108 years of change in spatial pattern following selective harvest of a Pinus ponderosa stand in northern Arizona,USA

Questions: How did an initial tree harvest in 1894 influence the spatial and temporal patterns of Pinus ponderosa recruitment? How do these patterns compare to our understanding of P. ponderosa stand dynamics prior to Euro‐American settlement? How might spatial pattern information, particularly with respect to patch characteristics, inform current restoration and management practices? Location: A 2.59‐ha permanent sample plot in the Fort Valley Experimental Forest, Flagstaff, Arizona. The plot was selectively harvested in 1894 and measured in 1909 and 2002. Methods: We used historical stem‐map and ledger data, contemporary data, and dendrochronological techniques to reconstruct stand structure (tree size, age, location) in three scenarios: (1) unharvested (1909), (2) harvested (1909), and (3) contemporary (2002). We used Clark and Evans' R, Ripley's K(t) univariate analysis, and correlogram analysis to assess the spatial pattern in each scenario. We also used Ripley's K₁₂(t) bivariate analysis and tree age data to examine spatial and temporal recruitment patterns as observed in the contemporary scenario. Results and Conclusions: The unharvested stand was aggregated at scales up to 28 m. The selective harvest accentuated the spatial patchiness of the stand in 1909 and changed spatial patterns by homogenizing tree size within patches. By 2002, the stand was a single patch dominated by small trees. Post‐harvest recruitment patterns were not spatially random; Pinus seedlings initially established in natural grass openings and then proceeded to fill‐in stump patches created by harvesting. Knowledge of spatial pattern should be explicitly incorporated into restoration activities in these forests.     

Pine invasions in treeless environments: dispersal overruns microsite heterogeneity

Understanding biological invasions patterns and mechanisms is highly needed for forecasting and managing these processes and their negative impacts. At small scales, ecological processes driving plant invasions are expected to produce a spatially explicit pattern driven by propagule pressure and local ground heterogeneity. Our aim was to determine the interplay between the intensity of seed rain, using distance to a mature plantation as a proxy, and microsite heterogeneity in the spreading of Pinus contorta in the treeless Patagonian steppe. Three one‐hectare plots were located under different degrees of P. contorta invasion (Coyhaique Alto, 45° 30′S and 71° 42′W). We fitted three types of inhomogeneous Poisson models to each pine plot in an attempt for describing the observed pattern as accurately as possible: the “dispersal” models, “local ground heterogeneity” models, and “combined” models, using both types of covariates. To include the temporal axis in the invasion process, we analyzed both the pattern of young and old recruits and also of all recruits together. As hypothesized, the spatial patterns of recruited pines showed coarse scale heterogeneity. Early pine invasion spatial patterns in our Patagonian steppe site is not different from expectations of inhomogeneous Poisson processes taking into consideration a linear and negative dependency of pine recruit intensity on the distance to afforestations. Models including ground‐cover predictors were able to describe the point pattern process only in a couple of cases but never better than dispersal models. This finding concurs with the idea that early invasions depend more on seed pressure than on the biotic and abiotic relationships seed and seedlings establish at the microsite scale. Our results show that without a timely and active management, P. contorta will invade the Patagonian steppe independently of the local ground‐cover conditions.     

Grazing effects on the species‐area relationship: Variation along a climatic gradient in NE Spain

Questions: Does grazing have the same effect on plant species richness at different spatial scales? Does the effect of spatial scale vary under different climatic conditions and vegetation types? Does the slope of the species‐area curve change with grazing intensity similarly under different climatic conditions and vegetation types? Location: Pastures along a climatic gradient in northeastern Spain. Methods: In zones under different regimes of sheep grazing (high‐, low‐pressure, abandonment), plant species richness was measured in different plot sizes (from 0.01 to 100 m2) and the slope of the species‐area curves was calculated. The study was replicated in five different locations along a climatic gradient from lowland semi‐arid rangelands to upland moist grasslands. Results: Species richness tended to increase with grazing intensity at all spatial scales in the moist upland locations. On the contrary, in the most arid locations, richness tended to decrease, or remain unchanged, with grazing due to increased bare soil. Grazing differentially affected the slope (z) of the species‐area curve (power function S=c A^z) in different climatic conditions: z tended to increase with grazing in arid areas and decrease in moist‐upland ones. ß‐diversity followed similar pattern as z. Conclusions: Results confirm that the impact of grazing on plant species richness are spatial‐scale dependent. However, the effects on the species‐area relationship vary under different climatic conditions. This offers a novel insight on the patterns behind the different effects of grazing on diversity in moist vs. arid conditions reported in the literature. It is argued that the effect of spatial scale varies because of the different interaction between grazing and the intrinsic spatial structure of the vegetation. Variations in species‐area curves with grazing along moisture gradients suggest also a different balance of spatial components of diversity (i.e. a‐ and ß‐diversity).     

A test for spatial relationships between neighbouring plants in plots of heterogeneous plant density

Abstract. Maps of plant individuals in (x, y) coordinates (i.e. point patterns) are currently analysed through statistical methods assuming a homogeneous distribution of points, and thus a constant density within the study area. Such an assumption is seldom met at the scale of a field plot whilst delineating less heterogeneous subplots is not always easy or pertinent. In this paper we advocate local tests carried out in quadrats partitioning the plot and having a size objectively determined via a trade‐off between squared bias and variance. In each quadrat, the observed pattern of points is tested against complete spatial randomness (CSR) through a classical Monte‐Carlo approach and one of the usual statistics. Local tests yield maps of p‐values that are amenable to diversified subsequent analyses, such as computation of a variogram or comparison with co‐variates. Another possibility uses the frequency distribution of p‐values to test the whole point pattern against the null hypothesis of an inhomogeneous Poisson process. The method was demonstrated by considering computer‐generated inhomoge‐neous point patterns as well as maps of woody individuals in banded vegetation (tiger bush) in semi‐arid West Africa. Local tests proved able to properly depict spatial relationships between neighbours in spite of heterogeneity/clustering at larger scales. The method is also relevant to investigate interaction between density and spatial pattern in the presence of resource gradients.     

Point pattern analysis under conditions of replicated sampling

Aims The analysis of point patterns, which deals with data sets consisting of mapped locations of organisms in a study region, is especially important to plant ecological studies because the locations of plants can often be approximated as points. However, few studies used point pattern analysis with data collected by replicated sampling a principle procedure of acquiring data in ecological research. Therefore, we explore the applicability of point pattern analysis under conditions of replicated sampling in this studyMethodsThree replicated 5 m × 5 m plots of homogenous communities were established on a site with eight years of restoration in Nei Mongol steppe. In each plot, the locations of individuals in Leymus chinensis and Stipa grandis populations were mapped. O-Ring function was used to describe the population patterns and species association between L. chinensis and S. grandis for each plot as well as the integrative data of the three replicates.Important findings Population patterns and species associations differed among the three replicated plots. This illustrates that if point pattern analysis was applied to describe the population patterns and species associations only by using data from a single plot sampling, the results could be misleading. Whereas it would be more reliable to integrate the data of replicated plots in the point pattern analysis because in this way the resulting O-Ring function is a weighted average, where the weight is the number of points in the replicate i divided by the total number of points in all replicated plots.     

Point pattern analysis under conditions of replicated sampling北大核心CSCD

Aims: The analysis of point patterns, which deals with data sets consisting of mapped locations of organisms in a study region, is especially important to plant ecological studies because the locations of plants can often be approximated as points. However, few studies used point pattern analysis with data collected by replicated sampling. a principle procedure of acquiring data in ecological research. Therefore, we explore the applicability of point pattern analysis under conditions of replicated sampling in this study. Methods: Three replicated 5 m × 5 m plots of homogenous communities were established on a site with eight years of restoration in Nei Mongol steppe. In each plot, the locations of individuals in Leymus chinensis and Stipa grandis populations were mapped. O-Ring function was used to describe the population patterns and species association between L. chinensis and S. grandis for each plot as well as the integrative data of the three replicates. Important findings: Population patterns and species associations differed among the three replicated plots. This illustrates that if point pattern analysis was applied to describe the population patterns and species associations only by using data from a single plot sampling, the results could be misleading. Whereas it would be more reliable to integrate the data of replicated plots in the point pattern analysis because in this way the resulting O-Ring function is a weighted average, where the weight is the number of points in the replicate i divided by the total number of points in all replicated plots.     

A new digital method of data collection for spatial point pattern analysis in grassland communities

A major objective of plant ecology research is to determine the underlying processes responsible for the observed spatial distribution patterns of plant species. Plants can be approximated as points in space for this purpose, and thus, spatial point pattern analysis has become increasingly popular in ecological research. The basic piece of data for point pattern analysis is a point location of an ecological object in some study region. Therefore, point pattern analysis can only be performed if data can be collected. However, due to the lack of a convenient sampling method, a few previous studies have used point pattern analysis to examine the spatial patterns of grassland species. This is unfortunate because being able to explore point patterns in grassland systems has widespread implications for population dynamics, community‐level patterns, and ecological processes. In this study, we developed a new method to measure individual coordinates of species in grassland communities. This method records plant growing positions via digital picture samples that have been sub‐blocked within a geographical information system (GIS). Here, we tested out the new method by measuring the individual coordinates of Stipa grandis in grazed and ungrazed S. grandis communities in a temperate steppe ecosystem in China. Furthermore, we analyzed the pattern of S. grandis by using the pair correlation function g(r) with both a homogeneous Poisson process and a heterogeneous Poisson process. Our results showed that individuals of S. grandis were overdispersed according to the homogeneous Poisson process at 0–0.16 m in the ungrazed community, while they were clustered at 0.19 m according to the homogeneous and heterogeneous Poisson processes in the grazed community. These results suggest that competitive interactions dominated the ungrazed community, while facilitative interactions dominated the grazed community. In sum, we successfully executed a new sampling method, using digital photography and a geographical information system, to collect experimental data on the spatial point patterns for the populations in this grassland community.     

A systematic comparison of summary characteristics for quantifying point patterns in ecology

Many functional summary characteristics such as Ripley's K function have been used in ecology to describe the spatial structure of point patterns to aid understanding of the underlying processes. However, their use is poorly guided in ecology because little is understood how well single summary characteristics, or a combination of them, capture the spatial structure of real world patterns. Here, we systematically tested the performance of combinations of eight summary characteristics [i.e. pair correlation function g(r), K‐function K(r), the proportion E(r) of points with no neighbor at distance r, the nearest neighbor distribution function D(r), the spherical contact distribution H_s(r), the kth nearest‐neighbor distribution functions D_k(r), the mean distance nn(k) to the kth neighbor, and the intensity function λ( x )]. To this end we used point pattern data covering a wide range of spatial structures including simulated (stationary) as well as real, possibly non‐stationary, patterns on tree species in a tropical forest in Panamá. To measure the information contained in a given combination of summary characteristics we used simulated annealing to reconstruct the observed patterns based only on the limited information provided by this combination and assessed how well other characteristics of the observed pattern were recovered. We found that the number of summary characteristics required to capture the spatial structure of stationary patterns varied between one (for patterns with near random structures) and three (for patterns with complex cluster and superposition structures), but with a robust ranking g(r), D_k(r), and H_s(r) that was largely independent on pattern idiosyncrasies. Stationary summary characteristics [with ranking g(r), D_k(r), H_s(r), E(r)] captured small‐ to intermediate scale properties of non‐stationary patterns, but for describing large‐scale spatial structures the intensity function was required. Our finding revealed that the current practice in ecology of using only one or two summary characteristics bears danger that essential characteristics of more complex patterns would not be detected. The technique of pattern reconstruction presented here has wide applications in ecology.     

尺度变化对关帝山庞泉沟云杉次生林空间分布格局的影响

林分空间格局研究对认识和理解森林群落结构的生态学过程具有重要作用。适宜的样地尺度不仅可以有效降低工作和时间成本,也可以提高林分属性的精确估计。同时,抽样尺度的适宜程度对科学评价林分空间结构调整也具有重要的现实意义。以关帝山庞泉沟4 hm²云杉次生林固定监测样地为研究对象,运用样地划分法和空间点格局的K2函数,评估了林分主要树种空间格局随样地面积变化的规律。结果表明:通过重要值排序,选取云杉(青杄+白杄)、华北落叶松、桦树(白桦+红桦)+其它阔叶树(花楸+辽东栎+山杨+山楂)作为主要树种(组)。随着样地尺度的减小(从4 hm²到0.25 hm²),空间分布格局主要表现为较小尺度(≤ 4 m)的聚集分布过度为随机分布与均匀分布,以及聚集和随机分布交替出现。所有树种的次级样地与参考样地的一致性指数差异显著,云杉和华北落叶松组合1 hm²样地一致性指数最高,而桦树和其它阔叶树完整1 hm²样地一致性指数最高;此外,云杉、华北落叶松和桦树0.25 hm²样地与组合1 hm²样地空间格局一致性指数组间差异显著。研究认为1 hm²样地尺度可以作为该地区云杉次生林空间分布格局的最小尺度。研究为探索云杉次生林空间格局的变化规律及样地抽样尺度的选取方面,提供了一定的理论基础和技术依据。     

Squamate richness in the Brazilian Cerrado and its environmental–climatic associations

We investigate patterns of species richness of squamates (lizards, snakes, and amphisbaenians) in the Brazilian Cerrado, identifying areas of particularly high richness, and testing predictions of large‐scale richness hypotheses by analysing the relationship between species richness and environmental climatic variables. We used point localities from museum collections to produce maps of the predicted distributions for 237 Cerrado squamate species, using niche‐modelling techniques. We superimposed distributions of all species on a composite map, depicting richness across the ecosystem. Then, we performed a multiple regression analysis using eigenvector‐based spatial filtering (Principal Coordinate of Neighbour Matrices) to assess environmental–climatic variables that are best predictors of species richness. We found that the environmental–climatic and spatial filters multiple regression model explained 78% of the variation in Cerrado squamate richness (r² = 0.78; F = 32.66; P < 0.01). Best predictors of species richness were: annual precipitation, precipitation seasonality, altitude, net primary productivity, and precipitation during the driest quarter. A model selection approach revealed that several mechanisms related to the different diversity hypothesis might work together to explain richness variation in the Cerrado. Areas of higher species richness in Cerrado were located mainly in the south‐west, north, extreme east, and scattered areas in the north‐west portions of the biome. Partitioning of energy among species, habitat differentiation, and tolerance to variable environments may be the primary ecological factors determining variation in squamate richness across the Cerrado. High richness areas in northern Cerrado, predicted by our models, are still poorly sampled, and biological surveys are warranted in that region. The south‐western region of the Cerrado exhibits high species richness and is also undergoing high levels of deforestation. Therefore, maintenance of existing reserves, establishment of ecological corridors among reserves, and creation of new reserves are urgently needed to ensure conservation of species in these areas.     

A practical approach to the study of spatial structure in simple cases of heterogeneous vegetation

Abstract. Spatial heterogeneity is a characteristic of most natural ecosystems which is difficult to handle analytically, particularly in the absence of knowledge about the exogenous factors responsible for this heterogeneity. While classical methods for analysis of spatial point patterns usually require the hypothesis of homogeneity, we present a practical approach for partitioning heterogeneous vegetation plots into homogeneous subplots in simple cases of heterogeneity without drastically reducing the data. It is based on the detection of endogenous variations of the pattern using local density and second‐order local neighbour density functions that allow delineation of irregularly shaped subplots that could be considered as internally homogeneous. Spatial statistics, such as Ripley's K‐function adapted to analyse plots of irregular shape, can then be computed for each of the homogeneous subplots. Two applications to forest ecological field data demonstrate that the method, addressed to ecologists, can avoid misinterpretations of the spatial structure of heterogeneous vegetation stands.     

Differences in forest composition in two boreal forest ecoregions of Quebec

Abstract. In order to describe and compare the post‐fire succession patterns of the two ecological regions (mixed‐wood and coniferous ecoregions) of northwestern Quebec, 260 forest stands were sampled with the point‐centred plot method. The mixed‐wood ecological region belongs to the Abies balsamea‐Betula papyrifera bioclimatic domain whereas the coniferous ecological region belongs to the Picea mariana‐moss bioclimatic domain. In each plot, tree composition was described, surficial deposits and drainage were recorded, and fire history was reconstructed using standard dendro‐ecological methods. Ordination techniques (Correspondence Analysis and Canonical Correspondence Analysis) were used to describe the successional patterns of forest vegetation and to correlate them with the explanatory variables. The results showed the importance of surficial deposits, the time since fire and the ecoregion in explaining the variation of stand composition. Abies balsamea tends to increase in importance with an increase in time since fire, and this trend is more pronounced in the mixed‐wood region. Even when controlling both for surficial deposits and time since fire, differences in successional trends were observed between the two ecoregions. As all the species are present in both ecoregions and as they are all observed further north, our results suggest that both the landscape configuration and fire regime parameters such as fire size and fire intensity are important factors involved in these differences.     

Within‐field spatial distribution patterns of corn planthopper,Peregrinus maidis,and severity of hopperburn and Maize mosaic virus symptoms as influenced by sunn hemp intercropping

Habitat management (e.g., intercropping) may alter within‐field spatial distribution patterns of herbivores, from a typical pattern as observed in a monoculture, and may influence patterns of crop injury. Field trials were conducted to study the effect of intercropping maize, Zea mays L. (Poaceae), with sunn hemp, Crotalaria juncea L. (Fabaceae) strips on within‐field spatial distribution patterns of corn planthopper, Peregrinus maidis (Ashmead) (Hemiptera: Delphacidae), and combined severity of hopperburn and Maize mosaic virus (MMV) (Rhabdoviridae: Nucleorhabdovirus) symptoms. In each field trial, spatially explicit data on P. maidis counts and ratings of severity of symptoms were obtained by sampling maize plants at weekly intervals. These data were used to examine the spatial patterns of P. maidis and severity of symptoms in maize‐intercropped and monoculture plots with Spatial Analysis for Distance IndicEs (SADIE) methodology. Spatial aggregation patterns of P. maidis in each treatment plot were not consistent among the field trials and tended to be mediated by their population densities. Interpolation of local cluster indices showed that P. maidis were more often aggregated at the field edges, irrespective of treatment. At times of MMV incidence in field trials (fall 2010 and spring 2011), the patch clusters of P. maidis and symptomatic plants were located at the field edges, but were spatially unassociated in both treatment plots. The results provided an approximation of the unpredictability of P. maidis spatial patterns at different population densities and their association with severity of symptoms in two maize‐cropping systems. However, the gap clusters of symptomatic plants were primarily located at the field interiors and were larger in intercropped than in monoculture plots. Such spatial pattern of symptomatic plants resulted in the reduced incidence of MMV in the intercropped plot compared with the monoculture plot, suggesting intercropping sunn hemp can be a useful tool in the management of MMV in maize fields.     

Spatial patterns of tree recruitment in a relict population of Pinus uncinata: forest expansion through stratified diffusion

Aim To infer future changes in the distribution of isolated relict tree populations at the limit of a species’ geographical range, a deep understanding of the regeneration niche and the spatial pattern of tree recruitment is needed. Location A relict Pinus uncinata population located at the south‐western limit of distribution of the species in the Iberian System of north‐eastern Spain. Methods Pinus uncinata individuals were mapped within a 50 × 40‐m plot, and their size, age and reproductive status were estimated. Data on seed dispersal were obtained from a seed‐release experiment. The regeneration niche of the species was assessed based on the associations of seedling density with substrate and understorey cover. The spatial pattern of seedlings was described using point‐pattern (Ripley's K) and surface‐pattern (correlograms, Moran's I) analyses. Statistical and inverse modelling were used to characterize seedling clustering. Results Pine seedlings appeared aggregated in 6‐m patches. Inverse modelling estimated a longer mean dispersal distance (27 m), which corresponded to the size of a large cluster along the north to north‐eastward direction paralleled by an eastward trend of increasing seedling age. The two spatial scales of recruitment were related to two dispersal processes. The small‐scale clustering of seedlings was due to local seed dispersal in open areas near the edge of Calluna vulgaris mats: the regeneration niche. The long‐range expansion might be caused by less frequent medium‐distance dispersal events due to the dominant north‐westerly winds. Main conclusions To understand future range shifts of marginal tree populations, data on seed dispersal, regeneration niche and spatial pattern of recruitment at local scales should be obtained. The monitoring of understorey communities should be a priority in order to predict correctly shifts in tree species range in response to global warming.     

Cuticular melanisation and immune response in a butterfly: local adaptation and lack of correlation

1. Despite growing knowledge on the relationship between ecological variables and individual immune function, data on the spatial variability of immune defence in invertebrate natural populations are scarce. 2. Here, we use replicated populations of the butterfly Lycaena tityrus from different altitudes to investigate genetic variation in the melanin‐based encapsulation response. As high‐ and low‐altitude populations differ in cuticular pupal melanisation, we further tested for any associations between pupal melanisation and parasite resistance. 3. Although pupal melanisation was higher at higher compared with lower altitudes (and at a higher compared with a lower rearing temperature), any obvious relations to the encapsulation response were absent. Further phenotypic correlations within groups were significant in one out of four cases only, suggesting that in L. tityrus encapsulation operates largely independent of cuticular melanisation. 4. A significant interaction between altitude and temperature indicated that high‐altitude animals show a stronger melanisation response than low‐altitude ones at the lower temperature and vice versa, indicating local adaptation to different climates.     

Sprouting as a survival strategy for non-coniferous trees: Relation to population structure and spatial pattern of Emmenopterys henryi (Rubiales)

To improve the management and protection strategies of Emmenopterys henryi, the effect of sprouting on the population and spatial distribution pattern was explored. Environmental conditions of the community, tree diameter at breast height (DBH), and height of each individual tree were obtained using a contiguous grid quadrate method in four plots of deciduous and evergreen broad-leaved forests in Dapan Mountain National Nature Research in Zhejiang, China with the largest distribution area of E. henryi. The principal components analysis (PCA) showed that the sprouting ability of E. henryi is strongly related to the degrees of rock bareness, altitude, and slope. The analysis of the population structures showed that the population of group A only with parental trees was in decline due to a lack of seedlings and saplings, whereas the population of group B with both parental trees and sprouts (group B) was increasing. Groups A and B differed in their spatial distribution patterns in the plot 2, with group A showing a random distribution and group B displaying an aggregated distribution. Because the optimum block scale was between 16?m² and 32?m², analyses of the spatial pattern and dynamics of the spatial pattern at 25?m² could accurately reflect the true distribution. The population of E. henryi is small, and the spatial patterns of the population indicated an aggregated distribution with the exception of plot 2 of group A. Plot 2 showed significant environmental deterioration from nearby rocks and ravines, and as a result, a number of small trees died from root exposure, which led to a random distribution of plot 2. The effects of sprouting should be considered when studying the population and spatial patterns of plants.     

Disturbance affects spatial patterning and stand structure of a tropical rainforest tree

The distribution and spatial patterns of plant populations in natural ecosystems have recently received much attention; yet the impacts of human‐induced disturbances on these patterns and underlying processes remain poorly understood. We used the sub‐canopy tree, Ryparosa kurrangii (Achariaceae), to explore the possible effects of such disturbances on stand structure and spatial patterning in an Australian tropical rainforest. We studied three populations that differed in their extent of habitat modification: anthropogenic disturbance (proximate settlement and roads) and internal damage by an invasive alien species, the feral pig (Sus scrofa). Populations were mapped, characterized, and three size cohorts (seedlings, saplings, trees) were analysed using a suite of spatial point pattern analyses (univariate: Diggle's G and F and Ripley's K; bivariate: Diggle's G and Ripley's K). Ryparosa kurrangii has a typical stand structure for a sub‐canopy tree species, but occurs at high densities locally (>400 stems ha^?1). At all sites, the tree cohort were randomly distributed and saplings were spatially aggregated at distances of up to 2–3 m. Between sites there were distinct differences in the size structure and spatial pattern of seedlings, the cohort most affected by recent habitat modification. That is, the least disturbed site had no aggregation among seedlings, the site with the greatest anthropogenic disturbance had many small, clustered seedlings that were spatially associated with trees, and the site with pig damage had clustered seedlings that had no spatial relationship with trees. We propose that habitat modification by anthropogenic and pig disturbance disrupts seed dispersal and establishment regimes, which leads to altered seedling spatial patterns. These disturbances could have long‐term implications for the population structure and health of R. Kurrangii.     

A grid‐based method for sampling and analysing spatially ambiguous plants

Abstract. Spatial data can provide much information about the interrelations of plants and the relationship between individuals and the environment. Spatially ambiguous plants, i.e. plants without readily identifiable loci, and plants that are profusely abundant, present non‐trivial impediments to the collection and analysis of vegetation data derived from standard spatial sampling techniques. Sampling with grids of presence/absence quadrats can ameliorate much of this difficulty. Our analysis of 10 fully‐mapped grassland plots demonstrates the applicability of the grid‐based approach which revealed spatial dependence at a much lower sampling effort than mapping each plant. Ripley's K‐function, a test commonly used for point patterns, was effective for pattern analysis on the grids and the gridded quadrat technique was an effective tool for quantifying spatial patterns. The addition of spatial pattern measures should allow for better comparisons of vegetation structure between sites, instead of sole reliance on species composition data.