Human perspectives and conservation of grizzly bears in Banff National Park, Canada

Some conservation initiatives provoke intense conflict among stakeholders. The need for action, the nature of the conservation measures, and the effects of these measures on human interests may be disputed. Tools are needed to depolarize such situations, foster understanding of the perspectives of people involved, and find common ground. We used Q methodology to explore stakeholders' perspectives on conservation and management of grizzly bears (Ursus arctos horribilis) in Banff National Park and the Bow River watershed of Alberta, Canada. Twenty-nine stakeholders participated in the study, including local residents, scientists, agency employees, and representatives of nongovernmental conservation organizations and other interest groups. Participants rank ordered a set of statements to express their opinions on the problems of grizzly bear management (I-IV) and a second set of statements on possible solutions to the problems (A-C). Factor analysis revealed that participants held 4 distinct views of the problems: individuals associated with factor I emphasized deficiencies in goals and plans; those associated with factor II believed that problems had been exaggerated; those associated with factor III blamed institutional flaws such as disjointed management and inadequate resources; and individuals associated with factor IV blamed politicized decision making. There were 3 distinct views about the best solutions to the problems: individuals associated with factor A called for increased conservation efforts; those associated with factor B wanted reforms in decision-making processes; and individuals associated with factor C supported active landscape management. We connected people's definitions of the problem with their preferred solutions to form 5 overall problem narratives espoused by groups in the study: the problem is deficient goals and plans, the solution is to prioritize conservation efforts (planning-oriented conservation advocates); the problem is flawed institutions, the solution is to prioritize conservation efforts (institutionally-oriented conservation advocates); the problems have been exaggerated, but there is a need to improve decision-making processes (optimistic decision-process reformers); the problems have been exaggerated, but managers should more actively manage the landscape (optimistic landscape managers); and the problem is politicized decision making, solutions vary (democratizers). Although these 5 groups differed on many issues, they agreed that the population of grizzly bears is vulnerable to extirpation, human use of the area should be designed around ecological constraints, and more inclusive decision-making processes are needed. We used our results to inform a series of workshops in which stakeholders developed and agreed on new management strategies that were implemented by Parks Canada. Our research demonstrates the usefulness of Q method to illuminate people's perspectives and identify common ground in settings where conservation is contested.     

Age-dependent survival analyzed with Bayesian models of mark-recapture data

We describe a Bayesian random effects model of mark-recapture data that accounts for age-dependence in survival and individual heterogeneity in capture probabilities and survival. The model is applied to data on the Glanville fritillary butterfly (Melitaea cinxia) collected from a population enclosed in a large cage in the field. The cage population consisted of a mixture of butterflies originating from newly established and old populations in a large metapopulation in the Aland Islands in Finland. The explanatory variables in the model included the effects of temperature, sex, and population type (new vs. old) on capture probabilities, and the effects of age, sex, population type, and day vs. night on survival. We found that mortality rate increased with age, that mortality rate was much higher during the day than during the night, and that the life span of females originating from newly established populations was shorter than the life span of females from old populations. Capture probability decreased with increasing temperature and decreased with increasing mobility of individuals.     

Photographic mark-recapture analysis of local dynamics within an open population of dolphins

Identifying demographic changes is important for understanding population dynamics. However, this requires long-term studies of definable populations of distinct individuals, which can be particularly challenging when studying mobile cetaceans in the marine environment. We collected photo-identification data from 19 years (1992-2010) to assess the dynamics of a population of bottlenose dolphins (Tursiops truncatus) restricted to the shallow (<7 m) waters of Little Bahama Bank, northern Bahamas. This population was known to range beyond our study area, so we adopted a Bayesian mixture modeling approach to mark-recapture to identify clusters of individuals that used the area to different extents, and we specifically estimated trends in survival, recruitment, and abundance of a "resident" population with high probabilities of identification. There was a high probability (p= 0.97) of a long-term decrease in the size of this resident population from a maximum of 47 dolphins (95% highest posterior density intervals, HPDI = 29-61) in 1996 to a minimum of just 24 dolphins (95% HPDI = 14-37) in 2009, a decline of 49% (95% HPDI = approximately 5% to approximately 75%). This was driven by low per capita recruitment (average approximately 0.02) that could not compensate for relatively low apparent survival rates (average approximately 0.94). Notably, there was a significant increase in apparent mortality (approximately 5 apparent mortalities vs. approximately 2 on average) in 1999 when two intense hurricanes passed over the study area, with a high probability (p = 0.83) of a drop below the average survival probability (approximately 0.91 in 1999; approximately 0.94, on average). As such, our mark-recapture approach enabled us to make useful inference about local dynamics within an open population of bottlenose dolphins; this should be applicable to other studies challenged by sampling highly mobile individuals with heterogeneous space use.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

Abundance of the New Zealand subantarctic southern right whale population estimated from photo-identification and genotype mark-recapture

The abundance of New Zealand subantarctic southern right whales (Eubalaena australis) was estimated for the first time using mark-recapture methods based on photo-identification and microsatellite genotyping (13 loci). Individual identification photographs of 383 whales and microsatellite genotypes of 235 whales were collected during annual austral winter field surveys from 1995 to 1998. Given the 4-year survey period and lack of geographic and demographic closure, we estimated super-population abundance using the POPAN Jolly-Seber model implemented in the software programme MARK. Models with constant survivorship but time-varying capture probability and probability of entry into the population were the most suitable due to the survey design. This provided estimates of abundance in 1998 of 908 non-calf whales (95% C.L. = 755, 1,123) for the photo-identification and 910 non-calf whales (95% C.L. = 641, 1,354) for the microsatellite genotype data sets. The current estimate of 900 whales may represent less than 5% of the pre-whaling abundance in New Zealand waters.     

Sensitivity analysis of North American bird population estimates

The Partners in Flight North American Landbird Conservation Plan provided estimates of population sizes for 448 landbird species using a multiplicative model. Input parameters in this calculation included the area of state × Bird Conservation Region polygons, area-specific mean Breeding Bird Survey counts circa 1995, and adjustment factors for the distance over which species may presumably be correctly counted, the assumed pairing of singing males with non-singing females, and variability in the propensity of birds to sing over the course of the survey day. I assessed the sensitivity of this population calculation to changes in the input parameters. I assessed both local and global sensitivity of the model to changes in the parameters with Monte Carlo one-at-a-time simulations and the Fourier amplitude sensitivity test (FAST). Monte Carlo simulations were an estimate of local model sensitivity whereas FAST estimated global model sensitivity, accommodating the potential shared variance between model parameters. Monte Carlo simulations suggested population estimates were 39% more sensitive to changes in the detection distance adjustment than to the other parameters; the other parameters were nearly equal in their contribution to model sensitivity. Conversely, FAST analysis determined that each of the input variables aside from the pair adjustment provided roughly equal contributions to variability in population estimates. The most efficient means for improving continental population estimates for birds surveyed by the Breeding Bird Survey will be through increased scrutiny of the species-specific distance detection and time-of-day adjustments and improved understanding in the spatial and temporal variability in the mean Breeding Bird Survey count.     

Use of ambiguous detections to improve estimates from species distribution models

As large carnivores recover throughout Europe, their distribution needs to be studied to determine their conservation status and assess the potential for human-carnivore conflicts. However, efficient monitoring of many large carnivore species is challenging due to their rarity, elusive behavior, and large home ranges. Their monitoring can include opportunistic sightings from citizens in addition to designed surveys. Two types of detection errors may occur in such monitoring schemes: false negatives and false positives. False-negative detections can be accounted for in species distribution models (SDMs) that deal with imperfect detection. False-positive detections, due to species misidentification, have rarely been accounted for in SDMs. Generally, researchers use ad hoc data-filtering methods to discard ambiguous observations prior to analysis. These practices may discard valuable ecological information on the distribution of a species. We investigated the costs and benefits of including data types that may include false positives rather than discarding them for SDMs of large carnivores. We used a dynamic occupancy model that simultaneously accounts for false negatives and positives to jointly analyze data that included both unambiguous detections and ambiguous detections. We used simulations to compare the performances of our model with a model fitted on unambiguous data only. We tested the 2 models in 4 scenarios in which parameters that control false-positive detections and true detections varied. We applied our model to data from the monitoring of the Eurasian lynx (Lynx lynx) in the European Alps. The addition of ambiguous detections increased the precision of parameter estimates. For the Eurasian lynx, incorporating ambiguous detections produced more precise estimates of the ecological parameters and revealed additional occupied sites in areas where the species is likely expanding. Overall, we found that ambiguous data should be considered when studying the distribution of large carnivores through the use of dynamic occupancy models that account for misidentification.     

Databanks of data sources for environmental chemicals

There exist a vast variety of data sources, either manual sources or computerized databases in the field of environmental chemicals. To facilitate the access and to retrieve the information wanted efficiently, we built up two “databanks of data sources”, one called “Databank of Manual Sources (DMAS)” and the other named “Databank of Databases (DADB)”. The set‐up of these databanks is explained and the load status statistics are shown. DMAS has 164 and DADB 106 hits.     

Evaluating orangutan census techniques using nest decay rates: implications for population estimates.

An accurate estimate for orangutan nest decay time is a crucial factor in commonly used methods for estimating orangutan population size. Decay rates are known to vary, but the decay process and, thus, the temporal and spatial variation in decay time are poorly understood. We used established line-transect methodology to survey orangutan nests in a lowland forest in East Kalimantan, Indonesia, and monitored the decay of 663 nests over 20 months. Using Markov chain analysis we calculated a decay time of 602 days, which is significantly longer than times found in other studies. Based on this, we recalculated the orangutan density estimate for a site in East Kalimantan; the resulting density is much lower than previous estimates (previous estimates were 3-8 times higher than our recalculated density). Our data suggest that short-term studies where decay times are determined using matrix mathematics may produce unreliable decay times. Our findings have implications for other parts of the orangutan range where population estimates are based on potentially unreliable nest decay rate estimates, and we recommend that for various parts of the orangutan range census estimates be reexamined. Considering the high variation in decay rates there is a need to move away from using single-number decay time estimates and, preferably, to test methods that do not rely on nest decay times as alternatives for rapid assessments of orangutan habitat for conservation in Borneo.     

Improved estimates of net primary productivity from modis satellite data at regional and local scales.

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak-hickory forests in the region. However, MODIS underestimated NPP for less-dominant northern hardwood forests and overestimated NPP for coniferous forests. Causes of inaccurate estimates of NPP by MODIS were (1) an aggregated classification and parameterization of diverse deciduous forests in different climatic environments into a single class that averages different radiation conversion efficiencies; and (2) lack of soil water constraints on NPP for forests or areas that occur on thin or sandy, coarse-grained soil. We developed the "available soil water index" for adjusting the MODIS NPP estimates, which significantly improved NPP estimates for coniferous forests. The MODIS NPP estimates have many advantages such as globally continuous monitoring and remarkable accuracy for large scales. However, at regional or local scales, our study indicates that it is necessary to adjust estimates to specific vegetation types and soil water conditions.     

Can modeling improve estimation of desert tortoise population densities?

The federally listed desert tortoise (Gopherus agassizii) is currently monitored using distance sampling to estimate population densities. Distance sampling, as with many other techniques for estimating population density, assumes that it is possible to quantify the proportion of animals available to be counted in any census. Because desert tortoises spend much of their life in burrows, and the proportion of tortoises in burrows at any time can be extremely variable, this assumption is difficult to meet. This proportion of animals available to be counted is used as a correction factor (g0) in distance sampling and has been estimated from daily censuses of small populations of tortoises (6-12 individuals). These censuses are costly and produce imprecise estimates of go due to small sample sizes. We used data on tortoise activity from a large (N = 150) experimental population to model activity as a function of the biophysical attributes of the environment, but these models did not improve the precision of estimates from the focal populations. Thus, to evaluate how much of the variance in tortoise activity is apparently not predictable, we assessed whether activity on any particular day can predict activity on subsequent days with essentially identical environmental conditions. Tortoise activity was only weakly correlated on consecutive days, indicating that behavior was not repeatable or consistent among days with similar physical environments.     

Diurnal measurements of F v/F m used to improve productivity estimates in macroalgae

The ratio of variable fluorescence to maximal fluorescence (F _v/F _m) was measured during a night and day cycle in five different macroalgae growing in the littoral zone at the Swedish west coast; the green algae Ulva lactuca, Cladophora sp. and Enteromorpha flexousa, the red alga Ceramium nodulosum and the brown alga Fucus vesiculosus. All the green algae and C. nodulosum showed both diurnal fluctuations in F _v/F _m during days of high light intensities and a significant negative correlation between F _v/F _m and photon irradiance (PI). An attempt has been made to improve calculations of macroalgal net growth based on carbon fixation (α_net) considering this diurnal change in F _v/F _m. By assuming that the negative linear correlation between F _v/F _m and the maximum quantum yield for photosynthesis (Φ) is proportional to that between F _v/F _m and α_net, it was possible to include the daily variation of α_net due to photoinhibition. To compensate for the variation of F _v/F _m, a representative value for each day was obtained by weighting all values of F _v/F _m over the diurnal period in relation to total PI. For all algal species there was a fairly good agreement between this representative value and the F _v/F _m value measured around noon. As the daily representative F _v/F _m value showed a negative linear correlation with the daily mean PI, it was possible to correct α_net for differences of daily mean PI. Received: 10 March 1997 / Accepted: 25 August 1997     

Effects of interpolation and data resolution on methane emission estimates from rice paddies

Rice paddies are an important source of the greenhouse gas methane (CH₄). Global methane emission estimates are highly uncertain and do not account for effects of interpolation or data resolution errors. This paper determines such scaling effects for the influence of soil properties on calculated CH₄ emissions for the island of Java, Indonesia. The effects of different interpolation techniques, variograms and neighbor optimization were tested for soil properties by cross-validation. Interpolated organic carbon values were not significantly different from the original soil samples, in contrast to interpolated soil iron contents. Interpolation of soil properties coupled to a process-based model on CH₄emissions led to a significant change in distribution of calculated CH₄ emissions, i.e., the variance decreased. Effects of data resolution were examined by interpolating soil properties to derive data at different data resolutions and then calculating CH₄ emissions by applying the process-based model at these resolutions. The soil properties did not differ significantly for different data resolutions, in contrast to calculated CH₄ emissions. These scaling effects were caused by the combination of interpolation and a non-linear model. Real scaling effects may even be larger because small-scale variability was not accounted for. Scaling effects, including those caused by small-scale variability, have to be considered to achieve unbiased and less uncertain global CH₄emissions estimates from rice paddies.     

Mortality estimates from repeated visual censuses of a parrotfish (Sparisoma viride) population: demographic implications

Repeated visual censuses of different categories (juveniles, females, territorial and group males) of the stoplight parrotfish (Sparisoma viride, a protogynous hermaphrodite) over a 3-year period indicated a relatively stable size and structure of the adult population. This allowed estimates of size-specific mortality, sex change, and territory acquisition probabilities from previously reported growth rates. Comparison of the predicted number of survivors, sex changers, and territory take overs with field observations indicates that our estimates are quite reliable. However, rather large differences in mortality are obtained for the largest three size classes (>25 cm), which may be due to reduced accuracy of length estimates of large fish. A pooled mortality for these classes is therefore suggested as a more realistic estimate. The life-history implications of our findings are investigated by comparing the predicted survival and future reproductive success of fish that change sex at different sizes. Ten percent of the adults reach an age of ca. 17 years, once a length of 20 cm is attained, as predicted from the pooled estimates. Calculations based on these estimates indicate that the predicted reproductive output of a 15-year-old fish (2500 matings) is the same for early (i.e. at 20 cm) and late (>30 cm) sex changers and for an average fish subject to the estimated daily sex change and territory acquisition probabilities. These findings suggest that S. viride individuals are able to flexibly adjust the timing of sex change in an adaptive way to unpredictable local conditions. However, independent mortality estimates are needed to corroborate our present findings. Received: 2 January 1997 / Accepted: 27 January 1997     

Multiple paternity in a wild population of northern water snakes,Nerodia sipedon

Summary For most animal species, a single mating is sufficient to fertilize all of a female's offspring. As a result, females do not usually increase their reproductive success with successive matings. However, multiple paternity has been discovered in many animal taxa. We demonstrate that the majority of female water snakes in a wild population mate with more than one male for each litter. Field observations indicated that a highly skewed operational sex ratio (3.6:1 M : F) during the breeding season, while not necessary for multiple paternity to occur, created ample opportunity for females to mate multiply. Protein electrophoretic analysis showed that at least 12 of 14 litters from naturally mated females had more than one father. Since male snakes can not force copulations, multiple matings seem likely to be the result of female choice. Offprint requests to: F.E. Barry     

Assessing plausible rates of population growth in humpback whales from life-history data

The rate of growth of any population is a quantity of interest in conservation and management and is constrained by biological factors. In this study, recent data on life-history parameters influencing rates of population growth in humpback whales, including survival, age at first parturition and calving rate are reviewed. Monte Carlo simulations are used to compute a distribution of rates of increase (ROIs) taking into account uncertainty in biological parameter estimates. Two approaches for computing juvenile survival are proposed, which taken into account along with other life-history data, resulted in the following estimates of the rate of population growth: Approach A: mean of 7.3%/year (95% CI = 3.5–10.5%/year) and Approach B: mean of 8.6%/year (95% CI = 5.0–11.4%/year). It is proposed that the upper 99% quantile of the resulting distribution of the ROI for Approach B (11.8%/year) be established as the maximum plausible ROI for humpback whales and be used in population assessment of the species. Possible sources of positive and negative biases in the present estimates are presented and include measurement error in estimation of life-history parameters, changes in the environment within the period these quantities are measured, density dependence or other natural factors. However, it is difficult to evaluate potential biases without additional data. The methods presented in this study can be applied to other species for which life-history parameters are available and are useful in assessing plausibility in the estimation of population growth rates from time series of abundance estimates.     

Landscape ecology of eastern coyotes based on large-scale estimates of abundance.

Since their range expansion into eastern North America in the mid-1900s, coyotes (Canis latrans) have become the region's top predator. Although widespread across the region, coyote adaptation to eastern forests and use of the broader landscape are not well understood. We studied the distribution and abundance of coyotes by collecting coyote feces from 54 sites across a diversity of landscapes in and around the Adirondacks of northern New York. We then genotyped feces with microsatellites and found a close correlation between the number of detected individuals and the total number of scats at a site. We created habitat models predicting coyote abundance using multi-scale vegetation and landscape data and ranked them with an information-theoretic model selection approach. These models allow us to reject the hypothesis that eastern forests are unsuitable habitat for coyotes as their abundance was positively correlated with forest cover and negatively correlated with measures of rural non-forest landscapes. However, measures of vegetation structure turned out to be better predictors of coyote abundance than generalized "forest vs. open" classification. The best supported models included those measures indicative of disturbed forest, especially more open canopies found in logged forests, and included natural edge habitats along water courses. These forest types are more productive than mature forests and presumably host more prey for coyotes. A second model with only variables that could be mapped across the region highlighted the lower density of coyotes in areas with high human settlement, as well as positive relationships with variables such as snowfall and lakes that may relate to increased numbers and vulnerability of deer. The resulting map predicts coyote density to be highest along the southwestern edge of the Adirondack State Park, including Tug Hill, and lowest in the mature forests and more rural areas of the central and eastern Adirondacks. Together, these results support the need for a nuanced view of how eastern coyotes use forested habitats.