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Urban environments are dynamic landscapes shaped by a multitude of factors, including environmental conditions and socio-economic influences. This study systematically investigates how various factors shape urban plant diversity in Haikou City, Hainan Province, China, focusing on 30 key drivers including socioeconomic aspects, biophysical conditions, landscape elements, and management practices. Our research methodology involved a comprehensive analysis of these factors' impact on six types of urban plant species: spontaneous, native spontaneous, exotic spontaneous, cultivated, native cultivated, and exotic cultivated. Conducted in urban areas with varying population densities and landscape features, our sampling approach aimed to understand the species' distribution patterns. We discovered significant correlations between plant species diversity and specific environmental and socio-economic variables. Our results indicate that spontaneous species are prevalent in densely populated areas with strong social ties, whereas areas rich in tree and shrub cover see fewer such species. Native cultivated species favor more serene, less urbanized landscapes, while exotic cultivated species are predominantly found in economically affluent areas with diverse vegetation. These findings offer valuable insights for urban planning and biodiversity conservation, emphasizing the need for customized greening strategies that align with local environmental and social contexts. By adopting such tailored approaches, urban planners can more effectively manage landscapes, enrich green spaces, and foster biodiverse, sustainable ecosystems. This research not only enhances our understanding of urban plant biodiversity but also lays the groundwork for future studies and policy-making, promoting harmonious integration of diverse plant life within urban settings. [ABSTRACT FROM AUTHOR]

Spatial patterns of biodiversity are inextricably linked to their collection methods, yet no synthesis of bias patterns or their consequences exists. As such, views of organismal distribution and the ecosystems they make up may be incorrect, undermining countless ecological and evolutionary studies. Using 742 million records of 374 900 species, we explore the global patterns and impacts of biases related to taxonomy, accessibility, ecotype and data type across terrestrial and marine systems. Pervasive sampling and observation biases exist across animals, with only 6.74% of the globe sampled, and disproportionately poor tropical sampling. High elevations and deep seas are particularly unknown. Over 50% of records in most groups account for under 2% of species and citizen‐science only exacerbates biases. Additional data will be needed to overcome many of these biases, but we must increasingly value data publication to bridge this gap and better represent species' distributions from more distant and inaccessible areas, and provide the necessary basis for conservation and management. [ABSTRACT FROM AUTHOR]

[Display omitted] • Longterm data is vital for management, but is frequently missing for many ecosystems. • Cave ecosystems are neglected hotspots of diversity and endemism. • Developing baselines for these systems requires integrating diverse data. • We discuss methods to reconstruct cave histories based on multiple data types. • Understanding past change and drivers may facilitate improved conservation. Whilst restoration and recovery of ecosystems has become a major priority, developing a baseline of what biodiversity was like prior to disturbance, and what might have driven changes in wildlife populations often remains unknown in many systems. Challenging to access ecosystems, such as subterranean ecosystems which cannot be monitored by remote sensing and frequently have very little information provide a significant challenge to understanding how biodiversity patterns may have changed, and how they might be more effectively managed. Caves represent unique ecosystems, key sites for our own human history, but with their unique conditions and stability can provide insights into their own past use as well as an index of local climate and vegetation. In addition, caves host many of the worlds over 1400 bat species, meaning that the ability to reconstruct past population trajectories may facilitate their conservation, as well as that of the many other, often undescribed cave dependant species. Here we discuss the various types of data from biological, chemical, geological and social that can be used to reconstruct the past history of cave sites across various timescales. We discuss the considerations needed for each approach as well as providing examples to guide the application of such approaches to better understand cave systems and their varying uses over time, and highlight how such data may facilitate cave management. [ABSTRACT FROM AUTHOR]