Survival of adult mountain goats in Washington: effects of season,translocation, snow,and precipitation

Elucidating patterns of adult survival rates is key to understanding population dynamics of large mammals. We used data from 7 separate studies of mountain goats (Oreamnos americanus) conducted from 2002 through 2022 in western Washington, USA, to quantify survival rates in relation to key biotic and abiotic factors using known fate models implemented in program MARK. We monitored 324 (206 females, 118 males) radio-marked mountain goats for 178,339 days. A substantial number of mountain goats in our sample (n = 217) had been translocated from the Olympic Peninsula to the Cascade Mountains on Washington's mainland, providing an added opportunity to examine translocation effects. We adopted a sequential modeling approach, first building a set of models to examine fundamental survival patterns by age, sex, season, study area, and translocated status. We used variables retained from the top model in a second set to investigate relationships between annual survival and local weather covariates hypothesized by previous studies to influence mountain goat behavior, habitat selection, and vital rates. Survival among adult females in spring was slightly lower than other sex and age categories, but seasonal patterns were otherwise not evident. There were significant negative relationships between survival and winter snow depth, an index of the previous year's drought, and mean daily temperature during the previous May, and a positive relationship with previous year's precipitation. Weather effects were similar among resident and translocated animals. By the end of the study period, weather effects had evidently contributed to reductions in mountain goat survival to a level low enough that population stability was unlikely. Because the frequency of droughts and warm spring temperatures are expected to increase with climate change, mountain goat populations in Washington will likely be increasingly challenged as the atmosphere warms.     

Long-term data reveal effects of climate,road access,and latitude on mountain goat horn size

Potential negative artificial selection on horn size is a concern for many harvested ungulates. The mountain goat (Oreamnos americanus) has distinct black horns, but targeting animals based on horn size in the field can be challenging. We analyzed over 23,000 horn records that included base circumference and total length, from which we also derived horn volume, from mountain goats harvested in Alaska, British Columbia, and the Northwest Territories from 1980 to 2016. We tested 3 potential drivers of horn size variation: geographical location, environmental conditions, and artificial selection. We found no support for a latitudinal effect with surprisingly little variation across the sampling distribution. The Pacific Decadal Oscillation had the largest effect outside age in the model, suggesting a role of climate in shaping variation. Mountain goats harvested closer to roads had larger horns, indicating that ease of access might allow hunters to be more selective, though the effect size was small. Our findings reinforce the value of accurate and complete record keeping on horn size, age, and sex of harvested animals, and highlight the importance of explicitly considering climate and accessibility when devising management strategies for the mountain goat.     

Integrating Genetic Data and Demographic Modeling to Facilitate Conservation of Small,Isolated Mountain Goat Populations

Acquisition of field data and analytical methods needed for conservation and management of wildlife populations represent significant challenges, particularly for species that inhabit landscapes that are difficult to access or species that persist in small, isolated populations. In such instances, integrating diverse and complementary data streams, such as genetic and non-genetic data, can advance our understanding of population dynamics and associated management implications. We examined how genetic and morphologic data can be used to articulate population structure of a low-density, peninsular population of mountain goats (Oreamnos americanus) on the Cleveland Peninsula, Alaska, USA, and surrounding areas, 2005–2018. We then use a population demographic modeling approach to examine how the use of population structure information influences sustainable harvest quotas, as compared to a panmictic, null model. Specifically, we conducted extensive field sampling of genetic (n = 446) and morphologic (i.e., horn length, n = 371) data to characterize population structure. We conducted demographic analyses and examined harvest modeling scenarios using a sex- and age-specific matrix population modeling approach. Genetic and morphologic data analyses suggested peninsular subpopulations were demographically isolated, relative to surrounding mainland populations. Specifically, genetic structuring was evident and followed an isolation-by-distance, stepping-stone pattern indicating limited interchange, low effective population sizes, and reduced genetic diversity along a peninsular extremity to mainland gradient. Harvest modeling indicated that overharvest would likely occur if the panmictic, null model was used to guide harvest because the smallest genetically defined population at the peninsular extremity was too small to permit any level of sustainable harvest. Our analyses illustrate the importance of using genetic and morphologic data, in combination with demographic modeling, to quantitatively delineate population boundaries and dynamics for ensuring viability of small, isolated populations. © 2020 The Wildlife Society.     

Staying close to home: Ecological constraints on space use and range fidelity in a mountain ungulate

Understanding patterns of animal space use and range fidelity has important implications for species and habitat conservation. For species that live in highly seasonal environments, such as mountain goats (Oreamnos americanus), spatial use patterns are expected to vary in relation to seasonal changes in environmental conditions and sex‐ or age‐specific selection pressures. To address hypotheses about sex, age, and seasonality influence on space‐use ecology, we collected GPS location data from 263 radio‐collared mountain goats (males, n = 140; females, n = 123) in coastal Alaska during 2005–2016. Location data were analyzed to derive seasonal and sex‐specific fixed‐kernel home range estimates and to quantify the degree of seasonal range and utilization distribution overlap. Overall, we determined that home range size was smallest during winter, expanded coincident with the onset of green‐up and parturition, and was largest during summer. Home range size of males and females did not differ significantly during winter, but females had larger home ranges than males during summer, a relationship that was switched during the mating season. Pairwise comparisons involving individual females across subsequent years indicated home ranges were significantly smaller during years when they gave birth to offspring. Mountain goats exhibited a strong degree of range fidelity, and 99% (n = 138) of individual animals returned to their previous year''s seasonal range with an average annual Bhattacharyya''s affinity utilization distribution overlap index of 68%. Similarity of seasonal home range utilization distributions varied in relation to sex and season in some respects. Home range overlap was highest during the summer vegetation growing season, particularly among females. These findings advance our understanding about how environmental variation and sex‐ and age‐related reproductive constraints influence space use and range fidelity among alpine ungulates. Documentation of the high degree of range fidelity among mountain goats has important conservation implications in landscapes increasingly altered by anthropogenic activities.     

Genome-wide cross-amplification of domestic sheep microsatellites in bighorn sheep and mountain goats

We tested for cross‐species amplification of microsatellite loci located throughout the domestic sheep (Ovis aries) genome in two north American mountain ungulates (bighorn sheep, Ovis canadensis, and mountain goats, Oreamnos americanus). We identified 247 new polymorphic markers in bighorn sheep (≥ 3 alleles in one of two study populations) and 149 in mountain goats (≥ 2 alleles in a single study population) using 648 and 576 primer pairs, respectively. Our efforts increased the number of available polymorphic microsatellite markers to 327 for bighorn sheep and 180 for mountain goats. The average distance between successive polymorphic bighorn sheep and mountain goat markers inferred from the Australian domestic sheep genome linkage map (mean ± 1 SD) was 11.9 ± 9.2 and 15.8 ± 13.8 centimorgans, respectively. The development of genomic resources in these wildlife species enables future studies of the genetic architecture of trait variation.     

Effects of predator treatments,individual traits,and environment on moose survival in Alaska

We studied moose (Alces alces) survival, physical condition, and abundance in a 3-predator system in western Interior Alaska, USA, during 2001–2007. Our objective was to quantify the effects of predator treatments on moose population dynamics by investigating changes in survival while evaluating the contribution of potentially confounding covariates. In May 2003 and 2004, we reduced black bear (Ursus americanus) and brown bear (U. arctos) numbers by translocating bears ≥240 km from the study area. Aircraft-assisted take reduced wolf (Canis lupus) numbers markedly in the study area during 2004–2007. We estimated black bears were reduced by approximately 96% by June 2004 and recovered to within 27% of untreated numbers by May 2007. Brown bears were reduced approximately 50% by June 2004. Late-winter wolf numbers were reduced by 75% by 2005 and likely remained at these levels through 2007. In addition to predator treatments, moose hunting closures during 2004–2007 reduced harvests of male moose by 60% in the study area. Predator treatments resulted in increased calf survival rates during summer (primarily from reduced black bear predation) and autumn (primarily from reduced wolf predation). Predator treatments had little influence on survival of moose calves during winter; instead, calf survival was influenced by snow depth and possibly temperature. Increased survival of moose calves during summer and autumn combined with relatively constant winter survival in most years led to a corresponding increase in annual survival of calves following predator treatments. Nonpredation mortalities of calves increased following predator treatments; however, this increase provided little compensation to the decrease in predation mortalities resulting from treatments. Thus, predator-induced calf mortality was primarily additive. Summer survival of moose calves was positively related to calf mass (β > 0.07, SE = 0.073) during treated years and lower (β = −0.82, SE = 0.247) for twins than singletons during all years. Following predator treatments, survival of yearling moose increased 8.7% for females and 21.4% for males during summer and 2.2% for females and 15.6% for males during autumn. Annual survival of adult (≥2 yr old) female moose also increased in treated years and was negatively (β = −0.21, SE = 0.078) related to age. Moose density increased 45%, from 0.38 moose/km² in 2001 to 0.55 moose/km² in 2007, which resulted from annual increases in overall survival of moose, not increases in reproductive rates. Indices of nutritional status remained constant throughout our study despite increased moose density. This information can be used by wildlife managers and policymakers to better understand the outcomes of predator treatments in Alaska and similar environments. © 2011 The Wildlife Society.     

Projecting the future of an alpine ungulate under climate change scenarios

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key “early warning signs” about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37‐year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate‐driven effects influence mountain goat populations, we developed an age‐structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70‐year time window (2015–2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., “thermoneutral”) summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%–86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate‐linked bottom‐up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence.     

Winter Distribution,Movements, and Annual Survival of Radiomarked Vancouver Canada Geese in Southeast Alaska

ABSTRACT Management of Pacific Flyway Canada geese (Branta canadensis) requires information on winter distribution of different populations. Recoveries of tarsus bands from Vancouver Canada geese (B. canadensis fulva) marked in southeast Alaska, USA, ≥4 decades ago suggested that ≥83% of the population was non-migratory and that annual adult survival was high (Ŝ = 0.836). However, recovery distribution of tarsus bands was potentially biased due to geographic differences in harvest intensity in the Pacific Flyway. Also, winter distribution of Vancouver Canada geese could have shifted since the 1960s, as has occurred for some other populations of Canada geese. Because winter distribution and annual survival of this population had not recently been evaluated, we surgically implanted very high frequency radiotransmitters in 166 adult female Canada geese in southeast Alaska. We captured Vancouver Canada geese during molt at 2 sites where adults with goslings were present (breeding areas) and 2 sites where we observed nonbreeding birds only. During winter radiotracking flights in southeast Alaska, we detected 98% of 85 females marked at breeding areas and 83% of 70 females marked at nonbreeding sites, excluding 11 females that died prior to the onset of winter radiotracking. We detected no radiomarked females in coastal British Columbia, or western Washington and Oregon, USA. Most (70%) females moved ≤30 km between November and March. Our model-averaged estimate of annual survival (Ŝ = 0.844, SE = 0.050) was similar to the estimate of annual survival of geese marked from 1956 to 1960. Likely <2% of Vancouver Canada geese that nest in southeast Alaska migrate to winter areas in Oregon or Washington where they could intermix with Canada geese from other populations in the Pacific Flyway. Because annual survival of adult Vancouver Canada geese was high and showed evidence of long-term consistency, managers should examine how reproductive success and recruitment may affect the population.     

Effects of Snow on Sitka Black-Tailed Deer Browse Availability and Nutritional Carrying Capacity in Southeastern Alaska

ABSTRACT Snow affects the nutritional ecology of northern ungulates during winter through burial of important winter forages. We used nonlinear regression analyses to model snow-burial dynamics of blueberry (Vaccinium spp.) browse biomass, a key winter food item of Sitka black-tailed deer (Odocoileus hemionus sitchensis) in southeastern Alaska, USA. During November 2003—March 2004 we collected data from 546 individually marked twigs located on 100 plants of differing sizes and architectures across a range of snow depths. In general, browse biomass became buried and unavailable to deer at snow depths substantially lower than prewinter twig heights. Plant architecture and plant height were related to the probability of a twig being buried. Probability of twig burial was higher on plants with lateral than on those with erect architectures. Twig height also affected the probability of burial by snow but the relationship was complex. For twigs located on erect plants, probability of burial was greatest for twigs near the bottom and top of the plant due to ground-up burial and bending of flexible apex stems, respectively. We used estimated nonlinear equations to model blueberry browse availability in a simulated upland old-growth habitat patch subject to a range of snow depths. We then compared subsequent estimates of deer winter nutritional carrying capacity for this habitat patch to findings derived using an alternative, simple linear (ground-up) model of winter-browse burial by snow. Comparisons indicated that ground-up models of browse burial overestimated browse availability and nutritional carrying capacity for most snow depths. Our findings demonstrate the importance of applying detailed snow-burial models when characterizing nutritional landscape of northern ungulates during winter.     

Climate change and voltinism in Californian insect pest species: sensitivity to location,scenario and climate model choice

Experimental studies of the impact of climatic change are hampered by their inability to consider multiple climate change scenarios and indeed often consider no more than simple climate sensitivity such as a uniform increase in temperature. Modelling efforts offer the ability to consider a much wider range of realistic climate projections and are therefore useful, in particular, for estimating the sensitivity of impact predictions to differences in geographical location, and choice of climate change scenario and climate model projections. In this study, we used well‐established degree‐day models to predict the voltinism of 13 agronomically important pests in California, USA. We ran these models using the projections from three Atmosphere–Ocean Coupled Global Circulation Models (AOCGCMs or GCMs), in conjunction with the SRES scenarios. We ran these for two locations representing northern and southern California. We did this for both the 2050s and 2090s. We used anova to partition the variation in the resulting voltinism among time period, climate change scenario, GCM and geographical location. For these 13 pest species, the choice of climate model explained an average of 42% of the total variation in voltinism, far more than did geographical location (33%), time period (17%) or scenario (1%). The remaining 7% of the variation was explained by various interactions, of which the location by GCM interaction was the strongest (5%). Regardless of these sources of uncertainty, a robust conclusion from our work is that all 13 pest species are likely to experience increases in the number of generations that they complete each year. Such increased voltinism is likely to have significant consequences for crop protection and production.     

Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach

Aim To understand drivers of vegetation type distribution and sensitivity to climate change. Location Interior Alaska. Methods A logistic regression model was developed that predicts the potential equilibrium distribution of four major vegetation types: tundra, deciduous forest, black spruce forest and white spruce forest based on elevation, aspect, slope, drainage type, fire interval, average growing season temperature and total growing season precipitation. The model was run in three consecutive steps. The hierarchical logistic regression model was used to evaluate how scenarios of changes in temperature, precipitation and fire interval may influence the distribution of the four major vegetation types found in this region. Results At the first step, tundra was distinguished from forest, which was mostly driven by elevation, precipitation and south to north aspect. At the second step, forest was separated into deciduous and spruce forest, a distinction that was primarily driven by fire interval and elevation. At the third step, the identification of black vs. white spruce was driven mainly by fire interval and elevation. The model was verified for Interior Alaska, the region used to develop the model, where it predicted vegetation distribution among the steps with an accuracy of 60–83%. When the model was independently validated for north‐west Canada, it predicted vegetation distribution among the steps with an accuracy of 53–85%. Black spruce remains the dominant vegetation type under all scenarios, potentially expanding most under warming coupled with increasing fire interval. White spruce is clearly limited by moisture once average growing season temperatures exceeded a critical limit (+2 °C). Deciduous forests expand their range the most when any two of the following scenarios are combined: decreasing fire interval, warming and increasing precipitation. Tundra can be replaced by forest under warming but expands under precipitation increase. Main conclusion The model analyses agree with current knowledge of the responses of vegetation types to climate change and provide further insight into drivers of vegetation change.     

Predicting spatial and temporal patterns of bud‐burst and spring frost risk in north‐west Europe: the implications of local adaptation to climate

The timing of spring bud‐burst and leaf development in temperate, boreal and Arctic trees and shrubs fluctuates from year to year, depending on meteorological conditions. Over several generations, the sensitivity of bud‐burst to meteorological conditions is subject to selection pressure. The timing of spring bud‐burst is considered to be under opposing evolutionary pressures; earlier bud‐burst increases the available growing season (capacity adaptation) but later bud‐burst decreases the risk of frost damage to actively growing parts (survival adaptation). The optimum trade‐off between these two forms of adaptation may be considered an evolutionarily stable strategy that maximizes the long‐term ecological fitness of a phenotype under a given climate. Rapid changes in climate, as predicted for this century, are likely to exceed the rate at which trees and shrubs can adapt through evolution or migration. Therefore the response of spring phenology will depend not only on future climatic conditions but also on the limits imposed by adaptation to current and historical climate. Using a dataset of bud‐burst dates from twenty‐nine sites in Finland for downy birch (Betula pubescens Ehrh.), we parameterize a simple thermal time bud‐burst model in which the critical temperature threshold for bud‐burst is a function of recent historical climatic conditions and reflects a trade‐off between capacity and survival adaptation. We validate this approach with independent data from eight independent sites outside Finland, and use the parameterized model to predict the response of bud‐burst to future climate scenarios in north‐west Europe. Current strategies for budburst are predicted to be suboptimal for future climates, with bud‐burst generally occurring earlier than the optimal strategy. Nevertheless, exposure to frost risk is predicted to decrease slightly and the growing season is predicted to increase considerably across most of the region. However, in high‐altitude maritime regions exposure to frost risk following bud‐burst is predicted to increase.     

Interactive Effects of Fire, Soil Climate, and Moss on CO2 Fluxes in Black Spruce Ecosystems of Interior Alaska

Fire is an important control on the carbon (C) balance of the boreal forest region. Here, we present findings from two complementary studies that examine how fire modifies soil organic matter properties, and how these modifications influence rates of decomposition and C exchange in black spruce (Picea mariana) ecosystems of interior Alaska. First, we used laboratory incubations to explore soil temperature, moisture, and vegetation effects on CO₂ and DOC production rates in burned and unburned soils from three study regions in interior Alaska. Second, at one of the study regions used in the incubation experiments, we conducted intensive field measurements of net ecosystem exchange (NEE) and ecosystem respiration (ER) across an unreplicated factorial design of burning (2 year post-fire versus unburned sites) and drainage class (upland forest versus peatland sites). Our laboratory study showed that burning reduced the sensitivity of decomposition to increased temperature, most likely by inducing moisture or substrate quality limitations on decomposition rates. Burning also reduced the decomposability of Sphagnum-derived organic matter, increased the hydrophobicity of feather moss-derived organic matter, and increased the ratio of dissolved organic carbon (DOC) to total dissolved nitrogen (TDN) in both the upland and peatland sites. At the ecosystem scale, our field measurements indicate that the surface organic soil was generally wetter in burned than in unburned sites, whereas soil temperature was not different between the burned and unburned sites. Analysis of variance results showed that ER varied with soil drainage class but not by burn status, averaging 0.9 ± 0.1 and 1.4 ± 0.1 g C m⁻² d⁻¹ in the upland and peatland sites, respectively. However, a more complex general linear model showed that ER was controlled by an interaction between soil temperature, moisture, and burn status, and in general was less variable over time in the burned than in the unburned sites. Together, findings from these studies across different spatial scales suggest that although fire can create some soil climate conditions more conducive to rapid decomposition, rates of C release from soils may be constrained following fire by changes in moisture and/or substrate quality that impede rates of decomposition. Author contributions: JAO: performed research, analyzed data, contributed new methods, wrote the paper; MRT: designed laboratory study, performed research, analyzed data; JWH: designed field study, performed research; KLM: performed research; LEP: performed research, contributed new method; GS: performed research; JCN: performed research.     

Effects of sexual differences of age at maturity and survival on population sex ratio

Summary Five demographical factors influencing the sex ratio of a population are classically considered. The influence of two of them is dependent on the longevity of individuals in the population. The effect of differential age at maturity between males and females is higher for animals with low annual survival, whereas the effect of differential annual survival between males and females is higher for animals with high annual survival. Such a conclusion applied to turtles, which are long life-span animals, allows us to retain differential survival between sexes as a major factor influencing the population sex ratio.     

Ice‐age persistence and genetic isolation of the disjunct distribution of larch in Alaska

Larix laricina (eastern larch, tamarack) is a transcontinental North American conifer with a prominent disjunction in the Yukon isolating the Alaskan distribution from the rest of its range. We investigate whether in situ persistence during the last glacial maximum (LGM) or long‐distance postglacial migration from south of the ice sheets resulted in the modern‐day Alaskan distribution. We analyzed variation in three chloroplast DNA regions of 840 trees from a total of 69 populations (24 new sampling sites situated on both sides of the Yukon range disjunction pooled with 45 populations from a published source) and conducted ensemble species distribution modeling (SDM) throughout Canada and United States to hindcast the potential range of L. laricina during the LGM. We uncovered the genetic signature of a long‐term isolation of larch populations in Alaska, identifying three endemic chlorotypes and low levels of genetic diversity. Range‐wide analysis across North America revealed the presence of a distinct Alaskan lineage. Postglacial gene flow across the Yukon divide was unidirectional, from Alaska toward previously glaciated Canadian regions, and with no evidence of immigration into Alaska. Hindcast SDM indicates one of the broadest areas of past climate suitability for L. laricina existed in central Alaska, suggesting possible in situ persistence of larch in Alaska during the LGM. Our results provide the first unambiguous evidence for the long‐term isolation of L. laricina in Alaska that extends beyond the last glacial period and into the present interglacial period. The lack of gene flow into Alaska along with the overall probability of larch occurrence in Alaska being currently lower than during the LGM suggests that modern‐day Alaskan larch populations are isolated climate relicts of broader glacial distributions, and so are particularly vulnerable to current warming trends.     

Unexpected role of winter precipitation in determining heat requirement for spring vegetation green‐up at northern middle and high latitudes

Heat requirement, expressed in growing degree days (GDD), is a widely used method to assess and predict the effect of temperature on plant development. Until recently, the analysis of spatial patterns of GDD requirement for spring vegetation green‐up onset was limited to local and regional scales, mainly because of the sparse and aggregated spatial availability of ground phenology data. Taking advantage of the large temporal and spatial scales of remote sensing‐based green‐up onset data, we studied the spatial patterns of GDD requirement for vegetation green‐up at northern middle and high latitudes. We further explored the correlations between GDD requirement for vegetation green‐up and previous winter season chilling temperatures and precipitation, using spatial partial correlations. We showed that GDD requirement for vegetation green‐up onset declines towards the north at a mean rate of 18.8 °C‐days per degree latitude between 35°N and 70°N, and vary significantly among different vegetation types. Our results confirmed that the GDD requirement for vegetation green‐up is negatively correlated with previous winter chilling, which was defined as the number of chilling days from the day when the land surface froze in the previous autumn to the day of green‐up onset. This negative correlation is a well‐known phenomenon from local studies. Interestingly, irrespective of the vegetation type, we also found a positive correlation between the GDD requirement and previous winter season precipitation, which was defined as the sum of the precipitation of the month when green‐up onset occur and the precipitation that occurred during the previous 2 months. Our study suggests that GDD requirement, chilling and precipitation may have complex interactions in their effects on spring vegetation green‐up phenology. These findings have important implications for improving phenology models and could therefore advance our understanding of the interplay between spring phenology and carbon fluxes.