Further, the precipitation-related climatic variables explained a greater proportion of the variation in SR compared to temperature-related variables; but converse was true for PDses, MPDses, and MNTDses, thereby indicating that niche conservatism and environmental filtering shape the composition of pteridophytes along the elevation in this Himalayan region. Overall, the findings of the present study advance our understanding about the elevational distribution patterns in pteridophytes with wide implications for ecology, evolution and biogeography of mountain biodiversity.

Geographic and ecological effects on species richness of liverworts worldwide

Liverworts are one of the oldest lineages of the extant land plants but the geographic patterns and ecological determinants of their species richness have not yet been studied at a global scale until now. Here, using a comprehensive global database, we find that regional species richness of liverworts in general 1) shows a clear latitudinal diversity pattern, 2) is highest in mountains, presumably reflecting the effects of habitat heterogeneity and the occurrence of cloud forest, 3) is more strongly influenced by contemporary climate than by climate change during the Quaternary, 4) is more strongly affected by precipitation‐related than by temperature‐related variables, reflecting the poikilohydric nature of liverworts and hence their water‐dependence, and 5) is more strongly affected by climate extremes than by climate seasonality. However, we find regional deviations from these general patterns, especially in the Southern Hemisphere where the distinct arrangement of land masses leads to different climatic patterns and thus climate–species richness relationships. Compared with other major land plant lineages, liverworts show the same importance of precipitation‐related factors as ferns, whereas in angiosperms temperature also plays an important role, reflecting the different physiological adaptations of these groups to drought and cold stress, and providing insights into the different evolutionary pathways taken by these lineages.

Understory plant biodiversity is inversely related to carbon storage in a high carbon ecosystem.

Given that terrestrial ecosystems globally are facing the loss of biodiversity from land use conversion, invasive species, and climate change, effective management requires a better understanding of the drivers and correlates of biodiversity. Increasingly, biodiversity is co-managed with aboveground carbon storage because high biodiversity in animal species is observed to correlate with high aboveground carbon storage. Most previous investigations into the relationship of biodiversity and carbon co-management do not focus on the biodiversity of the species rich plant kingdom, which may have tradeoffs with carbon storage. To examine the relationships of plant species richness with aboveground tree biomass carbon storage, we used a series of generalized linear models with understory plant species richness and diversity data from the USDA Forest Service Forest Inventory and Analysis dataset and high-resolution modeled carbon maps for the Tongass National Forest. Functional trait data from the TRY database was used to understand the potential mechanisms that drive the response of understory plants. Understory species richness and community weighted mean leaf dry matter content decreased along an increasing gradient of tree biomass carbon storage, but understory diversity, community weighted mean specific leaf area, and plant height at maturity did not. Leaf dry matter content had little variance at the community level. The decline of understory plant species richness but not diversity to increases in aboveground biomass carbon storage suggests that rare species are excluded in aboveground biomass carbon dense areas. These decreases in understory species richness reflect a tradeoff between the understory plant community and aboveground carbon storage. The mechanisms that are associated with observed plant communities along a gradient of biomass carbon storage in this forest suggest that slower-growing plant strategies are less effective in the presence of high biomass carbon dense trees in the overstory.

Improved Equations of the Lagrange Top and Examples of Analytical Solutions

Equations of a heavy rotating body with one fixed point can be deduced starting from a variational problem with holonomic constraints. When applying this formalism to the particular case of a Lagrange top, in the formulation with a diagonal inertia tensor the potential energy has a more complicated form as compared with that assumed in the literature on dynamics of a rigid body. This implies the corresponding improvements in equations of motion. Therefore, we revised this case, presenting several examples of analytical solutions to the improved equations. The case of precession without nutation has a surprisingly rich relationship between the rotation and precession rates, which is discussed in detail.

Convivialist multilingual education: theoretical and practical suggestions from a Norwegian perspective

The article aims at exploring the use of multilingual education to build a convivialist society. The article reflects theoretically on how to combine convivialist education and multilingual education. Today’s hyperdiversity in society faces a dual challenge in accelerating and unsettling climate change. The convivialist manifesto entails five key principles namely: common naturality where humans are interdependent with nature; common humanity which must be respected in each person beyond any identity differences; common sociality, based on long-lasting and rich relationships in various human communities; legitimate individuation where the singularity of the person contributes to the common good; and eventually, creative opposition where conflicts are dealt in a fertile, peaceful and deliberative manner. These key principles are additionally subordinated to the need to control human desire for hubris and never-ending possession which represents a political alternative to material growth ideology. The concept of intertwining convivialist education and multilingual education is illustrated through a case study [Master dissertation] in a Norwegian school context focusing on the significance of mother tongue education in the school curriculum for mitigating climate change. The data for the case study was gathered by conducting focus group discussions with three mother tongue teachers and two Norwegian language teachers working in a language school for newly arrived immigrant pupils in Norway. The findings identified the limitation of the Norwegian, section 2-8, lacunas in the bilingual learning curricula and it argued for the need to strengthen mother tongue education and the role of mother tongue teachers in promoting sustainable development in the school curriculum. Based on the study’s specific contextual findings and theoretical perspectives combining convivialist and multilingual education, the article infers that promoting multilingual education in schools can help mitigate climate change, and promote biocultural diversity and build a more convivialist society. The article thus aims to suggest some practical suggestions in a Norwegian plurilingual context and furthermore, it explores an expanded theoretical frame for convivialist multilingual education.

Integrative framework of multiple processes to explain plant productivity–richness relationships

Plant diversity and productivity, two crucial properties that sustain ecosystem structures, functions, and services, are intrinsically linked to numerous ecological fields, making productivity–richness relationships (PRR) a central ecological concern. Despite extensive research from the Darwinian era to the 21st century, the various shapes of PRR and their underlying theories have sparked ongoing debates. While several processes, theories, and integrative models have been proposed to explain PRR, a comprehensive understanding of the types of PRR, the effects of these processes on plant productivity and richness, and the relationships between PRR shapes remains elusive. This paper proposes a new integrative framework that focuses on these aspects, aiming to elucidate the diverse shapes of PRR and their interconnections. We review recent integrative methods that explain the roles of processes and the varying shapes in PRR to support this new framework. The paper traces the distinct phases in PRR research, including the discovery of PRR shapes, tests of influencing processes, and integrative research. We discuss the application of the Structural Equation Model (SEM), Statistical Dynamical Model (SDM), and Differential Dynamical Model (DDM) in integrative research. This integrative framework can guide theoretical and applied ecologists in identifying, deriving, explaining, and predicting the interconnected but distinct shapes of PRR. The humped, asymptotic, positive, negative, and irregular shapes of PRR are interconnected, with one shape potentially transforming into another. The balance between the positive and negative effects of different processes determines the different shapes of PRR, ultimately leading to a globally positive effect of plant diversity on plant productivity and other ecosystem functions.

Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion

Hypergraph captures high-order information in structured data and obtains much attention in machine learning and data mining. Existing approaches mainly learn representations for hypervertices by transforming a hypergraph to a standard graph, or learn representations for hypervertices and hyperedges in separate spaces. In this paper, we propose a hypergraph expansion method to transform a hypergraph to a standard graph while preserving high-order information. Different from previous hypergraph expansion approaches like clique expansion and star expansion, we transform both hypervertices and hyperedges in the hypergraph to vertices in the expanded graph, and construct connections between hypervertices or hyperedges, so that richer relationships can be used in graph learning. Based on the expanded graph, we propose a learning model to embed hypervertices and hyperedges in a joint representation space. Compared with the method of learning separate spaces for hypervertices and hyperedges, our method is able to capture common knowledge involved in hypervertices and hyperedges, and also improve the data efficiency and computational efficiency. To better leverage structure information, we minimize the graph reconstruction loss to preserve the structure information in the model. We perform experiments on both hypervertex classification and hyperedge classification tasks to demonstrate the effectiveness of our proposed method.

A new perspective on the spatial, environmental, and metacommunity controls of local biodiversity

Influential ecological research in the 1980s, elucidating that local biodiversity (LB) is a function of local ecological factors and the size of the regional species pool (γ-diversity), has prompted numerous investigations on the local and regional origins of LB. These investigations, however, have been mostly limited to single scales and target groups and centered exclusively on γ-diversity. Here we developed a unified framework including scale, environmental factors (heterogeneity and ambient levels), and metacommunity properties (intraspecific spatial aggregation, regional evenness, and γ-diversity) as hierarchical predictors of LB. We tested this framework with variance partitioning and structural equation modeling using subcontinental data on stream diatoms, insects, and fish as well as local physicochemistry, climate, and land use. Pure aggregation + regional evenness outperformed pure γ-diversity in explaining LB across groups. The covariance of the environment with aggregation + regional evenness rather than with γ-diversity generally explained a much greater proportion of the variance in diatom and insect LB, especially at smaller scales. Thus, disregarding aggregation and regional evenness, as commonly done, may lead to gross underestimation of the pure metacommunity effects and the indirect environmental effects on LB. We examined the shape of the local-regional species richness relationship, which has been widely used to infer local vs. regional effects on LB. We showed that this shape has an ecological basis, but its interpretation is not straightforward. Therefore, we advocate that the variance partitioning analysis under the proposed framework is adopted instead. In diatoms, metacommunity properties had the greatest total effects on LB, while in insects and fish, it was the environment, suggesting that larger organisms are more strongly controlled by the environment. Broader use of our framework may lead to novel biogeographical insights into the drivers of LB and improved projections of its trends along current and future environmental gradients.

Dwelling and healing with saints and jinn in the haunted landscapes of Palestine

The Jinn of Islamic and Middle Eastern popular mythology play a role in maintaining spatial divisions between sacred and profane space, public and protected areas, and acceptable and exceptional behaviour. Though research on jinn continues to be of importance in cross-cultural psychology, the rich relationship between jinn and place has largely been lost or severed. This paper seeks to restore this link through an examination of the relationship between unseen spirits and place in Palestine and throughout the Levant ( Bilad ash-Sham). Drawing upon both European and Palestinian historical ethnographic writing, as well as oral history interviews with Palestinian elders, this paper examines spatial practices that can attract, prevent, or heal harm from jinn and other unseen forces, as well as places where such spirits dwell, including graveyards, caves, wells, sacred trees, and shrines. Jinn play a dual role in helping to protect the sanctity of these places, while also threatening to violate the intimate space hearth and home. In this way, jinn play an important role in both establishing, and at times blurring and negotiating social mores and their related physical boundaries. In examining how jinn threaten the sanctity of homes and bodies, but also how place-dwelling spirits help to heal bodies and sooth souls, this paper moves beyond mere metaphorical understandings of spectral geographies to understand the material implications of unseen and imagined forces. By doing so, this paper builds upon recent research exploring the deep connection between the environment and spiritual/sacred understandings of place.

Seed sowing shifts native–exotic richness relationships in favor of natives during restoration

AbstractA central goal of ecological restoration is to promote diverse ecosystems dominated by native species, but restorations are often plagued by exotic species. A better understanding of factors underlying positive correlations between native and exotic species richness, a pattern that is nearly ubiquitous at large scales in plant communities, may help managers modify these correlations to favor native plant species during restoration. Across 29 tallgrass prairie sites restored through seed sowing onto former agricultural lands, we examined whether the relationship between native and exotic richness is (1) altered by management, such as seed additions and prescribed fire; (2) controlled instead by environmental conditions and successional processes; or (3) altered by management in certain environments and not in others. As is commonly found, native and exotic richness were positively correlated at large scales (i.e., across sites) in this study. Management actions explained much of the remaining variation in native richness, while environmental conditions explained very little. Sites sown with more species at higher seeding rates, especially forb species, had higher native richness than predicted by the native–exotic richness relationship. In contrast, native richness was lower in older restorations than predicted by the native–exotic richness relationship, because native richness, and not exotic richness, declined with restoration age. We show that management actions such as seed sowing can modify the native–exotic richness relationship to favor native species during restoration. The development of management actions that mitigate native species richness declines over time will further benefit native species restoration.

Sampling completeness changes perceptions of continental scale climate–species richness relationships in odonates

AbstractAimInsects are one of the least studied taxa, with most species lacking basic ecological and biogeographical information. This problem is particularly acute in the tropics, where low sampling effort hampers accurate estimates of species richness at scale and potentially confounds efforts to identify the drivers of biogeographical gradients. Here, we evaluate the quality of the data on the distribution and diversity of odonate species in the Neotropics, while also examining the influence of sampling completeness on climate–richness relationships using a comprehensive database of odonates.LocationThe Neotropics.TaxonOdonata.MethodsUsing 56,535 records collected from 1970 to 2021, we assess whether climate–species richness models vary under different scenarios of survey completeness.ResultsOur survey compilation revealed that most Neotropical diversity of Odonata likely remains unknown. Only 1% of the one‐degree cells covering the Neotropics held reliable information on odonate species richness, with particularly severe gaps in the Caribbean, Central America, northeastern Brazil and northern Chile. Temperature, precipitation and potential evapotranspiration exert consistent effects on Odonata richness across the entire Neotropics, regardless the level of survey completeness. Whereas seasonality‐related variables are less important predictors of species richness at the biogeographical scale.Main ConclusionsBy highlighting areas where inventories are more reliable and identifying regions that require increased data collection efforts and mobilization, our assessment offers a roadmap for improving the reliability of odonate inventories in the Neotropics. Furthermore, our findings underscore the importance of accounting for varying levels of survey completeness in macroecological models to reveal robust climate–species richness relationships. Simultaneously, they highlight strong climatic predictors of species richness, irrespective of survey effort intensity. These predictors provide a solid foundation for modelling and predicting odonate species richness in the Neotropics.

Species richness of Orthoptera declines with elevation while elevational range of individual species peaks at mid elevation.

Species richness has been shown to decrease, and elevational range increase (the Rapoport effect), with elevation as a consequence of biotic and abiotic factors, but patterns are inconsistent across taxonomic groups. Despite being an important indicator taxon and a component of local communities, Orthoptera distributions at higher elevations in Europe remain unclear. We investigated the relationship of Orthoptera species richness and elevational range with elevation in the Pyrenees mountains, Europe. We conducted sweepnetting surveys supplemented by hand-sampling, at 28 sites stratified by elevation, across three study areas. Using generalised linear models, we found that species richness declined with elevation. Elevation was an important predictor of species richness, but sampling effort and vegetation structure (height and cover) also contributed to estimates of species richness. Using a nonlinear regression to model the elevational range of species over the elevational gradient, we did not observe a Rapoport effect, with elevational range peaking at mid-elevation instead. Smaller elevational ranges of species found at high elevations may be due to a combination of sampling over a restricted elevational range and the presence of specialist high-elevation species. We argue that our findings are useful for understanding species distributions with elevation at the interface between local and regional scales. Clarifying the biotic and abiotic predictors of species distribution is important for informing conservation efforts and predicting consequences of climate change.

Foredune‐forming grass and plant diversity show contrasting responses along the southeastern United States coast after hurricane disturbance

AbstractAimsLatitudinal gradients in plant communities are well studied, yet how these fundamental ecological patterns influence ecosystem recovery after extreme weather events remains largely unknown. In coastal foredunes, we investigated how the cover of a key dune‐building grass (Uniola paniculata), vegetation diversity and vegetation cover vary along a short latitudinal gradient during recovery from hurricane disturbance.LocationSoutheastern USA.MethodsWe surveyed 24 sites, from central Florida to north Georgia (>400 km), four times over 18 months. General linear mixed‐effect models were used to unravel patterns of vegetation responses across latitude.ResultsVegetation properties showed countervailing patterns across the latitudinal gradient. While vegetation richness, functional diversity and total cover generally declined, Uniola cover increased with increasing latitude. Further, the latitude–richness relationship strengthened while the latitude–functional diversity relationship was invariant with increasing time since the hurricane disturbance. Meanwhile, the latitude–Uniola association was seasonally dependent and strongest in the summer. Latitude also influenced diversity–cover relationships: vegetation cover was positively related to species richness at lower latitudes, while it was positively associated with functional diversity only at northern sites. We found no relationship between species richness or functional diversity and increases in cover between time steps; however, recruitment of new species and functional groups was associated with increases in vegetation cover between time steps at northern sites.ConclusionsOur study highlights the temporal dynamism and contrasting patterns along latitudinal gradients exhibited by key engineering species and overall plant diversity in foredunes — a crucial line of coastal protection — exposed to hurricane disturbances. These results suggest a need for greater integration of latitudinal and diversity effects into our understanding of coastal dune resilience. They also highlight the potential benefits of enhancing dune plant biodiversity, particularly in areas where the dune‐building grasses that are classically employed in restoration (e.g., Uniola) are unfavoured, to accelerate the re‐establishment of well‐vegetated dunes.

Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach

The escalating use of alicyclic compounds in modern industrial production has led to a rapid increase of these substances in the environment, posing significant health hazards. Addressing this challenge necessitates a comprehensive understanding of these compounds, which can be achieved through the deep learning approach. Graph neural networks (GNN) known for its' extraordinary ability to process graph data with rich relationships, have been employed in various molecular prediction tasks. In this study, alicyclic molecules screened from PCBA, Toxcast and Tox21 are made as general bioactivity and biological targets' activity prediction datasets. GNN-based models are trained on the two datasets, while the Attentive FP and PAGTN achieve best performance individually. In addition, alicyclic carbon atoms make the greatest contribution to biological activity, which indicate that the alicycle structures have significant impact on the carbon atoms' contribution. Moreover, there are terrific number of active molecules in other public datasets, indicates that alicyclic compounds deserve more attention in POPs control. This study uncovered deeper structural-activity relationships within these compounds, offering new perspectives and methodologies for academic research in the field.

Linking Allusion Words: A Method of Combining Fine‐Grained Co‐citation Relationship and Semantic Features

ABSTRACTIt is a common phenomenon for Tang poems to cite the allusions, which can generate a rich relationship network. However, insufficient attention has been paid to investigating the relationship network. To address the research gap, by employing theories and methods of information science, this study presents a method of combining fine‐grained co‐citation relationship and semantic features to link allusion words. We constructed a fine‐grained co‐citation network between allusion words by adding cited positions and sentiments. We then transformed the fine‐grained weights into relational similarities. Moreover, we also leveraged the explanatory text as semantic information for each allusion word, mapping the semantic embedding vectors and calculating the similarities as the semantic similarities. Finally, we applied the link prediction algorithm to implement the allusion word linking. Our experimental results reveal that adding the cited positions and sentiments as well as semantic similarities can improve the performance of allusion word linking, achieving 0.869 on score. Additionally, we explore the linking results from the perspective of the shortest path and find some regular knowledge. Overall, our study extends the application of information science and promotes the development of Chinese traditional cultural resources.

Relationship of fungal spore richness, evenness, and abundance in school air with surrounding forest

Relationship of fungal spore richness, evenness, and abundance in school air with surrounding forest

Carbon and biodiversity cobenefits of second-growth tropical forest: The role of leaf phenology

Second-growth tropical forests offer important carbon and biodiversity cobenefits, as well as different leaf functional types of tree species. Leaf deciduousness is an important functional trait that can contribute to seasonal and spatial changes in carbon balance. We investigated the distribution pattern of carbon stock, species richness, and functional dominance among trees with differing leaf phenology (evergreen, semideciduous and deciduous) as well as the carbon and biodiversity cobenefits of tree communities in contrasting topographical conditions in a second-growth tropical Atlantic forest. We tested the hypotheses that topographic conditions shape differences in species richness and aboveground carbon stock between leaf phenology groups, as well as the carbon-biodiversity cobenefits within the tree communities. We studied fourteen 20 m × 40 m plots established in the forest with contrasting topographical conditions. We selected the mean functional traits related to carbon stock capacity in tropical forest: wood density and maximum tree height and calculated community-weighted mean metrics based on these traits. Aboveground biomass of trees for each stem sampled was calculated from a combination of variables using the general allometric equation. We constructed linear mixed-effect models (LMMs, with random and fixed effects) to test the cobenefits between aboveground carbon stock and leaf phenology group (evergreen, semideciduous and deciduous species) on species richness at community level. Our results showed that evergreen species had a higher richness, while the deciduous species had a greater contribution to aboveground carbon stock. Thus, the leaf phenology groups can affect the relationships between species richness and aboveground carbon stock. The deciduous species are key to maintaining higher carbon stock with smaller numbers of species; meanwhile evergreen species are important to maintain a higher species richness. Leaf phenology groups could be responsible for important cobenefits (i.e. positive aboveground carbon stock and species richness relationship) in Atlantic forests. Therefore, this study showed a relevant result on the relative contribution of leaf phenology groups in the carbon and biodiversity cobenefits along topographic gradients. In addition, our results allow for the selection of key tree species to improve management, conservation and restoration practices in the Atlantic forest in order to protect threatened biodiversity as a cobenefit of maintaining forests and the carbon they store.

How Biodiversity, Climate and Landscape Drive Functional Redundancy of British Butterflies.

Biodiversity promotes the functioning of ecosystems, and functional redundancy safeguards this functioning against environmental changes. However, what drives functional redundancy remains unclear. We analyzed taxonomic diversity, functional diversity (richness and β-diversity) and functional redundancy patterns of British butterflies. We explored the effect of temperature and landscape-related variables on richness and redundancy using generalized additive models, and on β-diversity using generalized dissimilarity models. The species richness-functional richness relationship was saturating, indicating functional redundancy in species-rich communities. Assemblages did not deviate from random expectations regarding functional richness. Temperature exerted a significant effect on all diversity aspects and on redundancy, with the latter relationship being unimodal. Landscape-related variables played a role in driving observed patterns. Although taxonomic and functional β-diversity were highly congruent, the model of taxonomic β-diversity explained more deviance than the model of functional β-diversity did. Species-rich butterfly assemblages exhibited functional redundancy. Climate- and landscape-related variables emerged as significant drivers of diversity and redundancy. Τaxonomic β-diversity was more strongly associated with the environmental gradient, while functional β-diversity was driven more strongly by stochasticity. Temperature promoted species richness and β-diversity, but warmer areas exhibited lower levels of functional redundancy. This might be related to the land uses prevailing in warmer areas (e.g., agricultural intensification).

Down syndrome or Rett syndrome in the family: Parental reflections on sibling experience

ABSTRACT Background Siblings of children with intellectual disability have unique family experiences, varying by type of disability. Methods Parents of children with Down syndrome (156) or with Rett syndrome (149) completed questionnaires relating to sibling advantages and disadvantages, experiences of holidays and recreation, and perceived availability of parental time. Qualitative responses were analysed using thematic analysis. Results Positive personality traits, an optimistic outlook, enhanced skills, and rich relationships were strong and consistent parental perceptions for siblings in both disability groups. Parents of children with Rett syndrome were more likely to rank themselves lower on time availability, and to report sibling difficulties with social engagement and family holidays. Conclusions Parental responses appeared to be influenced by disability type, and reflective of child capabilities. Perceptions of sibling experience should be supplemented by data collected directly from siblings to fully understand their unique perspective, and the ways in which their experiences could be enhanced.

Temporal Dynamic Concept Modeling Network for Explainable Video Event Recognition

Recently, with the vigorous development of deep learning and multimedia technology, intelligent urban computing has received more and more extensive attention from academia and industry. Unfortunately, most of the related technologies are black-box paradigms that lack interpretability. Among them, video event recognition is a basic technology. Event contains multiple concepts and their rich interactions, which can assist us to construct explainable event recognition methods. However, the crucial concepts needed to recognize events have various temporal existing patterns, and the relationship between events and the temporal characteristics of concepts has not been fully exploited. This brings great challenges for concept-based event categorization. To address the above issues, we introduce the temporal concept receptive field, which is the length of the temporal window size required to capture key concepts for concept-based event recognition methods. Accordingly, we introduce the temporal dynamic convolution (TDC) to model the temporal concept receptive field dynamically according to different events. Its core idea is to combine the results of multiple convolution layers with the learned coefficients from two complementary perspectives. These convolution layers contain a variety of kernel sizes, which can provide temporal concept receptive fields of different lengths. Similarly, we also propose the cross-domain temporal dynamic convolution (CrTDC) with the help of the rich relationship between different concepts. Different coefficients can help us to capture suitable temporal concept receptive field sizes and highlight crucial concepts to obtain accurate and complete concept representations for event analysis. Based on the TDC and CrTDC, we introduce the temporal dynamic concept modeling network (TDCMN) for explainable video event recognition. We evaluate TDCMN on large-scale and challenging datasets FCVID, ActivityNet, and CCV. Experimental results show that TDCMN significantly improves the event recognition performance of concept-based methods, and the explainability of our method inspires us to construct more explainable models from the perspective of the temporal concept receptive field.