Cross-scale monitoring of habitat suitability changes using satellite time series and ecological niche models

Exploring the conservation of historic avian corridors under urbanization threats in China: A case study of egrets in the Greater Bay Area

This study explores the conservation of historic flyway corridors for egret in the Greater Bay Area (GBA), with a focus on habitat connectivity and dynamic corridors. To address the gaps in previous research, we used field observations, bio-climatic data and landcover information spanning three decades. Our approach involves MaxENT modeling and the Linkage Mapper method. The results showed that the MaxENT model effectively simulated the egret habitats at different levels, with coastlines and riverbanks emerging as primary habitat zones. Moreover, bio-climatic factors, particularly Bio 19 and Bio 8, played a dominant role, accounting for 90 % of the habitat suitability in 2020. Other factors contributed rather minimally. Through the utilization of resistance surface and corridor extraction methods, noteworthy alterations in the flyway networks emerged post-2000, followed by a gradual return to normal. Connectivity analyses highlighted a critical 30 km threshold for the egret preservation. Corridor widths should be determined based on cost-effective considerations. We conclude that combining MaxENT with the Linkage Mapper method, even with limited egret observations and integrating multi-source data, such as land cover, might simulate potential suitable habitats and flyway dynamics for waterbirds such as egrets. This study provides valuable insights for the egret conservation and the preservation of their habitats in the GBA, contributing to a global waterbird diversity and habitat quality.

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis

BACKGROUND

The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB.

METHODS

We searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level.

FINDINGS

We retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by B lonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species.

INTERPRETATION

The predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions.

FUNDING

National Key Research and Development Program of China.

Assessing vulnerability of reptile hotspots through temporal trends of global change factors in the Iberian Peninsula

Habitat degradation and climate change are major threats to the long-term persistence of reptile populations. However, their roles on primary productivity instability remain unclear at certain scales. Besides, the design of protected areas has often overlooked reptiles or assumed that their ecological requirements are represented under the umbrella of more charismatic species. Here, we assess the vulnerability of areas of high diversity of reptiles in the Iberian Peninsula to global change using data from satellite imagery. We focused on primary productivity, climate and land-use change because they are indicators of environmental variability that might impair ecosystem functioning and alter wildlife communities. We used linear regressions to detect monotonic temporal trends in primary productivity (through the enhanced vegetation index, EVI) and climate (mean temperature and accumulated precipitation) at two spatial resolutions (10-km² UTM squares and CORINE land-cover polygon level) over the period 2000-2020. We also determined how the strength of land-use and climate change affected the intensity of change in primary productivity at both spatial scales with multivariate linear regressions. We identified 339 hotspots (10-km² UTM squares) and monotonic increments of temperature, EVI or both occurred in 43 %, 16 % and 22 % of them, respectively. Positive trends of the EVI were related to increasing temperatures and changes in shrubland and forest cover. Within the hotspots with monotonic increments in EVI and temperature, EVI increments occurred in 65 % of the CORINE polygons that did not change their land-cover type, with stronger increases in tree crops. Finally, the Natura 2000 network provides only moderate protection to reptile hotspots, being most of the vegetation types relatively underrepresented. The proportion of forest and shrubland protected by the Natura 2000 network was higher in hotspots where EVI changed. Our procedures are relevant to prioritize hotspots requiring ground monitoring that allows economic and time savings.

Choosing among correlative, mechanistic, and hybrid models of species' niche and distribution

Different models are available to estimate species' niche and distribution. Mechanistic and correlative models have different underlying conceptual bases, thus generating different estimates of a species' niche and geographic extent. Hybrid models, which combining correlative and mechanistic approaches, are considered a promising strategy; however, no synthesis in the literature assessed their applicability for terrestrial vertebrates to allow best-choice model considering their strengths and trade-offs. Here, we provide a systematic review of studies that compared or integrated correlative and mechanistic models to estimate species' niche for terrestrial vertebrates under climate change. Our goal was to understand their conceptual, methodological, and performance differences, and the applicability of each approach. The studies we reviewed directly compared mechanistic and correlative predictions in terms of accuracy or estimated suitable area, however, without any quantitative analysis to support comparisons. Contrastingly, many studies suggest that instead of comparing approaches, mechanistic and correlative methods should be integrated (hybrid models). However, we stress that the best approach is highly context-dependent. Indeed, the quality and effectiveness of the prediction depends on the study's objective, methodological design, and which type of species' niche and geographic distribution estimated are more appropriate to answer the study's issue.

Strategies to Mitigate the Deteriorating Habitat Quality in Dong Trieu District, Vietnam

Dong Trieu district is a vital connection for territorial ecological security and human welfare between Hanoi (the capital of Vietnam) and Quang Ninh province. Therefore, habitat quality (HQ) is of extraordinary importance to the area’s sustainable development. The ArcGIS platform, Dyna-CLUE, and InVEST models were utilized in this study to assess the spatial and temporal transformations of land use and the changes of HQ in 2030 under various scenarios, with intentions to find strategies that may mitigate the HQ’s deteriorating trend in the district. Simulated results indicated that, assuming the development is maintained as usual, the average HQ of the District at 2030 could diminish by 0.044 from that of 2019 (a four-times decrease compared to the previous decade). Cases comprised of four basic scenarios, including development as usual, built-up expansion slowdown, forest protection emphasized, and agricultural land conversion, were used to identify potential strategies to mitigate the deteriorating trend. Simulated results revealed that keeping the built-up expansion rate lower than 100 ha y−1, the deforestation rate lower than 20 ha y−1, and preferring orchards over agricultural land conversion is required to limit the drop in HQ to within 0.01 in the next decade. Other than the existing population growth control policy, new guidelines such as (1) changing urban expansion type from outward to upward to control the built-up expansion rate, (2) substituting forest-harming industries to forest-preservation industries to reduce deforestation rate, (3) encouraging orchards preferred over agricultural land conversion to increase incomes while maintaining higher habitat quality, (4) practicing better farming technologies to improve crop production and to alleviate potential food security issues due to considerable reduction in cropland, and (5) promoting Green Infrastructure and the Belt and Road Initiative to increase urban green cover and raise residents’ income should be considered in designing the new mitigation strategies.

Predicting the Potential Global Distribution of Amblyomma americanum (Acari: Ixodidae) under Near Current and Future Climatic Conditions, Using the Maximum Entropy Model

Amblyomma americanum (the lone star tick) is a pathogen vector, mainly from eastern North America, that bites humans. With global integration and climate change, some ticks that are currently confined to a certain place may begin to spread out; some reports have shown that they are undergoing rapid range expansion. The difference in the potential geographic distribution of A. americanum under current and future climatic conditions is dependent on environment variables such as temperature and precipitation, which can affect their survival. In this study, we used a maximum entropy (MaxEnt) model to predict the potential geographic distribution of A. americanum. The MaxEnt model was calibrated at the native range of A. americanum using occurrence data and the current climatic conditions. Seven WorldClim climatic variables were selected by the jackknife method and tested in MaxEnt using different combinations of model feature class functions and regularization multiplier values. The best model was chosen based on the omission rate and the lowest Akaike information criterion. The resulting model was then projected onto the global scale using the current and future climate conditions modeled under four greenhouse gas emission scenarios.