The platform will undergo maintenance on Sep 14 at about 9:30 AM EST and will be unavailable for approximately 1 hour.
1994
DOI: 10.1111/j.1365-2028.1994.tb00569.x
|View full text |Cite
|
Sign up to set email alerts
|

The long‐term impact of elephant browsing on baobab trees at Msembe, Ruaha National Park, Tanzania

Abstract: SummaryThe baobab tree population of the Msembe study area was surveyed for the third time in 1989. Although tree density had dropped between the 1976 and 1982 surveys, there was no significant change between 1982 and 1989, probably because most bull éléphants had been killed by poachers. The change in the baobab size distribution between 1976 and 1989 is similar to that predicted by a model simulating the effects of elephant browsing on baobabs. It suggests that elephant browsing has a different effect on bao… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
29
0

Year Published

2003
2003
2021
2021

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 36 publications
(38 citation statements)
references
References 15 publications
1
29
0
Order By: Relevance
“…Several factors including those not investigated, could explain this spatial distribution. Wilson (1988) and Barnes et al (1994) suggested that baobab densities are very variable across landscapes as they are affected by a number of establishment factors, such as insect outbreaks, past human activities, droughts or edaphic variables (Edkins et al 2007), all interacting in a complex and unpredictable ways (Scholes and Walker 1993). In Gonarezhou, Tafangenyasha (1992) suggested that herbivores (e.g., elephant and tree squirrels), drought, and increased density of associated species could bring about deaths of baobabs.…”
Section: Figmentioning
confidence: 99%
“…Several factors including those not investigated, could explain this spatial distribution. Wilson (1988) and Barnes et al (1994) suggested that baobab densities are very variable across landscapes as they are affected by a number of establishment factors, such as insect outbreaks, past human activities, droughts or edaphic variables (Edkins et al 2007), all interacting in a complex and unpredictable ways (Scholes and Walker 1993). In Gonarezhou, Tafangenyasha (1992) suggested that herbivores (e.g., elephant and tree squirrels), drought, and increased density of associated species could bring about deaths of baobabs.…”
Section: Figmentioning
confidence: 99%
“…PFR may be an extreme case of increased animalrelated damage resulting from increases in animal densities within reserves, but shifts in community composition following animal-induced damage to vegetation have been proposed in several studies, e.g. elephant browsing in African savannahs (Barnes et al 1994) and white-tailed deer browsing in eastern North America (Long & Carson 1998). We concur with Guariguata (1998) that 'interspecific patterns of post-damage response' may generally be a critical lifehistory parameter that affects the structure, species composition and diversity of tropical forests.…”
Section:       mentioning
confidence: 99%
“…Rather, we assess the impact of elephants visiting this square kilometer, i.e., elephants can be dealt with as a timevarying input into the model, and different scenarios may be analyzed. We consider this approach more realistic than limiting our analysis, as in some earlier studies [4,5,82,99], to various constant elephant "stocking densities." In addition, this approach naturally extends to a geographic information systems setting in which our model is used to evaluate the effects of elephants in each of many grid cells on top of which elephant movements are imposed (cf.…”
Section: Elephant Populationmentioning
confidence: 97%
“…for transitions within metaclasses), we set l i =1 (i=2, 3,4,6,8). Any given level of growth, g i , may also entail shading out other plants in the same or lower height class and so we introduce h i as a "crowding coefficient", representing the proportion of plants overshadowed by the individuals growing from class i to i+1 (see Fig.…”
Section: Wet Season Dynamicsmentioning
confidence: 99%