A preliminary examination of genetic variation in a peripheral population of Blanding's turtle, Emydoidea blandingii

Random amplified polymorphic DNA (RAPD) was used to compare the Nova Scotia population of Blanding's turtle (Emydoidea blandingii) with several populations from the species' main range. The Nova Scotia population is believed to have been isolated from the main range for 4000-8000 years. Cluster analysis using a neighbour-joining algorithm produced a dendrogram showing the Nova Scotia population clustering separately from those populations in the main range. Analysis of molecular variance shows 34.28% of total variance to be accounted for between the Nova Scotia population and populations in the main range. While this study is preliminary, the results suggest that the Nova Scotia population of Blanding's turtle may be important to the maintenance of genetic diversity in the species.     

Habitat suitability modelling to improve conservation status of two critically endangered endemic Afromontane forest bird species in Taita Hills,Kenya

Tropical montane forests are known to support many endemic species with restricted geographic ranges. Many of these species are however, faced with numerous threats, most notably from habitat loss and degradation, invasive alien species, and climate change. Examples include Taita Apalis and Taita Thrush. Taita Apalis (Apalis fuscigularis) and Taita Thrush (Turdus helleri) are species of birds listed as Critically Endangered by the Government of Kenya and the International Union for Conservation of Nature (IUCN). They are endemic to Taita Hills’ cloud forests in southeastern Kenya and protected under Wildlife Conservation and Management Act. As they face high risk of extinction, exploring their habitat suitability is imperative for their protection. To determine the current spatial distribution and the key ecogeographical explanatory factors and conditions affecting species distribution and indirect effects on species survival and reproduction, we employed Maximum Entropy (MaxEnt) modelling. This study was conducted in Ngangao and Vuria forests in June and July 2019 and 2020. Ngangao forest is gazetted as forest reserve and managed by the Kenya Forest Service whereas Vuria is non-gazetted and thus remains without official protection status. Ecogeographical explanatory variables; climatic, remote sensing-, LIDAR-, topography- and landscape-based variables were used in modelling and separate models were produced. 23 occurrence records of Taita Apalis and 30 of Taita Thrush from Ngangao and 21 of Taita Apalis from Vuria forests were used in the modelling. According to the models, less than 7% of the total area of Ngangao and Vuria forests was predicted as suitable habitat for Taita Apalis and Taita Thrush. This shows that these two species are more vulnerable to extinction from demographic stochasticity. Consequently, managing their habitats is critical for their long-term persistence. LIDAR-based canopy height range and elevation greatly influenced Taita Apalis distribution in Ngangao forest, with areas of high elevation (1620–1750 m a.s.l.) and having open middle-storey preferred. Elevation, slope and topographic wetness index (twi) were the major determinants of Taita Thrush distribution in Ngangao, where gentle sloping areas with moderately dry surfaces within high elevation (1620–1730 m a.s.l.) were favoured. Mean annual temperature, Euclidean distance to the forest edge, slope and land cover type greatly influenced the distribution of Taita Apalis in Vuria, with gentle sloping areas within forest interior made up of indigenous vegetation preferred. This study proposes reforesting open and degraded sites next to areas predicted as highly suitable for the two species; establishment of agroforestry belts based on indigenous trees on the boundaries of the two forests to reduce grazing and firewood collection pressure and enhance resilience to the edge effects; and enhancing forest protection through Participatory Forest Management.     

Mapping suitability for Buruli ulcer at fine spatial scales across Africa: A modelling study

Buruli ulcer (BU) is a disabling and stigmatising neglected tropical disease (NTD). Its distribution and burden are unknown because of underdiagnosis and underreporting. It is caused by Mycobacterium ulcerans, an environmental pathogen whose environmental niche and transmission routes are not fully understood. The main control strategy is active surveillance to promote early treatment and thus limit morbidity, but these activities are mostly restricted to well-known endemic areas. A better understanding of environmental suitability for the bacterium and disease could inform targeted surveillance, and advance understanding of the ecology and burden of BU. We used previously compiled point-level datasets of BU and M. ulcerans occurrence, evidence for BU occurrence within national and sub-national areas, and a suite of relevant environmental covariates in a distribution modelling framework. We fitted relationships between BU and M. ulcerans occurrence and environmental predictors by applying regression and machine learning based algorithms, combined in an ensemble model to characterise the optimal ecological niche for the disease and bacterium across Africa at a resolution of 5km x 5km. Proximity to waterbodies was the strongest predictor of suitability for BU, followed potential evapotranspiration. The strongest predictors of suitability for M. ulcerans were deforestation and potential evapotranspiration. We identified patchy foci of suitability throughout West and Central Africa, including areas with no previous evidence of the disease. Predicted suitability for M. ulcerans was wider but overlapping with that of BU. The estimated population living in areas predicted suitable for the bacterium and disease was 46.1 million.These maps could be used to inform burden estimations and case searches which would generate a more complete understanding of the spatial distribution of BU in Africa, and may guide control programmes to identify cases beyond the well-known endemic areas.     

桥边河大型底栖动物生境适宜性

构建精度高,适用性强的水生生物生境适宜性评价模型,为河流生境质量评价和生境修复提供理论依据。以长江一级支流桥边河为例,采用典范对应分析和独立性分析,筛选出影响桥边河大型底栖无脊椎动物优势种河蚬生境质量的关键化学因子和物理因子,利用广义加性模型与多项式拟合模型构建生境因子与生物选择的关系。结果表明:(1)影响桥边河河蚬生境质量的主要因子为COD_Mn、TN、DO、Tur (浊度)和Dep (水深);其中COD_Mn、TN、Tur、Dep与大型底栖无脊椎动物分布成负相关,DO与大型底栖无脊椎动物分布成正相关;(2)桥边河流域河蚬的最适宜COD_Mn含量为1.228 mg/L,最适宜TN含量为0.269 mg/L,最适宜DO含量为11.170 mg/L,最适宜Dep为0.3 m,最适宜Tur为1.130 NTU。(3)线性拟合情况下两种方法均适用;非线性拟合情况下广义加性模型较优于传统多项式拟合模型,且GAM模型在处理离散程度大的数据集时,可以很好的规避多项式拟合过程中出现的过拟合现象。研究显示,运用GAM模型可以更加精确、合理的模...     

Amphibian species richness and distribution in relation to pond water chemistry in south-western Ontario, Canada

1. We assessed the patterns of amphibian species richness and distribution in relation to water chemistry over a large geographical area in 1992–94.
2. Thirteen amphibian species were observed at 180 ponds, with mean species richness 3.5 ± 0.13 species per pond (range zero to nine). Water samples were collected from 143 ponds, analysed for fifteen chemical variables, and further analysed by multivariate statistical techniques.
3. Water in the study area was hard, alkaline and well-buffered against pH change, and most ponds were eutrophic. Amphibian species richness was negatively correlated with five chemical variables (chloride, conductivity, magnesium, total hardness, turbidity).
4. Principle components analysis reduced the data set to four chemical components that explained 65.4% of the variance in the original variables. Principle component scores were retained for use in further multivariate tests. Multiple regression accounted for only 19.0% of the variance in amphibian species richness. Discriminant function analysis (DFA) was used to determine if water chemistry variables discriminated among species, but it was only able to classify 17.5% of cases correctly. DFA was also used to determine if water chemistry distinguished between used and unused sites for individual species. DFA was moderately successful, classifying 61–77% of cases correctly.
5. General water chemistry appears to play only a minor part in affecting amphibian species richness in south-western, Ontario. However, chemical variables may be helpful to distinguish between used and unused sites for some species.     

Amphibian species richness and distribution in relation to pond water chemistry in south-western Ontario, Canada

1. We assessed the patterns of amphibian species richness and distribution in relation to water chemistry over a large geographical area in 1992–94.
2. Thirteen amphibian species were observed at 180 ponds, with mean species richness 3.5 ± 0.13 species per pond (range zero to nine). Water samples were collected from 143 ponds, analysed for fifteen chemical variables, and further analysed by multivariate statistical techniques.
3. Water in the study area was hard, alkaline and well-buffered against pH change, and most ponds were eutrophic. Amphibian species richness was negatively correlated with five chemical variables (chloride, conductivity, magnesium, total hardness, turbidity).
4. Principle components analysis reduced the data set to four chemical components that explained 65.4% of the variance in the original variables. Principle component scores were retained for use in further multivariate tests. Multiple regression accounted for only 19.0% of the variance in amphibian species richness. Discriminant function analysis (DFA) was used to determine if water chemistry variables discriminated among species, but it was only able to classify 17.5% of cases correctly. DFA was also used to determine if water chemistry distinguished between used and unused sites for individual species. DFA was moderately successful, classifying 61–77% of cases correctly.
5. General water chemistry appears to play only a minor part in affecting amphibian species richness in south-western, Ontario. However, chemical variables may be helpful to distinguish between used and unused sites for some species.     

The value of endangered species in protected areas at risk: the case of the leatherback turtle in the Dominican Republic

Protected areas are considered essential elements for global biodiversity conservation. They may not necessarily result in an effective conservation of resources in developing countries due to lack of funding for management and enforcement. In addition, poor governance aligned with conflicts of economic interests related to their use can further threaten their integrity and persistence. In the Dominican Republic, the western beaches of the Jaragua National Park (JNP), a protected area which is also part of a UNESCO Biosphere Reserve, have been proposed for development using a mass-tourism model. One of the most charismatic species found in this area is the leatherback turtle (Dermochelys coriacea). In the present study, we assess hatching success, and factors affecting it, to determine the reproductive value across the area for the leatherback turtle. The main factors found driving hatching success at the study beaches are beach sector, incubation duration, date of lay and clutch size. Our results show that clutches in La Cueva (located in the buffer zone of the park) and Bahía de las Águilas (located inside the limits of the park) have an unusually high hatching success (~75 %) for this species, highlighting the importance of increasing protection efforts at these sites. We strongly recommend including La Cueva inside the limits of the JNP.     

Habitat suitability for three species of Anopheles mosquitoes: larval growth and survival in reciprocal placement experiments

Larval habitats of the main malaria vectors in Belize are associated with three distinctly different aquatic environments: marshes with sparse macrophytes and cyanobacterial mats (Anopheles albimanus), tall dense macrophyte marshes (An. vestitipennis), and floating detritus assemblages within freshwater rivers (An. darlingi). We assessed species-specific habitat suitability based upon nutrient characteristics using larval survival rates (SR) and wing lengths (WL) from floating habitat enclosures. Anopheles albimanus showed a high SR (81%) in all three habitats, while An. vestitipennis had a similarly high SR in its own habitat (82%) and An. darlingi's habitat (81%). Anopheles darlingi only showed high SR (85%) in its own habitat. Both An. vestitipennis and An. darlingi showed very low SR in the An. albimanus habitat. There were no significant WL differences among field-caught, laboratory-reared, and experimental populations of An. vestitipennis and An. albimanus, with the exception of An. vestitipennis experimental populations and An. vestitipennis field populations placed in the An. albimanus habitat. Habitat quality indicators, particulate organic carbon (POC), dissolved organic carbon (DOC), and particulate organic nitrogen (PON), were consistently higher in An. vestitipennis habitats than in the habitats of the other two species. Correspondingly, An. vestitipennis adults were larger when measured both as dry mass and from WL. There were no differences in dry mass, lipids, or protein content among the same species reared at different locations. We compared SR and WL among mosquitoes from shaded and unshaded containers to test whether the high mortality rates for An. vestitipennis and An. darlingi in the An. albimanus habitat were due to intense sun exposure. There were no significant differences among developmental times, survivorship, or adult size for shaded versus sun-exposed populations. This indicates that other factors such as larval toxins, predator avoidance, interspecific species competition, etc. may be responsible for the higher mortality rates in those species not adapted to this particular habitat.     

Widespread occurrence of Batrachochytrium dendrobatidis in Ontario,Canada, and predicted habitat suitability for the emerging Batrachochytrium salamandrivorans

Chytridiomycosis, caused by the fungi Batrachochytrium dendrobatidis and Batrachochytrium salamandrivorans, is associated with massive amphibian mortality events worldwide and with some species’ extinctions. Previous ecological niche models suggest that B. dendrobatidis is not well‐suited to northern, temperate climates, but these predictions have often relied on datasets in which northern latitudes are underrepresented. Recent northern detections of B. dendrobatidis suggest that these models may have underestimated the suitability of higher latitudes for this fungus. We used qPCR to test for B. dendrobatidis in 1,041 non‐invasive epithelial swab samples from 18 species of amphibians collected across 735,345 km² in Ontario and Akimiski Island (Nunavut), Canada. We detected the pathogen in 113 samples (10.9%) from 11 species. Only one specimen exhibited potential clinical signs of disease. We used these data to produce six Species Distribution Models of B. dendrobatidis, which classified half of the study area as potential habitat for the fungus. We also tested each sample for B. salamandrivorans, an emerging pathogen that is causing alarming declines in European salamanders, but is not yet detected in North America. We did not detect B. salamandrivorans in any of the samples, providing a baseline for future surveillance. We assessed the potential risk of future introduction by comparing salamander richness to temperature‐dependent mortality, predicted by a previous exposure study. Areas with the highest species diversity and predicted mortality risk extended 60,530 km² across southern Ontario, highlighting the potential threat B. salamandrivorans poses to northern Nearctic amphibians. Preventing initial introduction will require coordinated, transboundary regulation of trade in amphibians (including frogs that can carry and disperse B. salamandrivorans), and surveillance of the pathways of introduction (e.g., water and wildlife). Our results can inform surveillance for both pathogens and efforts to mitigate the spread of chytridiomycosis through wild populations.     

Risk factors for outbreaks of SARS-CoV-2 infection at retirement homes in Ontario,Canada: a population-level cohort study

BACKGROUND:The epidemiology of SARS-CoV-2 infection in retirement homes (also known as assisted living facilities) is largely unknown. We examined the association between home-and community-level characteristics and the risk of outbreaks of SARS-CoV-2 infection in retirement homes since the beginning of the first wave of the COVID-19 pandemic.METHODS:We conducted a population-based, retrospective cohort study of licensed retirement homes in Ontario, Canada, from Mar. 1 to Dec. 18, 2020. Our primary outcome was an outbreak of SARS-CoV-2 infection (≥ 1 resident or staff case confirmed by validated nucleic acid amplification assay). We used time-dependent proportional hazards methods to model the associations between retirement home– and community-level characteristics and outbreaks of SARS-CoV-2 infection.RESULTS:Our cohort included all 770 licensed retirement homes in Ontario, which housed 56 491 residents. There were 273 (35.5%) retirement homes with 1 or more outbreaks of SARS-CoV-2 infection, involving 1944 (3.5%) residents and 1101 staff (3.0%). Cases of SARS-CoV-2 infection were distributed unevenly across retirement homes, with 2487 (81.7%) resident and staff cases occurring in 77 (10%) homes. The adjusted hazard of an outbreak of SARS-CoV-2 infection in a retirement home was positively associated with homes that had a large resident capacity, were co-located with a long-term care facility, were part of larger chains, offered many services onsite, saw increases in regional incidence of SARS-CoV-2 infection, and were located in a region with a higher community-level ethnic concentration.INTERPRETATION:Readily identifiable characteristics of retirement homes are independently associated with outbreaks of SARS-CoV-2 infection and can support risk identification and priority for vaccination.

Frail older adults living in congregate care settings have been at the centre of the COVID-19 pandemic in Canada and internationally.^1,2 Long-term care facilities — whose residents are the congregate living population most affected by COVID-19 — have been the subject of immense scientific and public interest during the pandemic.³ Retirement homes (often known as assisted living facilities) have received far less examination despite also housing many vulnerable older adults.^4–7 In contrast to long-term care facilities, retirement homes are private residential complexes that provide a range of supportive care and lifestyle services that are purchased out of pocket by residents or their families.⁸ Although residents of retirement homes access supportive care services, they are substantially less frail and dependent than residents of long-term care homes.⁵ Inconsistent regulation of these facilities throughout Canada and the United States has limited research into the epidemiology of SARS-CoV-2 infection in retirement homes.⁹There are 770 licensed retirement homes in Ontario, Canada’s most populous province, that house more than 50 000 older adults, a population size that approaches the number of Ontario residents of long-term care homes.¹⁰ Since the onset of the COVID-19 pandemic in Ontario, the number of positive cases and deaths in retirement homes has continued to grow. As of Apr. 11, 2021, retirement home residents accounted for about 8% of deaths from COVID-19 in Ontario (596/7552).¹¹ Outbreaks of SARS-CoV-2 infection surged in retirement homes during the first and second waves in Canada and the US,^11,12 and there has been limited examination in the literature beyond early reports of case surveillance.¹³We examined the association between home- and community-level characteristics and the risk of outbreaks of SARS-CoV-2 infection during the first wave of the COVID-19 epidemic in Ontario’s retirement homes. Consistent with our previous population-level work in Ontario long-term care homes,^2,14 we hypothesized that home size and regional incidence of SARS-CoV-2 infection would be associated with the risk of an outbreak.     

Habitat rehabilitation for juvenile fish in urban waterways: A case study from Berlin,Germany

This study examines the improvement of juvenile fish recruitment by technical rehabilitation measures implemented in two urban waterways in Berlin, Germany: the River Spree and the Teltow Canal. Rehabilitation sites provide new littoral habitats protected from navigation‐induced flow and wake wash and are intended to improve habitat quality for juvenile fish and to support urban fish diversity. Both sites and four control sites with common embankments have been sampled monthly by point electric fishing (875 dips in total) from May to September 2009. In total, 6,243 fish were caught representing 12 species. Two of the species, roach (Rutilus rutilus) and perch (Perca fluviatilis), dominated the fish community, comprising 81.5% and 16.1% of the total catch. Nine species were rare, with relative abundances <1%, which hampered more detailed species‐specific analyses. Of the dips 33% contained no fish, causing zero‐inflation of the dataset. A hurdle regression model confirmed positive effects of reduced hydraulic disturbances and resulting vegetation cover on juvenile fish occurrence. However, it also showed low oxygen concentrations limiting habitat quality, as observed at the older, densely vegetated rehabilitation site in the River Spree. The general improvement of the juvenile fish assemblage by the rehabilitation measure appeared rather low, as partially vegetated, rectangle trapeze and trapeze profile banks had even higher fish abundance. The study also revealed a need for adaptive maintenance to improve the long‐term performance of this type of rehabilitation structure. With the recovery of aquatic vegetation, the technical bank protection should be adaptively removed to retain the connectivity with the main channel for a sufficient oxygen supply for the long‐term functionality as a fish habitat.     

Using habitat suitability models to sample rare species in high-altitude ecosystems: a case study with Tibetan argali

Models of the distribution of rare and endangered species are important tools for their monitoring and management. Presence data used to build up distribution models can be based on simple random sampling, but this for patchy distributed species results in small number of presences and therefore low precision. Convenience sampling, either based on easily accessible units or a priori knowledge of the species habitat but with no known probability of sampling each unit, is likely to result in biased estimates. Stratified random sampling, with strata defined using habitat suitability models [estimated in the resource selection functions (RSFs) framework] is a promising approach for improving the precision of model parameters. We used this approach to sample the Tibetan argali (Ovis ammon hodgsoni) in Indian Transhimalaya in order to estimate their distribution and to test if it can lead to a significant reduction in survey effort compared to random sampling. We first used an initial sample of argali feeding sites in 2005 and 2006 based on a priori selected vantage points and survey transects. This initial sample was used to build up an initial distribution model. The spatial predictions based on estimated RSFs were then used to define three strata of the study area. The strata were randomly sampled in 2007. As expected, much more presences per hour were obtained in the high quality strata compared to the low quality strata—1.33 obs/h vs. 0.080/h. Furthermore the best models selected on the basis of the prospective sample differed from those using the first a priori sample, suggesting bias in the initial sampling effort. The method therefore has significant implications for decreasing sampling effort in terms of sampling time in the field, especially when dealing with rare species, and removing initial sampling bias.     

The contribution of small collections to species distribution modelling: A case study from Fuireneae (Cyperaceae)

The recent and rapid digitization of biodiversity data from natural history collection (NHC) archives has enriched collections based data repositories; this data continues to inform studies of species' geographic distributions. Here we investigate the relative impact of plant data from small natural history collections (collections with < 100,000 specimens) on species distributional models in an effort to document the potential of data from small NHCs to contribute to and inform biodiversity research. We modelled suitable habitat of five test case species from Fuireneae (Cyperaceae) in the United States using specimen records available via the Global Biodiversity Information Facility and that of data ready to mobilize from two regional small herbaria. Data were partitioned into three datasets based on their source: 1) collections-based records from large NHCs accessed GBIF, 2) collections-based records from small NHCs accessed from GBIF, and 3) collections-based records from two small regional herbaria not yet mobilized to GBIF. We extracted and evaluated the ecological niche represented for each of the three datasets by applying dataset occurrences to 14 environmental factors, and we modelled habitat suitability using Maxent to compare the represented distribution of the environmental values among the datasets. Our analyses indicate that the data from small NHCs contributed unique information in both geographic and environmental space. When data from small collections were combined with data from large collections, species models of the ecological niche resulted in more refined predictions of habitat suitability, indicating that small collections can contribute unique occurrence data which enhance species distribution models by bridging geographic collection gaps and shifting modelled predictions of suitable habitat. Inclusion of specimen records from small collections in ongoing digitization efforts is essential for generating informed models of a species' niche and distribution.     

Ranking birdstrike risk: A case study at Huanghua International Airport, Changsha, China

Bird-aircraft collisions (birdstrikes) pose a major threat to aviation safety worldwide. The bird distribution at the airfield of Huanghua International Airport in Changsha, Hunan Province, China, was investigated between December of 2006 and December of 2008, to study birdstrike avoidance and aviation safety. A total of 60 bird species was found and their risks were assessed by a birdstrike ranking assessment system. The highest-risk species were Barn swallow (Hirundo rustica), Red-rumped swallow (H. daurica), Grey-headed lapwing (Vanellus cinereus), Pintail snipe (Gallinago stenura), Oriental skylark (Alauda gulgula), Little egret (Egretta garzetta), and Eurasian woodcock (Scolopax rusticola), whereas the lowest-risk species were Black-capped kingfisher (Halcyon pileata) and White-throated kingfisher (H. smyrnensis). Through a hierarchical cluster analysis, all species were classified as four groups: (1) the extremely high-risk group with a risk level between 84% and 100%, which includes bird species ranked from the 1st to the 16th, and is the priori group in birdstrike prevention; (2) the high-risk group with a risk level between 71% and 81%, which includes bird species ranked from the 17th to the 28th, and is the sub-prior group in birdstrikes; (3) the sub-high-risk group with a risk level between 60% and 69%, which includes bird species ranked from the 29th to the 43rd, and is the concern group in birdstrike prevention; (4) the low-risk group with a risk level between 60% and 69%, which includes bird species ranked from the 44th to the 60th, and is the negligible group in birdstrike prevention. Finally, the first 16 bird species with high-risk values, which are the main focus of birdstrike prevention, were categorized as six prevention groups by a hierarchical cluster analysis. Therefore, this study provides targeted implementations for birdstrike prevention at Huanghua International Airport, Changsha.     

Ranking birdstrike risk: A case study at Huanghua International Airport, Changsha, China

Bird-aircraft collisions (birdstrikes) pose a major threat to aviation safety worldwide. The bird distribution at the airfield of Huanghua International Airport in Changsha, Hunan Province, China, was investigated between December of 2006 and December of 2008, to study birdstrike avoidance and aviation safety. A total of 60 bird species was found and their risks were assessed by a birdstrike ranking assessment system. The highest-risk species were Barn swallow (Hirundo rustica), Red-rumped swallow (H. daurica), Grey-headed lapwing (Vanellus cinereus), Pintail snipe (Gallinago stenura), Oriental skylark (Alauda gulgula), Little egret (Egretta garzetta), and Eurasian woodcock (Scolopax rusticola), whereas the lowest-risk species were Black-capped kingfisher (Halcyon pileata) and White-throated kingfisher (H. smyrnensis). Through a hierarchical cluster analysis, all species were classified as four groups: (1) the extremely high-risk group with a risk level between 84% and 100%, which includes bird species ranked from the 1st to the 16th, and is the priori group in birdstrike prevention; (2) the high-risk group with a risk level between 71% and 81%, which includes bird species ranked from the 17th to the 28th, and is the sub-prior group in birdstrikes; (3) the sub-high-risk group with a risk level between 60% and 69%, which includes bird species ranked from the 29th to the 43rd, and is the concern group in birdstrike prevention; (4) the low-risk group with a risk level between 60% and 69%, which includes bird species ranked from the 44th to the 60th, and is the negligible group in birdstrike prevention. Finally, the first 16 bird species with high-risk values, which are the main focus of birdstrike prevention, were categorized as six prevention groups by a hierarchical cluster analysis. Therefore, this study provides targeted implementations for birdstrike prevention at Huanghua International Airport, Changsha.     

Habitat suitability modelling reveals a strong niche overlap between two poorly known species,the broom hare and the Pyrenean grey partridge,in the north of Spain

In the present work, we derive a habitat suitability model of the broom hare and the Pyrenean grey partridge in the Cantabrian Mountains by using the Ecological Niche Factor Analysis. Both species are endemic to the northern of Iberian mountains, and because of the vulnerability of the hare to endangerment or extinction and because of the great interest in the partridge, this habitat requires specific conservation measures. Literature on these animals' biology and ecology is practically nonexistent. Habitat suitability analyses show that the hare and partridge occupy very similar ecological niches, characterized by a high percentage of broom and heather scrublands, high altitude and slope, and limited human accessibility. We have identified differences in habitat selection between the Pyrenean grey partridge and other subspecies of partridge present in central-northern Europe. Our results indicate a probable metapopulation structure for both the hare and partridge; however, according to our predictive maps, there is a high connectivity between suitable habitats. Current decline of traditional rural activities, such as mountain livestock, are affecting the mosaic landscape. This, in turn, enhances biodiversity in the area and, particularly, the viability of these valuable animal populations.     

Polygenic risk scores in cardiovascular risk prediction: A cohort study and modelling analyses

BackgroundPolygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD.Methods and findingsUsing data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703–0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009–0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40–75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to <10%) 10-year CVD risk could help prevent 1 additional CVD event for approximately every 340 individuals screened. Such a targeted strategy could help prevent 7% more CVD events than conventional risk prediction alone. Potential gains afforded by assessment of PRSs on top of conventional risk factors would be about 1.5-fold greater than those provided by assessment of C-reactive protein, a plasma biomarker included in some risk prediction guidelines. Potential limitations of this study include its restriction to European ancestry participants and a lack of health economic evaluation.ConclusionsOur results suggest that addition of PRSs to conventional risk factors can modestly enhance prediction of first-onset CVD and could translate into population health benefits if used at scale.

Luanluan Sun and colleagues investigate whether adding polygenic risk scores to conventional risk factors of cardiovascular disease helps predict disease risk.