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Seasonal movements and habitat use of African buffalo in Ruaha National Park, Tanzania

Seasonal movements and habitat use of African buffalo in Ruaha National Park, Tanzania Background: Assessing wildlife movements and habitat use is important for species conservation and management and can be informative for understanding population dynamics. The African buffalo (Syncerus caffer) population of Ruaha National Park, Tanzania has been declining, and little was known about the movement, habitat selection, and space use of the population, which is important for understanding possible reasons behind the decline. A total of 12 African buffalo cows from four different herds were collared with satellite transmitters. Movements were assessed over 2 years from 11 animals. Results: The space use of the individual collared buffaloes as an approximation of the 95% home range size esti- mated using Brownian bridge models, ranged from 73 to 601 km . The estimated home ranges were larger in the wet season than in the dry season. With the exception of one buffalo all collared animals completed a wet season migra- tion of varying distances. A consistent pattern of seasonal movement was observed with one herd, whereas the other herds did not behave the same way in the two wet seasons that they were tracked. Herd splitting and herd switch- ing occurred on multiple occasions. Buffaloes strongly associated with habitats near the Great Ruaha River in the dry season and had little association to permanent water sources in the wet season. Daily movements averaged 4.6 km (standard deviation, SD = 2.6 km), with the longest distances traveled during November (mean 6.9 km, SD = 3.6 km) at the end of the dry season and beginning of the wet season. The shortest daily distances traveled occurred in the wet season in April–June (mean 3.6 km, SD = 1.6–1.8 km). Conclusion: The Great Ruaha River has experienced significant drying in the last decades due to water diversions upstream, which likely has reduced the suitable range for buffaloes. The loss of dry season habitat due to water scar - city has likely contributed to the population decline of the Ruaha buffaloes. Keywords: African buffalo, Habitat use, Home range, Ruaha National Park, Tanzania Background Understanding wildlife movements and habitat use is critical for species conservation and management on a landscape scale [1]. Information on emigration and immigration, habitat preferences, and herd interactions may be important for evaluating population dynam- *Correspondence: aroug@ucdavis.edu Epaphras A. Muse and Deana L. Clifford contributed equally to this work ics [2]. Movement data can also be used to identify Karen C. Drayer Wildlife Health Center, University of California, 1089 critical interfaces for potential disease transmission Veterinary Medicine Drive, Davis, CA 95616, USA between wildlife and domestic animal species [3]. The Full list of author information is available at the end of the article © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Roug et al. BMC Ecol (2020) 20:6 Page 2 of 13 movements and habitat preferences of large ungulate The GPS collars were used to determine movements species such as African buffaloes (Syncerus caffer) has as well as habitat use of African buffaloes in Ruaha been studied in multiple locations across Africa, includ- National Park in order to better understand possible ing South Africa [4], Botswana [5, 6], and Namibia [7, seasonal population impacts from herds entering sur- 8]. Migratory behavior ranged from resident [5], par- rounding reserves or risks of contracting disease from tially migratory [7], to long distance [8]. In Tanzania, local livestock populations at the borders of the park. We African buffalo ecology has been studied extensively expected that the main herds of the park completed sea- in the Serengeti in northern Tanzania [9], but limited sonal movements, but mainly stayed within park bounda- information is available from other areas of Tanzania. ries while utilizing the wildlife management area near the Over recent decades, the African buffalo popula - Great Ruaha River and bordering village lands. Gathered tion in Ruaha National Park in south-central Tanzania information could contribute to understanding possible appeared to be declining. Subjectively, park staff and reasons for the observed population decline and ben- tourist guides reported seeing fewer buffaloes than in efit Ruaha National Park for future management of this the past, and a decline in absolute numbers was con- species. firmed when comparing aerial counts conducted in comparable areas in the dry seasons of 2004 and 2013 Results (https ://www.halip rojec t.org, unpublished). In addi- Collaring tion to the suspected decline in numbers, park staff and A total of 5 adult cows were collared in a 700–1000 tour operators reported rarely seeing buffaloes in the animal mixed (both males and females) buffalo herd wet season between November and May, but no infor- near Mwagusi, 4 adult cows were collared in a large mation existed on annual herd movements and habitat 400 + mixed buffalo herd near Jongomero, 2 adult cows use. Buffaloes are seasonally hunted in game reserves in a mixed 100–200 animal large herd near TelekiMboga, surrounding the park, but as herd movements were not and one in a small, 30–40 animal herd with mainly bulls known, it was unclear whether the park’s buffaloes con - and a few cows between TelekiMboga and Jongomero stituted a part of the hunted population. (Figs. 1, 2). Ten of the buffaloes were collared in October As an additional concern, Ruaha National Park’s main 2014 and two in September 2015. One collar from 2015 water source, the Great Ruaha River, has experienced was only active for approximately 4  months (SAT1500), significant drying since the 1990s due to water diver - and data from this animal were not included in the habi- sions for agricultural irrigation upstream [10]. Buf- tat use, home range analyses, or movement analyses. faloes are water dependent [11], and access to water determines which areas can be utilized by buffaloes in Home ranges and movement the dry season [6, 12]. Further, the reduction in flow The 95% and 50% home range sizes, as estimated by of the Great Ruaha River has seasonally increased the computing isopleths of the utilization distribution using pressure on remaining water sources, and possibly Brownian Bridge Models (BBMM), were calculated for increased the interaction between livestock and wild- each individual buffalo within four time periods (Novem - life at the park’s boundaries [13]. Local cattle herds are ber–May = wet season, and June–October = dr y season known to be affected by bovine tuberculosis and bru - for 2  years) as well as overall (Table  1). The areas that cellosis, and bovine tuberculosis has been detected the buffaloes utilized varied with the largest for SAT in 8 wildlife species outside the park [14, 15]. African 1494 (overall 95% estimated home range = 601  km ) buffaloes are considered maintenance hosts for bovine and smallest for SAT 1495 (overall 95% estimated home tuberculosis [16], and while this disease is not thought range = 73  km ). Estimated home ranges were larger in to cause population declines in buffaloes, it may the wet season compared to the dry season for all the col- increase the populations susceptibility to other stress- lared buffaloes, and buffaloes consistently stayed closer ors such as drought [17]. to permanent water sources in the dry season. The Health for Animals and Livelihood Improve - Early in the 2014–2015 wet season, the buffaloes col - ment (HALI) project, a University of California, Davis lared in the same herd near Mwagusi (SAT 1494, 1497, and Sokoine University of Agriculture, Morogoro col- 1498, and 1503, Fig.  2a–d) split up into separate groups laborative project, and Ruaha National Park, partnered as reflected of moving several kilometers apart from each to investigate the apparent buffalo decline. Components other, but then reunited in the middle of the wet season of the study included an aerial population count, demo- and migrated to the high elevation plateau near Ilan- graphic surveys, health assessments, and marking buffa - gulu (Fig.  2a–d). In the second wet season, the Mwagusi loes with GPS collars. buffaloes split again without reuniting, with SAT 1494 (Fig.  2a) and SAT 1498 (Fig.  2b) moving to the locations Roug et al. BMC Ecol (2020) 20:6 Page 3 of 13 the wet season for all but one animal (SAT1495), which appeared to be resident (Fig.  3). The distances trave - led were largest for the buffaloes collared near Mwagusi (SAT1494, 1497, 1498, and 1503, Figs. 2a–d, 3), followed by the two buffaloes collared near TelekiMboga/Mdonya (SAT1492 and 1493, Figs.  2f, g, 3). The Jongomero buf - faloes (SAT 1496, 1499, 1501, and 1502, Figs.  2h–k, 3) only moved a short distance from the dry season habi- tat. After the wet season, the buffaloes largely returned to the previous dry season’s habitat by July, except for in the second wet season where two buffaloes collared near Mwagusi (SAT1494 and 1492, Fig. 2d, e), who had moved to Mdonya during the second wet season, did not return to the previous dry season’s habitat. Resource selection Our top models for both the dry season and wet season contained most of the AIC weight (wi > 0.65 for the dry season and 0.42 for the wet season). Models ranked below the top model within each season were judged to con- tain uninformative parameters or coefficients [18] that were so similar to the top model for each season that we elected not to model average. The top model for dry sea - son versus wet season were similar with only slope miss- Fig. 1 Overview of the Greater Ruaha Ecosystem in Tanzania and ing from the dry season and aspect excluded from the approximate capture locations of the collared African buffalo. wet season. In the dry season, the buffaloes selected habi - 1 = Mwagusi, 2 = Mdonya, 3 = Telek iMboga, 4 = Jongomero. Other features shown: 5 = Escarpment, 6 = Pawaga-Idodi Wildlife tats at lower elevation and in more rugged terrain closer Management Area. GR game reserve, GCA game controlled area to the river compared to the wet season (Table 2, Fig. 4). (Creator and copyright holder: A. Roug) All vegetation types except closed to open woody vegeta- tion were preferred in comparison to the reference cat- egory (very open trees with 15–40% crown cover), with the strongest selection for open to closed herbaceous near Mdonya, and SAT 1497 (Fig.  2d) moving into the vegetation on temporary flooded land, closed shrubs, wildlife management area between the park and village open shrubs or with 40–65% crown cover, closed trees land. In contrast, the movement of the Jongomero buf- on temporarily flooded land, isolated rainfed herbaceous faloes (Fig. 2h–k) was quite consistent across years, with crops, and scattered rainfed herbaceous crops (Table  2, buffaloes moving closer to the Great Ruaha River in the Fig. 4). The latter two vegetation types were only present dry season and into more rugged and remote areas near in the wildlife management area adjacent to the park, the escarpment in the wet season. No spatial overlap where SAT1497 spent part of a dry season and an entire between the Jongomero buffaloes and other buffaloes wet season (Fig. 2d). In the wet season (November–May), were observed (Fig.  2). The buffaloes collared near Tel - the association with distance to the river was weaker than ekiMboga (SAT 1492 and 1493, Fig.  2e–f ) spent the first in the dry season, and the selection for vegetation types wet season near Mdonya, but in the subsequent wet sea- containing more shrub and trees was stronger, such as son, SAT 1492 (Fig. 2e) appeared to switch herds and join closed to open woody vegetation, shrub savannah, open the Mwagusi buffaloes (SAT 1494 and 1498, Fig.  2a, b) to closed shrubs on temporarily flooded land, and closed near Mdonya, whereas SAT1493 (Fig.  2f ) moved across trees on temporarily flooded land (Table 2, Fig. 4). the Ruaha River and spent the entire wet season south of the Great Ruaha River. In the following dry season both buffaloes stayed near the river around TelekiMboga Daily movements (Fig. 2e–f ). The distance traveled in the previous 5 h was highest for These movements were reflected as net displacement points collected at 10.00 h (mean over all data = 1505  m, from the location of capture (Fig.  3). All buffaloes were SD = 1107 m, n = 1245 points) and 20.00 h (mean over all collared during the height of the dry season, and then data = 1430  m, SD = 969  m, n = 1247 points), and lowest showed movements away from the Great Ruaha River in at 14.00 h (mean = 471  m, SD = 627  m, n = 1235 points), Roug et al. BMC Ecol (2020) 20:6 Page 4 of 13 Fig. 2 Brownian bridge models for 11 adult female African buffaloes in Ruaha National Park, Tanzania. The panels show the individual models for buffaloes collared near Mwagusi (a–d), TelekiMboga (e–f), TelekiMboga/Jongomero (g), and Jongomero (h–k). The collars were active between October 2014 and April 2017 (see Table 1 for details on collar duration) (Creator and copyright holder: A. Roug) indicating that the buffaloes were crepuscular with the The average total distance moved in 24  h was 4.9  km highest activity levels in the late morning and evening (Standard deviation (SD) = 2.9  km) in November–May and lowest activity level in the heat of the day (Fig.  5). and 4.2  km (SD = 1.9  km) in June-October. The longest The daily movements increased with progression of the distances were traveled during November at the end of dry season and peaked in November, where the average the dry season and beginning of the wet season (mean distance traveled in the last five hours was over 2000  m daily distance = 6.9  km, SD = 3.6  km). The shortest daily twice a day (Fig.  5). The shortest average daily distances distances traveled occurred in the wet season in April– traveled over the previous 5  h were observed in April, June (mean 3.6  km, SD = 1.6–1.8  km). Across both sea- where the mean peak movements in the previous 5  h sons combined, the average daily distance traveled was where less than 1250 m twice a day (Fig. 5). 4.6 km (SD = 2.6 km, n = 6486). Roug et al. BMC Ecol (2020) 20:6 Page 5 of 13 Table 1 Size (in km ) of the 95% and 50% isopleth of the utilization distribution estimated using Brownian Bridge Models (as an approximation of home range sizes), of  each collared buffalo in  Ruaha National Park, Tanzania in  the  rainy (November–May) and  dry (June–October) seasons as  well as  overall (entire time period) Location collared MWG MWG MWG MWG TKM TKM TKM/JGM JGM JGM JGM JGM Time period % use SAT1497 SAT1498 SAT1503 SAT1494 SAT1492 SAT1493 SAT1495 SAT1496 SAT1499 SAT1501 SAT1502 Oct14–May15 95 219 306 290 254 – 205 86 215 246 174 253 Oct14–May15 50 47 59 67 55 – 30 12 44 46 39 49 Jun15–Oct15 95 129 137 136 142 – 98 9 109 100 112 98 Jun15–Oct15 50 27 29 27 28 – 35 1 28 23 28 23 Nov15–May16 95 84 183 – 256 203 101 50 247 203 254 183 Nov15–May16 50 15 25 – 38 42 13 10 57 44 60 42 Jun16–Oct16 95 80 35 – 149 139 51 – 109 96 100 a a a b a a a Jun16–Oct16 50 16 6 – 21 27 8 – 27 23 24 Nov16–Apr17 95 – – – – 345 – – – – – – Nov16–Apr17 50 – – – – 67 – – – – – – Entire time period 95 357 488 290 601 296 304 73 289 283 297 283 Entire time period 50 67 88 67 123 68 47 7 63 58 63 58 Month ended Sept 16 Aug 16 Oct 15 Oct 16 Apr 17 Nov 16 Jan 16 Oct 16 Sept 16 May 16 Oct 16 The space use by year is shown in order to compare variations between seasons and years. MWG = Mwagusi, TKM = TelekiMboga, JGM = Jongomero (–) no data Month ended: The last month that the collar was emitting points. For example, the collar SAT 1497 ceased working in September 2016 For SAT 1493, the data from November 2016 is included in the “entire time period” but not in the Jun 16–Oct 16 time window Roug et al. BMC Ecol (2020) 20:6 Page 6 of 13 Fig. 3 Net displacement in kilometers from location of collaring by year for African buffaloes in Ruaha National park between November 2014 and October 2016. The dry season is indicated with darker shading and wet season with lighter shading. In the first year, buffaloes largely returned to the previous dry season’s habitat near the Ruaha River as illustrated by the distances from the collaring location approaching zero in September– October 2015. In the second year, 3 animals (SAT 1493, 1494, and 1492) did not return to the same location after the second wet season Discussion animals much more independent of the permanent water Our study showed that the space use (estimated home sources. Consequently, the area utilized by the buffaloes ranges) of the individual collared buffaloes varied widely were generally larger in the wet season than in the dry and were consistently larger in the wet season than in season and the buffaloes showed a stronger selection for the dry season. Buffaloes showed strong preference for shrubby and woody habitats in the wet season (Table  2, habitats near the Great Ruaha River in the dry season Fig.  4). Shorter daily travel distances for collared buffa - and less association to permanent water sources in the loes in the middle of the wet season, especially during wet season. With the exception of one buffalo, all collared April–May, compared to the beginning of the wet season animals completed a wet season migration of varying dis- (November–December) can be explained by the fact that tances, and daily distances traveled were longest during some animals ranged widely in the beginning of the wet the late dry season and shortest in the height of the wet season before settling into an area with abundant forage season. Several buffaloes appeared to switch herd during for the wettest month of the year (Fig. 5). The size of the the study period. Buffaloes utilized the Wildlife Manage - areas utilized were quite variable among the individual ment Area on the southeastern border of the park, but animals, and the largest area was observed with SAT1494 did not venture into game reserves bordering Ruaha to (95% estimated home range size of 601  km across all the north and northeast. season) and the smallest with SAT1495 (95% estimated home range size of 73  km across all seasons). SAT1494 Home ranges and movements was collared in a 700 + animal herd near Mwagusi, During the dry season in Ruaha, water is limited to a whereas the herd with SAT1495 likely did not have more few springs and the Great Ruaha River, constraining the than 20 animals at any time. Larger home range sizes for buffaloes to stay much closer to the river than in the buffaloes belonging to larger herds has been reported in wet season, when seasonal pools and springs make the buffalo herds from the Kruger National Park in South Roug et al. BMC Ecol (2020) 20:6 Page 7 of 13 Table 2 Dry season (June-October) and  wet season Nature Reserve in South Africa, the estimated home (November–May) resource selection models for  11 adult range sizes ranged from 170.7 to 327 km using the same female African buffaloes in Ruaha National Park, Tanzania methodology [4], and home ranges for two breeding herds in the Sengwa Wildlife Research Area of Zimbabwe Parameter June–October November–May were reported as 207 and 286 km [21]. Coefficient SE Coefficient SE Another factor that may have influenced the home Intercept − 0.076 0.192 − 0.762 0.069 range size measured in several buffalo was herd switch - ELEV (m) − 0.761 0.228 0.261 0.013 ing, or, for SAT1494 and 1498, at least movement into Rugged 0.076 0.016 − 0.024 0.013 areas that was occupied by different buffaloes during the DISTRIV (m) − 0.126 0.021 − 0.067 0.015 previous wet season (Fig. 2a, b). Herd switching was also Aspect − 0.045 0.014 – – reported from Botswana buffalo herds, where 7 out of 45 Slope (%) – – − 0.055 0.012 collared adult female buffaloes switched herds [22], but contradict earlier literature that generally considered V_OP_TR_15_40% CC Ref Ref Ref Ref buffalo cows to inhabit stable herds without inter-herd OP_TR_40_65%CC 0.610 0.057 0.464 0.042 movements [9, 23]. The difference between the earlier TR_SHR_SAV 0.603 0.055 0.843 0.041 literature and the observations in our and the Botswana OP_SHR_40_65% CC 1.141 0.056 0.809 0.041 study can likely be explained by the use of GPS collars CL_OP_WOODVEG − 1.505 0.525 0.485 0.179 in the Botswana and our study, as more fine scale move - SHR_SAV 0.412 0.069 1.276 0.047 ment data can be obtained with GPS technology. OP_CL_HRBVG_TEMP_FL 2.007 0.074 1.407 0.057 While herd switching was observed, herds also V_OP_SHR_15_40% CC 0.677 0.099 0.277 0.059 appeared to avoid each other to some degree. Two buf- OP_CL_SHR_TEMP_FL 0.399 0.093 1.602 0.056 faloes were collared near TelekiMboga (SAT1492 and CL_TR_TEMP_FL 0.923 0.121 1.079 0.098 1493, Fig. 2e, f ), and while SAT1492 joined the buffaloes CL_SHR 1.506 0.181 1.704 0.135 coming from Mwagusi (SAT 1494 and 1498, Fig. 2a, b) in IS_RF_HERB_CRP 2.125 0.239 2.893 0.157 the second wet season (Fig.  2e), SAT 1493 moved south SCAT_RF_HRB_CRP 2.362 0.203 2.594 0.176 of the river and did not appear to share the same area CL_TR – – 10.064 43.955 as SAT1493, 1494, and 1498 in the subsequent dry sea- The collars were active for varying durations between October 2014 and April son (Fig.  2f ). Also, the Jongomero buffaloes (Fig.  2h–k) 2017. Models were generated using mixed-effects logistic regression models with a random intercept specified for each buffalo and herd. The continuous never directly overlapped with areas occupied by any of covariates were standardized to improve model performance and allow for the other collared buffaloes even though they frequently comparison of effect sizes across variables. A priori models were developed for each season and then ranked by model weight using the Akaike Information moved into areas adjacent to the range occupied by Criterion. ELEV (m) = elevation in meters, RUGGED = ruggedness, DISTRIV SAT1495 (Fig. 2g). One collared buffalo (SAT 1497) spent (m) = distance to nearest river in meters, V_OP_TR_15_40% CC = very open trees with 15–40% crown cover, OP_TR_40_65% CC = open trees with 40–65% crown an entire wet season in the wildlife management area cover, TR_SHR_SAV = trees and shrub savannah, OP_SHR_40_65% CC = open outside the park (Fig. 2d). It is possible that the buffaloes shrubs with 40–65% crown cover, CL_OP_WOODVEG = closed to open woody that ventured into the wildlife management area were vegetation (thicket), SHR_SAV = shrub savannah, OP_CL_HERBVEG_TEMP_ FL = open to closed herbaceous vegetation on temporarily flooded land, trapped there during the wettest time of the year as the V_OP_SHR_15_40% CC = very open shrubs with 15–40% crown cover, OP_CL_ river was unusually high during the second wet season SHR_TEMP_FL = open to closed shrubs on temporarily flooded land, CL_TR_ TEMP_FL = closed trees on temporarily flooded land, CL_SHR = closed shrubs, and likely did not allow for buffaloes crossing safely, espe - IS_RF_HERB_CRP = isolated (in natural vegetation or other) rainfed herbaceous cially with small calves. More data are needed in order to crops, SCAT_RF_HERB_CRP = scattered rainfed herbaceous crop, CL_TR = closed understand the observed movements and elicit any con- trees, SE = standard error, Ref = reference category for categorical variables sistent patterns in the Mwagusi and TelekiMboga herds. Movement of animals can be classified as migratory, Africa and the Caprivi strip in Namibia [7, 19]; however, mixed migratory, dispersal, or non-migratory using net whether the estimated home range sizes truly were rep- square displacement [24, 25]. From a buffalo study in the resentative of what the buffaloes do every year is difficult Caprivi strip of Namibia a fifth class of migratory behav - to ascertain based on only 2 years of data. The 2015–2016 ior, “expanders”, has been suggested, which are animals wet season had unusually high levels of precipitation [20] that expanded their range rather than moving entirely and water was likely not a limiting factor anywhere in the away from their dry season home ranges during the wet park. This may have influenced how buffaloes moved in season [8]. The Jongomero buffaloes did move from their the second year. In comparison, home ranges from adult dry season location to areas closer to the escarpment, but female African buffalo collared near the Caprivi strip also regularly returned to areas that were used during in Namibia ranged from 5.5 to 564.7  km using the 90% the dry season, and could, therefore, tentatively be clas- Local Convex Hull method [7]. In the Klaserie Private sified as expanders. The buffaloes collared near Mwagusi Roug et al. BMC Ecol (2020) 20:6 Page 8 of 13 (See figure on next page.) Fig. 4 Vegetation and habitat selection in June–October (dry season) and November–May (wet season) within a polygon surrounding all collar points from 11 adult female African buffaloes collared in Ruaha National Park between October 2014 and April 2017 (see Table 1). The relative probability of use (Use) was based on the habitat selection models shown in Table 2. Abbreviations for vegetation types: CL_HERB_PERM_ FL = closed herbaceous vegetation on permanently flooded land, CL_SHR = closed shrubs, CL_OP_WOODVEG = closed to open woody vegetation (thicket), CL_TR = Closed trees, CL_TR_TEMP_FL = closed trees on temporarily flooded land, IS_RF_HERB_CRP = isolated (in natural vegetation or other) rainfed herbaceous crops, OP_SHR_40_65% CC = open shrubs with 40–65% crown cover, OP_CL_HERBVEG_TEMP_FL = open to closed herbaceous vegetation on temporarily flooded land, OP_CL_SHR_TEMP_FL = open to closed shrubs on temporarily flooded land, OP_TR_40_65% CC = open trees with 40–65% crown cover, RAIN_TR_CRP = rainfed tree crop (mixed unit with natural vegetation or other), SCAT_RF_HERB_ CRP = scattered rainfed herbaceous crop, SHR_SAV = shrub savannah, TR_SHR_SAV = trees and shrub savannah, V_OP_SHR_40_15% CC = very open shrubs with 15–40% crown cover, V_OP_TR_15_40% CC = very open trees with 15–40% crown cover (Creator and copyright holder: A. Roug) and TelekiMboga/Mdonya behaved differently in the Resource selection 2 years they were observed and, based on available data, As expected, buffaloes selected habitats near the river could therefore be categorized as mixed migratory, and in the dry season compared to the wet season when SAT1495 did not migrate (Fig. 2g) and could therefore be rainfall made water abundant across the park. Similar classified as non-migratory or resident [8]. observations have been reported in other locations; e.g. in the Caprivi strip of Namibia buffaloes moved to the Daily movements flood plain near the rivers and adjacent woodland in the The patterns of daily distances traveled were consistent dry season and moved away from rivers into areas with with field observations, as buffaloes usually were seen ephemeral water in distant woodland in the wet season arriving at the river between 8 and 11 in the morning, [7]. However, in studies from the Doornkloof Nature and again around 16 and 19 in the afternoon and evening Reserve in the Nama-Karoo in the Northern Cape Prov- (Fig. 5). The daily movements increased with progression ince of South Africa, and Klaserie Private Nature Reserve of the dry season and peaked in November, which is the in South Africa, buffaloes ranged farther and wider in last month of the dry season, when animals are forced to the dry season than in the wet season in order to find travel longer distances to find adequate forage but have adequate forage [4, 29]. Similar observations were made to return to the river on a daily basis to drink. The end in Kruger National Park, South Africa, where buffaloes of November is also the beginning of the rainy season ranged farther in dry years than in wet years [12]. when buffaloes moved away from the area around the None of the collared buffaloes ventured into the north - Great Ruaha river to their wet season habitats. The short - ern game reserves during the hunting season, and only est daily distances traveled were observed in April (Fig. 5) one herd spent significant time outside the park within which is the middle of the wet season, where abundant the wildlife management area. Harvest of animals is forage and availability of seasonal pools makes it unnec- therefore unlikely to have a direct population impact for essary for the buffaloes to travel long distances to find the observed herds. Whether other herds in which no water. collars were placed are impacted by hunting pressure The average daily distance moved of 4.6  km cannot be elicited from our data. (SD = 2.6  km) is lower than what has been reported Nonetheless, buffaloes are occasionally detected with in other buffalo herds. Buffalo herds in Cameroon, for camera traps on village land (Ruaha Carnivore Pro- example, moved an average of 7.2 ± 2.62  km in the dry ject, personal communication), indicating that they do season and 5.6 ± 0.87  km in the wet season [26]. Buf- spend time outside the park. The extent of contact with faloes in the Sengwa Wildlife Research Area of Zimba- livestock and consequent risk of disease transmission bwe moved an average of 6.1  km (SD = 2.02  km) in the between these species is unknown. Studies from Uganda dry season [21], and buffaloes in Rwenzori National and Zimbabwe showed that direct contact between cat- Park in Uganda moved an average of 9.6  km per day tle and buffaloes is unlikely [30, 31] and disease transmis- (range = 5.2–14.4  km) [27]. In contrast, breeding herds sion between buffaloes and cattle therefore likely occurs of buffaloes in Kruger National Park moved an average of through shared environments and not through direct only 3.35  km per 24  h (standard error = 0.35  km); how- contact. ever, this distance did not vary with season, indicating that reliable water and grazing was available in both the Conclusions wet and dry seasons [28]. The seasonal pattern of buffalo movement observed suggests that the Ruaha buffaloes may be restricted in their movement during the dry season due to depend- ence on a few perennially available water sources, which Roug et al. BMC Ecol (2020) 20:6 Page 9 of 13 Roug et al. BMC Ecol (2020) 20:6 Page 10 of 13 Fig. 5 Mean and 95% confidence intervals of distance moved (in meters) in the previous 5 h by time of day and month, based on data from 11 collared adult female African buffaloes from 4 herds in Ruaha National Park, Tanzania. The time of sunrise and sunset is indicated for each month by the black vertical lines consequently increases the pressure on the habitat impact of seasonal water scarcity on Ruaha’s wildlife, and around these areas. Hunting is unlikely to have major benefit the conservation of buffaloes in Ruaha National impact on the buffaloes in the core herds of the park, and Park. On a broader scale, our observations demonstrate buffaloes generally appeared to be in good health with the importance of linking population data, migration, adequate calf recruitment as observed during the cap- habitat preferences, and ecosystem changes in order to ture work and based on demographic surveys, although understand population dynamics of large ungulate spe- the recruitment varied with rainfall [32]. Our study find - cies in Africa and beyond. ings may therefore indicate that the buffalo population in Ruaha declined due to seasonal reductions in the flow of Methods the areas main water source, the Great Ruaha River. As a Study area water-dependent species, the area of suitable and reach- Ruaha National Park, Tanzania’s largest national park, is able habitat would have diminished drastically with dry a part of the Rungwa-Kizigo-Muhesi ecosystem and cov- season cessation of water flow. Additional movement ers an area of 20,226  km [33]. The park is bordered by data, including collaring of buffaloes belonging to herds game reserves to the north-east and a wildlife manage- along the border of Ruaha’s protected areas, is needed to ment area to the south-east (Fig.  1). Together, this eco- fully delineate the home ranges and habitat preferences. system spans an area of over 45,000 km , making it one of Long term monitoring of water flow and buffalo popu - the largest contiguous wilderness areas in the world [13]. lations trends may increase the understanding of the The rainy seasons extend from November to February Roug et al. BMC Ecol (2020) 20:6 Page 11 of 13 and from March to April, and annual mean precipita- (GDEM) [36]. The elevation (in meters), slope (per - tion is 500–800  mm [33, 34]. The vegetation is domi - cent), aspect (north, south, east, west), distance to near- nated by miombo woodland in the south-western part est river (Euclidian distance, in meters), and ruggedness of the park and commiphora-combretum woodland and were calculated in ArcMap (vs. 10.6, ESRI, Redding, CA, acacia Savannah in the central and eastern parts of the USA) from the GDEM data. We evaluated habitat selec- park [34]. Main rivers include the Great Ruaha, Mzombe, tion at the 3rd order [37]. For each buffalo and season Mdonya, Mwagusi and Jongomero rivers [33]. The south - (November–May = wet season, and June–October = dr y ern portion of the park is located within a valley, and the season), data on vegetation type, elevation, slope, rug- valley edge creates a steep escarpment extending from gedness, aspect, and distance to river were extracted for the north-east to the south-west [33] (Fig. 1). each collar point. Shapefiles delineating the 99% isopleth of the utilization distribution generated with the Brown- ian bridge models were used as boundaries for creating Collaring an equal number of random points as there were collar The locations of major buffalo herds within Ruaha points. Resource selection was evaluated within a used- National Park were known from annual demographic available design at the individual animal level [37, 38]. surveys [32] as well as from local tour guides and park We used mixed-effects logistic regression models with rangers. During September–October of 2014–2015, a a random intercept specified for each buffalo and herd total of 12 adult buffalo cows from 5 herds were immo - (3rd order selection) using the glmer function (nAGQ bilized via dart delivered from vehicles using 8–10  mg optimization algorithm) within package lme4 in the soft- of etorphine hydrochloride (M99, 9.8  mg/ml, all drugs ware R [39]. We also standardized the continuous covari- obtained through Alphavet, Arusha, Tanzania) and ates (z-score) to improve model performance and allow 60–100  mg of azaperone (100  mg/ml). Immobilization for comparison of effect sizes across variables. A priori was reversed with 36 mg diprenorphine (M5050, 12 mg/ models were developed for each season and then ranked ml) and 80 mg naltrexone (50 mg/ml) injected via hand- by model weight (w ) using the Akaike Information Crite- syringe intravenously. All 12 adult cows were fitted with rion (AIC) [40]. We carefully inspected model output to iridium satellite GPS collars (African Wildlife Track- avoid use of models with uninformative parameters [18]. ing, Pretoria, South Africa, weight 1.7  kg, length of belt Coefficients from models of habitat selection were then 1060  cm). The collars were programmed to transmit 5 used to generate a map of the relative probability of use points per day by satellite uplink until September 2016, across our study area. This model was projected at 30 m where after the transmission was slowed to 2 times per spatial resolution within a minimum convex polygon day with 12 and 13 h between each uplink. The frequency surrounding all buffalo points. Data on elevation, slope, of transmission was slowed in the hope of being able to aspect, ruggedness, distance to river, and habitat type obtain a third year of wet season data; however, for all were extracted for each point, and the averaged regres- but one animal, the batteries failed before the third wet sion equation was applied to each point in order to gener- season. model model ate the relative probability of use [p = (e /1 + e )]. The probabilities of use were then mapped in ArcMap for Determination of space use the wet season and dry season. The probability of space use was estimated for individual buffaloes using Brownian Bridge Models (BBMM) using Daily movements the packages BBMM in R [35]. Rasters and shapefiles of The distribution of the distance (in meters) moved the space use, as an estimate of the home ranges, were between each 5-hour collar transmission was shown created with the R-packages rgdal, maptools, and raster using the mean and 95% confidence intervals by hour of [35]. The 99, 95, and 50% isopleth of the utilization dis - the day and month for all buffaloes combined using the tribution were calculated in square kilometers for each package ggplot2 [41]. The net displacement from the individual buffalo by season and year in order to compare location of collaring was determined using established space use by season and variation between years. methods [24] with the packages adehabitatLT [42] and dplyr [43] in R, and plots were generated using the pack- Resource selection age ggplot2. Only the data from when the collars were We used a resource selection function (RSF) to evaluate transmitting every 5 h were included in this analysis. patterns of habitat selection of buffaloes in RNP. Vegeta - tion and river data were obtained from Ruaha National Park, and topography data were obtained using the Abbreviations Advanced Spaceborne Thermal Emission and Reflection HALI: Health for Animals and Livelihood Improvement Project; MWG: Mwagusi; TKM: TelekiMboga; JGM: Jongomero; ELEV (M): elevation in meters; RUGGED: Radiometer (ASTER) Global Digital Elevation Model Roug et al. BMC Ecol (2020) 20:6 Page 12 of 13 ruggedness; DISTRIV (M): distance to nearest river in meters; V_OP_TR_15_40% Received: 15 March 2019 Accepted: 11 January 2020 CC: very open trees with 15–40% crown cover; OP_TR_40_65% CC: open trees with 40–65% crown cover; TR_SHR_SAV: trees and shrub savannah; OP_SHR_40_65% CC: open shrubs with 40–65% crown cover; CL_OP_WOOD- VEG: closed to open woody vegetation (thicket); SHR_SAV: shrub savannah; OP_CL_HERBVEG_TEMP_FL: open to closed herbaceous vegetation on tem- References porarily flooded land; V_OP_SHR_15_40% CC: very open shrubs with 15–40% 1. Allen AM, Singh NJ. Linking movement ecology with wildlife manage- crown cover; OP_CL_SHR_TEMP_FL: open to closed shrubs on temporarily ment and conservation. Front Ecol Evol. 2016;3:155. flooded land; CL_TR_TEMP_FL: closed trees on temporarily flooded land; 2. Morales JM, Moorcroft PR, Matthiopoulos J, Frair JL, Kie JG, Powell RA, CL_SHR: closed shrubs; IS_RF_HERB_CRP: isolated (in natural vegetation or Merril EH, Haydon DT. Building the bridge between animal move- other) rainfed herbaceous crops; SCAT_RF_HERB_CRP: scattered rainfed herba- ment and population dynamics. Philos Trans R Soc Lond B Biol Sci. ceous crop; CL_TR: closed trees; SE: standard error; SD: standard deviation; ref: 2010;365:2289–301. reference category for categorical variables in the regression model; hrs: hours; 3. Valls-Fox H, Chamaillé-Jammes S, de Garine-Wichatitsky M, Perrotton A, m: meters; BBMM: Brownian bridge models; AIC: Akaike Information Criterion; Courbin N, Miguel E, Guerbois C, Caron A, Loveridge A, Stapelkamp B, ASTER: Advanced Spaceborne Thermal Emission and Reflection Radiometer; Muzamba M, Fritz H. Water and cattle shape habitat selection by wild her- GDEM: Global Digital Elevation Model. bivores at the edge of a protected area. Anim Conserv. 2018;21:365–75. 4. Ryan SJ, Knechtel CU, Getz WM. Range and habitat selection of African Acknowledgements buffalo in South Africa. J Wildl Manage. 2006;70:764–76. We sincerely thank Ruaha National Park and HALI project staff for the support 5. Bennitt E, Bonyongo MC, Harris S. Eec ff ts of divergent migratory strate - with this project. We thank the Tanzanian Commission for Science and Tech- gies on access to resources for Cape buffalo (Syncerus caffer caffer). J nology and Tanzania Wildlife Research Institute ( TAWIRI) for permitting this Mammal. 2016;97:1682–98. study. ASTER GDEM is a product of METI and NASA. 6. Bennitt E, Bonyongo MC, Harris S. Habitat selection by African buffalo (Syncerus caffer) in response to landscape-level fluctuations in water avail- Authors’ contributions ability on two temporal scales. PLoS ONE. 2014;9:e101346. AR: Designed study, conducted field work, analyzed data, prepared manu- 7. Naidoo R, Du Preez P, Stuart-Hill G, Jago M, Wegmann M. Home on the script. EAM, DC, JK, RK: Designed study, conducted field work, corrected range: factors explaining partial migration of African buffalo in a tropical manuscript. RL: Assisted with data analysis, corrected manuscript. GP, DM, DM, environment. PLoS ONE. 2012;7(5):e36527. https ://doi.org/10.1371/journ HK: Assisted with field work and corrected manuscript. WS, JK, RK: Assisted al.pone.00365 27. with study design and corrected manuscript. All authors read and approved 8. Naidoo R, Du Preez P, Stuart-Hill G, Beytell P, Taylor R. Long-range migra- the final manuscript. tions and dispersals of African buffalo (Syncerus caffer) in the Kavango- Zambezi Transfrontier Conservation area. Afr J Ecol. 2014;52:581–4. https Funding ://doi.org/10.1111/aje.12163 . The collaring study was funded by the Safari Club International Foundation. 9. Sinclair ARE. The African buffalo. A study of resource limitation of popula- The funding body did not play any roles in the design of the study and collec- tions. Chicago: The University of Chicago Press; 1977. tion, analysis, and interpretation of data, or in the writing of the manuscript. 10. Coppolillo P, Clifford DL, Mazet JAK. The unintended consequences of development assistance: The case of Usangu in Tanzania. Research Brief Availability of data and materials 08-02-HALI Global Livestock Collaborative Research Support Program The data is available from the corresponding author upon reasonable request (CRSP). 2008. http://halip rojec t.org/publi catio ns/. and with permission from Tanzania National Parks. 11. Western D. Water availability and its influence on the structure and dynamics of a Savannah large mammal community. Afr J Ecol. Ethics approval and consent to participate 1975;13:265–86. The research was reviewed by the National Research Registration Committee 12. Redfern JV, Grant R, Biggs H, Getz WM. Surface-water constraints on of the Tanzanian Commission for Science and Technology for scientific merit, herbivore foraging in the Kruger National Park, South Africa. Ecology. safety, suitability, and ethical appropriateness. The research was approved by 2003;84:2092–107. the Tanzanian Commission for Science and Technology and Tanzania Wildlife 13. Mazet JA, Clifford DL, Coppolillo PB, Deolalikar AB, Erickson JD, Kazwala Research Institute and Ruaha National Park under permit number 2015-116 RR. A “one health” approach to address emerging zoonoses: the HALI – ER – 2006 – 179. All animal handling methods were further reviewed and project in Tanzania. PLoS Med. 2009;6:e1000190. approved by the Institutional Animal Care and Use Committee (IACUC) of the 14. Roug A, Clifford D, Mazet J, Kazwala R, John J, Coppolillo P, Smith W. Spa- University of California Davis under the IACUC permit number 19217. Consent tial predictors of bovine tuberculosis infection and Brucella spp. exposure to participate: Not applicable. No human subjects were included in the study. in pastoralist and agropastoralist livestock herds in the Ruaha ecosystem of Tanzania. Trop Anim Health Prod. 2014;46:837–43. Consent for publication 15. Clifford DL, Kazwala RR, Sadiki H, Roug A, Muse EA, Coppolillo PC, Mazet Not applicable. JAK. Tuberculosis infection in wildlife from the Ruaha ecosystem Tanzania: implications for wildlife, domestic animals, and human health. Epidemiol Competing interests Infect. 2013;141:1371–81. The authors declare that they have no competing interests. 16. de Garine-Wichatitsky M, Caron A, Kock R, Tschopp R, Munyeme M, Hofmeyr M, Michel A. A review of bovine tuberculosis at the wildlife- Author details livestock-human interface in sub-Saharan Africa. Epidemiol Infect. Karen C. Drayer Wildlife Health Center, University of California, 1089 2013;141:1342–56. Veterinary Medicine Drive, Davis, CA 95616, USA. Utah Division of Wildlife 17. Caron A, Cross PC, du Toit JT. Ecological implications of bovine tuberculo- Resources, 1594 West North Temple, Suite 2110, Salt Lake City, UT 84116, USA. sis in African buffalo herds. Ecol Appl. 2003;13:1338–45. Ruaha National Park, Tanzania National Parks, PO Box 369, Iringa, Tanzania. 18. Arnold T. Uninformative parameters and model selection using Akaike’s California Department of Fish and Wildlife, 1701 Nimbus Road Suite D, Information Criterion. J Wildlife Manage. 2010;74:1175–8. Rancho Cordova, CA 95670, USA. Department of Plant and Wildlife Sciences, 19. Winnie JA, Cross P, Getz W. Habitat quality and heterogeneity influence College of Life Sciences, Brigham Young University, Provo, UT 84602, USA. distribution and behavior in African buffalo (Syncerus caffer). Ecology. Department of Veterinary Medicine and Public Health, Sokoine University 2008;89:1457–68. of Agriculture, PO Box 3021, Morogoro, Tanzania. Department of Veterinary 20. L’Heureux ML, Takahashi K, Watkins AB, Barnston AG, Becker EJ, Liberto Surgery and Theriogenology, Sokoine University of Agriculture, PO Box 3021, TED, Gamble F, Gottschalck J, Halpert MS, Huang B, Mosquera-Vasquez K, Morogoro, Tanzania. Wittenberg AT. Observing and predicting the 2015/16 El Niño. Bull Amer Meteor. 2017;98:1363–82. Roug et al. BMC Ecol (2020) 20:6 Page 13 of 13 21. Conybeare A. Buffalo numbers, home range and daily movement 34. Mtahiko MGG. Wilderness in the Ruaha National Park, Tanzania. IJW. in the Sengua Wildlife Research Area, Zimbabwe. S Afr J Wildl Res. 2004;10:41–4. 1981;11:89–93. 35. R. A language and environment for statistical computing. R Foundation 22. Halley D, Vandewalle M, Mari M, Taolo C. Herd-switching and long- for Statistical Computing, Vienna, Austria. 2018. http://www.R-proje distance dispersal in female African buffalo Syncerus caffer. Afr J Ecol. ct.org/. 2002;40:97–9. 36. NASA. The Advanced Spaceborne Thermal Emission and Reflection 23. Prins HHT. Ecology and behavior of the African buffalo. London. UK: Radiometer (ASTER) Global Digital Elevation Model (GDEM) version 2. Chapman and Hall; 1996. NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation 24. Bunnefeld N, Börger L, van Moorter B, Rolandsen CM, Dettki H, Solberg and Science (EROS) Center, Sioux Falls, South Dakota (https ://lpdaa c.usgs. EJ, Ericsson G. A model-driven approach to quantify migration patterns: gov). 2011. https ://lpdaa c.usgs.gov/datas et_disco very. Accessed January individual, regional and yearly differences. J Anim Ecol. 2011;80:466–76. 2018. 25. Jakes AF, Gates CC, Decesare NJ, Jones PF, Goldberg JF, Kunkel KE, Heb- 37. Johnson DH. The comparison of usage and availability measurements for blewhite M. Classifying the migration behaviors of pronghorn on their evaluating resource preference. Ecology. 1980;61:65–71. northern range. J Wildl Manage. 2018;82:1229–42. 38. Manly BFJ, McDonald LL, Thomas DL, McDonald TL, Erickson WP. Resource 26. Stark MA. Daily movement, grazing activity and diet of savanna buffalo, selection by animals: statistical design and analysis for field studies. Syncerus caffer brachyceros, in Benoue National Park. Cameroon. Afr J Ecol. Boston: Kluwer Academics; 2002. p. 221p. 1986;24:255–62. 39. Bates D, Maechler M, Bolker B, Walker S. Fitting Linear Mixed-Eec ff ts 27. Grimsdell J, Field C. Grazing patterns of buffaloes in the Rwenzori Models Using lme4. J Stat Softw. 2015;67:1–48. National Park, Uganda. Afr J Ecol. 1976;14:339–44. 40. Burnham KP, Anderson DR. Model selection and multimodel inference: 28. Ryan SJ, Jordaan W. Activity patterns of African buffalo Syncerus caffer a practical information-theoretic approach. 2nd ed. New York: Springer; in the Lower Sabie Region, Kruger National Park, South Africa. Koedoe. 2002. 2005;48:117–24. 41. Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: 29. Venter JA, Watson LH. Feeding and habitat use of buffalo (Syncerus caffer Springer Verlag; 2006. caffer) in the Nama-Karoo, South Africa. S Afr J Wildl Res. 2008;38:42–51. 42. Calenge C. The package adehabitat for the R software: a tool for the 30. Meunier NV, Sebulime P, White RG, Kock R. Wildlife-livestock interactions analysis of space and habitat use by animals. Ecol Model. 2006;197:516–9. and risk areas for cross-species spread of bovine tuberculosis. Onderste- 43. Wickham HF, Francois R, Henry L, Müller K. dplyr: A Grammar of Data poort J Vet Res. 2017;84:1–10. Manipulation. R package version 0.7.4. https ://CRAN.R-proje ct.org/packa 31. Miguel E, Grosbois V, Caron A, Boulinier T, Fritz H, Cornélis D, Foggin C, ge=dplyr . 2017. Makaya PV, Tshabalala PT, de Garine-Wichatitsky M. Contacts and foot and mouth disease transmission from wild to domestic bovines in Africa. Publisher’s Note Ecosphere. 2013;4:art51. https ://doi.org/10.1890/es12-00239 .1. Springer Nature remains neutral with regard to jurisdictional claims in pub- 32. Roug A, Muse EA, Smith WA, Mazet JAK, Kazwala RR, Harvey D, Paul G, lished maps and institutional affiliations. Meing’ataki GO, Banga P, Clifford DL. Demographics and parasites of African buffalo (Syncerus caffer Sparrman, 1779) in Ruaha National Park. Tanzania. Afr J Ecol. 2016;54:146–53. 33. TANAPA. Ruaha National Park, official website. Available from: http:// www.tanza niapa rks.go.tz/index .php?optio n=com_conte nt&view=artic le&id=37&Itemi d=204 Accessed September 16, 2019. Ready to submit your research ? 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Seasonal movements and habitat use of African buffalo in Ruaha National Park, Tanzania

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Abstract

Background: Assessing wildlife movements and habitat use is important for species conservation and management and can be informative for understanding population dynamics. The African buffalo (Syncerus caffer) population of Ruaha National Park, Tanzania has been declining, and little was known about the movement, habitat selection, and space use of the population, which is important for understanding possible reasons behind the decline. A total of 12 African buffalo cows from four different herds were collared with satellite transmitters. Movements were assessed over 2 years from 11 animals. Results: The space use of the individual collared buffaloes as an approximation of the 95% home range size esti- mated using Brownian bridge models, ranged from 73 to 601 km . The estimated home ranges were larger in the wet season than in the dry season. With the exception of one buffalo all collared animals completed a wet season migra- tion of varying distances. A consistent pattern of seasonal movement was observed with one herd, whereas the other herds did not behave the same way in the two wet seasons that they were tracked. Herd splitting and herd switch- ing occurred on multiple occasions. Buffaloes strongly associated with habitats near the Great Ruaha River in the dry season and had little association to permanent water sources in the wet season. Daily movements averaged 4.6 km (standard deviation, SD = 2.6 km), with the longest distances traveled during November (mean 6.9 km, SD = 3.6 km) at the end of the dry season and beginning of the wet season. The shortest daily distances traveled occurred in the wet season in April–June (mean 3.6 km, SD = 1.6–1.8 km). Conclusion: The Great Ruaha River has experienced significant drying in the last decades due to water diversions upstream, which likely has reduced the suitable range for buffaloes. The loss of dry season habitat due to water scar - city has likely contributed to the population decline of the Ruaha buffaloes. Keywords: African buffalo, Habitat use, Home range, Ruaha National Park, Tanzania Background Understanding wildlife movements and habitat use is critical for species conservation and management on a landscape scale [1]. Information on emigration and immigration, habitat preferences, and herd interactions may be important for evaluating population dynam- *Correspondence: aroug@ucdavis.edu Epaphras A. Muse and Deana L. Clifford contributed equally to this work ics [2]. Movement data can also be used to identify Karen C. Drayer Wildlife Health Center, University of California, 1089 critical interfaces for potential disease transmission Veterinary Medicine Drive, Davis, CA 95616, USA between wildlife and domestic animal species [3]. The Full list of author information is available at the end of the article © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creat iveco mmons .org/publi cdoma in/ zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Roug et al. BMC Ecol (2020) 20:6 Page 2 of 13 movements and habitat preferences of large ungulate The GPS collars were used to determine movements species such as African buffaloes (Syncerus caffer) has as well as habitat use of African buffaloes in Ruaha been studied in multiple locations across Africa, includ- National Park in order to better understand possible ing South Africa [4], Botswana [5, 6], and Namibia [7, seasonal population impacts from herds entering sur- 8]. Migratory behavior ranged from resident [5], par- rounding reserves or risks of contracting disease from tially migratory [7], to long distance [8]. In Tanzania, local livestock populations at the borders of the park. We African buffalo ecology has been studied extensively expected that the main herds of the park completed sea- in the Serengeti in northern Tanzania [9], but limited sonal movements, but mainly stayed within park bounda- information is available from other areas of Tanzania. ries while utilizing the wildlife management area near the Over recent decades, the African buffalo popula - Great Ruaha River and bordering village lands. Gathered tion in Ruaha National Park in south-central Tanzania information could contribute to understanding possible appeared to be declining. Subjectively, park staff and reasons for the observed population decline and ben- tourist guides reported seeing fewer buffaloes than in efit Ruaha National Park for future management of this the past, and a decline in absolute numbers was con- species. firmed when comparing aerial counts conducted in comparable areas in the dry seasons of 2004 and 2013 Results (https ://www.halip rojec t.org, unpublished). In addi- Collaring tion to the suspected decline in numbers, park staff and A total of 5 adult cows were collared in a 700–1000 tour operators reported rarely seeing buffaloes in the animal mixed (both males and females) buffalo herd wet season between November and May, but no infor- near Mwagusi, 4 adult cows were collared in a large mation existed on annual herd movements and habitat 400 + mixed buffalo herd near Jongomero, 2 adult cows use. Buffaloes are seasonally hunted in game reserves in a mixed 100–200 animal large herd near TelekiMboga, surrounding the park, but as herd movements were not and one in a small, 30–40 animal herd with mainly bulls known, it was unclear whether the park’s buffaloes con - and a few cows between TelekiMboga and Jongomero stituted a part of the hunted population. (Figs. 1, 2). Ten of the buffaloes were collared in October As an additional concern, Ruaha National Park’s main 2014 and two in September 2015. One collar from 2015 water source, the Great Ruaha River, has experienced was only active for approximately 4  months (SAT1500), significant drying since the 1990s due to water diver - and data from this animal were not included in the habi- sions for agricultural irrigation upstream [10]. Buf- tat use, home range analyses, or movement analyses. faloes are water dependent [11], and access to water determines which areas can be utilized by buffaloes in Home ranges and movement the dry season [6, 12]. Further, the reduction in flow The 95% and 50% home range sizes, as estimated by of the Great Ruaha River has seasonally increased the computing isopleths of the utilization distribution using pressure on remaining water sources, and possibly Brownian Bridge Models (BBMM), were calculated for increased the interaction between livestock and wild- each individual buffalo within four time periods (Novem - life at the park’s boundaries [13]. Local cattle herds are ber–May = wet season, and June–October = dr y season known to be affected by bovine tuberculosis and bru - for 2  years) as well as overall (Table  1). The areas that cellosis, and bovine tuberculosis has been detected the buffaloes utilized varied with the largest for SAT in 8 wildlife species outside the park [14, 15]. African 1494 (overall 95% estimated home range = 601  km ) buffaloes are considered maintenance hosts for bovine and smallest for SAT 1495 (overall 95% estimated home tuberculosis [16], and while this disease is not thought range = 73  km ). Estimated home ranges were larger in to cause population declines in buffaloes, it may the wet season compared to the dry season for all the col- increase the populations susceptibility to other stress- lared buffaloes, and buffaloes consistently stayed closer ors such as drought [17]. to permanent water sources in the dry season. The Health for Animals and Livelihood Improve - Early in the 2014–2015 wet season, the buffaloes col - ment (HALI) project, a University of California, Davis lared in the same herd near Mwagusi (SAT 1494, 1497, and Sokoine University of Agriculture, Morogoro col- 1498, and 1503, Fig.  2a–d) split up into separate groups laborative project, and Ruaha National Park, partnered as reflected of moving several kilometers apart from each to investigate the apparent buffalo decline. Components other, but then reunited in the middle of the wet season of the study included an aerial population count, demo- and migrated to the high elevation plateau near Ilan- graphic surveys, health assessments, and marking buffa - gulu (Fig.  2a–d). In the second wet season, the Mwagusi loes with GPS collars. buffaloes split again without reuniting, with SAT 1494 (Fig.  2a) and SAT 1498 (Fig.  2b) moving to the locations Roug et al. BMC Ecol (2020) 20:6 Page 3 of 13 the wet season for all but one animal (SAT1495), which appeared to be resident (Fig.  3). The distances trave - led were largest for the buffaloes collared near Mwagusi (SAT1494, 1497, 1498, and 1503, Figs. 2a–d, 3), followed by the two buffaloes collared near TelekiMboga/Mdonya (SAT1492 and 1493, Figs.  2f, g, 3). The Jongomero buf - faloes (SAT 1496, 1499, 1501, and 1502, Figs.  2h–k, 3) only moved a short distance from the dry season habi- tat. After the wet season, the buffaloes largely returned to the previous dry season’s habitat by July, except for in the second wet season where two buffaloes collared near Mwagusi (SAT1494 and 1492, Fig. 2d, e), who had moved to Mdonya during the second wet season, did not return to the previous dry season’s habitat. Resource selection Our top models for both the dry season and wet season contained most of the AIC weight (wi > 0.65 for the dry season and 0.42 for the wet season). Models ranked below the top model within each season were judged to con- tain uninformative parameters or coefficients [18] that were so similar to the top model for each season that we elected not to model average. The top model for dry sea - son versus wet season were similar with only slope miss- Fig. 1 Overview of the Greater Ruaha Ecosystem in Tanzania and ing from the dry season and aspect excluded from the approximate capture locations of the collared African buffalo. wet season. In the dry season, the buffaloes selected habi - 1 = Mwagusi, 2 = Mdonya, 3 = Telek iMboga, 4 = Jongomero. Other features shown: 5 = Escarpment, 6 = Pawaga-Idodi Wildlife tats at lower elevation and in more rugged terrain closer Management Area. GR game reserve, GCA game controlled area to the river compared to the wet season (Table 2, Fig. 4). (Creator and copyright holder: A. Roug) All vegetation types except closed to open woody vegeta- tion were preferred in comparison to the reference cat- egory (very open trees with 15–40% crown cover), with the strongest selection for open to closed herbaceous near Mdonya, and SAT 1497 (Fig.  2d) moving into the vegetation on temporary flooded land, closed shrubs, wildlife management area between the park and village open shrubs or with 40–65% crown cover, closed trees land. In contrast, the movement of the Jongomero buf- on temporarily flooded land, isolated rainfed herbaceous faloes (Fig. 2h–k) was quite consistent across years, with crops, and scattered rainfed herbaceous crops (Table  2, buffaloes moving closer to the Great Ruaha River in the Fig. 4). The latter two vegetation types were only present dry season and into more rugged and remote areas near in the wildlife management area adjacent to the park, the escarpment in the wet season. No spatial overlap where SAT1497 spent part of a dry season and an entire between the Jongomero buffaloes and other buffaloes wet season (Fig. 2d). In the wet season (November–May), were observed (Fig.  2). The buffaloes collared near Tel - the association with distance to the river was weaker than ekiMboga (SAT 1492 and 1493, Fig.  2e–f ) spent the first in the dry season, and the selection for vegetation types wet season near Mdonya, but in the subsequent wet sea- containing more shrub and trees was stronger, such as son, SAT 1492 (Fig. 2e) appeared to switch herds and join closed to open woody vegetation, shrub savannah, open the Mwagusi buffaloes (SAT 1494 and 1498, Fig.  2a, b) to closed shrubs on temporarily flooded land, and closed near Mdonya, whereas SAT1493 (Fig.  2f ) moved across trees on temporarily flooded land (Table 2, Fig. 4). the Ruaha River and spent the entire wet season south of the Great Ruaha River. In the following dry season both buffaloes stayed near the river around TelekiMboga Daily movements (Fig. 2e–f ). The distance traveled in the previous 5 h was highest for These movements were reflected as net displacement points collected at 10.00 h (mean over all data = 1505  m, from the location of capture (Fig.  3). All buffaloes were SD = 1107 m, n = 1245 points) and 20.00 h (mean over all collared during the height of the dry season, and then data = 1430  m, SD = 969  m, n = 1247 points), and lowest showed movements away from the Great Ruaha River in at 14.00 h (mean = 471  m, SD = 627  m, n = 1235 points), Roug et al. BMC Ecol (2020) 20:6 Page 4 of 13 Fig. 2 Brownian bridge models for 11 adult female African buffaloes in Ruaha National Park, Tanzania. The panels show the individual models for buffaloes collared near Mwagusi (a–d), TelekiMboga (e–f), TelekiMboga/Jongomero (g), and Jongomero (h–k). The collars were active between October 2014 and April 2017 (see Table 1 for details on collar duration) (Creator and copyright holder: A. Roug) indicating that the buffaloes were crepuscular with the The average total distance moved in 24  h was 4.9  km highest activity levels in the late morning and evening (Standard deviation (SD) = 2.9  km) in November–May and lowest activity level in the heat of the day (Fig.  5). and 4.2  km (SD = 1.9  km) in June-October. The longest The daily movements increased with progression of the distances were traveled during November at the end of dry season and peaked in November, where the average the dry season and beginning of the wet season (mean distance traveled in the last five hours was over 2000  m daily distance = 6.9  km, SD = 3.6  km). The shortest daily twice a day (Fig.  5). The shortest average daily distances distances traveled occurred in the wet season in April– traveled over the previous 5  h were observed in April, June (mean 3.6  km, SD = 1.6–1.8  km). Across both sea- where the mean peak movements in the previous 5  h sons combined, the average daily distance traveled was where less than 1250 m twice a day (Fig. 5). 4.6 km (SD = 2.6 km, n = 6486). Roug et al. BMC Ecol (2020) 20:6 Page 5 of 13 Table 1 Size (in km ) of the 95% and 50% isopleth of the utilization distribution estimated using Brownian Bridge Models (as an approximation of home range sizes), of  each collared buffalo in  Ruaha National Park, Tanzania in  the  rainy (November–May) and  dry (June–October) seasons as  well as  overall (entire time period) Location collared MWG MWG MWG MWG TKM TKM TKM/JGM JGM JGM JGM JGM Time period % use SAT1497 SAT1498 SAT1503 SAT1494 SAT1492 SAT1493 SAT1495 SAT1496 SAT1499 SAT1501 SAT1502 Oct14–May15 95 219 306 290 254 – 205 86 215 246 174 253 Oct14–May15 50 47 59 67 55 – 30 12 44 46 39 49 Jun15–Oct15 95 129 137 136 142 – 98 9 109 100 112 98 Jun15–Oct15 50 27 29 27 28 – 35 1 28 23 28 23 Nov15–May16 95 84 183 – 256 203 101 50 247 203 254 183 Nov15–May16 50 15 25 – 38 42 13 10 57 44 60 42 Jun16–Oct16 95 80 35 – 149 139 51 – 109 96 100 a a a b a a a Jun16–Oct16 50 16 6 – 21 27 8 – 27 23 24 Nov16–Apr17 95 – – – – 345 – – – – – – Nov16–Apr17 50 – – – – 67 – – – – – – Entire time period 95 357 488 290 601 296 304 73 289 283 297 283 Entire time period 50 67 88 67 123 68 47 7 63 58 63 58 Month ended Sept 16 Aug 16 Oct 15 Oct 16 Apr 17 Nov 16 Jan 16 Oct 16 Sept 16 May 16 Oct 16 The space use by year is shown in order to compare variations between seasons and years. MWG = Mwagusi, TKM = TelekiMboga, JGM = Jongomero (–) no data Month ended: The last month that the collar was emitting points. For example, the collar SAT 1497 ceased working in September 2016 For SAT 1493, the data from November 2016 is included in the “entire time period” but not in the Jun 16–Oct 16 time window Roug et al. BMC Ecol (2020) 20:6 Page 6 of 13 Fig. 3 Net displacement in kilometers from location of collaring by year for African buffaloes in Ruaha National park between November 2014 and October 2016. The dry season is indicated with darker shading and wet season with lighter shading. In the first year, buffaloes largely returned to the previous dry season’s habitat near the Ruaha River as illustrated by the distances from the collaring location approaching zero in September– October 2015. In the second year, 3 animals (SAT 1493, 1494, and 1492) did not return to the same location after the second wet season Discussion animals much more independent of the permanent water Our study showed that the space use (estimated home sources. Consequently, the area utilized by the buffaloes ranges) of the individual collared buffaloes varied widely were generally larger in the wet season than in the dry and were consistently larger in the wet season than in season and the buffaloes showed a stronger selection for the dry season. Buffaloes showed strong preference for shrubby and woody habitats in the wet season (Table  2, habitats near the Great Ruaha River in the dry season Fig.  4). Shorter daily travel distances for collared buffa - and less association to permanent water sources in the loes in the middle of the wet season, especially during wet season. With the exception of one buffalo, all collared April–May, compared to the beginning of the wet season animals completed a wet season migration of varying dis- (November–December) can be explained by the fact that tances, and daily distances traveled were longest during some animals ranged widely in the beginning of the wet the late dry season and shortest in the height of the wet season before settling into an area with abundant forage season. Several buffaloes appeared to switch herd during for the wettest month of the year (Fig. 5). The size of the the study period. Buffaloes utilized the Wildlife Manage - areas utilized were quite variable among the individual ment Area on the southeastern border of the park, but animals, and the largest area was observed with SAT1494 did not venture into game reserves bordering Ruaha to (95% estimated home range size of 601  km across all the north and northeast. season) and the smallest with SAT1495 (95% estimated home range size of 73  km across all seasons). SAT1494 Home ranges and movements was collared in a 700 + animal herd near Mwagusi, During the dry season in Ruaha, water is limited to a whereas the herd with SAT1495 likely did not have more few springs and the Great Ruaha River, constraining the than 20 animals at any time. Larger home range sizes for buffaloes to stay much closer to the river than in the buffaloes belonging to larger herds has been reported in wet season, when seasonal pools and springs make the buffalo herds from the Kruger National Park in South Roug et al. BMC Ecol (2020) 20:6 Page 7 of 13 Table 2 Dry season (June-October) and  wet season Nature Reserve in South Africa, the estimated home (November–May) resource selection models for  11 adult range sizes ranged from 170.7 to 327 km using the same female African buffaloes in Ruaha National Park, Tanzania methodology [4], and home ranges for two breeding herds in the Sengwa Wildlife Research Area of Zimbabwe Parameter June–October November–May were reported as 207 and 286 km [21]. Coefficient SE Coefficient SE Another factor that may have influenced the home Intercept − 0.076 0.192 − 0.762 0.069 range size measured in several buffalo was herd switch - ELEV (m) − 0.761 0.228 0.261 0.013 ing, or, for SAT1494 and 1498, at least movement into Rugged 0.076 0.016 − 0.024 0.013 areas that was occupied by different buffaloes during the DISTRIV (m) − 0.126 0.021 − 0.067 0.015 previous wet season (Fig. 2a, b). Herd switching was also Aspect − 0.045 0.014 – – reported from Botswana buffalo herds, where 7 out of 45 Slope (%) – – − 0.055 0.012 collared adult female buffaloes switched herds [22], but contradict earlier literature that generally considered V_OP_TR_15_40% CC Ref Ref Ref Ref buffalo cows to inhabit stable herds without inter-herd OP_TR_40_65%CC 0.610 0.057 0.464 0.042 movements [9, 23]. The difference between the earlier TR_SHR_SAV 0.603 0.055 0.843 0.041 literature and the observations in our and the Botswana OP_SHR_40_65% CC 1.141 0.056 0.809 0.041 study can likely be explained by the use of GPS collars CL_OP_WOODVEG − 1.505 0.525 0.485 0.179 in the Botswana and our study, as more fine scale move - SHR_SAV 0.412 0.069 1.276 0.047 ment data can be obtained with GPS technology. OP_CL_HRBVG_TEMP_FL 2.007 0.074 1.407 0.057 While herd switching was observed, herds also V_OP_SHR_15_40% CC 0.677 0.099 0.277 0.059 appeared to avoid each other to some degree. Two buf- OP_CL_SHR_TEMP_FL 0.399 0.093 1.602 0.056 faloes were collared near TelekiMboga (SAT1492 and CL_TR_TEMP_FL 0.923 0.121 1.079 0.098 1493, Fig. 2e, f ), and while SAT1492 joined the buffaloes CL_SHR 1.506 0.181 1.704 0.135 coming from Mwagusi (SAT 1494 and 1498, Fig. 2a, b) in IS_RF_HERB_CRP 2.125 0.239 2.893 0.157 the second wet season (Fig.  2e), SAT 1493 moved south SCAT_RF_HRB_CRP 2.362 0.203 2.594 0.176 of the river and did not appear to share the same area CL_TR – – 10.064 43.955 as SAT1493, 1494, and 1498 in the subsequent dry sea- The collars were active for varying durations between October 2014 and April son (Fig.  2f ). Also, the Jongomero buffaloes (Fig.  2h–k) 2017. Models were generated using mixed-effects logistic regression models with a random intercept specified for each buffalo and herd. The continuous never directly overlapped with areas occupied by any of covariates were standardized to improve model performance and allow for the other collared buffaloes even though they frequently comparison of effect sizes across variables. A priori models were developed for each season and then ranked by model weight using the Akaike Information moved into areas adjacent to the range occupied by Criterion. ELEV (m) = elevation in meters, RUGGED = ruggedness, DISTRIV SAT1495 (Fig. 2g). One collared buffalo (SAT 1497) spent (m) = distance to nearest river in meters, V_OP_TR_15_40% CC = very open trees with 15–40% crown cover, OP_TR_40_65% CC = open trees with 40–65% crown an entire wet season in the wildlife management area cover, TR_SHR_SAV = trees and shrub savannah, OP_SHR_40_65% CC = open outside the park (Fig. 2d). It is possible that the buffaloes shrubs with 40–65% crown cover, CL_OP_WOODVEG = closed to open woody that ventured into the wildlife management area were vegetation (thicket), SHR_SAV = shrub savannah, OP_CL_HERBVEG_TEMP_ FL = open to closed herbaceous vegetation on temporarily flooded land, trapped there during the wettest time of the year as the V_OP_SHR_15_40% CC = very open shrubs with 15–40% crown cover, OP_CL_ river was unusually high during the second wet season SHR_TEMP_FL = open to closed shrubs on temporarily flooded land, CL_TR_ TEMP_FL = closed trees on temporarily flooded land, CL_SHR = closed shrubs, and likely did not allow for buffaloes crossing safely, espe - IS_RF_HERB_CRP = isolated (in natural vegetation or other) rainfed herbaceous cially with small calves. More data are needed in order to crops, SCAT_RF_HERB_CRP = scattered rainfed herbaceous crop, CL_TR = closed understand the observed movements and elicit any con- trees, SE = standard error, Ref = reference category for categorical variables sistent patterns in the Mwagusi and TelekiMboga herds. Movement of animals can be classified as migratory, Africa and the Caprivi strip in Namibia [7, 19]; however, mixed migratory, dispersal, or non-migratory using net whether the estimated home range sizes truly were rep- square displacement [24, 25]. From a buffalo study in the resentative of what the buffaloes do every year is difficult Caprivi strip of Namibia a fifth class of migratory behav - to ascertain based on only 2 years of data. The 2015–2016 ior, “expanders”, has been suggested, which are animals wet season had unusually high levels of precipitation [20] that expanded their range rather than moving entirely and water was likely not a limiting factor anywhere in the away from their dry season home ranges during the wet park. This may have influenced how buffaloes moved in season [8]. The Jongomero buffaloes did move from their the second year. In comparison, home ranges from adult dry season location to areas closer to the escarpment, but female African buffalo collared near the Caprivi strip also regularly returned to areas that were used during in Namibia ranged from 5.5 to 564.7  km using the 90% the dry season, and could, therefore, tentatively be clas- Local Convex Hull method [7]. In the Klaserie Private sified as expanders. The buffaloes collared near Mwagusi Roug et al. BMC Ecol (2020) 20:6 Page 8 of 13 (See figure on next page.) Fig. 4 Vegetation and habitat selection in June–October (dry season) and November–May (wet season) within a polygon surrounding all collar points from 11 adult female African buffaloes collared in Ruaha National Park between October 2014 and April 2017 (see Table 1). The relative probability of use (Use) was based on the habitat selection models shown in Table 2. Abbreviations for vegetation types: CL_HERB_PERM_ FL = closed herbaceous vegetation on permanently flooded land, CL_SHR = closed shrubs, CL_OP_WOODVEG = closed to open woody vegetation (thicket), CL_TR = Closed trees, CL_TR_TEMP_FL = closed trees on temporarily flooded land, IS_RF_HERB_CRP = isolated (in natural vegetation or other) rainfed herbaceous crops, OP_SHR_40_65% CC = open shrubs with 40–65% crown cover, OP_CL_HERBVEG_TEMP_FL = open to closed herbaceous vegetation on temporarily flooded land, OP_CL_SHR_TEMP_FL = open to closed shrubs on temporarily flooded land, OP_TR_40_65% CC = open trees with 40–65% crown cover, RAIN_TR_CRP = rainfed tree crop (mixed unit with natural vegetation or other), SCAT_RF_HERB_ CRP = scattered rainfed herbaceous crop, SHR_SAV = shrub savannah, TR_SHR_SAV = trees and shrub savannah, V_OP_SHR_40_15% CC = very open shrubs with 15–40% crown cover, V_OP_TR_15_40% CC = very open trees with 15–40% crown cover (Creator and copyright holder: A. Roug) and TelekiMboga/Mdonya behaved differently in the Resource selection 2 years they were observed and, based on available data, As expected, buffaloes selected habitats near the river could therefore be categorized as mixed migratory, and in the dry season compared to the wet season when SAT1495 did not migrate (Fig. 2g) and could therefore be rainfall made water abundant across the park. Similar classified as non-migratory or resident [8]. observations have been reported in other locations; e.g. in the Caprivi strip of Namibia buffaloes moved to the Daily movements flood plain near the rivers and adjacent woodland in the The patterns of daily distances traveled were consistent dry season and moved away from rivers into areas with with field observations, as buffaloes usually were seen ephemeral water in distant woodland in the wet season arriving at the river between 8 and 11 in the morning, [7]. However, in studies from the Doornkloof Nature and again around 16 and 19 in the afternoon and evening Reserve in the Nama-Karoo in the Northern Cape Prov- (Fig. 5). The daily movements increased with progression ince of South Africa, and Klaserie Private Nature Reserve of the dry season and peaked in November, which is the in South Africa, buffaloes ranged farther and wider in last month of the dry season, when animals are forced to the dry season than in the wet season in order to find travel longer distances to find adequate forage but have adequate forage [4, 29]. Similar observations were made to return to the river on a daily basis to drink. The end in Kruger National Park, South Africa, where buffaloes of November is also the beginning of the rainy season ranged farther in dry years than in wet years [12]. when buffaloes moved away from the area around the None of the collared buffaloes ventured into the north - Great Ruaha river to their wet season habitats. The short - ern game reserves during the hunting season, and only est daily distances traveled were observed in April (Fig. 5) one herd spent significant time outside the park within which is the middle of the wet season, where abundant the wildlife management area. Harvest of animals is forage and availability of seasonal pools makes it unnec- therefore unlikely to have a direct population impact for essary for the buffaloes to travel long distances to find the observed herds. Whether other herds in which no water. collars were placed are impacted by hunting pressure The average daily distance moved of 4.6  km cannot be elicited from our data. (SD = 2.6  km) is lower than what has been reported Nonetheless, buffaloes are occasionally detected with in other buffalo herds. Buffalo herds in Cameroon, for camera traps on village land (Ruaha Carnivore Pro- example, moved an average of 7.2 ± 2.62  km in the dry ject, personal communication), indicating that they do season and 5.6 ± 0.87  km in the wet season [26]. Buf- spend time outside the park. The extent of contact with faloes in the Sengwa Wildlife Research Area of Zimba- livestock and consequent risk of disease transmission bwe moved an average of 6.1  km (SD = 2.02  km) in the between these species is unknown. Studies from Uganda dry season [21], and buffaloes in Rwenzori National and Zimbabwe showed that direct contact between cat- Park in Uganda moved an average of 9.6  km per day tle and buffaloes is unlikely [30, 31] and disease transmis- (range = 5.2–14.4  km) [27]. In contrast, breeding herds sion between buffaloes and cattle therefore likely occurs of buffaloes in Kruger National Park moved an average of through shared environments and not through direct only 3.35  km per 24  h (standard error = 0.35  km); how- contact. ever, this distance did not vary with season, indicating that reliable water and grazing was available in both the Conclusions wet and dry seasons [28]. The seasonal pattern of buffalo movement observed suggests that the Ruaha buffaloes may be restricted in their movement during the dry season due to depend- ence on a few perennially available water sources, which Roug et al. BMC Ecol (2020) 20:6 Page 9 of 13 Roug et al. BMC Ecol (2020) 20:6 Page 10 of 13 Fig. 5 Mean and 95% confidence intervals of distance moved (in meters) in the previous 5 h by time of day and month, based on data from 11 collared adult female African buffaloes from 4 herds in Ruaha National Park, Tanzania. The time of sunrise and sunset is indicated for each month by the black vertical lines consequently increases the pressure on the habitat impact of seasonal water scarcity on Ruaha’s wildlife, and around these areas. Hunting is unlikely to have major benefit the conservation of buffaloes in Ruaha National impact on the buffaloes in the core herds of the park, and Park. On a broader scale, our observations demonstrate buffaloes generally appeared to be in good health with the importance of linking population data, migration, adequate calf recruitment as observed during the cap- habitat preferences, and ecosystem changes in order to ture work and based on demographic surveys, although understand population dynamics of large ungulate spe- the recruitment varied with rainfall [32]. Our study find - cies in Africa and beyond. ings may therefore indicate that the buffalo population in Ruaha declined due to seasonal reductions in the flow of Methods the areas main water source, the Great Ruaha River. As a Study area water-dependent species, the area of suitable and reach- Ruaha National Park, Tanzania’s largest national park, is able habitat would have diminished drastically with dry a part of the Rungwa-Kizigo-Muhesi ecosystem and cov- season cessation of water flow. Additional movement ers an area of 20,226  km [33]. The park is bordered by data, including collaring of buffaloes belonging to herds game reserves to the north-east and a wildlife manage- along the border of Ruaha’s protected areas, is needed to ment area to the south-east (Fig.  1). Together, this eco- fully delineate the home ranges and habitat preferences. system spans an area of over 45,000 km , making it one of Long term monitoring of water flow and buffalo popu - the largest contiguous wilderness areas in the world [13]. lations trends may increase the understanding of the The rainy seasons extend from November to February Roug et al. BMC Ecol (2020) 20:6 Page 11 of 13 and from March to April, and annual mean precipita- (GDEM) [36]. The elevation (in meters), slope (per - tion is 500–800  mm [33, 34]. The vegetation is domi - cent), aspect (north, south, east, west), distance to near- nated by miombo woodland in the south-western part est river (Euclidian distance, in meters), and ruggedness of the park and commiphora-combretum woodland and were calculated in ArcMap (vs. 10.6, ESRI, Redding, CA, acacia Savannah in the central and eastern parts of the USA) from the GDEM data. We evaluated habitat selec- park [34]. Main rivers include the Great Ruaha, Mzombe, tion at the 3rd order [37]. For each buffalo and season Mdonya, Mwagusi and Jongomero rivers [33]. The south - (November–May = wet season, and June–October = dr y ern portion of the park is located within a valley, and the season), data on vegetation type, elevation, slope, rug- valley edge creates a steep escarpment extending from gedness, aspect, and distance to river were extracted for the north-east to the south-west [33] (Fig. 1). each collar point. Shapefiles delineating the 99% isopleth of the utilization distribution generated with the Brown- ian bridge models were used as boundaries for creating Collaring an equal number of random points as there were collar The locations of major buffalo herds within Ruaha points. Resource selection was evaluated within a used- National Park were known from annual demographic available design at the individual animal level [37, 38]. surveys [32] as well as from local tour guides and park We used mixed-effects logistic regression models with rangers. During September–October of 2014–2015, a a random intercept specified for each buffalo and herd total of 12 adult buffalo cows from 5 herds were immo - (3rd order selection) using the glmer function (nAGQ bilized via dart delivered from vehicles using 8–10  mg optimization algorithm) within package lme4 in the soft- of etorphine hydrochloride (M99, 9.8  mg/ml, all drugs ware R [39]. We also standardized the continuous covari- obtained through Alphavet, Arusha, Tanzania) and ates (z-score) to improve model performance and allow 60–100  mg of azaperone (100  mg/ml). Immobilization for comparison of effect sizes across variables. A priori was reversed with 36 mg diprenorphine (M5050, 12 mg/ models were developed for each season and then ranked ml) and 80 mg naltrexone (50 mg/ml) injected via hand- by model weight (w ) using the Akaike Information Crite- syringe intravenously. All 12 adult cows were fitted with rion (AIC) [40]. We carefully inspected model output to iridium satellite GPS collars (African Wildlife Track- avoid use of models with uninformative parameters [18]. ing, Pretoria, South Africa, weight 1.7  kg, length of belt Coefficients from models of habitat selection were then 1060  cm). The collars were programmed to transmit 5 used to generate a map of the relative probability of use points per day by satellite uplink until September 2016, across our study area. This model was projected at 30 m where after the transmission was slowed to 2 times per spatial resolution within a minimum convex polygon day with 12 and 13 h between each uplink. The frequency surrounding all buffalo points. Data on elevation, slope, of transmission was slowed in the hope of being able to aspect, ruggedness, distance to river, and habitat type obtain a third year of wet season data; however, for all were extracted for each point, and the averaged regres- but one animal, the batteries failed before the third wet sion equation was applied to each point in order to gener- season. model model ate the relative probability of use [p = (e /1 + e )]. The probabilities of use were then mapped in ArcMap for Determination of space use the wet season and dry season. The probability of space use was estimated for individual buffaloes using Brownian Bridge Models (BBMM) using Daily movements the packages BBMM in R [35]. Rasters and shapefiles of The distribution of the distance (in meters) moved the space use, as an estimate of the home ranges, were between each 5-hour collar transmission was shown created with the R-packages rgdal, maptools, and raster using the mean and 95% confidence intervals by hour of [35]. The 99, 95, and 50% isopleth of the utilization dis - the day and month for all buffaloes combined using the tribution were calculated in square kilometers for each package ggplot2 [41]. The net displacement from the individual buffalo by season and year in order to compare location of collaring was determined using established space use by season and variation between years. methods [24] with the packages adehabitatLT [42] and dplyr [43] in R, and plots were generated using the pack- Resource selection age ggplot2. Only the data from when the collars were We used a resource selection function (RSF) to evaluate transmitting every 5 h were included in this analysis. patterns of habitat selection of buffaloes in RNP. Vegeta - tion and river data were obtained from Ruaha National Park, and topography data were obtained using the Abbreviations Advanced Spaceborne Thermal Emission and Reflection HALI: Health for Animals and Livelihood Improvement Project; MWG: Mwagusi; TKM: TelekiMboga; JGM: Jongomero; ELEV (M): elevation in meters; RUGGED: Radiometer (ASTER) Global Digital Elevation Model Roug et al. BMC Ecol (2020) 20:6 Page 12 of 13 ruggedness; DISTRIV (M): distance to nearest river in meters; V_OP_TR_15_40% Received: 15 March 2019 Accepted: 11 January 2020 CC: very open trees with 15–40% crown cover; OP_TR_40_65% CC: open trees with 40–65% crown cover; TR_SHR_SAV: trees and shrub savannah; OP_SHR_40_65% CC: open shrubs with 40–65% crown cover; CL_OP_WOOD- VEG: closed to open woody vegetation (thicket); SHR_SAV: shrub savannah; OP_CL_HERBVEG_TEMP_FL: open to closed herbaceous vegetation on tem- References porarily flooded land; V_OP_SHR_15_40% CC: very open shrubs with 15–40% 1. Allen AM, Singh NJ. Linking movement ecology with wildlife manage- crown cover; OP_CL_SHR_TEMP_FL: open to closed shrubs on temporarily ment and conservation. Front Ecol Evol. 2016;3:155. flooded land; CL_TR_TEMP_FL: closed trees on temporarily flooded land; 2. Morales JM, Moorcroft PR, Matthiopoulos J, Frair JL, Kie JG, Powell RA, CL_SHR: closed shrubs; IS_RF_HERB_CRP: isolated (in natural vegetation or Merril EH, Haydon DT. Building the bridge between animal move- other) rainfed herbaceous crops; SCAT_RF_HERB_CRP: scattered rainfed herba- ment and population dynamics. Philos Trans R Soc Lond B Biol Sci. ceous crop; CL_TR: closed trees; SE: standard error; SD: standard deviation; ref: 2010;365:2289–301. reference category for categorical variables in the regression model; hrs: hours; 3. Valls-Fox H, Chamaillé-Jammes S, de Garine-Wichatitsky M, Perrotton A, m: meters; BBMM: Brownian bridge models; AIC: Akaike Information Criterion; Courbin N, Miguel E, Guerbois C, Caron A, Loveridge A, Stapelkamp B, ASTER: Advanced Spaceborne Thermal Emission and Reflection Radiometer; Muzamba M, Fritz H. Water and cattle shape habitat selection by wild her- GDEM: Global Digital Elevation Model. bivores at the edge of a protected area. Anim Conserv. 2018;21:365–75. 4. Ryan SJ, Knechtel CU, Getz WM. Range and habitat selection of African Acknowledgements buffalo in South Africa. J Wildl Manage. 2006;70:764–76. We sincerely thank Ruaha National Park and HALI project staff for the support 5. Bennitt E, Bonyongo MC, Harris S. Eec ff ts of divergent migratory strate - with this project. We thank the Tanzanian Commission for Science and Tech- gies on access to resources for Cape buffalo (Syncerus caffer caffer). J nology and Tanzania Wildlife Research Institute ( TAWIRI) for permitting this Mammal. 2016;97:1682–98. study. ASTER GDEM is a product of METI and NASA. 6. Bennitt E, Bonyongo MC, Harris S. Habitat selection by African buffalo (Syncerus caffer) in response to landscape-level fluctuations in water avail- Authors’ contributions ability on two temporal scales. PLoS ONE. 2014;9:e101346. AR: Designed study, conducted field work, analyzed data, prepared manu- 7. Naidoo R, Du Preez P, Stuart-Hill G, Jago M, Wegmann M. Home on the script. EAM, DC, JK, RK: Designed study, conducted field work, corrected range: factors explaining partial migration of African buffalo in a tropical manuscript. RL: Assisted with data analysis, corrected manuscript. GP, DM, DM, environment. PLoS ONE. 2012;7(5):e36527. https ://doi.org/10.1371/journ HK: Assisted with field work and corrected manuscript. WS, JK, RK: Assisted al.pone.00365 27. with study design and corrected manuscript. All authors read and approved 8. Naidoo R, Du Preez P, Stuart-Hill G, Beytell P, Taylor R. Long-range migra- the final manuscript. tions and dispersals of African buffalo (Syncerus caffer) in the Kavango- Zambezi Transfrontier Conservation area. Afr J Ecol. 2014;52:581–4. https Funding ://doi.org/10.1111/aje.12163 . The collaring study was funded by the Safari Club International Foundation. 9. Sinclair ARE. The African buffalo. A study of resource limitation of popula- The funding body did not play any roles in the design of the study and collec- tions. Chicago: The University of Chicago Press; 1977. tion, analysis, and interpretation of data, or in the writing of the manuscript. 10. Coppolillo P, Clifford DL, Mazet JAK. The unintended consequences of development assistance: The case of Usangu in Tanzania. Research Brief Availability of data and materials 08-02-HALI Global Livestock Collaborative Research Support Program The data is available from the corresponding author upon reasonable request (CRSP). 2008. http://halip rojec t.org/publi catio ns/. and with permission from Tanzania National Parks. 11. Western D. Water availability and its influence on the structure and dynamics of a Savannah large mammal community. Afr J Ecol. Ethics approval and consent to participate 1975;13:265–86. The research was reviewed by the National Research Registration Committee 12. Redfern JV, Grant R, Biggs H, Getz WM. Surface-water constraints on of the Tanzanian Commission for Science and Technology for scientific merit, herbivore foraging in the Kruger National Park, South Africa. Ecology. safety, suitability, and ethical appropriateness. The research was approved by 2003;84:2092–107. the Tanzanian Commission for Science and Technology and Tanzania Wildlife 13. Mazet JA, Clifford DL, Coppolillo PB, Deolalikar AB, Erickson JD, Kazwala Research Institute and Ruaha National Park under permit number 2015-116 RR. A “one health” approach to address emerging zoonoses: the HALI – ER – 2006 – 179. All animal handling methods were further reviewed and project in Tanzania. PLoS Med. 2009;6:e1000190. approved by the Institutional Animal Care and Use Committee (IACUC) of the 14. Roug A, Clifford D, Mazet J, Kazwala R, John J, Coppolillo P, Smith W. Spa- University of California Davis under the IACUC permit number 19217. Consent tial predictors of bovine tuberculosis infection and Brucella spp. exposure to participate: Not applicable. No human subjects were included in the study. in pastoralist and agropastoralist livestock herds in the Ruaha ecosystem of Tanzania. Trop Anim Health Prod. 2014;46:837–43. Consent for publication 15. Clifford DL, Kazwala RR, Sadiki H, Roug A, Muse EA, Coppolillo PC, Mazet Not applicable. JAK. Tuberculosis infection in wildlife from the Ruaha ecosystem Tanzania: implications for wildlife, domestic animals, and human health. Epidemiol Competing interests Infect. 2013;141:1371–81. The authors declare that they have no competing interests. 16. de Garine-Wichatitsky M, Caron A, Kock R, Tschopp R, Munyeme M, Hofmeyr M, Michel A. A review of bovine tuberculosis at the wildlife- Author details livestock-human interface in sub-Saharan Africa. Epidemiol Infect. Karen C. Drayer Wildlife Health Center, University of California, 1089 2013;141:1342–56. Veterinary Medicine Drive, Davis, CA 95616, USA. Utah Division of Wildlife 17. Caron A, Cross PC, du Toit JT. Ecological implications of bovine tuberculo- Resources, 1594 West North Temple, Suite 2110, Salt Lake City, UT 84116, USA. sis in African buffalo herds. Ecol Appl. 2003;13:1338–45. Ruaha National Park, Tanzania National Parks, PO Box 369, Iringa, Tanzania. 18. Arnold T. Uninformative parameters and model selection using Akaike’s California Department of Fish and Wildlife, 1701 Nimbus Road Suite D, Information Criterion. J Wildlife Manage. 2010;74:1175–8. Rancho Cordova, CA 95670, USA. Department of Plant and Wildlife Sciences, 19. Winnie JA, Cross P, Getz W. Habitat quality and heterogeneity influence College of Life Sciences, Brigham Young University, Provo, UT 84602, USA. distribution and behavior in African buffalo (Syncerus caffer). Ecology. Department of Veterinary Medicine and Public Health, Sokoine University 2008;89:1457–68. of Agriculture, PO Box 3021, Morogoro, Tanzania. Department of Veterinary 20. L’Heureux ML, Takahashi K, Watkins AB, Barnston AG, Becker EJ, Liberto Surgery and Theriogenology, Sokoine University of Agriculture, PO Box 3021, TED, Gamble F, Gottschalck J, Halpert MS, Huang B, Mosquera-Vasquez K, Morogoro, Tanzania. Wittenberg AT. Observing and predicting the 2015/16 El Niño. Bull Amer Meteor. 2017;98:1363–82. Roug et al. BMC Ecol (2020) 20:6 Page 13 of 13 21. Conybeare A. Buffalo numbers, home range and daily movement 34. Mtahiko MGG. Wilderness in the Ruaha National Park, Tanzania. IJW. in the Sengua Wildlife Research Area, Zimbabwe. S Afr J Wildl Res. 2004;10:41–4. 1981;11:89–93. 35. R. A language and environment for statistical computing. R Foundation 22. Halley D, Vandewalle M, Mari M, Taolo C. Herd-switching and long- for Statistical Computing, Vienna, Austria. 2018. http://www.R-proje distance dispersal in female African buffalo Syncerus caffer. Afr J Ecol. ct.org/. 2002;40:97–9. 36. NASA. The Advanced Spaceborne Thermal Emission and Reflection 23. Prins HHT. Ecology and behavior of the African buffalo. London. UK: Radiometer (ASTER) Global Digital Elevation Model (GDEM) version 2. Chapman and Hall; 1996. NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation 24. Bunnefeld N, Börger L, van Moorter B, Rolandsen CM, Dettki H, Solberg and Science (EROS) Center, Sioux Falls, South Dakota (https ://lpdaa c.usgs. EJ, Ericsson G. A model-driven approach to quantify migration patterns: gov). 2011. https ://lpdaa c.usgs.gov/datas et_disco very. Accessed January individual, regional and yearly differences. J Anim Ecol. 2011;80:466–76. 2018. 25. Jakes AF, Gates CC, Decesare NJ, Jones PF, Goldberg JF, Kunkel KE, Heb- 37. Johnson DH. The comparison of usage and availability measurements for blewhite M. Classifying the migration behaviors of pronghorn on their evaluating resource preference. Ecology. 1980;61:65–71. northern range. J Wildl Manage. 2018;82:1229–42. 38. Manly BFJ, McDonald LL, Thomas DL, McDonald TL, Erickson WP. Resource 26. Stark MA. Daily movement, grazing activity and diet of savanna buffalo, selection by animals: statistical design and analysis for field studies. Syncerus caffer brachyceros, in Benoue National Park. Cameroon. Afr J Ecol. Boston: Kluwer Academics; 2002. p. 221p. 1986;24:255–62. 39. Bates D, Maechler M, Bolker B, Walker S. Fitting Linear Mixed-Eec ff ts 27. Grimsdell J, Field C. Grazing patterns of buffaloes in the Rwenzori Models Using lme4. J Stat Softw. 2015;67:1–48. National Park, Uganda. Afr J Ecol. 1976;14:339–44. 40. Burnham KP, Anderson DR. Model selection and multimodel inference: 28. Ryan SJ, Jordaan W. Activity patterns of African buffalo Syncerus caffer a practical information-theoretic approach. 2nd ed. New York: Springer; in the Lower Sabie Region, Kruger National Park, South Africa. Koedoe. 2002. 2005;48:117–24. 41. Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: 29. Venter JA, Watson LH. Feeding and habitat use of buffalo (Syncerus caffer Springer Verlag; 2006. caffer) in the Nama-Karoo, South Africa. S Afr J Wildl Res. 2008;38:42–51. 42. Calenge C. The package adehabitat for the R software: a tool for the 30. Meunier NV, Sebulime P, White RG, Kock R. Wildlife-livestock interactions analysis of space and habitat use by animals. Ecol Model. 2006;197:516–9. and risk areas for cross-species spread of bovine tuberculosis. Onderste- 43. Wickham HF, Francois R, Henry L, Müller K. dplyr: A Grammar of Data poort J Vet Res. 2017;84:1–10. Manipulation. R package version 0.7.4. https ://CRAN.R-proje ct.org/packa 31. Miguel E, Grosbois V, Caron A, Boulinier T, Fritz H, Cornélis D, Foggin C, ge=dplyr . 2017. Makaya PV, Tshabalala PT, de Garine-Wichatitsky M. Contacts and foot and mouth disease transmission from wild to domestic bovines in Africa. Publisher’s Note Ecosphere. 2013;4:art51. https ://doi.org/10.1890/es12-00239 .1. Springer Nature remains neutral with regard to jurisdictional claims in pub- 32. Roug A, Muse EA, Smith WA, Mazet JAK, Kazwala RR, Harvey D, Paul G, lished maps and institutional affiliations. Meing’ataki GO, Banga P, Clifford DL. Demographics and parasites of African buffalo (Syncerus caffer Sparrman, 1779) in Ruaha National Park. Tanzania. Afr J Ecol. 2016;54:146–53. 33. TANAPA. Ruaha National Park, official website. Available from: http:// www.tanza niapa rks.go.tz/index .php?optio n=com_conte nt&view=artic le&id=37&Itemi d=204 Accessed September 16, 2019. Ready to submit your research ? 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