| 1. |
- Arnqvist, Per, et al.
(författare)
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Functional clustering of varved lake sediment to reconstruct past seasonal climate
- 2016
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Ingår i: Environmental and Ecological Statistics. - : Springer. - 1352-8505 .- 1573-3009. ; 23:4, s. 513-529
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Tidskriftsartikel (refereegranskat)abstract
- Annually laminated (varved) lake sediments constitutes excellent environmental archives, and have the potential to play an important role for understanding past seasonal climate with their inherent annual time resolution and within-year seasonal patterns. We propose to use functional data analysis methods to extract the relevant information with respect to climate reconstruction from the rich but complex information in the varves, including the shapes of the seasonal patterns, the varying varve thickness, and the non-linear sediment accumulation rates. In particular we analyze varved sediment from lake Kassjon in northern Sweden, covering the past 6400 years. The properties of each varve reflect to a large extent weather conditions and internal biological processes in the lake the year that the varve was deposited. Functional clustering is used to group the seasonal patterns into different types, that can be associated with different weather conditions. The seasonal patterns were described by penalized splines and clustered by the k-means algorithm, after alignment. The observed (within-year) variability in the data was used to determine the degree of smoothing for the penalized spline approximations. The resulting clusters and their time dynamics show great potential for seasonal climate interpretation, in particular for winter climate changes.
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| 2. |
- Baey, Charlotte, et al.
(författare)
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A model to account for data dependency when estimating floral cover in different land use types over a season
- 2017
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 24:4, s. 505-527
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Tidskriftsartikel (refereegranskat)abstract
- We propose a model to consider data dependencies and assess spatial and temporal variability in land use specific floral coverage across landscapes. Data dependence arising from repeated measurements across the flowering season is taken into account using hierarchical Archimedean copulas, where the correlation is assumed to be stronger within seasonal periods than between periods. For each seasonal period, a bounded probability distribution is assigned to capture spatial variability in floral cover. The model uses a Bayesian approach and can assess land-use-specific floral covers by integrating experts judgments and field data. The model is applied to assess floral covers in four land use types in southern Sweden, where seasonal variability is captured by dividing the season into two periods according to winter oilseed rape flowering. Floral cover is updated using Markov Chain Monte Carlo sampling based on data from 16 landscapes and 2 years, with repeated measures available from each of the two seasonal periods. Our results indicate that considering data dependence improved the estimation of floral cover based on data observed during a season. Different copula families specifying multivariate probability distributions were tested, and no family had a consistently higher performance in the four tested land use types. Uncertainty in both mode and variability of floral cover was higher when data dependence were accounted for. Posterior modes of floral covers in semi-natural grassland were higher than in field edges, but both expert’s best guesses were higher than these estimates. This confirms previous findings in expert elicitation processes that experts may fail to discriminate extreme values on a bounded range. Floral cover in flower strips were estimated to be smaller/higher than semi-natural grasslands early/late in the season. The mode of floral cover in oil seed rape was estimated to be close to 100%, and higher than estimates provided by expert judgment. Floral covers for different land use classes are key parameters when quantifying floral resources at a landscape level whose assessments rely on both expert judgment and field measurements.
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| 3. |
- Hedström Ringvall, Anna, et al.
(författare)
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Conditioning post-stratified inference following two-stage, equal-probability sampling
- 2016
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 23, s. 141-154
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Tidskriftsartikel (refereegranskat)abstract
- This paper considers conditioning on the size of the samples observed in post-strata following a two-stage sampling design. We argue that it is reasonable to do so despite the complexity of the design. We derive an expression for the covariances among post-strata estimates resulting from secondary sampling units on the same primary sampling unit which reside in different post-strata. To motivate both issues we describe a two-stage LiDAR-assisted sample for aboveground biomass that was reported in Gregoire et al. (Can J For Res 41: 83-95, 2011).
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| 4. |
- Holm, Sören, et al.
(författare)
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A distance dependent contagion function for vector-based data
- 2012
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 19, s. 161-181
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Tidskriftsartikel (refereegranskat)abstract
- Landscape pattern is of primary interest to landscape ecologists and landscape metrics are used to quantify landscape pattern. Metrics are commonly defined and calculated on raster-based land cover maps. One metric is the contagion, existing in several versions, e.g., unconditional and conditional, used as a measure of fragmentation. However, mapped data is sometimes in vector-based format or there may be no mapped data but only a point sample. In this study a definition of contagion for such cases is investigated. The metric is an extension of the usual contagion, based on pairs of points at varying distances and gives a function of the distance. In this study the extended contagion is calculated for vector-based delineated real landscapes and for simulated ones. Both unconditional and conditional contagions are studied using two classification systems. The unconditional contagion function was decreasing and convex, with upper and lower limits highly correlated to the Shannon diversity index, thus carrying only area proportion information. The spatial information lies in the speed by which the function converges to the lower limit; using a proxy function this can be expressed by a single parameter b, with high values for fragmented landscapes. No proxy function was found for the conditional contagion, for which only qualitative information was found. The extended contagion is applicable both in patch mosaic models of landscapes and in gradient-based models, where landscape characteristics change continuously without distinct borders between patches. The extended contagion can be useful in sample based surveys where there no map of the entire landscape is available.
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| 5. |
- Knape, Jonas
(författare)
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Effects of choice of baseline on the uncertainty of population and biodiversity indices
- 2023
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 30, s. 1-16
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Tidskriftsartikel (refereegranskat)abstract
- Many monitoring programs provide annual indices of relative change over time in some quantitative measure of ecological status, such as population abundance or species richness. These indices are usually scaled relative to a reference year so that they represent change in ecological status compared to this particular year. An issue with this approach is that uncertainty about ecological status in the reference year can propagate into large uncertainty in all other index values. Taking instead the mean of the ecological status over several years as the reference-a reference period-may reduce uncertainty in indices. At present, this approach is not commonly used in practice. I quantitatively evaluate how the choice of reference period affects the uncertainty of two variants of population indices, either estimated independently each year or smoothed over several years, for 100 bird species using monitoring data. Short reference periods containing years early in the series lead to reduced uncertainty in independently estimated index values, but not in smoothed indices, compared to when using a single reference year. When a long reference period was used, uncertainty was substantially reduced for independently estimated annual indices in particular, but also for smoothed indices. An exception to the reduction in uncertainty with the length of the reference period was found when indices are constrained to be log-linear. Given an appropriate model and indices that are not strictly log-linear, using smoothing and/or reference the periods can be useful ways of reducing irrelevant uncertainty in the presentation of indices.
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| 6. |
- Knape, Jonas, et al.
(författare)
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Multivariate state space modelling of bird migration count data
- 2009
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Ingår i: Environmental and Ecological Statistics. - Berlin : Springer. - 1352-8505 .- 1573-3009. ; 3:1, s. 59-79
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Tidskriftsartikel (refereegranskat)abstract
- We analyse 54 year long time series data on the numbers of common redstart (Phoenicurus phoenicurus), common whitethroat (Sylvia communis), garden warbler (Sylvia borin) and lesser whitethroat (Sylvia curruca) trapped in spring and autumn at Ottenby Bird Observatory, Sweden. The Ottenby time series could potentially serve as a reference on how much information on population change is available in count data on migrating birds. To investigate this, we combine spring and autumn data in a Bayesian state-space model trying to separate demographic signals and observation noise. The spring data are assumed to be a measure of the breeding population size, whereas the autumn data measure the population size after reproduction. At the demographic level we include seasonal density dependence and model winter dynamics as a function of precipitation in the Sahel region, south of the Sahara desert, where these species are known to spend the winter. Results show that the large fluctuations in the data restrict what conclusions can be drawn about the dynamics of the species. Annual catches are highly correlated between species and we show that a likely explanation for this is that trapping numbers are strongly dependent on local weather conditions. A comparative analysis of a related data set from the Courish Spit, Russia, gives rather different dynamics which may be caused by low information in the two data sets, but also by distinct populations passing Ottenby and the Courish Spit. This highlights the difficulty of validating results of the analyses when abundance indices derived by other methods or from other populations do not agree.
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| 7. |
- Kuhlmann-Berenzon, S., et al.
(författare)
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Accounting for large-scale factors in the study of understory vegetation using a conditional logistic model
- 2007
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 14:2, s. 149-159
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Tidskriftsartikel (refereegranskat)abstract
- Local-scale and large-scale factors can affect the presence of a species of understory vegetation in the forest. Local-scale factors may be the influence of surrounding trees, while climate and latitude are typically considered large-scale factors. A model for the presence of a species needs to take into account both scales. A conditional logistic model is proposed for those studies where only the local-scale factors are of interest and that avoids estimating the large-scale parameters. Conditioning is carried out by the number of quadrats in the plot where the vegetation is found. As the latter is a sufficient statistic for the large-scale factors, a model free from these parameters is obtained. Data gathered in the permanent sample plots of the 1985-1986 National Forest Inventory of Finland is used for illustration, where the local-scale factor of interest is the influence of the trees, quantified by an index based on the size and location of the trees. The model fitted to Vaccinium vitis-idaea showed a significant and positive influence of Scots pine on the presence of this species, while for Calamagrostis arundinacea, a decrease in the odds ratio was observed due to the influence of Norway spruce.
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| 8. |
- Kuronen, M., et al.
(författare)
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Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests
- 2022
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 29:1, s. 185-205
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Tidskriftsartikel (refereegranskat)abstract
- We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to investigate the effect of large trees on the locations of seedlings. In the model, every point in x has a parametric influence kernel or signal, which together form an influence field. Conditionally on the parameters, the influence field acts as a spatial covariate in the intensity of the model, and the intensity itself is a non-linear function of the parameters. Points outside the observationwindowmay affect the influence field inside the window. We propose an edge correction to account for this missing data. The parameters of the model are estimated in a Bayesian framework using Markov chain Monte Carlo where a Laplace approximation is used for the Gaussian field of the LGCP model. The proposed model is used to analyze the effect of large trees on the success of regeneration in uneven-aged forest stands in Finland.
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| 9. |
- Lehsten, Veiko, et al.
(författare)
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Fourth-corner generation of plant functional response groups
- 2009
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 16:4, s. 561-584
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Tidskriftsartikel (refereegranskat)abstract
- Plant functional response groups (PFGs) are now widely established as a tool to investigate plant-environment relationships. Different statistical methods to form PFGs are used in the literature. One way is to derive emergent groups by classifying species based on correlation of biological attributes and subjecting these groups to tests of response to environmental variables. Another way is to search for associations of occurrence data, environmental variables and trait data simultaneously. The fourth-corner method is one way to assess the relationships between single traits and habitat factors. We extended this statistical method to a generally applicable procedure for the generation of plant functional response groups by developing new randomization procedures for presence/absence data of plant communities. Previous PFG groupings used either predefined groups or emergent groups i.e. classifications based on correlations of biological attributes (Lavorel et al Trends Ecol Evol 12:474-478, 1997), of the global species pool and assessed their functional response. However, since not all PFGs might form emergent groups or may be known by experts, we used a permutation procedure to optimise functional grouping. We tested the method using an artificial test data set of virtual plants occurring in different disturbance treatments. Direct trait-treatment relationships as well as more complex associations are incorporated in the test data. Trait combinations responding to environmental variables could be clearly distinguished from non-responding combinations. The results are compared with the method suggested by Pillar (J Veg Sci 10:631-640) for the identification of plant functional groups. After exploring the statistical properties using an artificial data set, the method is applied to experimental data of a greenhouse experiment on the assemblage of plant communities. Four plant functional response groups are formed with regard to differences in soil fertility on the basis of the traits canopy height and spacer length.
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| 10. |
- Lindström, Johan, et al.
(författare)
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A flexible spatio-temporal model for air pollution with spatial and spatio-temporal covariates
- 2014
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 21:3, s. 411-433
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Tidskriftsartikel (refereegranskat)abstract
- The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system covariates. The model presented in this paper has been implemented in an R package, SpatioTemporal, available on CRAN. The model is used by the EPA funded Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) to produce estimates of ambient air pollution; MESA Air uses the estimates to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. In this paper we use the model to predict long-term average concentrations of in the Los Angeles area during a 10 year period. Predictions are based on measurements from the EPA Air Quality System, MESA Air specific monitoring, and output from a source dispersion model for traffic related air pollution (Caline3QHCR). Accuracy in predicting long-term average concentrations is evaluated using an elaborate cross-validation setup that accounts for a sparse spatio-temporal sampling pattern in the data, and adjusts for temporal effects. The predictive ability of the model is good with cross-validated of approximately at subject sites. Replacing four geographic covariate indicators of traffic density with the Caline3QHCR dispersion model output resulted in very similar prediction accuracy from a more parsimonious and more interpretable model. Adding traffic-related geographic covariates to the model that included Caline3QHCR did not further improve the prediction accuracy.
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| 11. |
- Ramezani, Habib, et al.
(författare)
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Estimating a distance dependent contagion function using point sample data
- 2014
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 21, s. 61-82
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Tidskriftsartikel (refereegranskat)abstract
- Natural events and human activities cause changes in landscape structure. Landscape metrics are used as a useful tool to study landscape trends and ecological processes related to the landscape structure. These metrics are commonly calculated on wall-to-wall raster data from remote sensing. A recent trend is to use sample data to estimate landscape metrics. In this study, point sampling was used to estimate a vector-based and distance dependent contagion metric. The metric is an extension of the established contagion. The statistical properties, for both unconditional and conditional contagions, were assessed by a point (point pairs) sampling experiment in maps from the National Inventory of landscapes in Sweden. Random and systematic sampling designs were tested for nine point distances and five sample sizes and for two classification systems.The systematic design showed slightly smaller root mean square error (RMSE) and bias than the random design. Both true and estimated values were calculated using computer programs in FORTRAN, which was specifically written for the purpose of the study. For a given sample size, RMSE and bias increased with increasing point distance. The estimator of unconditional contagion had acceptable RMSE and bias for moderate sample sizes, but in the conditional case the bias (and thus the RMSE) was unacceptably large. The main reason for this is that small classes (by area) affect both the true value of the contagion and are often missing in the sample. The method proposed can be adopted in gradient-based model of landscape structure where no distinct border is assumed between polygons. The method can also be applied in field-based inventories.
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| 12. |
- Ramezani, Habib, et al.
(författare)
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Sample based estimation of landscape metrics; accuracy of line intersect sampling for estimating edge density and Shannon's diversity index
- 2011
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 18, s. 109-130
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Tidskriftsartikel (refereegranskat)abstract
- A recent trend is to estimate landscape metrics using sample data and cost-efficiency is one important reason for this development. In this study, line intersect sampling (LIS) was used as an alternative to wall-to-wall mapping for estimating Shannon's diversity index and edge length and density. Monte Carlo simulation was applied to study the statistical performance of the estimators. All combinations of two sampling designs (random and systematic distribution of transects), four sample sizes, five transect configurations (straight line, L, Y, triangle, and quadrat), two transect orientations (fixed and random), and three configuration lengths were tested, each with a large number of simulations. Reference was 50 photos of size 1 km(2), already manually delineated in vector format by photo interpreters using GIS environment. The performance was compared by root mean square error (RMSE) and bias. The best combination for all three metrics was found to be the systematic design and as response design the straight line configuration with random orientation of transects, with little difference between the fixed and random orientation of transects. The rate of decrease of RMSE for increasing sample size and line length was studied with a mixed linear model. It was found that the RMSE decreased to a larger degree with the systematic design than the random one, especially with increasing sample size. Due to the nonlinearity in the definition of Shannon diversity estimator its estimator has a small and negative bias, decreasing with sample size and line length. Finally, a time study was conducted, measuring the time for registration of line intersections and their lengths on non-delineated aerial photos. The time study showed that long sampling lines were more cost-efficient than short ones for photo-interpretation.
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| 13. |
- Rydén, Jesper
(författare)
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Exploring possibly increasing trend of hurricane activity by a SiZer approach
- 2010
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Ingår i: Environmental and Ecological Statistics. - : Springer Science and Business Media LLC. - 1352-8505 .- 1573-3009. ; 17:1, s. 125-132
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Tidskriftsartikel (refereegranskat)abstract
- Statistical studies of hurricane activity in the North Atlantic basin are of current interest, not the least after the year of 2005 when many records were broken. An exploratory analysis of possibly increasing trend of the yearly number of hurricanes can be carried out by employing a graphic device, the SiZer map. Use of this method provides a useful complement to other statistical techniques for detection of trends or shifts in time series.
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| 14. |
- Møller-Olsen, Astrid
(författare)
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The City is a Journey : Heritage and Memory in Zhu Tianxin’s Novella ‘The Old Capital’
- 2021
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Ingår i: International Journal of Heritage Studies. - : Informa UK Limited. - 1470-3610 .- 1352-7258. ; 27:8, s. 819-829
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Tidskriftsartikel (refereegranskat)abstract
- Zhu Tianxin’s novella The Old Capital narrates the process of slowly losing contact with the past through forgetting, loss and material erasure. Instead of completely eradicating the past, this process prompts a renewed interest, and, in a sense, a renewed presence of that past in conscious remembering, literary evocation and narrative attendance. Inspired by David Crouch’s conception of heritage as a journey, this paper looks at how the protagonist’s physical and mental voyage in The Old Capital incorporates several spatiotemporal layers of cultural heritage to help her – and the reader - understand the complexity of the living historical city of Taipei.
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