Beyond climate envelope projections: Roe deer survival and environmental change

Predicting the spatial expansion of an animal population with presence-only data

Predictive models can improve the efficiency of wildlife management by guiding actions at the local, landscape and regional scales. In recent decades, a vast range of modelling techniques have been developed to predict species distributions and patterns of population spread. However, data limitations often constrain the precision and biological realism of models, which make them less useful for supporting decision-making. Complex models can also be challenging to evaluate, and the results are often difficult to interpret for wildlife management practitioners. There is therefore a need to develop techniques that are appropriately robust, but also accessible to a range of end users. We developed a hybrid species distribution model that utilises commonly available presence-only distribution data and minimal demographic information to predict the spread of roe deer (Capreolus caprelous) in Great Britain. We take a novel approach to representing the environment in the model by constraining the size of habitat patches to the home-range area of an individual. Population dynamics are then simplified to a set of generic rules describing patch occupancy. The model is constructed and evaluated using data from a populated region (England and Scotland) and applied to predict regional-scale patterns of spread in a novel region (Wales). It is used to forecast the relative timing of colonisation events and identify important areas for targeted surveillance and management. The study demonstrates the utility of presence-only data for predicting the spread of animal species and describes a method of reducing model complexity while retaining important environmental detail and biological realism. Our modelling approach provides a much-needed opportunity for users without specialist expertise in computer coding to leverage limited data and make robust, easily interpretable predictions of spread to inform proactive population management.

Validating a common tick survey method: cloth-dragging and line transects

Cloth-dragging is the most widely-used method for collecting and counting ticks, but there are few studies of its reliability. By using cloth-dragging, we applied a replicated line transects survey method, in two areas in Sweden with different Ixodes ricinus tick-densities (low at Grimsö and high at Bogesund) to evaluate developmental stage specific repeatability, agreement and precision in estimates of tick abundance. 'Repeatability' was expressed as the Intraclass Correlation Coefficient (ICC), 'agreement' with the Total Deviation Index (TDI) and 'precision' by the coefficient of variation (CV) for a given dragging distance. Repeatability (ICC) and agreement (TDI) were higher for the most abundant instar (nymphs) and in the area of higher abundance. At Bogesund tick counts were higher than at Grimsö and so also repeatability, with fair to substantial ICC estimates between 0.22 and 0.75, and TDI ranged between 1 and 44.5 counts of difference (thus high to moderate agreement). At Grimsö, ICC was poor to moderate and ranged between 0 and 0.59, whereas TDI remained low with estimates lower or equal to 1 count (thus high agreement). Despite a 100-fold lower abundance at Grimsö, the same level of precision for nymphs could be achieved with a 70% increase of dragging effort. We conclude that the cloth-dragging technique is useful for surveying ticks' and primarily to estimate abundance of the nymphal stage, whereas it rarely will be recommended for larvae and adults.

Relationships among white-tailed deer density, harvest, and landscape metrics in TN, USA

Landscape and harvest indices are frequently used to represent white-tailed deer (Odocoileus virginianus) density. However, the relationship between deer density and specific landscape indices is unclear. Harvest is another metric often used to estimate deer density. Our objective was to model the relationship among deer density, landscape metrics, and harvest density of deer in TN, USA. We estimated deer density across 11 regions in 2011 using distance sampling techniques. We developed 18 a priori models to assess relationships among deer density, harvest density, and landscape metrics. Estimates of deer density ranged from 1.85 to 19.99 deer/km2. Deer density was best predicted by harvest density and harvest density + percent woody area. However, harvest density was the only important variable in predicting deer density (Σωi = 0.700). Results of this study emphasize the significance of harvest density in deer management. While the importance of harvest as a management tool for deer is likely to increase as landscapes are fragmented and urbanized, specific management guidelines should be based upon deer densities and landscape metrics when they are important.

Prolongation of Tick-Borne Encephalitis Cycles in Warmer Climatic Conditions

Tick-borne encephalitis exhibits profound inter-annual fluctuations in incidence. Previous studies showed that three-fifths of the variation can be explained in terms of four superimposed oscillations: a quasi-biennial, triennial, pentennial, and a decadal cycle. This study was conducted to determine how these cycles could be influenced by climate change. Epidemiological data, spanning from the 1970s to the present, and originating from six regions/countries bridging Scandinavia and the Mediterranean, represented a temporal/latitudinal gradient. Spectral analysis of time series was used to determine variation in the cycles’ length/amplitude with respect to these gradients. The analysis showed that—whereas the lengths of the shorter cycles do not vary substantially—cycles in the decadal band tend to be longer southwards. When comparing the disease’s oscillations before- and after the mid-1990s, a shift towards longer oscillations was detected in the pentennial–decadal band, but not in the biennial– triennial band. Simultaneously, oscillations in the latter band increased in intensity whereas the decadal oscillations weakened. In summary, the rhythm of the cycles has been altered by climate change. Lengthened cycles may be explained by prolonged survival of some animal hosts, and consequently greater inertia in herd immunity changes, slowing down a feedback loop between the herd immunity and amount of virus circulating in nature.