Long-term spatial dynamics in an old-growth deciduous forest

Ward, Jeffrey S.; Parker, George R.; Ferrandino, Francis J.

doi:10.1016/0378-1127(96)03722-x

Cited by 94 publications

(85 citation statements)

References 29 publications

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“…3). Los ejemplos de patrones en agregados de los individuos juveniles o no dominantes, y aleatorios de los maduros o dominantes, son abundantes en la bibliografía (Stewart y Rose, 1990;Lusk y Ogden, 1992;Duncan, 1993;Ward et al, 1996;Chen y Bradshaw, 1999;Mast y Veblen, 1999). Estos son patrones característicos de especies que se establecen en huecos del dosel, en los cuales los procesos de mortalidad dependiente de la densidad transforman el patrón inicial en agregados en un patrón final aleatorio, o incluso regular para ciertos rangos de distancia (Ward et al, 1996;Aldrich et al, 2003).…”

Section: Interpretación Ecológica De Los Resultadosunclassified

“…4). Esta sería la evolución lógica del patrón espacial al aumentar la edad de los individuos, pues el efecto acumulado de las perturbaciones, la competencia, el ataque de patógenos, y un componente de azar, produciría un cambio desde un patrón en agregados hasta un patrón próximo a la regularidad (Turner y Franz, 1985;Sterner et al, 1986;Ward et al, 1996;He et al, 1997). Algunos trabajos han revelado que el patrón espacial final de los individuos maduros suele ser aleatorio, y que un patrón regular es excepcional en la naturaleza, observándose únicamente en ambientes muy estables en que apenas existen perturbaciones exógenas (Leps y Kindlmann, 1987;Szwagrzyk y Czerwczak, 1993;Mast y Veblen, 1999;Antos y Parish, 2002).…”

Section: Interpretación Ecológica De Los Resultadosunclassified

“…bios en la estructura espacial (Peterson y Squiers, 1995; Vacek y Ward et al, 1996;Aldrich et al, 2003). Un caso particular es la aplicación de la función K al análisis de los patrones de mortalidad, en el cual se plantea una hipótesis nula específica, calculándose los intervalos de confianza para la misma (Duncan, 1991;He y Duncan, 2000).…”

Section: La Función K De Ripleyunclassified

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Spatial analysis techniques applied in forest ecology: point pattern analyses

Rozas

Camarero

2005

For. syst.

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IntroducciónLos métodos cuantitativos de análisis espacial tienen como objetivo la detección y descripción de patrones de distribución espacial, permitiendo evaluar hipótesis sobre los procesos ecológicos que han causado el patrón observado. La heterogeneidad espacial derivada de perturbaciones que eliminan árboles dominantes en el dosel forestal, puede condicionar la regeneración, la estructura de las poblaciones y la coexistencia de las especies (Turner y Franz, 1985; He et ResumenEn este trabajo se revisan algunos métodos modernos de análisis uni-y bivariante de los patrones de puntos utilizados habitualmente en ecología. Se aplicaron el análisis refinado de la distancia al vecino más próximo, la función K de Ripley y la técnica SADIE para analizar patrones de puntos simulados y reales. Un patrón aleatorio, tres patrones en agregados de 3, 5 y 10 m de radio, y tres patrones regulares con distancias de inhibición de 2, 4 y 6 m, fueron simulados para comparar la eficiencia de los diferentes métodos. Los patrones reales proceden de dos bosques caducifolios del litoral cantábrico y un bosque de coníferas en la Sierra de Cebollera-Urbión. Las tres técnicas permitieron diferenciar entre un patrón univariante aleatorio, agregado y regular. El análisis del vecino más próximo y la función K reflejaron las distancias de inhibición en los patrones regulares, pero solo la función K permitió detectar el tamaño de los agregados. Los individuos juveniles mostraron un patrón en agregados, mientras que los adultos presentaron un patrón aleatorio. Respecto a los análisis bivariantes, se obtuvieron evidencias de atracción y repulsión espacial entre algunos patrones simulados, a pesar de que estos son procesos independientes. Los patrones reales mostraron repulsión espacial entre los individuos juveniles y adultos, así como atracción entre juveniles de tamaños diferentes. Los resultados se interpretaron en relación con la bibliografía disponible sobre ecología forestal. Se discute la importancia de aplicar métodos apropiados para la corrección del efecto de borde y la utilización de modelos nulos alternativos al de aleatoriedad espacial.Palabras clave: patrón espacial, vecino más próximo, K de Ripley, SADIE, modelos nulos. Abstract Spatial analysis techniques applied in forest ecology: point pattern analysesSeveral methods for analyzing uni-and bivariate point patterns, commonly used in ecology, are reviewed in this work. The refined nearest neighbor method, the Ripley's K function and the SADIE technique were used to analyze simulated and real spatial point patterns. A random pattern, three clumped patterns with radius of 3, 5 and 10 m, and three random patterns with inhibition distances of 2, 4 and 6 m, were simulated to check the efficiency of the methods. Real patterns were measured in two deciduous forests in the Cantabrian lowlands and a coniferous forest in the Cebollera-Urbión Range. All techniques were able to distinguish between random, clumped and regular patterns. Nearest neighbor method and K function displayed inh...

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Section: Interpretación Ecológica De Los Resultadosunclassified

Section: La Función K De Ripleyunclassified

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Spatial analysis techniques applied in forest ecology: point pattern analyses

Rozas

Camarero

2005

For. syst.

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“…O padrão de distribuição espacial de C. granulosa, incluindo todas as plantas, foi analisado por meio da função univariada de segunda ordem da densidade de vizinhos ou NDF (Neighbourhood Density Function) (Ward et al, 1996;Condit et al, 2000). A estatística NDF, também conhecida como correlação de função aos pares (Perry et al, 2006), é similar à função K de Ripley, porém não é cumulativa, o que favorece a interpretação.…”

Section: Análises Da Distribuição Espacialunclassified

Distribuição Espacial de Cattleya granulosa Lindl.: Uma Orquídea Ameaçada de Extinção

et al. 2015

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do Rio Grande do Norte -UFRN, Natal/RN, Brasil RESUMOCattleya granulosa é uma orquídea ameaçada de extinção endêmica da região litorânea do Nordeste do Brasil. Este estudo teve como objetivos avaliar os níveis de agregação espacial em uma população preservada da espécie, em uma área de 4.225 m 2 da unidade de conservação do Parque das Dunas, em Natal, RN. Além de caracterizar o hábito de vida da população, foi utilizada a função de segunda ordem da densidade de vizinhos (NDF) para determinar o padrão espacial nas classes de distância, com o uso do programa SpPack. Quanto ao hábito de vida, 73% das plantas eram epífitas (N = 136) e 27% terrestres (N = 50). As epífitas têm especificidade com um único forófito, indivíduos arbóreos de Eugenia spp. (Myrtaceae). C. granulosa possui padrão espacial agregado, com maior densidade de vizinhos (NDF) no raio de até 5 m. Esses dados sugerem um potencial dispersivo restrito e com influência direta sobre ações de conservação biológica da espécie.Palavras-chave: Orchidaceae, densidade de vizinhos, dispersão. Spatial Distribution of Cattleya granulosaLindl.: An Endangered Orchid Species ABSTRACTCattleya granulosa is an endemic and endangered orchid species of the coastal region of northeastern Brazil. This study aimed to evaluate the levels of spatial aggregation in a preserved population, in an area of 4,225 m 2 of the conservation unit of 'Parque das Dunas' Natal, Rio Grande do Norte state, Brazil. We evaluated the life form of the population as well as its neighborhood density factor (NDF) to determine the spatial distribution in distance classes, using the SpPack software program. Regarding the life form, 73% of the plants (N = 136) were epiphyte and 27% were terrestrial (N = 50). The epiphytes present specificity with a single host tree, Eugenia spp. (Myrtaceae). The spatial pattern of Cattleya granulosa is aggregated, with the highest density of neighbors (NDF) within a radius of 5 m. These data suggest restricted dispersion with direct influence on actions for conservation of the species.

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“…Of particular importance are changes in stand structure occurring during its various stages of development. The long life of trees, however, means that studying forest dynamics requires long-term work and analyses, repeated every several or several dozen years (Szymański 1964;Ward et al 1996;Kenkel et al 1997;Hessburg et al 2000;Woods 2000;Szmyt 2004;Wolf 2005;Saunders, Wagner 2008;LeMay et al 2009). Most research on forest dynamics has been conducted on natural forests; much less so on artificially established forests.…”

Section: Introductionmentioning

confidence: 99%

Spatial diversity of planted and untended silver birch (Betula pendula L.) stands

Szmyt¹,

Korzeniewicz²

2012

Forest Research Papers

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Abstract. The aim of this paper was to describe changes in the spatial distribution of living trees in planted and untended birch stands, as well as to determine the spatial differentiation of the diameters and height of their constituent trees. Analysis was performed in 9-and 39-year old stands.The structural diversity of birch stands was described using the following spatial indices: Clark-Evans index (CE), spatial differentiation index for DBH (TD) and height (TH). The CE index describes the horizontal distribution of trees within a stand and the TD/TH indices indicate the size differentiation between neighbouring trees within a stand (DBH and H, respectively). The indices mentioned above concern small spatial scales. Our results indicate a regular spatial distribution of living trees on the ground at age nine, shown by high CE index. After 30 further years of stand development CE values were distinctly lower and no longer significantly different from the value for a random distribution of trees. At age 39, the 2 stands had a random spatial distribution and in the planted stand living trees still retained a regular spatial arrangement. Analysing the spatial differentiation of diameter and height of trees revealed that there was little differentiation between neighbours in forest stands in neither their diameter and height. The highest average values for the TD index decreased for stands during the 30 years since their initial measurement at age nine. A similar trend was observed for height differentiation (TH),which decreased from a maximum at age nine.

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Long-term spatial dynamics in an old-growth deciduous forest

Cited by 94 publications

References 29 publications

Spatial analysis techniques applied in forest ecology: point pattern analyses

Spatial analysis techniques applied in forest ecology: point pattern analyses

Distribuição Espacial de Cattleya granulosa Lindl.: Uma Orquídea Ameaçada de Extinção

Spatial diversity of planted and untended silver birch (Betula pendula L.) stands

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