Harvest and density-dependent predation drive long-term population decline in a northern ungulate

The relative effect of top-down versus bottom-up forces in regulating and limiting wildlife populations is an important theme in ecology. Untangling these effects is critical for a basic understanding of trophic dynamics and effective management. We examined the drivers of moose (Alces alces) population growth by integrating two independent sources of observations within a hierarchical Bayesian population model. We used one of the largest existing spatiotemporal data sets on ungulate population dynamics globally. We documented a 20% population decline over the period examined. There was negative density-dependent population growth of moose. Although we could not determine the mechanisms producing density-dependent suppression of population growth, the relatively low densities at which we documented moose populations suggested it could be due to density-dependent predation. Predation primarily limited population growth, except at low density, where it was regulating. After we simulated several harvest scenarios, it appeared that harvest was largely additive and likely contributed to population declines. Our results highlight how population dynamics are context dependent and vary strongly across gradients in climate, forest type, and predator abundance. These results help clarify long-standing questions in population ecology and highlight the complex relationships between natural and human-caused mortality in driving ungulate population dynamics.

Comparing unmanned aerial systems with conventional methodology for surveying a wild white-tailed deer population

Abstract Context Ungulate populations are subject to fluctuations caused by extrinsic factors and require efficient and frequent surveying to monitor population sizes and demographics. Unmanned aerial systems (UAS) have become increasingly popular for ungulate research; however, little is understood about how this novel technology compares with conventional methodologies for surveying wild populations. Aims We examined the feasibility of using a fixed-wing UAS equipped with a thermal infrared sensor for estimating the population density of wild white-tailed deer (Odocoileus virginianus) at the Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota, USA. We compared UAS density estimates with those derived from faecal pellet-group counts. Methods We conducted UAS thermal survey flights from March to April of 2018 and January to March of 2019. Faecal pellet-group counts were conducted from April to May in 2018 and 2019. We modelled deer counts and detection probabilities and used these results to calculate point estimates and bootstrapped prediction intervals for deer density from UAS and pellet-group count data. We compared results of each survey approach to evaluate the relative efficacy of these two methodologies. Key results Our best-fitting model of certain deer detections derived from our UAS-collected thermal imagery produced deer density estimates (WR20204_IE1.gif, 95% prediction interval = 4.32–17.84 deer km−2) that overlapped with the pellet-group count model when using our mean pellet deposition rate assumption (WR20204_IE2.gif, 95% prediction interval = 4.14–11.29 deer km−2). Estimates from our top UAS model using both certain and potential deer detections resulted in a mean density of 13.77 deer km−2 (95% prediction interval = 6.64–24.35 deer km−2), which was similar to our pellet-group count model that used a lower rate of pellet deposition (WR20204_IE3.gif, 95% prediction interval = 6.46–17.65 deer km−2). The mean point estimates from our top UAS model predicted a range of 136.68–273.81 deer, and abundance point estimates using our pellet-group data ranged from 112.79 to 239.67 deer throughout the CCESR. Conclusions Overall, UAS yielded results similar to pellet-group counts for estimating population densities of wild ungulates; however, UAS surveys were more efficient and could be conducted at multiple times throughout the winter. Implications We demonstrated how UAS could be applied for regularly monitoring changes in population density. We encourage researchers and managers to consider the merits of UAS and how they could be used to enhance the efficiency of wildlife surveys.

Current Zoology Reconstructing landscapes of ungulate parturition and predation using vegetation phenology

Enhanced vegetation index (EVI) data can be used to identify and define the space in which ungulates practice parturition and encounter predation. This study explores the use of EVI data to identify landscapes linked to ungulate parturition and predation events across space, time, and environmental conditions. As a case study, we used the moose population (Alces alces) of northern Minnesota in the USA. Using remotely sensed EVI data rasters and global positioning system collar data, we quantified how vegetation phenology and moose movement shaped the births and predation of 52 moose calves from 2013 to 2020 on or adjacent to the Grand Portage Indian Reservation. The known sources of predation were American black bears (Ursus americanus, n = 22) and gray wolves (Canis lupus, n = 28). Satellite-derived data summarizing seasonal landscape features at the local level revealed that landscape heterogeneity use by moose can help to quantitatively identify landscapes of parturition and predation in space and time across large areas. Vegetation phenology proved to be differentiable between adult moose ranges, sites of cow parturition, and sites of calf predation. Landscape characteristics of each moose group were consistent and tractable based on environment, suggesting that sites of parturition and predation of moose are predictable in space and time. It is possible that moose selected specific landscapes for parturition despite risk of increased predation of their calves, which could be an example of an "ecological trap." This analytical framework can be employed to identify areas for future ungulate research on the impacts of landscape on parturition and predation dynamics.

Moose genomes reveal past glacial demography and the origin of modern lineages

Background

Numerous megafauna species from northern latitudes went extinct during the Pleistocene/Holocene transition as a result of climate-induced habitat changes. However, several ungulate species managed to successfully track their habitats during this period to eventually flourish and recolonise the holarctic regions. So far, the genomic impacts of these climate fluctuations on ungulates from high latitudes have been little explored. Here, we assemble a de-novo genome for the European moose (Alces alces) and analyse it together with re-sequenced nuclear genomes and ancient and modern mitogenomes from across the moose range in Eurasia and North America.

Results

We found that moose demographic history was greatly influenced by glacial cycles, with demographic responses to the Pleistocene/Holocene transition similar to other temperate ungulates. Our results further support that modern moose lineages trace their origin back to populations that inhabited distinct glacial refugia during the Last Glacial Maximum (LGM). Finally, we found that present day moose in Europe and North America show low to moderate inbreeding levels resulting from post-glacial bottlenecks and founder effects, but no evidence for recent inbreeding resulting from human-induced population declines.

Conclusions

Taken together, our results highlight the dynamic recent evolutionary history of the moose and provide an important resource for further genomic studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07208-3.

Deer, wolves, and people: costs, benefits and challenges of living together

Human-driven species annihilations loom as a major crisis. However the recovery of deer and wolf populations in many parts of the northern hemisphere has resulted in conflicts and controversies rather than in relief. Both species interact in complex ways with their environment, each other, and humans. We review these interactions in the context of the ecological and human costs and benefits associated with these species. We integrate scattered information to widen our perspective on the nature and perception of these costs and benefits and how they link to each other and ongoing controversies regarding how we manage deer and wolf populations. After revisiting the ecological roles deer and wolves play in contemporary ecosystems, we explore how they interact, directly and indirectly, with human groups including farmers, foresters, shepherds, and hunters. Interactions with deer and wolves generate various axes of tension, posing both ecological and sociological challenges. Resolving these tensions and conflicts requires that we address key questions using integrative approaches: what are the ecological consequences of deer and wolf recovery? How do they influence each other? What are the social and socio-ecological consequences of large deer populations and wolf presence? Finally, what key obstacles must be overcome to allow deer, wolves and people to coexist? Reviewing contemporary ecological and sociological results suggests insights and ways to improve our understanding and resolve long-standing challenges to coexistence. We should begin by agreeing to enhance aggregate benefits while minimizing the collective costs we incur by interacting with deer and wolves. We should also view these species, and ourselves, as parts of integrated ecosystems subject to long-term dynamics. If co-existence is our goal, we need deer and wolves to persevere in ways that are compatible with human interests. Our human interests, however, should be inclusive and fairly value all the costs and benefits deer and wolves entail including their intrinsic value. Shifts in human attitudes and cultural learning that are already occurring will reshape our ecological interactions with deer and wolves.

Comparing survey and multiple recruitment-mortality models to assess growth rates and population projections

Estimation of population trends and demographic parameters is important to our understanding of fundamental ecology and species management, yet these data are often difficult to obtain without the use of data from population surveys or marking animals. The northeastern Minnesota moose (Alces alces Linnaeus, 1758) population declined 58% during 2006-2017, yet aerial surveys indicated stability during 2012-2017. In response to the decline, the Minnesota Department of Natural Resources (MNDNR) initiated studies of adult and calf survival to better understand cause-specific mortality, calf recruitment, and factors influencing the population trajectory. We estimated population growth rate (λ) using adult survival and calf recruitment data from demographic studies and the recruitment-mortality (R-M) Equation and compared these estimates to those calculated using data from aerial surveys. We then projected population dynamics 50 years using each resulting λ and used a stochastic model to project population dynamics 30 years using data from the MNDNR's studies. Calculations of λ derived from 2012 to 2017 survey data, and the R-M Equation indicated growth (1.02 ± 0.16 [SE] and 1.01 ± 0.04, respectively). However, the stochastic model indicated a decline in the population over 30 years (λ = 0.91 ± 0.004; 2014-2044). The R-M Equation has utility for estimating λ, and the supporting information from demographic collaring studies also helps to better address management questions. Furthermore, estimates of λ calculated using collaring data were more certain and reflective of current conditions. Long-term monitoring using collars would better inform population performance predictions and demographic responses to environmental variability.

Fertilizing riparian forests: nutrient repletion across ecotones with trophic rewilding

Trophic rewilding maintains that large mammals are functionally important to resource subsidies and nutrient repletion, yet this prediction is understudied. Here, I report on the potential magnitude and variability of nitrogen that moose populations move from aquatic to terrestrial ecosystems. My aim is to provide justified approximations of the role of moose in the flux of a limiting nutrient across ecotones and to illustrate how this role is linked to wolf predation and climate warming. Using Isle Royale and northeastern Minnesota, USA as contrasting focal systems, I found that the long-term annual N gain for riparian forests likely ranges from 1 to 10 kg N ha^-1 yr^-1, depending on the heterogeneity of moose movements. For these systems, this range is equivalent to approximately 4-30% of net annual N mineralization, approximately 62-625% of annual N runoff, approximately 28-333% of annual atmospheric N deposition and approximately 31-312% of the N sequestered by trees. The N flux approximation is most sensitive to moose population levels and, as such, is influenced by wolves, climate warming and disease. The potential for other terrestrial ungulates that feed on aquatic plants to provide significant nutrient repletion across ecotones is unknown but important to examine in the context of trophic rewilding. The extent to which predators influence ungulate abundance indirectly impacts this nutrient repletion.This article is part of the theme issue 'Trophic rewilding: consequences for ecosystems under global change'.

Moose movement rates are altered by wolf presence in two ecosystems

Predators directly impact prey populations through lethal encounters, but understanding nonlethal, indirect effects is also critical because foraging animals often face trade-offs between predator avoidance and energy intake. Quantifying these indirect effects can be difficult even when it is possible to monitor individuals that regularly interact. Our goal was to understand how movement and resource selection of a predator (wolves; Canis lupus) influence the movement behavior of a prey species (moose; Alces alces). We tested whether moose avoided areas with high predicted wolf resource use in two study areas with differing prey compositions, whether avoidance patterns varied seasonally, and whether daily activity budgets of moose and wolves aligned temporally. We deployed GPS collars on both species at two sites in northern Minnesota. We created seasonal resource selection functions (RSF) for wolves and modeled the relationship between moose first-passage time (FPT), a method that discerns alterations in movement rates, and wolf RSF values. Larger FPT values suggest rest/foraging, whereas shorter FPT values indicate travel/fleeing. We found that the movements of moose and wolves peaked at similar times of day in both study areas. Moose FPTs were 45% lower in areas most selected for by wolves relative to those avoided. The relationship between wolf RSF and moose FPT was nonlinear and varied seasonally. Differences in FPT between low and high RSF values were greatest in winter (-82.1%) and spring (-57.6%) in northeastern Minnesota and similar for all seasons in the Voyageurs National Park ecosystem. In northeastern Minnesota, where moose comprise a larger percentage of wolf diet, the relationship between moose FPT and wolf RSF was more pronounced (ave. across seasons: -60.1%) than the Voyageurs National Park ecosystem (-30.4%). These findings highlight the role wolves can play in determining moose behavior, whereby moose spend less time in areas with higher predicted likelihood of wolf resource selection.