Correct testing of mark independence for marked point patterns

Grabarnik, Pavel; Myllymäki, Mari; Stoyan, Dietrich

doi:10.1016/j.ecolmodel.2011.10.005

Cited by 80 publications

(86 citation statements)

References 17 publications

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“…If the rank of u 0 is larger than 190, there is a significant departure from the null model with a ¼ 0.05 over the scales of interest (e.g., 1-150 m). Details about the GoF test can be found in Loosmore and Ford (2006), and Grabarnik et al (2011).…”

Section: Aggregation Of Mammal Feces At a Range Of Spatial Scalesmentioning

confidence: 99%

Hierarchical mechanisms of spatially contagious seed dispersal in complex seed‐disperser networks

Fedriani¹,

Wiegand²

2014

Ecology

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Abstract. Intra-and interspecific spatially contagious seed dispersal has far-reaching implications for plant recruitment, distribution, and community assemblage. However, logistical and analytical limitations have curtailed our understanding concerning the mechanisms and resulting spatial patterns of contagious seed dispersal in most systems and, especially, in complex seed-disperser networks. We investigated mechanisms of seed aggregation using techniques of spatial point pattern analysis and extensive data sets on mutispecific endozoochorous seed rain generated by five frugivorous mammals in three Mediterranean shrublands over two seasons. Our novel analytical approach revealed three hierarchical and complementary mechanisms of seed aggregation acting at different levels (fecal samples, seeds, pairs of seed species) and spatial scales. First, the three local guilds of frugivores tended to deliver their feces highly aggregated at small and intermediate spatial scales, and the overall pattern of fecal delivery could be described well by a nested doublecluster Thomas process. Second, once the strong observed fecal aggregation was accounted for, the distribution of mammal feces containing seeds was clustered within the pattern of all feces (i.e., with and without seeds), and the density of fecal samples containing seeds was higher than expected around other feces containing seeds in two out of the three studied seeddisperser networks. Finally, at a finer level, mark correlation analyses revealed that for some plant species pairs, the number of dispersed seeds was positively associated either at small or large spatial scales. Despite the relatively invariant patterning of nested double-clustering, some attributes of endozoochorous seed rain (e.g., intensity, scales of aggregation) were variable among study sites due to changes in the ecological context in which seeds and their dispersers interact. Our investigation disentangles for the first time the hierarchy of synergic mechanisms of spatially contagious seed dispersal at a range of spatial scales in complex seeddisperser networks, thus providing a robust and widely applicable framework for future studies.

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Section: Aggregation Of Mammal Feces At a Range Of Spatial Scalesmentioning

confidence: 99%

Hierarchical mechanisms of spatially contagious seed dispersal in complex seed‐disperser networks

Fedriani¹,

Wiegand²

2014

Ecology

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“…As the testing method uses a statistic with dependent values at different ranges, inflated type I errors may occur (Grabarnik (cm) et al 2011). Accordingly, to adjust the testing for multiple scales, thus avoiding the problem of simultaneous inference, a deviation test (Grabarnik et al 2011) may be adopted. Also, besides classical p-value testing, alternative approaches such as model validation techniques (Ling and Mahadevan 2013) may also be considered.…”

Section: Discussionmentioning

confidence: 99%

“…In addition to the spatial coordinates of individual plants represented by the points, marked point patterns provide information on the properties of each object, like species identity, size, etc. (Grabarnik et al 2011). The method proposed in this paper is thus a generalization of individual-centered analysis (Podani and Czárán 1997), which is in turn the multispecies extension of Ripley's (1981) second-order analysis of point patterns.…”

Section: A Phylogenetic Extension Of Individual-centered Analysismentioning

confidence: 99%

Spatial analysis of phylogenetic community structure: New version of a classical method

et al. 2017

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Abstract. The increasing availability of phylogenetic information facilitates the use of evolutionary methods in community ecology to reveal the importance of evolution in the species assembly process. However, while several methods have been applied to a wide range of communities across different spatial scales with the purpose of detecting non-random phylogenetic patterns, the spatial aspects of phylogenetic community structure have received far less attention. Accordingly, the question for this study is: can point pattern analysis be used for revealing the phylogenetic structure of multi-species assemblages? We introduce a new individual-centered procedure for analyzing the scale-dependent phylogenetic structure of multi-species point patterns based on digitized field data. The method uses nested circular plots with increasing radii drawn around each individual plant and calculates the mean phylogenetic distance between the focal individual and all individuals located in the circular ring delimited by two successive radii. This scale-dependent value is then averaged over all individuals of the same species and the observed mean is compared to a null expectation with permutation procedures. The method detects particular radius values at which the point pattern of a single species exhibits maximum deviation from the expectation towards either phylogenetic aggregation or segregation. Its performance is illustrated using data from a grassland community in Hungary and simulated point patterns. The proposed method can be extended to virtually any distance function for species pairs, such as functional distances. Nomenclature: Simon (1992).Abbreviation: MPD -Mean Phylogenetic Distance. 38Ricotta et al.community tests captured much of the same filtering patterns detected by trait-based methods.

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“…Each of the simulated patterns was the used to compute the empirical non homogeneous K-function to obtain the envelopes. We used the rank test (Grabarnik et al, 2011) to compute the 95% envelopes to get a better approximation to the true p-value for the test. To fit the models we used the R free software (R Development Core Team, 2010), and the contributed package spatstat (Baddeley and Turner, 2000 and 2005), which can be obtained from the R project website www.r-project.org.…”

Section: Discussionmentioning

confidence: 99%

Spatial point process modeling applied to the assessment of risk factors associated with forest wildfires incidence in Castellón, Spain

et al. 2016

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During the last decades the mediterranean zone in Europe has experienced an increment in the incidence of forest wildfires. This increase is partly explained by higher mean temperature and lower relative humidity, whilst socio-economic change has lead to the abandonment of farms, resulting in an increase in an unusual accumulation of forest fuels, increasing the risk of wildfires. Mapping wildfire risk is highly important because wildfires are known to potentially lead to landscape changes and to modify fire regime by inducing potential changes in vegetation composition. Also, they pose a hazard to human property and life. Maps of wildfire risk based on statistical models are provide a measure of uncertainty for the inferences derived from such risk maps, leaving a quantitative error margin for managers and decision takers. Further, some of the model parameters often have a physical or a biological interpretation which can give ecologists and forest engineers answers In this paper we analyze the incidence of wildfires in the province of Castellón, in Spain in order to identify risk factors associated to wildfire incidences during the years [2001][2002][2003][2004][2005][2006]. We used the discrete nature of wildfire events to build such models using point process theory and methods and included information about elevation, slope, aspect, land use and distance to nearest road as covariates in our modeling process. Our results show that wildfire risk in Castellón is associated to all the covariates considered, and that three land use categories have the highest risk of wildfire incidence. Also,wildfire incidences are not independent and some degree of interaction exists, which indicates that the commonly used Poisson point process models are not applicable in this case, but instead Area-Interaction models should be considered.

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Correct testing of mark independence for marked point patterns

Cited by 80 publications

References 17 publications

Hierarchical mechanisms of spatially contagious seed dispersal in complex seed‐disperser networks

Hierarchical mechanisms of spatially contagious seed dispersal in complex seed‐disperser networks

Spatial analysis of phylogenetic community structure: New version of a classical method

Spatial point process modeling applied to the assessment of risk factors associated with forest wildfires incidence in Castellón, Spain

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