Spatially-balanced sampling versus unbalanced stratified sampling for assessing forest change: evidences in favour of spatial balance

Large-scale remote sensing-based inventories of forest cover are usually carried out by combining unsupervised classifications of satellite pixels into forest/non forest classes (map data) with subsequent time-consuming visual on-screen imagery classification of a probabilistic sample of pixels taken as the ground truth (reference data). In this paper the estimation of forest change from a sample of reference data is approached by: (i) exploiting map data to construct strata in which changes are occurred, and then adopting the stratified sampling joined with the HT estimator with most sampling effort devoted to strata where changes are occurred irrespective of their size, as suggested in most remote sensing literature regarding land change assessments; (ii) adopting a spatial scheme ensuring spatially balanced samples, as suggested in most recent statistical literature regarding spatial surveys, and exploiting the map data in the difference estimator. The results of a comparison performed on an artificial population of reference data generated from a real population of map data recorded in Sardinia (Italy) discourage the use of unbalanced stratified samples that achieve the worst precision. The best results are obtained by means of spatially balanced samples or stratification with nearly proportional allocation to strata.     

Estimating wild boar density in hunting areas by a probabilistic sampling of drive counts

Environmental and Ecological Statistics - The evaluation of wild boar density in a hunting district can be performed by accurate drive counts of boars within the drive areas assigned to each...     

Species abundance estimation using point-to-plant sampling in a design-based setting

A new species abundance estimator is proposed when point-to-plant sampling is adopted in a design-based framework. The method is based on the relationship between each species abundance and the probability density function of the relative squared point-to-plant distance. Using this result, a kernel estimator for species abundance is provided and the nearest neighbor method is suggested for bandwidth selection. The proposed estimator requires no assumptions about the species point patterns nor corrections for sampling near the edges of the study region. Moreover, the estimator shows suitable statistical properties as well as good practical performance as is shown in a simulation study.     

Estimating abundance of killer whales in the nearshore waters of the Gulf of Alaska and Aleutian Islands using line-transect sampling

Killer whale (Orcinus orca Linnaeus, 1758) abundance in the North Pacific is known only for a few populations for which extensive longitudinal data are available, with little quantitative data from more remote regions. Line-transect ship surveys were conducted in July and August of 2001–2003 in coastal waters of the western Gulf of Alaska and the Aleutian Islands. Conventional and Multiple Covariate Distance Sampling methods were used to estimate the abundance of different killer whale ecotypes, which were distinguished based upon morphological and genetic data. Abundance was calculated separately for two data sets that differed in the method by which killer whale group size data were obtained. Initial group size (IGS) data corresponded to estimates of group size at the time of first sighting, and post-encounter group size (PEGS) corresponded to estimates made after closely approaching sighted groups. ‘Resident’-type (fish-eating) killer whales were more abundant than the ‘transient’-type (mammal-eating). Abundance estimates of resident killer whales (991 [95% CI = 379–2,585] [IGS] and 1,587 [95% CI = 608–4,140] [PEGS]), were at least four times greater than those of the transient killer whales (200 [95% CI = 81–488] [IGS] and 251 [95% CI = 97–644] whales [PEGS]). The IGS estimate of abundance is preferred for resident killer whales because the estimate based on PEGS data may show an upward bias. The PEGS estimate of abundance is likely more accurate for transients. Residents were most abundant near Kodiak Island in the northern Gulf of Alaska, around Umnak and Unalaska Islands in the eastern Aleutians, and in Seguam Pass in the central Aleutians. This ecotype was not observed between 156 and 164°W, south of the Alaska Peninsula. In contrast, transient killer whale sightings were found at higher densities south of the Alaska Peninsula between the Shumagin Islands and the eastern Aleutians. Only two sightings of ‘offshore’-type killer whales were recorded during the surveys, one northeast of Unalaska Island and the other south of Kodiak Island. These are the first estimates of abundance of killer whale ecotypes in the Aleutian Islands and Alaska Peninsula area and provide a baseline for quantifying the role of these top predators in their ecosystem. Electronic Supplementary Material  Supplementary material is available in the online version of this article at and is accessible for authorized users.

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Estimating behavioral parameters in animal movement models using a state-augmented particle filter

Data on fine-scale animal movement are being collected worldwide, with the number of species being tagged and the resolution of data rapidly increasing. In this study, a general methodology is proposed to understand the patterns in these high-resolution movement time series that relate to marine animal behavior. The approach is illustrated with dive data from a northern fur seal (Callorhinus ursinus) tagged on the Pribilof Islands, Alaska, USA. We apply a state-space model composed of a movement model and corresponding high-resolution vertical movement data. The central goal is to estimate parameters of this movement model, particularly their variation on appropriate time scales, thereby providing a direct link to behavior. A particle filter with state augmentation is used to jointly estimate the movement parameters and the state. A multiple iterated filter using overlapping data segments is implemented to match the parameter time scale with the behavioral inference. The time variation in the auto-covariance function facilitates identification of a movement model, allows separation of observation and process noise, and provides for validation of results. The analysis yields fitted parameters that show distinct time-evolving changes in fur seal behavior over time, matching well what is observed in the original data set.     

Testing for a change in diet using fatty acid signatures

Determining whether the diet of predators has changed is an important ecological problem and appropriate methodology is needed in order to test for differences or changes in diet. It is known that the fatty acid (FA) signature in a predator’s adipose tissue predictably reflects the prey consumed and that, consequently, a change in the FA signatures can be largely attributed to changes in the predator’s diet composition. The use of FA signatures as a means of detecting change in diet presents some statistical challenges however, since the FA signatures are compositional and sample sizes relative to the dimension of a signature are often small due to biological constraints. Furthermore, the FA signatures often contain zeros precluding the direct use of traditional compositional data analysis methods. In this paper, we provide the methodology to carry out valid statistical tests for detecting changes in FA signatures and we illustrate both independent and paired cases using simulation studies and real life seabird and seal data. We conclude that the statistical challenges using FA data are overcome through the use of nonparametric tests applied to the multivariate setting with suitable test statistics capable of handling the zeros that are present in the data.     

Numerical simulations of intrusive gravity currents interacting with a bottom-mounted obstacle in a continuously stratified ambient

In this study, the flow dynamics of intrusive gravity currents past a bottom-mounted obstacle were investigated using highly resolved numerical simulations. The propagation dynamics of a classic intrusive gravity current was first simulated in order to validate the numerical model with previous laboratory experiments. A bottom-mounted obstacle with a varying non-dimensional height of \(\tilde{D}=D/H\), where D is the obstacle height and H is the total flow depth, was then added to the problem in order to study the downstream flow pattern of the intrusive gravity current. For short obstacles, the intrusion re-established itself downstream without much distortion. However, for tall obstacles, the downstream flow was found to be a joint effect of horizontal advection, overshoot-springback phenomenon, and associated Kelvin-Helmholtz instabilities. Analysis of the numerical results show that the relationship between the downstream propagation speed and the obstacle height can be subdivided into three regimes: (1) a retarding regime (\(\tilde{D}\) \(\approx \) 0–0.3) where a 30 % increase in obstacle height leads to a 20 % reduction in propagation speed, simply due to the obstacle’s retarding effect; (2) an impounding regime (\(\tilde{D}\) \(\approx \) 0.3–0.6) where the additional 30 % increase in obstacle height only leads to a further (negligible) 5 % reduction in propagation speed, due to the accelerating effect of upstream impoundment and downstream enhanced mixing; and (3) a choking regime (\(\tilde{D}\) \(\approx \) 0.6–1.0) where the propagation speed is dramatically reduced due to the dominance of the obstacle’s blocking effect. The obstacle thickness was found to be irrelevant in determining the downstream propagation speed at least for the parameter range explored in this study. The present work highlights the significance of topographic effects in stratified flows with horizontal pressure forcing.     

Estimating the population size with a behavioral response in capture-recapture experiment

A new estimating procedure is suggested to estimate the population size in a capture-recapture experiment. The capture intensities for first-capture and recapture are allowed to be different and time dependent but they are assumed to be proportional. It is shown that the information on the proportionality constant is crucial to the estimation of the population size. Sensitivity analysis with a misspecification of the proportionality constant is conducted. The method has also been extended to the case with an unknown proportionality. A real example is given.     

Estimating Population Size in a Continuous-time Removal Experiment with a Known Sub-population Size Ratio

We study a continuous-time removal model for estimating the population size for a population in which a sub-population size ratio is known. The maximum likelihood estimate and the optimal martingale estimate of the population size are obtained; these are shown to be equivalent. A comparison between the proposed estimator and the maximum likelihood estimate which ignores the information on the known size ratio is made, using a simulation study. The asymptotic variances of these two estimators are also obtained, and a comparison between them is made. The sensitivity of mis-specification of the known size ratio is examined. We also apply the corresponding discrete-time model to the proposed continuous-time setting, and study the efficiency of the corresponding discrete-time type estimator relative to the proposed estimator.     

An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions

Although forest landscape models (FLMs) have benefited greatly from ongoing advances of computer technology and software engineering, computing capacity remains a bottleneck in the design and development of FLMs. Computer memory overhead and run time efficiency are primary limiting factors when applying forest landscape models to simulate large landscapes with fine spatial resolutions and great vegetation detail. We introduce LANDIS PRO 6.0, a landscape model that simulates forest succession and disturbances on a wide range of spatial and temporal scales. LANDIS PRO 6.0 improves on existing forest landscape models with two new data structures and algorithms (hash table and run-length compression). The innovative computer design enables LANDIS PRO 6.0 to simulate very large (>10⁸ ha) landscapes with a 30-m spatial resolution, which to our knowledge no other raster forest landscape models can do. We demonstrate model behavior and performance through application to five nested forest landscapes with varying sizes (from 1 million to 100 million 0.09-ha cells) in the southern Missouri Ozarks. The simulation results showed significant and variable effects of changing spatial extent on simulated forest succession patterns. Results highlighted the utility of a model like LANDIS PRO 6.0 that is capable of efficiently simulating large landscapes and scaling up forest landscape processes to a common regional scale of analysis. The programming methodology presented here may significantly advance the development of next generation of forest landscape models.     

Estimating growth charts via nonparametric quantile regression: a practical framework with application in ecology

We discuss a practical and effective framework to estimate reference growth charts via regression quantiles. Inequality constraints are used to ensure both monotonicity and non-crossing of the estimated quantile curves and penalized splines are employed to model the nonlinear growth patterns with respect to age. A companion R package is presented and relevant code discussed to favour spreading and application of the proposed methods.     

Estimating digestion time in gelatinous predators: a methodological comparison with the scyphomedusa Aurelia aurita

In order to quantify the trophic impact of gelatinous predators, digestion time estimates are commonly applied to counts of prey in the guts. Three primary approaches are used, the Manual-feeding, Natural-feeding and Steady-state methods; these differ in methodology and their underlying assumptions. The criteria used to define the end-point of digestion, and the resolution at which digestion progress is observed, also vary across studies. To understand the impact of such differences, we estimate digestion times of the scyphomedusa Aurelia aurita fed adult females of the copepod Acartia tonsa using these various approaches. We find ~fourfold differences which can be attributed to bias towards the slowest rates of digestion by some end-point criteria, and overestimation from low observation resolution. Artificial manipulation and the degree to which swimming and feeding behaviour are natural may also influence estimates. We provide recommendations for those quantifying digestion times of Aurelia aurita medusae and gelatinous predators.     

Estimating Plecoglossus altivelis altivelis migration using a mass balance model expressed by hydrological distribution parameters in a major limpid river basin in Japan

We examined the influence of several hydrological and meteorological parameters on the migratory movements of ayu Plecoglossus altivelis altivelis in central Japan. When comprehensively evaluating rivers and ayu behaviour on a catchment scale, the subjects of analysis typically include human activities and hydrological and meteorological phenomena. However, limiting analyses to such factors may be too restrictive when human activities are being conducted. Accordingly, we incorporated a biological viewpoint into the evaluation method, analysing hydrological data (river discharge, river water temperature, sea water temperature) to determine watershed characteristics and examining the relationship between these characteristics and the habitat conditions of ayu. Then we constructed a numerical model for ayu migratory runs that incorporated ayu ecology and watershed characteristics. Analyses of ayu movements from a lower estuarine dam demonstrated that downstream displacements were associated with high water flows of more than 200 m³ s⁻¹ at the beginning of summer. We conclude that it is important to consider the effects of environmental parameters on the movements of different fish species to understand the causes of spatial variation in fish distribution in lowland rivers.     

Uncertainty analysis of climate change mitigation options in the forestry sector using a generic carbon budget model

Industrialized countries agreed on a reduction of greenhouse gas emissions under the Kyoto Protocol. Many countries elected forest management activities and the resulting net balance of carbon emissions and removals of non-CO₂ greenhouse gases by forest management in their climate change mitigation measures. In this paper a generic dynamic forestry model (FORMICA) is presented. It has an empirical basis. Several modules trace C pools relevant for the Kyoto Protocol and beyond: biomass, litter, deadwood and soil, and harvested wood products. The model also accounts for the substitution of fossil fuels by wood products and bioenergy.     

External drift kriging of NOx concentrations with dispersion model output in a reduced air quality monitoring network

In the mid nineteen eighties the Dutch NO_x air quality monitoring network was reduced from 73 to 32 rural and city background stations, leading to higher spatial uncertainties. In this study, several other sources of information are being used to help reduce uncertainties in parameter estimation and spatial mapping. For parameter estimation, we used Bayesian inference. For mapping, we used kriging with external drift (KED) including secondary information from a dispersion model. The methods were applied to atmospheric NO_x concentrations on rural and urban scales. We compared Bayesian estimation with restricted maximum likelihood estimation and KED with universal kriging. As a reference we also included ordinary least squares (OLS). Comparison of several parameter estimation and spatial interpolation methods was done by cross-validation. Bayesian analysis resulted in an error reduction of 10 to 20% as compared to restricted maximum likelihood, whereas KED resulted in an error reduction of 50% as compared to universal kriging. Where observations were sparse, the predictions were substantially improved by inclusion of the dispersion model output and by using available prior information. No major improvement was observed as compared to OLS, the cause presumably being that much good information is contained in the dispersion model output, so that no additional spatial residual random field is required to explain the data. In all, we conclude that reduction in the monitoring network could be compensated by modern geostatistical methods, and that a traditional simple statistical model is of an almost equal quality.

Linking species- and ecosystem-level impacts of climate change in lakes with a complex and a minimal model

To study the interaction between species- and ecosystem-level impacts of climate change, we focus on the question of how climate-induced shifts in key species affect the positive feedback loops that lock shallow lakes either in a transparent, macrophyte-dominated state or, alternatively, in a turbid, phytoplankton-dominated state. We hypothesize that climate warming will weaken the resilience of the macrophyte-dominated clear state. For the turbid state, we hypothesize that climate warming and climate-induced eutrophication will increase the dominance of cyanobacteria. Climate change will also affect shallow lakes through a changing hydrology and through climate change-induced eutrophication. We study these phenomena using two models, the full ecosystem model PCLake and a minimal dynamic model of lake phosphorus dynamics. Quantitative predictions with the complex model show that changes in nutrient loading, hydraulic loading and climate warming can all lead to shifts in ecosystem state. The minimal model helped in interpreting the non-linear behaviour of the complex model. The main output parameters of interest for water quality managers are the critical nutrient loading at which the system will switch from clear to turbid and the much lower critical nutrient loading – due to hysteresis – at which the system switches back. Another important output parameter is the chlorophyll-a level in the turbid state. For each of these three output parameters we performed a sensitivity analysis to further understand the dynamics of the complex model PCLake. This analysis showed that our model results are most sensitive to changes in temperature-dependence of cyanobacteria, planktivorous fish and zooplankton. We argue that by combining models at various levels of complexity and looking at multiple aspects of climate changes simultaneously we can develop an integrated view of the potential impact of climate change on freshwater ecosystems.     

A hydrodynamic and water quality modeling study of spatial and temporal patterns of phytoplankton growth in a stratified lake with buoyant incoming flow

A three-dimensional hydrodynamic and water quality model was applied to Lake Paldang, a lake in South Korea that is stratified by incoming flows. The spatial and temporal patterns of phytoplankton growth in this lake were determined from the model. The model was calibrated and verified using data measured under different hydrological conditions. The model results were in reasonable agreement with the field measurements, in both the calibration and verification phases. The distributions of water quality and residence time in the lake and phytoplankton response to changes in nutrient loads were examined with the model, and the influence of the hydrodynamics on phytoplankton response was analyzed. The simulation results indicated that Lake Paldang is an essentially phosphorus-limited system, but that phytoplankton growth is limited by low water temperature and short residence time during the winter and the summer monsoon period, respectively. The results of sensitivity analyses also suggested that the hydrodynamics within the lake may have an indirect influence on phytoplankton responses to changes in the limiting nutrient loads, and that reducing phosphorus loading from Kyoungan Stream should be a high priority policy for controlling algal blooms during the pre- and post-monsoon periods. From this study, it was concluded that the three-dimensional water quality model incorporating hydrodynamic processes could successfully simulate phytoplankton response to changes in nutrient loads and that it could become a useful tool for identifying the essential factors determining phytoplankton growth and for developing the best management policy for algal blooms in Lake Paldang.     

Preventing behavioural interactions with a male facilitates sex change in female bluebanded gobies, Lythrypnus dalli

Sex change in marine teleost fishes is commonly regulated by social factors. In species that exhibit protogynous sex change, such as the bluebanded goby Lythrypnus dalli, the most dominant female typically initiates sex change when a male is removed from the social group. Females can use visual, chemical or tactile cues to assess the presence or absence of a male. The primary goal of our study was to determine whether the olfactory and visual presence of a male versus its behavioural interactions with females were important for mediating sex change. We exposed females to three different treatments: absence of a male, presence of a male that could physically interact with her and presence of a male behind a barrier that allowed visual and olfactory interactions but prohibited physical interactions. Sex change occurred in the absence of a male but not in the presence of a male that could physically interact with the female. The presence of a male behind the barrier did not prevent sex change but affected the timing of sex change. Season appeared to affect the latency to initiate male typical courtship, with a delay at the end of the reproductive season only when the male was present behind the barrier. We discuss the seasonal results in terms of L. dalli life history and the potential benefits and costs of changing sex late in the season in the presence or absence of aggressive reinforcement by the male. Our results identify direct behavioural interactions as an important proximate mechanism in the social regulation of sex change in L. dalli.     

Impact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas

Global warming impacts the water cycle not only by changing regional precipitation levels and temporal variability, but also by affecting water flows and soil moisture dynamics. In Brandenburg, increasing average annual temperature and decreasing precipitation in summer have already been observed. For this study, past trends and future effects of climate change on soil moisture dynamics in Brandenburg were investigated, considering regional and specific spatial impacts. Special Areas of Conservation (SACs) were focused on in particular. A decreasing trend in soil water content was shown for the past by analyzing simulation results from 1951 to 2003 using the integrated ecohydrological model SWIM [Krysanova, V., Müller-Wohlfeil, D.-I., Becker, A., 1998. Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecol. Model. 106, 261–289]. The trend was statistically significant for some areas, but not for the entire region. Simulated soil water content was particularly low in the extremely dry year 2003. Comparisons of simulated trends in soil moisture dynamics with trends in the average annual Palmer Drought Severity Index for the region showed largely congruent patterns, though the modeled soil moisture trends are characterized by a much higher spatial resolution. Regionally downscaled climate change projections representing the range between wetter and drier realizations were used to evaluate future trends of available soil water. A further decrease of average available soil water ranging from −4% to −15% was projected for all climate realizations up to the middle of the 21st century. An average decrease of more than 25 mm was simulated for 34% of the total area in the dry realization. Available soil water contents in SACs were generally higher and trends in soil moisture dynamics were lower mainly due to their favorable edaphic conditions. Stronger absolute and relative changes in the simulated trends for the past and future were shown for SACs within Brandenburg than for the state as a whole, indicating a high level of risk for many wetland areas. Nonetheless, soil water content in SACs is expected to remain higher than average under climate change conditions as well, and SACs therefore have an important buffer function under the projected climate change. They are thus essential for local climate and water regulation and their status as protected areas in Brandenburg should be preserved.     

Co-pyrolysis of oil sludge with hydrogen-rich plastics in a vertical stirring reactor: Kinetic analysis,emissions, and products

● Collaborative treatment of plastics and OS was established to improve oil quality. ● PE addition successfully improved OS pyrolysis process by deploying H/C_eff ratio. ● Higher H/C_eff ratio promoted cracking to obtain more gas and light oil fractions. ● The degradation of PE and OS was promoted each other under their temperature range. Pyrolysis is an effective method to treat oily sludge (OS) due to its balance between oil recovery and nonhazardous disposal. However, tank bottom OS contains a high content of heavy fractions, which creates obstacles for pyrolysis due to the high activation energy. The incomplete cracking of macromolecules and secondary polymerization decreases the oil quality and causes coking during the operation process. This study introduced polyethylene (PE) into OS to deploy the H/C_eff ratio of feedstocks for pyrolysis. A strong interaction between OS and PE during copyrolysis could be observed from the TG/DTG curves. PE tightly participated in OS degradation, while OS also promoted PE degradation at high temperature. Apparent pits were generated in solid residues from copyrolysis, which was attributed to the uniform and violent gas release. In addition to HCN, other nitrogenous and sulphurous pollutants were inhibited. Accordingly, more gas products were attained after PE addition with more value-added compositions of alkanes and alkenes. Although the oil yield decreased after PE addition, the oil products from copyrolysis possessed higher heating values and higher contents of light fractions with short chains as well as paraffins. Consequently, copyrolysis of OS and PE significantly improved the pyrolysis process and resulted in high oil quality.