Ecological Report Struwig Eco- Reserve by Wildlife & Ecological Investments: Mega-herbivores and impact on woody vegetation

Transcription

1 Ecological Report Struwig Eco- Reserve by Wildlife & Ecological Investments: Mega-herbivores and impact on woody vegetation

2 Contents Introduction... 3 Study Area... 4 Methods... 5 Habitat assessments... 5 Mega-herbivores... 8 Results... 8 Habitat assessments... 9 Mega-herbivores Discussion Recommendations References Wildlife & Ecological Investments Page 2

3 Introduction Wildlife and Ecological Investments (WEI) along with Operation Wallacea has conducted ecological surveys and biodiversity monitoring in the Struwig Eco-Reserve since 212. Consistent collection of data over an extended time period allows for an opportunity to detect trends and patterns. To best understand the health of an ecosystem we need to 1) monitor the response of organisms to their environment, 2) examine the response of populations of a specific species to the environment and considering processes such as abundance and fluctuations and 3) investigate the composition and structure of communities within a defined area. With this information we are better able to further examine the processes occurring within an ecosystem. Ecosystems have a wide range of components each responding to their environment. Complete and holistic biodiversity monitoring is impossible due to the large taxa representation. It is for this reason that WEI surveys macro fauna and flora. By surveying key organisms within an ecosystem, we obtain clues into ecosystem functioning and processes. To date the data that has been collected covers a wide ecological range and consists of herbaceous, woody vegetation, bird, insects and mammal surveys. The data has been collected systematically and consistently using the same methods within the same sampling sites. Vegetation communities are a critical foundation for determining numerous factors about an ecosystem. The health of an ecosystem can be determined by the quality of the vegetation particularly in terms of its function to provide food, shelter and soil stabilising amongst others. Detecting changes in vegetation quantity and quality influences the available browse and graze for ungulates. When considering large mammals such as elephants then monitoring of vegetation becomes of high importance for management. For this reason, WEI conducts habitat assessments and includes monitoring the impacts on woody vegetation by elephants specifically however other ungulates are taken into account. Although Struwig Eco-Reserve is an open system with the Kruger National Park, understanding the impacts of elephants on vegetation may provide insight into the role of elephants as drivers in an ecosystem. Elephants are recognised as having distinct seasonal dietary preferences between the wet and dry seasons (Viljoen et al., 213). (Owen-Smith & Chafota, 212). Although we did not directly measure the dietary components of elephants, we did however monitor the movement, location and the number of days that they are seen on the reserve. In closed systems elephants have a measurable constant impact on the habitat, however in an open system where elephants disperse, the localized effect would be anticipated to be less (Loarie, van Aarde & Pimm, 29). It is for this reason the WEI team measures the temporal and spatial scales of elephant interaction with the habitat in Struwig through habitat assessments and game transects. The reserve can make use of the data collected and analysed by WEI to review changes over time particularly pre and during the drought. A drought was defined as occurring when rainfall is below 75% of mean annual rainfall (Vogel 1994). In Limpopo province years of below average rainfall that were classified as drought were documented as recently as 22 (Maponya & Mpandeli 212). The baseline data can contribute towards understanding the movement patterns and resource use of mega-herbivores in an open system. This report supplies information on the trends and data collected between 212 and 216. For the purpose of this report we have analysed vegetation and specific meso-herbivore data (impala and kudu) and mega-herbivore data, particularly elephants. Wildlife & Ecological Investments Page 3

4 Study Area Struwig Eco- Reserve is approximately 2,7ha and falls within Balule Game Reserve. The Olifants River forms the northern border. Ecological surveying began in 212 in 17 sample sites evenly distributed across the reserve. The 16 sample sites are each 1ha plots and are GPS geotagged for ease of relocating (Figure 1). In 215 we used a different method where nine plots were set up according to distance from water. The collection of data from 212 to 216 has allowed us to obtain benchmark information to detect trends and patterns. This is particularly relevant in the face of drought and climatic changes that may impact the reserve. The survey sites are intended to be representative of the Struwig Eco-Reserve and thus we can use this data and methodology to infer the trends and patterns on neighbouring properties. When classifying the habitat sites, we used features which are outlined in the methodology and not floristic classification due to lack of statistical support when running the data through Primer 7. Figure 1: Location of the 1 ha habitat assessment sites surveyed from 212 to 216 (except 215). Wildlife & Ecological Investments Page 4

5 Methods Habitat assessments The original 17 sites were randomly selected however due to accessibility reasons one of the sites was removed. In 215 the habitat assessments where set up differently from the fixed 16 sites. The sites were identified using Google Earth at predefined distances from water. Data on the terrain and landscape (aspect, slope gradient, soil texture and stoniness) of the sites were recorded. After we identified each site, we classified them into habitat types (Table 1): Riparian Dry Riverbed Flowing River Dam Plateau Crest Valley bottom Hill slope Sodic Site Koppie Table 1: Terrain and landscape of the ecological sites where habitat assessments were conducted between 212 and 216 including 215. Site Habitat type Distance from Olifants River (m) 1 Dry riverbed / Riparian Dry riverbed Hill slope Hill slope 5-1, 5 Plateau >1, 6 Hill slope >1, 7 Dry riverbed / Riparian Crest Hill slope >1, 1 Plateau >1, 11 Hill slope >2, 12 Plateau >2, 13 Hill slope >2, 14 Plateau >3, 15 Plateau >3, 16 Hill slope - S4P S4P S4P S4P S5P S5P S5P S5P4-5 1, S5P5 - >1, Wildlife & Ecological Investments Page 5

6 At each of the habitat assessment sites we recorded all woody vegetation over 1 metre tall. Other data recorded included species name, height class, basal stem diameter, average stem diameter (for multi-stemmed bushes), the width of the widest point of the canopy, and the extent of elephant and fire impact (fire data is not featured in this report because of the lack of burning activity in the area). We recorded impact on vegetation by both meso and mega-herbivores. A qualitative and quantitative evaluation of elephant and other browser impact was graded according to the Walker Scale (Walker 1976) as detailed below: TYPE: CODE: Pulled or kicked out A Pushed over and dead or apparently dead B Main trunk broken, is or appears to be dead C Main trunk broken but re-sprouting or likely to re-sprout D Pushed over but still alive E Main trunk tusk-slashed F Main trunk debarked (% of the circumference) *G Roots exposed and eaten (% of the circumference) *H Primary branches broken *J Secondary and/or smaller branches broken *K None: Z *Impact types G, H, J, K must be quantified according to the percentage classes given below. The percentage classes refer to the percentage of the total canopy volume (J & K) and are estimated. In the case of exposed roots and debarking of the main trunk (types G & H), the percentage of the root base or trunk's perimeter (i.e. a circle) affected must be estimated and coded accordingly. 1-1% 11-25% 26-5% 51-75% 76-9% 91-1% For the purpose of this report we focused on the height categories and species of the woody vegetation at each site and habitat type. The One-way ANOVA was used to determine if at each site and habitat type there was an overall change between the years the woody vegetation was measured in terms of the species and height categories. If a significant difference was found, we used the Tukey Test to identify where the difference was. Although we measured all woody species, for this report seven woody plants of interest were focused on because they have been classified in literature as forming a critical component of elephant diet (Viljoen et al., 213; Owen-Smith & Chafota, 212). These species were: Vachellia erubesense Vachellia nigresense Combretum apiculatum Combretum herense Dichrostachys cinera Grewia bicolor Grewia flavesens Grewia monticola Sclerocarya birrea Terminalia pruniodes We used the Chao1 estimator to identify the species abundance at each site and a Chao 2 estimator to estimate species richness at each site. Wildlife & Ecological Investments Page 6

7 Chao1 with bias-corrected: S Chao1 = S obs + f 1 (f 1 1) 2 (f 2 1) Where S obs is the total number of species observed in a sample, f 1 is the number of singleton species and f 2 the number of doubleton species. The variance estimator calculates the degree of uncertainty. Variance estimator: var(s 1) = f 2 [( f 1/f 2 4 ) ⁴ + (f 1 f 2 )³ + ( f 1/f 2 2 ) ² ] To estimate the species richness, we used Chao2 which uses the occurrence data from multiple samples (sites) to estimate the species diversity of the area. Chao2: m 1 S Chao2 = S obs + ( ) m (q 1(q 1 1) ) 2 (q 2 +1) Where m represents the total number of samples, q 1 is species only occurring in one sample and q 2 the species occurring in two samples. Similar to Chao1, the variance estimator calculates the degree of uncertainty. Variance estimator: var(s Chao2) = q 2 [ A 2 (q 1 q 2 ) ² + A 2 ( q 1 q 2 ) ³ A2 ( q 1 q 2 ) ⁴] The impact of elephants on woody vegetation was analysed by generating an impact score (IS): % impacted = ( si Nti )x1 Where si is the number of trees of the species or height category impacted and N ti is the total number of trees impacted. % availability = ( s ) x 1 Nt Where s is the number of tree species or height category measured and N t is the total number of trees. IS = %impacted %availability If the resulting IS value is < 1. then there was no selection, if the value is >1. this demonstrates selection. If the species was impacted but not selected for then it was likely because of availability and not for preference. To verify this, we used the Jacobs s Index. We also used the Jacob s Index to identify if there was a preference for either a species or a height category: D = r p r+p 2rp Where r is the proportion of the impacted trees by elephants in a year and p is the proportional availability of each species given the total trees sampled. The resulting values range from +1 which is maximum preference and -1 which is maximum avoidance. Wildlife & Ecological Investments Page 7

8 Mean Rainfall (mm) Mega-herbivores The mega-herbivores that were monitored included elephant, buffalo and both black and white rhino. During game transects and drives through the reserve details regarding the observation of these mega-herbivores was recorded. This included the local, group size, age and sex ratios. The habitat that the animals were in was also recorded. This was divided into wet (between October and April) and dry season (between May and September) determined using rainfall data for the area from literature (Figure 2). The wet season rainfall is critical because it controls the vegetation growth and the annual food production for herbivores. Rainfall during the dry season helps to extend food availability for herbivores during the critical time when resources are scarce. For this reason, we used both the seasonal and annual rainfall patterns for the analysis. We identified the total number of days that drives were taken and the number of days each of the mega-herbivores were seen. This allowed us to estimate the number of days the animals were likely utilising the habitat. We used the proportion of days seen and not the total numbers to compensate for days when no drives were conducted Figure 2: Mean monthly rainfall (mm) from data collected in 212 to 216. Results Annual mean rainfall in the area is 492 mm therefore a drought at 75% below the mean was defined at 123 mm (Vogel 1994). Below average rainfall that was classified as drought was reported in 1997, 22 and more recently in 216 (Figure 3). From the start date of data collection in Struwig, the annual rainfall has been steadily declining (Figure 4). Although rainfall data collection for 216 is not yet complete, at the time of writing this report the mean rainfall was already within the drought category. Struwig is an open system most herbivores have the ability to relocate to other areas where resources may be greater. When we analysed the rainfall data, animal movement and frequency of observation during game drives we could better identify trends and patterns. Wildlife & Ecological Investments Page 8

9 Mean rainfall (mm) / / / /216 Mean rainfall (mm) Figure 3: Mean rainfall in with drought being defined as 75% mean annual rainfall as indicated with the orange line /13 213/ / /216 Figure 4: Mean rainfall (mm) during WEI study periods, between 212 and 216. Habitat assessments When we compared the methodology of habitat assessments between the I ha plots and the 15 x 15m plots of 215. When the methods were compared they both indicated similar patterns of woody vegetation abundance. However, overall the 15 x 15m plot did not sufficiently reflect the richness and diversity. In regards to impact on the vegetation, the methods were comparable. The total number of sites measured each year differed slightly due to accessibility, the number of people available and other unforeseen circumstances (Table 2). A total of 87 tree species was recorded between 212 and 216. Wildlife & Ecological Investments Page 9

10 Table 2: Number of sites measured each year between 212 and 215 and the number of trees measured at each site. Year # of sites surveyed # of trees measured # of species Of the trees measured there was greatest representation in the 1-2 m and the 2-4 m height category for all years (Figure 5). Trees below the 4m height category had the greatest impact detected (Figure 6 and 7). We did not detect a significant difference between sites in terms of the number of trees measured in 212 (F 9,8 = p<.5), 213 (F 9,14 = 1.14, p>.5), and in 214 (F 9,11 =.89 p>.5) using the One-Way ANOVA Available Impacted Figure 5: The total number of trees measured that were available and impacted in the different height categories over the study period 212 to >1 Wildlife & Ecological Investments Page 1

11 Number of trees measured Impact Score > Figure 6: The Impact Score of trees measured in the different height categories over the study period 212 to S4P1 S4P2 S4P3 S4P4 S5P1 S5P2 S5P3 S5P4 S5P >1 Figure 7: Height of trees measured in 215 with increasing distance from water (P1 = 3-1m to P4 1km). Wildlife & Ecological Investments Page 11

12 When comparing the woody species abundance, richness and diversity with distance from water, we found that according to Chao1 woody abundance increased with distance from water with 3km being the distinct difference. Similarly, we found that according to Chao2 woody species richness increased slightly with distance from water again with a distinct difference from 3km. Site 8 and 13 had the greatest species richness. Of the 87 tree species measured (Figure 8A) we found that there were seven species that were preferred, Vachellia erubescens, V. nigrescens, Combretum apiculatum, C. hereoense, Dichrostachys cinerea, Grewia bicolor, G. flavescense, G. monitocla, Sclerocarya birrea and Terminalia pruniodes. Of these species using the impact score (IS), in 212 Combretum apiculatum, Terminalia pruniodes and Grewia bicolor had the greatest impact. In 213 Combretum apiculatum, C. hereoense and Sclerocarya birrea had the greatest impact. In 214 Sclerocarya birrea and Combretum apiculatum had the greatest impact scores. In 216, the data suggests that Combretum heroense and Grewia flavenscens had the greatest impact (Figure 8B). To verify if species were selected because of availability or if they were preferred we used the Jacob s Index. According to the Jacob s Index, in 212 Vachellia nigrescense, Combretum hereoense and Dichrostachys cinerea were preferred. In 213 Dichrostachys cinerea and Combretum hereoense were preferred. In 214, according to the Jacob s Index, Combretum apiculatum was preferred and in 215, according to the Jacob s Index, Vachellia erubescens and V. nigrescense were preferred. From the data collected we began to compare the use of woody vegetation of meso-herbivores and elephants. We compared the proportion of impact on woody vegetation caused by browsers and elephants across the years (Figure 9). The extent of impact caused by browsers was generally between 11% and 25 % and classified as secondary branch damage. For this report the elephant damage categories we focused on were K (secondary branches or smaller branches). We used this category because it best represents both mega and meso-herbivore feeding behaviour. Wildlife & Ecological Investments Page 12

13 A B Figure 8: The total number of each tree species measured in the study period from 212 to 216 (A) and the Impact Score of the recorded woody species cross the study period from 212 to 216 (B). Wildlife & Ecological Investments Page 13

14 A B C D E F G J K JK Figure 9: Primary (A-G) damage and secondary (J-K, JK) damage on the woody vegetation by elephants and browsers during the study period 212 to 216. For ease of assessing and determining the movement of the browsers and the elephants, the sites were categorised according to landscape features and general habitat characteristics. We were able to classify the sites into five main categories; Hill slope (slope greater than 3 ), Dry Riverbed (Olifants River), Plateau (similar to plains) and Crest (inaccessible to elephants). We did not conduct a floristic classification because of the lack of statistical support. Only site number 13 and 8 had statistical support. According to the habitat types we did manage to categorise, site 8 was classified as Crest. The lack of statistical support is likely due to the ecological and environmental conditions in the area. We compared only the secondary elephant impact with the meso-herbivores to determine the proportion of woody impact per habitat type. In 212 and 213, the meso-herbivores had greater impact than elephants however in 214 and 216, the elephants had greater impact (Figure 1). In 214 and 216 we were unable to measure the vegetation impact on the crest due to inaccessibility. Mega-herbivores The sightings of the mega-herbivores were categorised into the same habitat types as the habitat assessments and were classified into dominant and secondary vegetation selected. This was then divided into seasons. The buffalo were predominantly seen in the Hill Slope habitat (55%) and secondary was in the Olifants River (29%). When divided into seasons, the Hill slope remained the dominant habitat where the buffalo were seen. The white rhino was predominantly seen in the Hill slope habitat (8%) and secondarily in the river (14%). There was insufficient data to determine seasonal preference. The elephant were predominantly seen in the Hill Slope habitat (59%) and secondarily in the Plateau (27%) and the Olifants River (21%). Generally, the primary preferred habitat was the Hill Slope and the Plateau. As the secondary habitat type, the mega-herbivores were generally seen either in the Olifants River and on the Plateau proportionately. Wildlife & Ecological Investments Page 14

15 Dry riverbed Hill slope Plateau Crest 2 1 Dry riverbed Hill slope Plateau Crest Browsers Elephants Browsers Elephants Dry riverbed Hill slope Plateau Crest Dry riverbed Hill slope Plateau Crest Browsers Elephants Browsers Elephants Figure 1: Proportion of woody vegetation impacted by elephants and browsers in 212, 213, 214 and 216 in the different habitats. Wildlife & Ecological Investments Page 15

16 We counted the number of days the elephants, buffalo and rhino were seen on game transects and compared this to the mean annual rainfall each year (Figure 11). There was a positive correlation between the number of days the mega-herbivores were seen on the reserve and the mean rainfall (R =.79) We specifically focused on the elephants so we could compare the impact score against the amount of time the elephants were seen in the area (Figure 12). There was a positive correlation (R =.2) between the amount of impact caused by elephants and the number of days the elephants were seen on the reserve Elephant Buffalo Rhino rainfall avg Figure 11: Proportion of days elephant, buffalo and rhino were seen on the reserve between 212 and 216 (excluding 215) and the average rainfall (mm) each year Elephant Days Elephant Impact Figure 12: The proportion of elephant impact given the proportion of days elephants were seen on Struwig Eco-Reserve between 212 and 216 (excluding 215).

17 Discussion The 1ha plots provided the best data regarding tree abundance, richness and diversity. The 15 x 15m plots did address the question of impact on vegetation however it did not adequately account the species richness and diversity. The data suggests that there was a positive relationship between the amount of time the megaherbivores were seen on the reserve and the mean rainfall each year. This is likely due to water availability in the Olifants River. The data further suggests that the elephant impact increased as the number of elephant days increased. As the mean rainfall decreased, the mega herbivores spent more time on the reserve or near the river. This explains why the damage increased with decreasing rainfall. Recommendations From the data collected, measuring the facilitation or competition by elephants and browsers could be further analysed. We suggest monitoring elephant feeding behaviour through direct observation. This will allow us to quantify how the elephants are using the habitat as mean annual rainfall fluctuates. Over the long term we will then better detect and anticipate the elephant impact. Although we did not analyse the amount of insect damage to the woody vegetation, it may be appropriate to assess if there is a relationship or pattern of insect impact on vegetation as a consequence of vulnerability from damage caused by elephants. We could adapt the methodology of distributing plots with distance from roads rather than distance from water. At the moment the plot distance from roads is within 2m, this will have to change by increasing the increments of distance. We will continue to use the 1ha plots as these provide the most relevant empirical data. The data collected to date provides an opportunity for future analysis as we continue surveying over the long term. We currently gather very detailed information from few sites in a small area. The lack of significance with some of the results is likely due to the lack of data from a larger survey area. From the data collected and the information provided thus far, we could significantly increase the number of survey sites throughout Balule Game Reserve so that we can start to develop species distribution maps and impact scores on vegetation for the wider area. We could then better map species richness and diversity facilitating the development of a floristic map of the reserve. Furthermore, we could detect trends and patterns and monitor the health of a greater ecosystem. The bird life recorded from Struwig was entered and sent to Birds in Reserves Project (BIRP) which is one of the largest Citizen Science projects based at University of Cape Town. The data is used to identify and collect the occurance of birds in South African protected areas. This data helps to identify if there are threatened or endangered birds that are nesting or using the area as part of their migration route. We suggest that in a larger area we can better supply BIRP with data regarding the occurrence and nesting/breeding activity of birds of interest. Acknowledgements Thank you to the WEI team who supervised the collection of the data and the students from Operation Wallacea who spent time in the field collecting the data. References Owen-Smith, N. & Chafota, J Selective feeding by a megaherbivore, the African elephant (Loxodonta Africana). Journal of Mammalogy. 93(3): Wildlife & Ecological Investments Page 17

18 Loarie, S.R., van Aarde, R.J & Pimm, S.L. 29. Elephant seasonal vegetation preferences across dry and wet savanna. Biological Conservation. 142: Maponya, P. & Mpandeli, S Impact of drought on food security in Limpopo province, South Africa. African Journal of Agricultural Research. 7(37): Viljoen, J.J., Reynecke, H.C., Panagos, M.D., Langbauer, W.R. & Ganswindt. A Seasonal selection preferences for woody plants by breeding herds of African elephants (Loxodonta africana) in a woody savanna. International Journal of Ecology. Vogel, C (Mis)management of droughts in South Africa: past, present and future. South African Journal of Science. 9: 4 6. Wildlife & Ecological Investments Page 18