Probability Of Presence Research Articles

Robust mapping of human–wildlife conflict: controlling for livestock distribution in carnivore depredation models

AbstractShifting human–wildlife conflict towards coexistence requires a robust understanding of where conflict happens and why. Spatial models of livestock depredation by wild predators commonly identify depredation hotspots in areas where livestock are most abundant (e.g. nearer villages or pasture). This may reflect underlying livestock distribution, rather than imply these areas are inherently risky for livestock. This limits the predictive power of these models and their usefulness for conflict mitigation and wild carnivore conservation. Here, we build spatial models of both cattle depredation (530 attacks mostly by lions and hyenas; 2009‐2013), and cattle presence (14 GPS‐collared herds; 2010‐2012) near Hwange National Park, Zimbabwe. We use Bayes’ theorem to combine the cattle depredation and presence models to quantify risk as the conditional probability of depredation given livestock presence. Our raw depredation models predicted higher depredation rates where cattle presence was more likely (near villages and in more open habitats). By contrast, our risk model predicted higher risk further from human activity and in more dense vegetation (where depredation rates were higher than expected given the low probability of cattle presence). Risk has also increased sharply towards protected areas (core carnivore habitat). Our formulation of risk captures high‐risk areas as those where livestock are most accessible (i.e. vulnerable) to predators as opposed to simply where they are most available (as in much previous work). We make recommendations for livestock protection and wild carnivore conservation based on our quantification of risk, such as where to avoid herding livestock and which areas to prioritize for livestock protection. Our approach may be profitably applied to guide safer livestock grazing or herding in other contexts where depredation and livestock movement data are available. We hope that the concepts and methods that we develop here will help advance the future study and mitigation of human–wildlife conflict more generally.

Changes in Stroke Hospital Care During the COVID-19 Pandemic: A Systematic Review and Meta-Analysis.

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Habitat suitability mapping of the black coral Leiopathes glaberrima to support conservation of vulnerable marine ecosystems

The black coral Leiopathes glaberrima is an important habitat forming species that supports benthic biodiversity. Due to its high sensitivity to fishing activities, it has been classified as indicator of Vulnerable Marine Ecosystems (VMEs). However, the information on its habitat selection and large-scale spatial distribution in the Mediterranean Sea is poor. In this study a thorough literature review on the occurrence of L. glaberrima across the Mediterranean Sea was undertaken. Predictive modelling was carried out to produce the first continuous map of L. glaberrima suitable habitat in the central sector of the Mediterranean Sea. MaxEnt modeling was used to predict L. glaberrima probability of presence as a function of seven environmental predictors (bathymetry, slope, aspect North–South and East–West, kinetic energy due to currents at the seabed, seabed habitat types and sea bottom temperature). Our results show that bathymetry, slope and aspect are the most important factors driving L. glaberrima spatial distribution, while in less extent the other environmental variables. This study adds relevant information on the spatial distribution of vulnerable deep water corals in relation to the environmental factors in the Mediterranean Sea. It provides an important background for marine spatial planning especially for prioritizing areas for the conservation of VMEs.

Chief Innovation Officers: An empirical study of behavioral and institutional antecedents

In order to better manage the opportunities and threats around innovation, many firms created a Chief Innovation Officer (CINO) position in their top management teams (TMTs). Using insights from behavioral theory of the firm and institutional theory, we investigate how performance feedback and legitimacy considerations are important drivers of CINO presence in TMTs. We analyze the data of 280 science-oriented firms from the Standard & Poor’s Index between 2008 and 2017 to assess how those factors influence CINO presence in TMTs and find convincing results. When a firm’s innovation performance falls below its “social” aspirations, that firm becomes more likely to have a CINO in its TMTs. Similarly, when a firm underperforms with regard to its “historical” market aspirations, the probability of a CINO presence in its TMT increases. Also, CINO prevalence in a firm’s industry significantly affects that firm’s decision to have a CINO in its TMT. The findings of this study present important contributions into upper echelons, behavioral theory of the firm and innovation governance literatures.

Evolutionary dynamics of Indo-European alignment patterns

Abstract This paper employs phylogenetic modeling to reconstruct the alignment system of Indo-European. We use a data set of categorical morphosyntactic features, which take states such as ‘nominative-accusative’, ‘active-stative’, or ‘ergative’. We analyze these characters with a standard Bayesian comparative phylogenetic method, inferring transition rates between character states on the basis of a phylogenetic representation of the languages in the data. Using these rates, we then reconstruct the probability of presence of traits at the root and nodes of Indo-European. We find that the most probable alignment system for Proto-Indo-European is a nominative-accusative system, with low probabilities of neutral marking and ergativity in the categories lower in grammatical hierarchies (nouns, past). Using a test of phylogenetic signal, we find that characters pertaining to categories higher in hierarchies show greater phylogenetic stability than categories lower in hierarchies. We examine our results in relation to theories of Proto-Indo-European alignment as well as to general typology.

Spatiotemporal Invasion Severity of Chinese Tallow (Triadica sebifera) and Invasibility of Forest Types in Southern US Forestlands

Abstract Quantifying invasion severity of nonnative invasive plant species is vital for the development of appropriate mitigation and control measures. We examined more than 23,250 Forest Inventory and Analysis (FIA) plots from the southern coastal states of the United States to develop an alternative method to classify and map the invasion severity of Chinese tallow (Triadica sebifera). Remeasured FIA plot-level data were used to examine the spatiotemporal changes in the presence probability and cover percentage of tallow. Four invasion severity classes were identified by using the product of presence probability and cover percentage. Chinese tallow invasion severity increased over time with 90 and 123 counties being classified into the highest severity class for the first and second measurement, respectively. Further, the invasibility of major forest-type groups by severity class was examined using the product of the county-level mean presence probability and mean cover percentage of Chinese tallow as a proxy of invasibility. Longleaf/slash pine (Pinus palustris/P. elliottii) forests were highly resilient to the Chinese tallow invasion. In contrast, elm/ash/cottonwood (Ulmus spp./Fraxinus spp./Populus deltoides) and oak/gum/cypress (Quercus spp./Nyssa spp./Taxodium spp.) forest-type groups were vulnerable to invasion.

Introducing a probabilistic definition of the target in a robust treatment planning framework

The ‘clinical target distribution’ (CTD) has recently been introduced as a promising alternative to the binary clinical target volume (CTV). However, a comprehensive study that considers the CTD, together with geometric treatment uncertainties, was lacking. Because the CTD is inherently a probabilistic concept, this study proposes a fully probabilistic approach that integrates the CTD directly in a robust treatment planning framework. First, the CTD is derived from a reported microscopic tumor infiltration model such that it explicitly features the probability of tumor cell presence in its target definition. Second, two probabilistic robust optimization methods are proposed that evaluate CTD coverage under uncertainty. The first method minimizes the expected-value (EV) over the uncertainty scenarios and the second method minimizes the sum of the expected value and standard deviation (EV-SD), thereby penalizing the spread of the objectives from the mean. Both EV and EV-SD methods introduce the CTD in the objective function by using weighting factors that represent the probability of tumor presence. The probabilistic methods are compared to a conventional worst-case approach that uses the CTV in a worst-case optimization algorithm. To evaluate the treatment plans, a scenario-based evaluation strategy is implemented that combines the effects of microscopic tumor infiltrations with the other geometric uncertainties. The methods are tested for five lung tumor patients, treated with intensity-modulated proton therapy. The results indicate that for the studied patient cases, the probabilistic methods favor the reduction of the esophagus dose but compensate by increasing the high-dose region in a low conflicting organ such as the lung. These results show that a fully probabilistic approach has the potential to obtain clinical benefits when tumor infiltration uncertainties are taken into account directly in the treatment planning process.

El Modelling potential distribution of the endemic ringtail (Bassariscus astutus saxicola) on an island in the Gulf of California

Objective: Analyze the topography of the island with a digital elevation model (DEM) at 30 m spatial resolution and generate the first distribution model for an endemic carnivore from the islands of the Gulf of California.
 Design/Methodology/Approach: This study employed the Maxent species distribution model to find the distribution of the ringtail in its habitat on Espíritu Santo Island. In 2015–2016, through four surveys, ringtails were trapped in eight glens on the west of the island. A total of 74 individuals were captured, with nine recaptures.
 Results: The variables with the greatest contributions to the models were elevation, contributing 71.6%; heat load index 15% and ruggedness 11.8%. The model predicts > 0.5 probabilities of presence of this carnivore in 3,018 hectares of the island. We obtained a high AUC value (0.928), which indicates that the model is accurate, and subsequently confirmed it with a value of pAUC = 1.917.
 Study Limitations/Implications: The habitat of the ringtail (Bassariscus astutus saxicola) was little known mainly because it is an endemic species. And there was not a published article that will show its distribution within the island.
 Conclusions: This model shows that topographic variables are useful to explain the potential distribution of the ringtail, mainly because the topography is related to sites that can offer thermal refuge, abundance of food, and escape routes from predators, among other features.

Hydrogen for Maritime Application—Quality of Hydrogen Generated Onboard Ship by Electrolysis of Purified Seawater

Maritime transport is investigating several options to reduce its greenhouse gases and air pollutant emissions. An experimental ship, Energy Observer, is using excess renewable energy to generate onboard hydrogen by electrolysis of purified seawater. As a promising option for storing energy, it can provide on-demand energy to the ship through a hydrogen fuel cell (FC). As hydrogen FCs lifetime and performance are correlated to hydrogen quality, the hydrogen produced onboard needs to be monitored. This study assesses the probability of contaminants presence for this electrolyser, using purified seawater and supports the results with a hydrogen fuel quality analysis from the Energy Observer ship. It demonstrates that an electrolyser using onboard purified seawater can generate hydrogen of a quality compliant with ISO 14687:2019. Additional contaminants (i.e., ions, heavy metal) were also measured. The study highlights the potential contaminants to be monitored and future research on new contaminants from seawater to further develop hydrogen fuel for maritime applications.

Insectivorous songbirds as early indicators of future defoliation by spruce budworm

ContextAlthough the spatiotemporal dynamics of spruce budworm outbreaks have been intensively studied, forecasting outbreaks remains challenging. During outbreaks, budworm-linked warblers (Tennessee, Cape May, and bay-breasted warbler) show a strong positive response to increases in spruce budworm, but little is known about the relative timing of these responses.ObjectivesWe hypothesized that these warblers could be used as sentinels of future defoliation of budworm host trees. We examined the timing and magnitude of the relationships between defoliation by spruce budworm and changes in the probability of presence of warblers to determine whether they responded to budworm infestation before local defoliation being observed by standard detection methods.MethodsWe modelled this relationship using large-scale point count surveys of songbirds and maps of cumulative time-lagged defoliation over multiple spatial scales (2–30 km radius around sampling points) in Quebec, Canada.ResultsAll three warbler species responded positively to defoliation at each spatial scale considered, but the timing of their response differed. Maximum probability of presence of Tennessee and Cape May warbler coincided with observations of local defoliation, or provided a one year warning, making them of little use to guide early interventions. In contrast, the probability of presence of bay-breasted warbler consistently increased 3–4 years before defoliation was detectable.ConclusionsEarly detection is a critical step in the management of spruce budworm outbreaks and rapid increases in the probability of presence of bay-breasted warbler could be used to identify future epicenters and target ground-based local sampling of spruce budworm.

Robustness and Sensitivity Tuning of the Kalman Filter for Speech Enhancement

Inaccurate estimates of the linear prediction coefficient (LPC) and noise variance introduce bias in Kalman filter (KF) gain and degrade speech enhancement performance. The existing methods propose a tuning of the biased Kalman gain, particularly in stationary noise conditions. This paper introduces a tuning of the KF gain for speech enhancement in real-life noise conditions. First, we estimate noise from each noisy speech frame using a speech presence probability (SPP) method to compute the noise variance. Then, we construct a whitening filter (with its coefficients computed from the estimated noise) to pre-whiten each noisy speech frame prior to computing the speech LPC parameters. We then construct the KF with the estimated parameters, where the robustness metric offsets the bias in KF gain during speech absence of noisy speech to that of the sensitivity metric during speech presence to achieve better noise reduction. The noise variance and the speech model parameters are adopted as a speech activity detector. The reduced-biased Kalman gain enables the KF to minimize the noise effect significantly, yielding the enhanced speech. Objective and subjective scores on the NOIZEUS corpus demonstrate that the enhanced speech produced by the proposed method exhibits higher quality and intelligibility than some benchmark methods.

Impact of Climate Change on Wine Tourism: An Approach through Social Media Data

Wine tourism is one of the best opportunities for rural development, but because it is partially exposed to climatic conditions, it is a climate-vulnerable tourism activity. However, an understanding of the potential impacts of global climate change on this popular activity remains limited. This study proposes a new methodology that combines current daily gridded climate data from the E-OBS project with big spatiotemporal data from the Flickr photo-sharing platform through a generalized additive model This methodology was implemented to study the potential impacts on tourism flows due to climate change and to make predictions about the future using data from the CMIP5 project. We applied the methodology to 5 European wine tourism regions: Alsace (FR), Chianti (IT), La Rioja (SP), Langhe-Monferrato (IT), and Moselle (DE). Results show an increased probability of presence and increased deseasonalization of tourism in all study areas and an anticipation of peak presence from summer to spring in three of the five regions. We believe that these results can be useful for public and private stakeholders to adapt the offer of wine tourism services to changes in demand and to direct the organization of events such as festivals and thematic tours.

ESTIMATION METHOD OF LEFT TURN LANE CAPACITY UNDER THE INFLUENCE OF PEDESTRIANS AND CROSSWALK LAYOUT AT SIGNALIZED CROSSWALKS

The left turn lane capacity is highly influenced by the presence of pedestrians under shared signal phasing. Pedestrian crossing time can be highly influenced by pedestrian platoon maneuver under the influence of traffic signal settings, crosswalk length and bidirectional interactions of pedestrian, due to that left turning vehicles movement may be significantly affected. However, existing capacity estimation methods of left turn lanes did not consider those factors. In addition, the influence of crosswalk layout did not properly consider in the existing methods and researches. This study aims to propose a method to estimate the left turn lane capacity, considering the characteristics of crossing pedestrians and crosswalk layout variations. Waiting pedestrian presence-time is estimated by applying pedestrian presence probability model. In addition, the left turning vehicles discharge flow rate under different crosswalk layout and pedestrian demand condition are investigated and modeled. The left turn lane capacity estimation equation is proposed by characterizing the observed discharge flow rate of left turning vehicles under the influence of crossing pedestrians. It was found that the proposed capacity estimation method can represent the realistic influence of pedestrians and crosswalk layout on the left turn lane capacity at signalized crosswalks.

Modeling climatically suitable areas for soybean and their shifts across China

CONTEXTCrop suitability determines its distribution and yield in a given region and can be greatly affected by climate change. In recent decades, the distribution of soybean cultivation has undergone significant spatial shifts in China. However, whether this change matches with climatic suitability for soybean at a national scale has not been reported. OBJECTIVEOur objectives were to investigate the spatial distribution and shifts in climatically suitable areas for soybean from 1961 to 2017 and to determine whether actual production matches with climatic suitability in China. METHODSThe MaxEnt model was used to simulate the presence probability of soybean from 1961 to 2017 based on soybean occurrence data and climate data across China. Regions were classified as climatically unsuitable or as having low, moderate, or high climatic suitability. Then, the overlay analysis was performed to assess spatial changes of soybean suitability and the consistency between climatic suitability and actual production. RESULTS AND CONCLUSIONSAccumulated temperature ≥ 10 °C, humidity index during the potential growing season, and annual temperature range were the major climatic factors that affected soybean distribution. Areas of high climatic suitability were mainly located in the Northeast and North-central Regions, and the total acreage of high suitability was 129.88 × 106 ha. Unsuitable areas for soybean contracted over the study period, whereas highly suitable areas migrated westward and southward. The climatic suitability for soybean across China has increased overall in the past decades. The area of improved climatic suitability from 1961 to 2017 comprised 14.60% of the entire land area of China and was concentrated primarily in the Northwest and North-central Regions. Nonetheless, consistency between climatic suitability and actual production decreased from 83.47% in 1985 to 65.16% in 2015. This may pose a risk to soybean production, especially in emerging major planting areas of the Southwest Region. SIGNIFICANCEThis study described the distribution of climatically suitable areas for soybean, used spatial analysis to illustrate the extent to which climatically suitable areas overlap with actual production areas, and discussed possible solutions for improving soybean production at a national scale in China. This work has practical significance for optimizing the regional layout of soybean production and implementing countermeasures to address future climate change.

EDNA sampled from stream networks correlates with camera trap detection rates of terrestrial mammals

Biodiversity monitoring delivers vital information to those making conservation decisions. Comprehensively measuring terrestrial biodiversity usually requires costly methods that can rarely be deployed at large spatial scales over multiple time periods, limiting conservation efficiency. Here we investigated the capacity of environmental DNA (eDNA) from stream water samples to survey terrestrial mammal diversity at multiple spatial scales within a large catchment. We compared biodiversity information recovered using an eDNA metabarcoding approach with data from a dense camera trap survey, as well as the sampling costs of both methods. Via the sampling of large volumes of water from the two largest streams that drained the study area, eDNA metabarcoding provided information on the presence and detection probabilities of 35 mammal taxa, 25% more than camera traps and for half the cost. While eDNA metabarcoding had limited capacity to detect felid species and provide individual-level demographic information, it is a cost-efficient method for large-scale monitoring of terrestrial mammals that can offer sufficient information to solve many conservation problems.

Role of ocean tidal asymmetry and estuarine geometry in the fate of plastic debris from ocean sources within tidal estuaries

Tidal asymmetry drives the transport of materials (e.g. plastic debris) within tidal estuaries. Most previous research has focused on the asymmetry that arises within estuaries and relates to sediment transport; however, estuaries exhibiting tidal asymmetry at the mouth and their relationship with materials other than sediments have received less attention. This study uses numerical hydrodynamic and Lagrangian transport models to assess the effect of estuary morphology on the propagation of asymmetric tides and how it influences the distribution of plastic debris that reaches tidal estuaries from ocean sources. A series of numerical experiments were conducted in idealised estuaries, specifically in tidal creeks. The results show that the asymmetry at the mouth results in flood/ebb dominance and influences the presence of plastic debris in areas where the main channel favours tidal flow. Flood-dominated estuaries show an import capacity 50% higher than those that show symmetric or negative asymmetric tides at their mouths. Numerical simulations show that the relevant role in defining flood or ebb dominance is played by the geometry of the estuary when increased friction that opposes flow and intertidal storage areas are present, although small influences of the external tidal asymmetry are also appreciated. The probability of plastic debris presence was 90% for positive asymmetric tides and varied between and 70%–80% for symmetric and negative-asymmetric tides. A remarkable finding of this study is the regulatory role of kurtosis which corrects the tendency induced by skewness in the fate of plastic debris. These findings were corroborated with the application of this methodology to a real estuary and a comparison of the obtained results with available field data on plastic debris.

Spatio-temporal distribution and agroecological factors associated with canine leptospirosis in Great Britain

Leptospirosis is an important global zoonotic disease that affects a wide range of mammalian species. Canine leptospirosis outbreaks have been reported after metereological events such as flooding (eg. in Brazil and the United States of America) suggesting an environmental association, but there has been no such study in Great Britain (GB). The distribution of cases across GB is also unreported. Objectives of this study were to: (1) assess the spatio-temporal variation of leptospirosis test submissions (2) explore associations between agroecological risk factors and distribution of different canine leptospirosis serogroups in GB, and (3) generate probability of presence maps for the different serogroups. Data analysed comprised laboratory submissions (n = 3986) to IDEXX laboratories between 1st January 2009 and 31st December 2018 for PCR or MAT leptospirosis testing. Spatial and seasonal scan statistics were used to investigate spatial and temporal clustering of positive tests, logistic regression was used to identify significant agroecological risk factors for positive tests, and the Maxent algorithm was used to model the environmental niche of four serogroups. There was an increased risk of a positive test result in the West Midlands of England (relative risk = 2.16) and between October and January (relative risk = 1.54). Logistic regression identified season and region to be significantly associated with a positive diagnosis,with higher odds of a positive test in Autumn (OR = 1.86 95 %CI 1.29−2.69) and Winter (OR = 1.51, 95 %CI 1.02−2.23) and in the East (OR = 2.20, 95 %CI = 1.31−3.71) and West Midlands (OR = 2.32, 95 %CI 1.45−3.71). The increased test-positive proportion in Autumn together with the increased odds of a positive diagnosis in Autumn suggests there may be a seasonal pattern to the canine leptospirosis in GB. The most important variable associated with higher leptospirosis presence in all ecological niche models was higher average annual temperature. The importance and retention of other variables differed between serogroups. Overall, a higher probability of leptospirosis presence was predicted in southern England and a low probability in Scotland and northern England. Although leptospirosis vaccine usage provides protection against the majority of serogroups identified here, one is not represented in the currently licensed vaccine formulations and therefore leptospirosis should remain a differential diagnosis in vaccinated dogs demonstrating consistent clinical signs of the disease.

Analysis of the relationship between the predicted biological activity and the chemical structure of S-derivatives of 5-(5-bromofuran-2-yl)-4R-1,2,4-triazole-3-thiols

1,2,4-Triazole derivatives are actively used as components in the development of new drugs, plant protection products, polymeric materials, anti-corrosion agents and etc. Chemical modeling of substituted 1,2,4-triazoles due to the introduction of different pharmacophores into the structure is very popular among scientists in various fields. Today it is known that some S-derivatives of 5-(5-bromofuran-2-yl)-4R-1,2,4-triazole-3-thiols have antimicrobial activity. The aim of the work is to analyze the relationships between the predicted biological activity and the chemical structure of S-derivatives of 5-(5-bromofuran-2-yl) -4R-1,2,4-triazole-3-thiols. Materials and methods. Virtual screening of compounds was performed using the computer program PASS (Prediction of activity spectra for substances). The results of the forecast were issued in the form of a list of names of probable types of activity with estimates of the probabilities of presence (Pa) and absence of each activity (Pi), which had values from 0 to 1. Results. Analyzing the prediction of biological activity on protein targets from the group of enzymes, we can said that derivatives of 5-(5-bromofuran-2-yl)-4R-1,2,4-triazole-3-thiols were active in the group of oxyreductases (Glutathione reductase, mitochondrial; Cyclooxygenase-2; Hypoxia-inducible factor prolyl hydroxylase 2), which catalyzed oxidation reactions, the transfer of electrons from one molecule (reducer, electron donor) to another (oxidant, electron acceptor). These compounds can demonstrate antioxidant, antihypoxic activity. Conclusions. The conducted forecast of biological activity revealed that derivatives of 5-(5-bromofuran-2-yl)-4R-1,2,4-triazole-3-thiols are the most active and there is a probability to show antitumor, antiviral, antibacterial, diuretic, actoprotective, and antioxidant activity.

An Explorative Application of Random Forest Algorithm for Archaeological Predictive Modeling. A Swiss Case Study

The present work proposes an innovative approach to surveys and demonstrates the effectiveness of bringing together traditional archaeological questions, such as the exploration and the analysis of settlement patterns, with the most innovative technologies related to Machine Learning. Namely, we applied Random Forest, an ensemble learning method based on decision trees, to perform archaeological predictive modeling (APM) for the Canton of Zurich, in Switzerland. This was done based on a dataset of known archaeological sites dating back to the Roman Age. The APM represents an automated decision-making and probabilistic reasoning tool that is relevant for archaeological risk assessment and cultural heritage management. Machine learning-based approaches can learn from data and make predictions, starting from the acquired knowledge, through the modeling of the hidden relationships between a set of observations, representing the dependent variable (i.e. the archeological sites), and the independent variables (i.e. the geo-environmental features prone to influence the site locations). The main objective of the present study is to assess the spatial probability of presence for Roman settlements within the study area. As results, we produced: 1) a probability map, expressing the likelihood of finding a Roman site at different locations; 2) the importance ranking of the geo-environmental features influencing the presence of the archeological sites. These outputs in our results are of paramount importance, not only in verifying the reliability of the data, but also in stimulating experts in different ways. Also, these results help evaluate the benefits and constraints of using such innovative techniques and, ultimately, help explore the performance of machine learning-based models in processing archaeological information.

Habitat and crop selection by red deer in two different landscape types

Crop raiding ungulates can cause costly yield losses and conflicts between agriculture, game management, and conservation. It is therefore crucial to know how, where, and when ungulates use different habitats and crops. In this study we used resource selection functions and GPS-tagged red deer Cervus elaphus (n = 38) in two different study areas (North – mainly forested land and South – mainly arable land), to investigate how red deer use arable land and different crop types in relation to availability and distance to forest cover in Sweden. Our study shows a transitional use of arable land and forests by red deer. Red deer spend on average 45% and 21% of their time in arable land in South and North respectively. In the North, arable land was selected while forest and wetlands were selected in the South. The selection of different crops also differed between the two study areas, for example rapeseed was highly selected during both seasons in South while it was used to a lower degree in relation to its availability in the North. In both study areas the probability of red deer presence on the agricultural fields decreased with distance to forest. The significant use of arable land and unharvested crops by the increasing red deer population in Sweden highlights a risk for crop damage that may need further consideration for farming practices as well as for damage and wildlife management. In our case damage mitigation should focus on rapeseed in the South, whereas there is a less clear pattern of selection among growing crops in the North. The differences in habitat and crop selection between the two areas also highlights the need of knowledge about red deer habitat selection at a regional level to be able to adapt damage mitigation and wildlife management strategies accordingly. Moreover, the transitional use of arable land and forests by red deer in mixed landscapes may imply that consumption of certain crops can affect browsing patterns and damage levels within forests and vice versa, that may have implication for both agriculture and forestry and calls for future studies.