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

Habitat dynamics of flagship species for conservation prioritization in southern Europe

Biodiversity loss is accelerating due to human actions, and decision-making for conservation needs to be streamlined. Ex situ biodiversity modeling and monitoring based on satellite time-series data could be an affordable and cost-efficient tool for improving the prioritization of conservation areas. We developed a set of dynamic indicators for conservation prioritization based on a habitat suitability index (HSI) trend analysis of 6 flagship species (two vascular plants, bird, amphibian, reptile, and mammal) over 19 years (2001-2019) in Andalucía (southern Spain). The HSI models were derived from ecological niche models (MaxEnt) and satellite time-series data (MODIS) as predictors. Based on the annual HSI models of all species and using the spatial conservation prioritization tool Marxan, we derived interannual dynamic indicators of habitat quality for conservation prioritization. Overall, models showed a generalized habitat regression. The best predictors of habitat quality were related to vegetation composition and structure (land cover), climate (land surface temperature), and energy balance (evapotranspiration), matching with the ecology of climate (such as Abies pinsapo) or vegetation-dependent (such as Alytes dickhilleni) species. Marxan identified interannual dynamics for the priority areas outside and inside protected areas. Interannual variation in habitat quality led to shifting conservation priorities across Andalucia from 2001 to 2019. Only 10.5% of the region and 20% of protected areas showed high spatial stability. Stable zones appeared both inside and outside protected areas. The south and northeast consistently exhibited high-priority regions. The legacy indicator highlighted areas of historical importance that have since declined in importance. New high-value areas emerged in the south. Static and dynamic approaches to conservation planning differed significantly. Many areas prioritized in 2019 alone ranked lower when long-term trends were considered. Our multiscale method underscores the need to integrate temporal dynamics into effective conservation strategies to achieve long-term conservation objectives in an efficient way.

The global distribution and risk prediction of Anaplasmataceae species: a systematic review and geospatial modelling analysis

BACKGROUND

The family Anaplasmataceae, reclassified under the order Rickettsiales, represents a highly complex group that poses an increasing global threat. However, their infection risk remains poorly understood. We aimed to map the diversity, distribution, and potential infection risk of Anaplasmataceae members.

METHODS

We searched PubMed, Web of Science, bioRvix, and MedRvix for published articles to extract data on the detection of Anaplasmatacea species in vectors, animals, and humans from 1910 to 2022. We mapped the richness and global distribution of identified Anaplasmatacea species. Machine learning algorithms were applied to determine the ecological and vector-related factors contributing to the occurrence of major Anaplasmatacea members and project their potential risk distributions.

FINDINGS

A total of 2605 studies meeting our inclusion criteria were used for data extraction. We identified 85 species of Anaplasmataceae family from 134 tick species, 312 wild animals, and 12 domestic animals. Anaplasma phagocytophilum had the widest range of vectors (97 species), followed by Anaplasma marginale (54 species), Anaplasma bovis (46 species), Anaplasma ovis (37 species), and Anaplasma platys (35 species). Aanaplasmaphagocytophilum was also detected in the widest range of wildlife (208 species), followed by Ehrlichia chaffeensis (46 species), Candidatus Neoehrlichia mikurensis (36 species), Ehrlichia canis (35 species), and A. bovis (32 species). In total, 52,315 human cases involving 15 Anaplasmataceae species were recorded, A. phagocytophilum and E. chaffeensis accounted for majority of human infections (66·5% and 32·4%, respectively). According to our modelling analysis, the geographic distribution of six major Anaplasmatacea species is primarily influenced by the projected habitat suitability index of tick vectors and climatic conditions. Among these, A. phagocytophilum presents the highest risk, with an estimated 3·97 billion individuals and 8·95 million km2 area potentially affected.

INTERPRETATION

The widespread distribution of Anaplasmataceae species emphasizes the need to enhance identification, surveillance, and diagnosis efforts in high-risk areas, particularly within low-income regions.

FUNDING

The National Key Research and Development Program of China (2023YFC2605603) and the Natural Science Foundation of China (82330103).

Temporal Range Dynamics of the Lataste's Viper (Vipera latastei Boscá, 1878) in Doñana (Spain): Insights into Anthropogenically Driven Factors

Doñana (southern Spain), a region of notable biodiversity richness, is highly threatened by ongoing landscape transformation and climate change. We investigated the local effect of these anthropogenic factors on the temporal range dynamics of Lataste's viper (Vipera latastei), an Iberian endemic Mediterranean reptile that has apparently become rare over the years in Doñana. Using ecological niche-based models, based on climatic and remote sensing variables, we analyzed historical (1959-1999) and contemporary (2000-2022) records of the species to assess range shifts and identify environmental factors that may influence them. Our results show that V. latastei is mostly restricted to the coastal region of Doñana and that one temperature variable is the most important factor explaining this distribution pattern in both periods. Additional climatic and vegetation variables play a role in its historical distribution, but they become less important in contemporary times, suggesting a niche simplification over time. We found 30.5% of reduction in the species suitable area from historical to contemporary conditions, a reduction that would be even greater (83.37%) in the absence of niche shift. These findings underscore the species' heightened vulnerability to ongoing environmental changes and highlight the urgent need for targeted conservation strategies.

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.