Using GPS telemetry to validate least-cost modeling of gray squirrel (Sciurus carolinensis) movement within a fragmented landscape

Predictive value of glycoprotein DKK3 for early neurological deterioration after ischemic stroke

OBJECTIVE

To explore the value of serum Dickkopf-3 (sDKK3) in predicting Early Neurological Deterioration (END) and in-hospital adverse outcomes in acute ischemic stroke (AIS) patients.

METHODS

AIS patients (n = 200) were included and assessed by the National Institutes of Health Stroke Rating Scale. Serum Dkk3 levels were assessed by ELISA. END was defined as an increase of ≥ 4 points in NIHSS score within 72h. The biological threshold of sDKK3 level and END occurrence were predicted based on X-tile software. Primary outcomes were END and all-cause death, and the secondary outcome was ICU admission during hospitalization. The logistic regression model and Cox risk regression model were applied to evaluate the relationship between DKK3 level and END incidence, all-cause in-hospital mortality, and in-hospital adverse outcomes (ICU admission).

RESULTS

During hospitalization, the incidence of END in patients with AIS was 13.0 %, and the mortality rate within 7 days after END was 11.54 % (3/26). In patients below the serum DKK3 cutoff (93.0 pg/mL), the incidence of END was 43.5 % (20/48). Patients with lower sDKK3 levels were associated with a 1.188-fold increased risk of developing END (OR = 1.188, 95 % CI 1.055‒1.369, p < 0.0001). However, there was no significant association with admission to the ICU. sDKK3 below the threshold (93.0 pg/mL) was a risk factor for death.

CONCLUSION

Predictive threshold levels of serum DKK3 based on X-tile software may be a potential predictive biomarker of in-hospital END in patients with AIS, and low levels of DKK3 are independently associated with increased in-hospital mortality.

An evaluation of isolation by distance and isolation by resistance on genetic structure of the Persian squirrel (Sciurus anomalus) in the Zagros forests of Iran

For the conservation of wild species, it is important to understand how landscape change and land management can affect gene flow and movement. Landscape genetic analyses provide a powerful approach to infer effects of various landscape factors on gene flow, thereby informing conservation actions. The Persian squirrel is a keystone species in the woodlands and oak forests of Western Asia, where it has experienced recent habitat loss and fragmentation. We conducted landscape genetic analyses of individuals sampled in the northern Zagros Mountains of Iran (provinces of Kurdistan, Kermanshah, and Ilam), focusing on the evaluation of isolation by distance (IBD) and isolation by resistance (IBR), using 16 microsatellite markers. The roles of geographical distance and landscape features including roads, rivers, developed areas, farming and agriculture, forests, lakes, plantation forests, rangelands, shrublands, and rocky areas of varying canopy cover, and swamp margins on genetic structure were quantified using individual-based approaches and resistance surface modeling. We found a significant pattern of IBD but only weak support for an effect of forest cover on genetic structure and gene flow. It seems that geographical distance is an important factor limiting the dispersal of the Persian squirrel in this region. The results of the current study inform ongoing conservation programs for the Persian squirrel in the Zagros oak forest.

Deterministic, random, or in between? Inferring the randomness level of wildlife movements

BACKGROUND

When assessing connectivity, it is crucial to rely on accurate modeling frameworks that consider species movement preferences and patterns. One important aspect is the level of randomness or unpredictability in the route selection. In this respect, traditional approaches (based on least-cost path or circuit theory) consider species movements unrealistically as totally deterministic or as totally random. A recent approach (randomized shortest path) advocates for choosing intermediate levels of randomness through a single parameter. This parameter may be optimized by validating connectivity surfaces developed from different levels of randomness against observed movement data. However, connectivity models are seldom validated, and it is still unclear how to approach this task. To address this knowledge gap, this paper aims at comparing different validation methods to infer the optimal randomness level in connectivity studies. Additionally, we aimed to disentangle the practical consequences of applying traditional connectivity approaches versus using an optimized level of movement randomness when delineating corridors.

METHODS

These objectives were accomplished through the study case of the Iberian lynx, an endangered species whose maintenance and recovery depend on the current connectivity among its population nuclei. We firstly determined a conductance surface based on point selection functions accounting for the behavioral state (territorial or exploratory) of individuals. Secondly, we identified the level of randomness that better fits lynxes' movements with independent GPS locations and different validation techniques. Lastly, we delineated corridors between lynx population nuclei through a) the randomized shortest path approach and the extreme and optimal levels of randomness of each validation method, and b) the traditional connectivity approaches.

RESULTS

According to all used validation methodologies, models with intermediate levels of randomness outperformed those with extreme randomness levels representing totally deterministic or random movements. We found differences in the optimal randomness level among validation methods but similar results in the delineation of corridors. Our results also revealed that models with extreme randomness levels (deterministic and random walk) of the randomized path approach provided equivalent corridor networks to those from traditional approaches. Moreover, these corridor networks calculated with traditional approaches showed notable differences in patterns from the corridor network calculated with an optimized randomness level.

CONCLUSIONS

Here we presented a connectivity model with a solid biological basis that calibrates the level of movement randomness and is supported by comprehensive validation methods. It is thus a step forward in the search and evaluation of connectivity approaches that lead to improved, efficient, and successful management actions.

Assessment of accuracy, fix success rate, and use of estimated horizontal position error (EHPE) to filter inaccurate data collected by a common commercially available GPS logger

Global positioning system (GPS) technologies have improved the ability of researchers to monitor wildlife; however, use of these technologies is often limited by monetary costs. Some researchers have begun to use commercially available GPS loggers as a less expensive means of tracking wildlife, but data regarding performance of these devices are limited. We tested a commercially available GPS logger (i-gotU GT-120) by placing loggers at ground control points with locations known to < 30 cm. In a preliminary investigation, we collected locations every 15 minutes for several days to estimate location error (LE) and circular error probable (CEP). Using similar methods, we then investigated the influence of cover on LE, CEP, and fix success rate (FSR) by constructing cover over ground control points. We found mean LE was < 10 m and mean 50% CEP was < 7 m. FSR was not significantly influenced by cover and in all treatments remained near 100%. Cover had a minor but significant effect on LE. Denser cover was associated with higher mean LE, but the difference in LE between the no cover and highest cover treatments was only 2.2 m. Finally, the most commonly used commercially available devices provide a measure of estimated horizontal position error (EHPE) which potentially may be used to filter inaccurate locations. Using data combined from the preliminary and cover investigations, we modeled LE as a function of EHPE and number of satellites. We found support for use of both EHPE and number of satellites in predicting LE; however, use of EHPE to filter inaccurate locations resulted in the loss of many locations with low error in return for only modest improvements in LE. Even without filtering, the accuracy of the logger was likely sufficient for studies which can accept average location errors of approximately 10 m.

The relationship between least-cost and resistance distance

Least-cost modelling and circuit theory are common analogs used in ecology and evolution to model gene flow or animal movement across landscapes. Least-cost modelling estimates the least-cost distance, whereas circuit theory estimates resistance distance. The bias added in choosing one method over the other has not been well documented. We designed an experiment to test whether both methods were linearly related. We also tested the sensitivity of these metrics to variation in Euclidean distance, spatial autocorrelation, the number of pixels representing the landscape, and data aggregation. We found that least-cost and resistance distance were not linearly related unless a transformation was applied. Resistance distance was less sensitive to the number of pixels representing a landscape and was also less sensitive than least-cost distance to the Euclidean distance between nodes. Spatial autocorrelation did not affect either method or the relationship between methods. Resistance distance was more sensitive to aggregation in any form compared to least-cost distance. Therefore, the metric used to infer movement or gene flow and the manipulations applied to the data used to calculate these metrics may govern findings.

Evaluation of micro-GPS receivers for tracking small-bodied mammals

GPS telemetry markedly enhances the temporal and spatial resolution of animal location data, and recent advances in micro-GPS receivers permit their deployment on small mammals. One such technological advance, snapshot technology, allows for improved battery life by reducing the time to first fix via postponing recovery of satellite ephemeris (satellite location) data and processing of locations. However, no previous work has employed snapshot technology for small, terrestrial mammals. We evaluated performance of two types of micro-GPS (< 20 g) receivers (traditional and snapshot) on a small, semi-fossorial lagomorph, the pygmy rabbit (Brachylagus idahoensis), to understand how GPS errors might influence fine-scale assessments of space use and habitat selection. During stationary tests, microtopography (i.e., burrows) and satellite geometry had the largest influence on GPS fix success rate (FSR) and location error (LE). There was no difference between FSR while animals wore the GPS collars above ground (determined via light sensors) and FSR generated during stationary, above-ground trials, suggesting that animal behavior other than burrowing did not markedly influence micro-GPS errors. In our study, traditional micro-GPS receivers demonstrated similar FSR and LE to snapshot receivers, however, snapshot receivers operated inconsistently due to battery and software failures. In contrast, the initial traditional receivers deployed on animals experienced some breakages, but a modified collar design consistently functioned as expected. If such problems were resolved, snapshot technology could reduce the tradeoff between fix interval and battery life that occurs with traditional micro-GPS receivers. Our results suggest that micro-GPS receivers are capable of addressing questions about space use and resource selection by small mammals, but that additional techniques might be needed to identify use of habitat structures (e.g., burrows, tree cavities, rock crevices) that could affect micro-GPS performance and bias study results.

Evaluation of micro-GPS receivers for tracking small-bodied mammals

GPS telemetry markedly enhances the temporal and spatial resolution of animal location data, and recent advances in micro-GPS receivers permit their deployment on small mammals. One such technological advance, snapshot technology, allows for improved battery life by reducing the time to first fix via postponing recovery of satellite ephemeris (satellite location) data and processing of locations. However, no previous work has employed snapshot technology for small, terrestrial mammals. We evaluated performance of two types of micro-GPS (< 20 g) receivers (traditional and snapshot) on a small, semi-fossorial lagomorph, the pygmy rabbit (Brachylagus idahoensis), to understand how GPS errors might influence fine-scale assessments of space use and habitat selection. During stationary tests, microtopography (i.e., burrows) and satellite geometry had the largest influence on GPS fix success rate (FSR) and location error (LE). There was no difference between FSR while animals wore the GPS collars above ground (determined via light sensors) and FSR generated during stationary, above-ground trials, suggesting that animal behavior other than burrowing did not markedly influence micro-GPS errors. In our study, traditional micro-GPS receivers demonstrated similar FSR and LE to snapshot receivers, however, snapshot receivers operated inconsistently due to battery and software failures. In contrast, the initial traditional receivers deployed on animals experienced some breakages, but a modified collar design consistently functioned as expected. If such problems were resolved, snapshot technology could reduce the tradeoff between fix interval and battery life that occurs with traditional micro-GPS receivers. Our results suggest that micro-GPS receivers are capable of addressing questions about space use and resource selection by small mammals, but that additional techniques might be needed to identify use of habitat structures (e.g., burrows, tree cavities, rock crevices) that could affect micro-GPS performance and bias study results.

Defining landscape resistance values in least-cost connectivity models for the invasive grey squirrel: a comparison of approaches using expert-opinion and habitat suitability modelling

Least-cost models are widely used to study the functional connectivity of habitat within a varied landscape matrix. A critical step in the process is identifying resistance values for each land cover based upon the facilitating or impeding impact on species movement. Ideally resistance values would be parameterised with empirical data, but due to a shortage of such information, expert-opinion is often used. However, the use of expert-opinion is seen as subjective, human-centric and unreliable. This study derived resistance values from grey squirrel habitat suitability models (HSM) in order to compare the utility and validity of this approach with more traditional, expert-led methods. Models were built and tested with MaxEnt, using squirrel presence records and a categorical land cover map for Cumbria, UK. Predictions on the likelihood of squirrel occurrence within each land cover type were inverted, providing resistance values which were used to parameterise a least-cost model. The resulting habitat networks were measured and compared to those derived from a least-cost model built with previously collated information from experts. The expert-derived and HSM-inferred least-cost networks differ in precision. The HSM-informed networks were smaller and more fragmented because of the higher resistance values attributed to most habitats. These results are discussed in relation to the applicability of both approaches for conservation and management objectives, providing guidance to researchers and practitioners attempting to apply and interpret a least-cost approach to mapping ecological networks.

Human-induced changes in landscape configuration influence individual movement routines: lessons from a versatile, highly mobile species

Landscape conversion by humans may have detrimental effects on animal populations inhabiting managed ecosystems, but human-altered areas may also provide suitable environments for tolerant species. We investigated the spatial ecology of a highly mobile nocturnal avian species-the red-necked nightjar (Caprimulgus ruficollis)-in two contrastingly managed areas in Southwestern Spain to provide management recommendations for species having multiple habitat requirements. Based on habitat use by radiotagged nightjars, we created maps of functional heterogeneity in both areas so that the movements of breeding individuals could be modeled using least-cost path analyses. In both the natural and the managed area, nightjars used remnants of native shrublands as nesting sites, while pinewood patches (either newly planted or natural mature) and roads were selected as roosting and foraging habitats, respectively. Although the fraction of functional habitat was held relatively constant (60.9% vs. 74.1% in the natural and the managed area, respectively), landscape configuration changed noticeably. As a result, least-cost routes (summed linear distances) from nest locations to the nearest roost and foraging sites were three times larger in the natural than in the managed area (mean ± SE: 1356±76 m vs. 439±32 m). It seems likely that the increased proximity of functional habitats in the managed area relative to the natural one is underlying the significantly higher abundances of nightjars observed therein, where breeders should travel shorter distances to link together essential resources, thus likely reducing their energy expenditure and mortality risks. Our results suggest that landscape configuration, but not habitat availability, is responsible for the observed differences between the natural and the managed area in the abundance and movements of breeding nightjars, although no effect on body condition was detected. Agricultural landscapes could be moderately managed to preserve small native remnants and to favor the juxtaposition of functional habitats to benefit those farm species relying on patchy resources.