Habitat selection of free-ranging cattle in productive coniferous forests of south-eastern Norway

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Microhabitat selection of free-ranging beef cattle in south-boreal forest

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Multiple factors influence local perceptions of snow leopards and Himalayan wolves in the central Himalayas, Nepal

An understanding of local perceptions of carnivores is important for conservation and management planning. In the central Himalayas, Nepal, we interviewed 428 individuals from 85 settlements using a semi-structured questionnaire to quantitatively assess local perceptions and tolerance of snow leopards and wolves. We used generalized linear mixed effect models to assess influential factors, and found that tolerance of snow leopards was much higher than of wolves. Interestingly, having experienced livestock losses had a minor impact on perceptions of the carnivores. Occupation of the respondents had a strong effect on perceptions of snow leopards but not of wolves. Literacy and age had weak impacts on snow leopard perceptions, but the interaction among these terms showed a marked effect, that is, being illiterate had a more marked negative impact among older respondents. Among the various factors affecting perceptions of wolves, numbers of livestock owned and gender were the most important predictors. People with larger livestock herds were more negative towards wolves. In terms of gender, males were more positive to wolves than females, but no such pattern was observed for snow leopards. People’s negative perceptions towards wolves were also related to the remoteness of the villages. Factors affecting people’s perceptions could not be generalized for the two species, and thus need to be addressed separately. We suggest future conservation projects and programs should prioritize remote settlements.publishedVersio

Small rodent cycles influence interactions among predators in a boreal forest ecosystem

Cyclic fuctuations of prey have profound efects on the functioning of ecosystems, for example, by changing the dynamics, behavior, and intraguild interactions of predators. The aim of this study was to assess the efect of rodent cyclic fuctuations in the interspecifc interactions of a guild of small- and medium-sized predators: red fox (Vulpes vulpes), pine marten (Martes martes), and weasels (Mustela erminea and Mustela nivalis) in the boreal ecosystem. We analyzed eight years (2007–2014) of snow tracking data from southeastern Norway using structural equation models to assess hypothesized networks of causal relationships. Our results show that fuctuations in rodent abundance alter the strength of predator’s interactions, as well as the efect of determinant environmental variables. Pine marten and weasel abundances were positively associated with rodent population growth rate, but not red fox abundance. All predators were positively associated with each other; however, the association between red fox and the other predators weakened when rodents increased. Rodent fuctuations had variable efects on the habitat use of the predators. The presence of agricultural land was important for all predators, but this importance weakened for the mustelids as rodent abundance increased. We discuss the shifting role of interference and exploitative competition as possible mechanisms behind these patterns. Overall, we highlight the importance of accounting for the dynamics of prey resources when studying interspecifc interactions among predators. Additionally, we demonstrate the importance of monitoring the predator populations in order to anticipate undesirable outcomes such as increased general ist predator abundances to the detriment of specialists.publishedVersio

The importance of evaluating standard monitoring methods: Observer bias and detection probabilities for moose pellet group surveys

Counting is not always a simple exercise. Specimens can be misidentified or not detected when they are present, giving rise to unidentified sources of error. Deer pellet group counts are a common method to monitor abundance, density, and population trend. Yet, detection errors and observer bias could introduce error into sometimes very large (spatially, temporally) datasets. For example, in Scandinavia, moose (Alces alces) pellet group counts are conducted by volunteer hunters and students, but it is unknown how much uncertainty observer error introduces into these datasets. Our objectives were to 1) estimate the detection probability of moose pellet groups; 2) identify the primary variables leading to detection errors including prior observer experience; and 3) compare density estimates using single and double observer counts. We selected a subset of single observer plots from a long-term monitoring project to be conducted as dependent double observer surveys, where primary and secondary observers worked simultaneously in the field. We did this to quantify detection errors for moose pellet groups, which were previously unknown in Scandinavia, and to identify covariates which introduced variation into our estimates. Our study area was in the boreal forests of southern Norway where we had a nested grid of 100-m2 plots that we surveyed each spring. Our observers were primarily inexperienced. We found that when pellet groups were detected by the primary observer, the secondary observer saw additional pellet groups 42% of the time. We found search time was the primary covariate influencing detection. We also found density estimates from double observer counts were 1.4 times higher than single observer counts, for the same plots. This density underestimation from single observer surveys could have consequences to managers, who sometimes use pellet counts to set harvest quotas. We recommend specific steps to improve future moose pellet counts.The importance of evaluating standard monitoring methods: Observer bias and detection probabilities for moose pellet group surveyspublishedVersio

First Record of Hepatozoon spp. in Alpine Wild Rodents: Implications and Perspectives for Transmission Dynamics across the Food Web

Among the Apicomplexa parasites, Hepatozoon spp. have been mainly studied in domestic animals and peri-urban areas. The epidemiology of Hepatozoon spp. is poorly investigated in natural systems and wild hosts because of their scarce veterinary and economic relevance. For most habitats, the occurrence of these parasites is unknown, despite their high ecosystemic role. To fill this gap for alpine small mammals, we applied molecular PCR-based methods and sequencing to determine the Hepatozoon spp. in 830 ear samples from 11 small mammal species (i.e., Apodemus, Myodes, Chionomys, Microtus, Crocidura and Sorex genera) live-trapped during a cross-sectional study along an altitudinal gradient in the North-Eastern Italian Alps. We detected Hepatozoon spp. with an overall prevalence of 35.9%. Two species ranging from 500 m a.s.l. to 2500 m a.s.l. were the most infected: My. glareolus, followed by Apodemus spp. Additionally, we detected the parasite for the first time in another alpine species: C. nivalis at 2000–2500 m a.s.l. Our findings suggest that several rodent species maintain Hepatozoon spp. along the alpine altitudinal gradient of habitats. The transmission pathway of this group of parasites and their role within the alpine mammal community need further investigation, especially in consideration of the rapidly occurring environmental and climatic changes.First Record of Hepatozoon spp. in Alpine Wild Rodents: Implications and Perspectives for Transmission Dynamics across the Food WebpublishedVersio

Predicting Habitat Properties Using Remote Sensing Data: Soil pH and Moisture, and Ground Vegetation Cover

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Remote sensing data comprise a valuable information source for many ecological landscape studies that may be under-utilized because of an overwhelming amount of processing methods and derived variables. These complexities, combined with a scarcity of quality control studies, make the selection of appropriate remote sensed variables challenging. Quality control studies are necessary to evaluate the predictive power of remote sensing data and to develop parsimonious models underpinned by functional variables, i.e., cause rather than solely correlation. Cause-based models yield superior model transferability across different landscapes and ecological settings. We propose two basic guidelines for conducting such quality control studies that increase transferability and predictive power. The first is to favour predictors that are causally related to the response. The second is to include additional variables controlling variation in the property of interest and testing for optimum processing method and/or scale. Here, we evaluated these principles in predicting ground vegetation cover, soil moisture and pH under challenging conditions with forest canopies hindering direct remote sensing of the ground. Our model using lidar data combined with natural resource maps explained most of the observed variation in soil pH and moisture, and somewhat less variation of ground vegetation cover. Soil pH was best predicted by topographic position, sediment type and site index (R 2 = 0.90). Soil moisture was best predicted by topographic position, radiation load, sediment type and site index (R 2 = 0.83). The best model for predicting ground vegetation cover was a combination of lidar-based estimates for light availability below canopy and forest type, including an interaction between these two variables (R 2 = 0.65).publishedVersio

Issues of under-representation in quantitative DNA metabarcoding weaken the inference about diet of the tundra vole Microtus oeconomus

During the last decade, methods based on high-throughput sequencing such as DNA metabarcoding have opened up for a range of new questions in animal dietary studies. One of the major advantages of dietary metabarcoding resides in the potential to infer a quantitative relationship between sequence read proportions and biomass of ingested food. However, this relationship’s robustness is highly dependent on the system under study, calling for case-specific assessments. Herbivorous small rodents often play important roles in the ecosystem, and the use of DNA metabarcoding for analyses of rodent diets is increasing. However, there has been no direct validation of the quantitative reliability of DNA metabarcoding for small rodents. Therefore, we used an experimental approach to assess the relationship between input plant biomass and sequence reads proportions from DNA metabarcoding in the tundra vole Microtus oeconomus. We found a weakly positive relationship between the number of high-throughput DNA sequences and the expected biomass proportions of food plants. The weak relationship was possibly caused by a systematic under-amplification of one of the three plant taxa fed. Generally, our results add to the growing evidence that case-specific validation studies are required to reliably make use of sequence read abundance as a proxy of relative food proportions in the diet

Steppe ungulate count in Great Gobi B Strictly Protected area 2022

English: The plains of Great Gobi B Strictly Protected Area (subsequently “Great Gobi B”) in southwestern Mongolia are home to three endangered wild ungulates, khulan (Equus hemionus), takhi (Equus ferus przewalskii), and goitered gazelle (Gazella subgutturosa). With Mongolia holding the largest populations of these species, their conservation is of global importance. To assess the effectiveness of conservation efforts, robust survey methods are needed to monitor population development. In late summer 2022 we conducted the 3rd plains ungulate count in Great Gobi B to estimate population size of khulan and goitered gazelle and describe population developmentsince the counts in 2010 and 2015 and tested the method for estimating the growing population of reintroduced Przewalski’s horses. We conducted Distance Sampling point counts at 101 observation points over 6 counting events (at 19:00, 7:00, 9:00, 11:00, 13:00, and 15:00) at each observation point. During each counting event the observers scanned the surroundings using binoculars and registered species, number of animals, time, bearing and distance for each observation. Over the 606 counts, we observed 5,744 khulan, 3,150 gazelles and 922 Przewalski’s horses. Using these observations, we created global models(over all observation points and counting events) using the distance analysis framework and selected models with the best fit based on AIC values. Populations estimates for 2022 were 5,204 (95% CI = 2,121 – 12,771) khulan, 10,980 (95% CI = 7,473 – 16,132) goitered gazelles, and 1,288 (95% CI = 213 – 7,776) Przewalski’s horses within the 13,000 km2 survey area. Population estimates of both khulan and goitered gazelle suggested an increase from 2010 to 2015, while the 2022 estimated is closer to the 2010 estimates for khulan and in between for goitered gazelles. However, confidence intervals, especially for khulan, are large and population development cannot be determined conclusively. The uncertainty in the khulan estimate for 2022 was caused by the combination of a highly clumped distribution due to draught conditions and a large variation in group sizes. Goitered gazelles were more evenly distributed and group sizes less variable. Estimating Przewalski’s horse population resulted in a gross overestimate because of the knowledge rangers had about the location of Przewalski’s horse groups from intensive weekly monitoring. The data suggests that they specifically looked for groups, as Przewalski’s horses were detected almost equally likely over all distance categories. Confidence intervals were large because the population is still small (numbering just over 400) and distribution was also highly clumped due to the drought condition. The 2022 population estimates for khulan and goitered gazelles and the comparison with the estimates from 2010 and 2015 should be regarded as preliminary because: 1) The 3 surveys were analysed using slightly different distance analysisframeworks and 2) Distance Sampling does not take the spatial distribution of groups into account and we plan to explore such methods before we will reanalyse the 3 surveys within the same analysis framework.Norsk: På de mongolske slettene lever det tre truede ville klovdyrarter; asiatisk villesel (Equus hemionus), Przewalskihest (Equus ferus przewalskii) og struma gaselle (Gazella subgutturosa). De største populasjonene av disse artene på verdensbasis lever i Mongolia, og landet har dermed et særskilt ansvar for å ta vare på og forvalte disse artene. For å sikre en kunnskapsbasert og bærekraftig forvalting av populasjonene trengs informasjon om populasjonsutvikling og bestandsstørrelse. I denne undersøkelsen har vi gjennomført tellinger av viltlevende klovdyrarter i «Great Gobi B» i SV Mongolia for å estimere populasjonsstørrelsen og populasjonsutviklingen av asiatisk villesel og struma gaselle. Det har tidligere blitt gjennomført tellinger i 2010 og 2015, men dette er første gang det blir forsøkt å estimere populasjonsstørrelsen av przewalskihest. Vi gjennomførte tellinger fra 101 observasjonspunkter fordelt på 3 områder med 24 timers økter på hvert punkt. På hvert observasjonspunkt ble det gjennomført 6 runder med tellinger hvor observatørene skannet området med kikkert og registrerte antall dyr, tidspunkt, kompassretning og avstand. Vi lagde ulike modeller ved bruk av distance sampling metoden for å estimere populasjonsstørrelsen av asiatisk villesel, przewalskihest og struma gaselle i studieområdet for alle observasjonene samlet, og valgte den modellen med best AIC verdi. I tillegg analyserte vi data fra hver observasjonsrunde separat for å estimere populasjonsstørrelse på de forskjellige tidspunktene for asiatisk villesel og struma gaselle. I løpet av alle 6 observasjonsrundene telte vi totalt 5 744 asiatiske villesel, 3 150 struma gaseller og 922 przewalskihester. Populasjonsstørrelsen ble estimert til 5 204 (95% KI = 2 121 – 12 771) asiatiske villesel, 10 980 (95% KI = 7 473 – 16 132) struma gaseller og 1288 (95% KI = 213 – 7 776) przewalskihester innenfor studieområdet. Populasjonene for asiatisk villesel og struma gaselle viste en positiv utvikling mellom 2010 og 2015, men hadde en negativ utvikling fra 2015 til 2022. Usikkerheten i estimatene, spesielt for asiatisk villesel, er høy og det er vanskelig å trekke konklusjoner om populasjonsutvikling ut ifra dataene. 2022 var et uvanlig tørt år, og de asiatiske villeslene samletseg i en mindre del av studieområdet i nærheten av en vannkilde der beitegrunnlaget var bedre. Denne ujevne fordelingen i studieområdet er mest sannsynlig årsaken til den store usikkerheten i estimatene. Struma gaseller var mere jevnt fordelt i studieområdet, men usikkerheten i dataene var fortsatt høy, dog på et nivå som kan forventes av en stor‐skala undersøkelse i et system med lav tetthet. Å estimere przewalskihest populasjonen bød på samme problemer som for asiatiske villesel, men gir enda større usikkerhet på grunn av det lave antallet observasjoner. Det ble brukt litt ulike analysemetoder innenfor distance metodikken i de 3 undersøkelsene fra 2010, 2015 og 2022, og det ble ikke tatt hensyn til forskjell i størrelsen av studieområdene mellom de ulike årene. For videre arbeid planlegger vi å analysere alle dataene samlet for å oppnå mer pålitelige resultater. Et av problemene med distance metoden er at analysene ikke tar hensyn til den romlige fordelingen av grupper, noe som vi ønsker å utforske ved bruk av andre metoder.Financed by: Vontobel‐Stiftung, International Takhi Group, Inland Norway University of Applied Sciences, Great Gobi B administration, Prague Zo

A brain and a head for a different habitat : Size variation in four morphs of Arctic charr (Salvelinus alpinus(L.)) in a deep oligotrophic lake

Adaptive radiation is the diversification of species to different ecological niches and has repeatedly occurred in different salmonid fish of postglacial lakes. In Lake Tinnsjoen, one of the largest and deepest lakes in Norway, the salmonid fish, Arctic charr (Salvelinus alpinus(L.)), has likely radiated within 9,700 years after deglaciation into ecologically and genetically segregated Piscivore, Planktivore, Dwarf, and Abyssal morphs in the pelagial, littoral, shallow-moderate profundal, and deep-profundal habitats. We compared trait variation in the size of the head, the eye and olfactory organs, as well as the volumes of five brain regions of these four Arctic charr morphs. We hypothesised that specific habitat characteristics have promoted divergent body, head, and brain sizes related to utilized depth differing in environmental constraints (e.g., light, oxygen, pressure, temperature, and food quality). The most important ecomorphological variables differentiating morphs were eye area, habitat, and number of lamellae. The Abyssal morph living in the deepest areas of the lake had the smallest brain region volumes, head, and eye size. Comparing the olfactory bulb with the optic tectum in size, it was larger in the Abyssal morph than in the Piscivore morph. The Piscivore and Planktivore morphs that use more illuminated habitats have the largest optic tectum volume, followed by the Dwarf. The observed differences in body size and sensory capacities in terms of vision and olfaction in shallow and deepwater morphs likely relates to foraging and mating habitats in Lake Tinnsjoen. Further seasonal and experimental studies of brain volume in polymorphic species are needed to test the role of plasticity and adaptive evolution behind the observed differences.Peer reviewe