Why populations are limited in their spatial distribution

Patchy breeding distributions will tend to increase spatial heterogeneity in population density, whereas dispersal from breeding patches will tend to decrease it. The potential for dispersal to homogenize densities is likely to differ both among organisms e. However, for mobile organisms, experimental studies of the importance of breeding distributions from the wild are largely lacking. In the present study, experimental manipulations replicated over eight natural streams and 2 years enabled us to test for effects of the distribution of Atlantic salmon eggs over spatial scales which are relevant to local interactions among individuals.

We also observed that immature P. As in many primeval forests, small young individuals are almost always located in groups Table 4 —often as a result of tree fall gaps in the canopy as the dominant type of disturbance [ 61 ][ 62 ].

The common clustering at small scales in the P. These forests tend to be horizontally structured, mainly because an initiating disturbance is followed by long periods when small-scale, low-intensity disturbances control tree regeneration [ 8 ]. Therefore, fire disturbance, which almost always homogenizes stands, is a rare event in the P.

Moreover, fires may bring an end to this fragmented tree community in very small and isolated locations [ 1 ] [ 17 ]. In contrast, the clustering by small-scale disturbances may be mainly caused by insect attack, disease or windthrow, which may create patchiness and spatial heterogeneity within locations [ 8 ].

The rare clustering at larger scales was mainly affected by the low tendency of aggregation of canopy trees Table 4 , as also reported by Malik et al.

Therefore, the overall random patterns were a result of shift from initial aggregation to a random distribution [ 67 ]. Self-thinning due to intra and inter-specific competition-induced mortality was probably the main cause of the decrease in aggregation intensity [ 42 ], [ 67 ] during the course of population development in the P. However, environmental heterogeneity, uneven-age distributions, insufficient competition, limited seed dispersal and random germination may have prevented the presence of a significantly regular pattern of the mature trees in the tree community under study [ 68 ].

The aforementioned factors, particularly insufficient competition in the plot may also have favoured clustering in the northern locations plots.

The number of P. The spatial distribution of P. In SJ, spruces had a repulsive pattern to other species, similarly to a study in an old growth spruce-fir forest in Changbaishan Natural Reserve, China [ 41 ]. We therefore assume that there was a similar but weaker inter- and intraspecific competition between the trees at the species level [ 68 ] and that P. The bivariate L -function showed that smaller trees of all species often grew in the neighbourhood of larger trees of all species Table 4 , typically in uneven-aged forests Fig 2 and probably as a result of some shade-tolerant frequent tree species under mature canopy such as Abies durangensis , Cupressus lindleyi and Juniperus deppeana and the slender shaped crowns of the mature canopy trees in this community [ 69 ].

The smaller P. In this study, P. The plots in which a clustered structure was observed tended to be associated not significantly with a large number of trees because of the presence of a greater number of understory trees. Understory trees often displayed a tendency to grouping Table 4. No covariation C between aggregation indices and diameter distributions was observed, because the 12 diameter distributions scarcely varied in their reverse J -shaped form Table 2.

The cluster structure was weakly positively related to higher tree species diversity, probably due to a combination of the accumulation effect [ 13 ] [ 70 ] and increasing competition in denser plots [ 71 ]. While the accumulation effect resulted in higher diversity, the self-thinning processes led to saturation in tree species diversity [ 72 ].

The high tree species diversity in the P. The probability that two or more trees of different species would fall at the same time and create a gap is lower than the probability of the same happening with trees of the same species.

We conclude that satisfactory understanding of spatial forest structure is essential for the sustainable conservation of this unique mixed uneven-aged Picea forest [ 20 ]. Our measures of spatial tree structure, particularly and failed in several plots because of an insufficient number of trees repetitions for the calculations. Conceived and designed the experiments: CW. Performed the experiments: CW. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract The very rare Mexican Picea chihuahuana tree community covers an area of no more than ha in the Sierra Madre Occidental.

This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Data Availability: All relevant data are within the paper and its Supporting Information files.

Material and Methods We confirm that the field studies provide the specific location of study Fig 1 , S1 Dataset. Download: PPT. Fig 1. Fig 2. Table 1. Summary of important stand parameters calculated from the tree data: stem number per hectare N , stand basal area G , quadratic mean diameter dg , mean breast height diameter d , mean total height h , maximum diameter dmax , and maximum height dmax of the all tree species total and Picea chihuahuana M. Pch in the 50 x 50 m plotsin the 12 study locations and minimum min , mean and maximum max parameter values for the stands.

Because of its hyperbolic behavior, the interpretation of the K -function is not straightforward and a modification, called the L -function, was proposed by Besag in order to normalize the function Besag, : 2 Now, the expected value of the univariate L -function under CSR is 0 for all r , positive when the pattern tends to be clustered and negative when the pattern tends to be regular.

Due to the edge effect, K ij and K ji are correlated, but not identical, and therefore the following means of estimating K B is recommended: 4 Its associated bivariate L -function is defined as 5 The expected value of the bivariate L -function under spatial independence is 0 for all r , positive when the two point processes tend to be aggregated and negative when the two point processes tend to be repulsive.

Table 2. Results Most of the P. Fig 3. Sample plots 50 x 50 m illustrating the location of each tree, univariate and bivariate L -functions. Table 3. Spatial structure of Picea chihuahuana M. Table 4. Table 5. Analysis of spatial tree structure in 50 x 50 m plots in the 12 locations including all tree species species shown [ 44 ] and based on the neighbourhood-based Clark-Evans index CE , Uniform Angle index , and Mean Directional index.

Table 6. Analysis of spatial structure of the suppressed and dominant trees in 50 x 50 m plots containing all Picea chihuahuana M. Table 7. Analysis of spatial structure of the suppressed and dominant trees in 50 x 50 m plots containing all tree species species shown [ 44 ] ,in the 12 study locations, based on the neighbourhood-based Clark-Evans index CE , Uniform Angle index , and Mean Directional index.

Discussion and Conclusions In this study, we analysed the fine-scale spatial tree patterns in a special forest tree community of P. No covariation C between aggregation indices and diameter distributions was observed, because the 12 diameter distributions scarcely varied in their reverse J -shaped form Table 2 The cluster structure was weakly positively related to higher tree species diversity, probably due to a combination of the accumulation effect [ 13 ] [ 70 ] and increasing competition in denser plots [ 71 ].

Supporting Information. S1 Dataset. Data set used in this study. Author Contributions Conceived and designed the experiments: CW. References 1. Locations of endangered spruce populations in Mexico and the demography of Picea chihuahuana. View Article Google Scholar 2. Norma Oficial Mexicana. Lista de especies en riesgo. Tree Genet. View Article Google Scholar 4. Gordon AG. View Article Google Scholar 5.

Cienc Forest. View Article Google Scholar 6. Contribution to the Knowledge of the Ecology of Picea chihuahuana. Afr J Biotechnol. View Article Google Scholar 8. Parish R. Stand development in an old-growth subalpine forest in southern interior British Columbia.

Forest Res. View Article Google Scholar 9. Recent evolution and divergence among populations of a rare Mexican endemic, Chihuahua spruce, following Holocene climatic warming. View Article Google Scholar Decoupled mitochondrial and chloroplast DNA population structure reveals holocene collapse and population isolation in a threatened Mexican-endemic conifer.

Mol Ecol. Pol J Ecol. Plos One. In: Ahuja M. Modeling the potential distribution of Picea chihuahuana Martinez, an endangered species on the Sierra Madre Occidental, Mexico, Forests. Projections of suitable habitat for rare species under global warming scenarios.

Am J Bot. Ledig FT. Climate Change and Conservation. Acta Silv. Proposal for conservation of three endangered species of Mexican spruce. Spies TA. Forest Structure: A Key to the Ecosystem.

Northwest Science. Pommerening A. Evaluating structural indices by reversing forest structural analysis. Forest Ecol. Continuous Cover Forestry. V; Density and Dispersion. Introduction to Population Demographics. Population Dynamics of Mutualism. Population Ecology Introduction. Population Limiting Factors. The Breeder's Equation. Global Atmospheric Change and Animal Populations. Semelparity and Iteroparity. Causes and Consequences of Dispersal in Plants and Animals. Disease Ecology.

Survivorship Curves. The Population Dynamics of Vector-borne Diseases. Density and Dispersion By: Sean E. Walker Dept. Citation: Walker, S. Nature Education Knowledge 3 10 Density and dispersion are two descriptors of populations that can provide insight into processes such as competition and territoriality. Their measurement is therefore fundamental to our understanding of biogeography. Aa Aa Aa. Patterns of Dispersion.

Figure 1: Clumped dispersion of individuals. The average number of individuals per square is 6. Figure 2: Uniform dispersion of individuals. The average number of individuals per square is 10, and the variance is 4. Figure 3: Random dispersion of individuals. The mean number of individuals per square is 5.

Which Dispersion Pattern is it? References and Recommended Reading Blackburn, T. Krebs, C. Ecological Methodology , 2nd ed.

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