Herbivory and Drought Generate Short‐Term Stochasticity and Long‐Term Stability in A Savanna Understory Community

Rainfall and herbivory are fundamental drivers of grassland plant dynamics, yet few studies have examined long‐term interactions between these factors in an experimental setting. Understanding such interactions is important, as rainfall is becoming increasingly erratic and native wild herbivores are being replaced by livestock. Livestock grazing and episodic low rainfall are thought to interact, leading to greater community change than either factor alone. We examined patterns of change and stability in herbaceous community composition through four dry periods, or droughts, over 15 years of the Kenya Long‐term Exclosure Experiment (KLEE), which consists of six different combinations of cattle, native wild herbivores (e.g., zebras, gazelles), and mega‐herbivores (giraffes, elephants). We used principal response curves to analyze the trajectory of change in each herbivore treatment relative to a common initial community and asked how droughts contributed to community change in these treatments. We examined three measures of stability (resistance, variability, and turnover) that correspond to different temporal scales and found that each had a different response to grazing. Treatments that included both cattle and wild herbivores had higher resistance (less net change over 15 years) but were more variable on shorter time scales; in contrast, the more lightly grazed treatments (no herbivores or wild herbivores only) showed lower resistance due to the accumulation of consistent, linear, short‐term change. Community change was greatest during and immediately after droughts in all herbivore treatments. But, while drought contributed to directional change in the less grazed treatments, it contributed to both higher variability and resistance in the more heavily grazed treatments. Much of the community change in lightly grazed treatments (especially after droughts) was due to substantial increases in cover of the palatable grass Brachiaria lachnantha. These results illustrate how herbivory and drought can act together to cause change in grassland communities at the moderate to low end of a grazing intensity continuum. Livestock grazing at a moderate intensity in a system with a long evolutionary history of grazing contributed to long‐term stability. This runs counter to often‐held assumptions that livestock grazing leads to directional, destabilizing shifts in grassland systems

Glade cascades: indirect legacy effects of pastoralism enhance the abundance and spatial structuring of arboreal fauna

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/117219/1/ecy2013944827.pd

Elephants Mitigate the Effects of Cattle on Wildlife and Other Ecosystem Traits: Experimental Evidence

On rangelands worldwide, cattle interact with many ecosystem components, most obviously with soils, plants, and other large herbivores. Since 1995, we have been manipulating the presence of cattle, mesoherbivores, and megaherbivores (elephants and giraffes) in a series of eighteen 4-ha (10-acre) plots at the Kenya Long-term Exclosure Experiment. We have demonstrated a wide array of cattle effects on this savanna rangeland, including their reduction of grass cover, wildlife use, and soil nitrogen and phosphorus pools, but their increase of primary productivity and termite abundance. Strikingly, we demonstrate that the presence of mega-herbivores (elephants, mainly) reduces the sizes of these cattle. We provide further experimental evidence that this may be because the elephants are reducing the most desirable (N-rich) forage, causing cattle to slow their extraction of (low-N) grasses, while simultaneously reducing tree cover

Data from: Climate and the landscape of fear in an African savanna

1.Herbivores frequently have to make tradeoffs between two basic needs: the need to acquire forage and the need to avoid predation. One manifestation of this tradeoff is the “landscape of fear” phenomenon – wherein herbivores avoid areas of high perceived predation risk even if forage is abundant or of high quality in those areas. Although this phenomenon is well-established among invertebrates, its applicability to terrestrial large herbivores remains debated, in part because experimental evidence is scarce. 2.This study was designed to (a) experimentally test the effects of tree density – a key landscape feature associated with predation risk for African ungulates – on herbivore habitat use, and (b) establish whether habitat use patterns could be explained by tradeoffs between foraging opportunities and predation risk-avoidance. 3.In a Kenyan savanna system, replicate plots dominated by the tree Acacia drepanolobium were cleared, thinned, or left intact. Ungulate responses were measured over four years, which included years of moderate rainfall as well as a severe drought. 4.Under average rainfall conditions, most herbivores (primarily plains zebra, Grant's gazelle, and hartebeest) favored sites with fewer trees and higher visibility – regardless of grass production – while elephants (too large to be vulnerable to predation) favored sites with many trees. During the drought, however, herbivores favored sites that had high grass biomass, but not high visibility. Thus, during the drought, herbivores sought areas where food was more abundant, despite probable higher risk of predation. 5.These results illustrate that the “landscape of fear”, and the associated interactions between top-down and bottom-up effects, is not static, but rather shifts markedly under different conditions. Climate thus has the potential to alter the strength and spatial dynamics of behaviorally-mediated cascades in large herbivore systems

All_Data_Density_Expt

Excel file containing data on herbivore use (dung counts, camera trap data), grass production, grass composition and nutrients, and visibility in a replicated manipulation of tree density

Disruption of a protective ant–plant mutualism by an invasive ant increases elephant damage to savanna trees

Invasive species can indirectly affect ecosystem processes via the disruption of mutualisms. The mutualism between the whistling thorn acacia (Acacia drepanolobium) and four species of symbiotic ants is an ecologically important one; ants strongly defend trees against elephants, which can otherwise have dramatic impacts on tree cover. In Laikipia, Kenya, the invasive big-headed ant (Pheidole megacephala) has established itself at numerous locations within the last 10-15 years. In invaded areas on five properties, we found that three species of symbiotic Crematogaster ants were virtually extirpated, whereas Tetraponera penzigi co-occurred with P. megacephala. T. penzigi appears to persist because of its nonaggressive behavior; in a whole-tree translocation experiment, Crematogaster defended host trees against P. megacephala, but were extirpated from trees within hours. In contrast, T. penzigi retreated into domatia and withstood invading ants for >30 days. In the field, the loss of defensive Crematogaster ants in invaded areas led to a five- to sevenfold increase in the number of trees catastrophically damaged by elephants compared to uninvaded areas. In savannas, tree cover drives many ecosystem processes and provides essential forage for many large mammal species; thus, the invasion of big-headed ants may strongly alter the dynamics and diversity of East Africa's whistling thorn savannas by disrupting this system's keystone acaciaant mutualism

A Simple Graphical Approach to Quantitative Monitoring of Rangelands

The Rangelands archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform March 202

Kenya Long-term Exclosure Experiment (KLEE) read me. Site and data description

<div>For a full site description, see Young et al. (1998). This manuscript is also included at the end of the “read me” document.  KLEE was established in 1995 and consists of three replicate blocks, each containing six 200 x 200 m treatment plots. The replicate blocks are 70 – 200 m apart. The experiment uses semi-permeable barriers to allow access by different combinations of cattle (‘C’), mesoherbivore wildlife 15 – 1000 kg (‘W’) and megaherbivores (‘M’). Each of the following six treatments is replicated across the three blocks: C, W, WC, MW, MWC and O. The capital letters indicate which herbivores are allowed access (e.g., ‘O’ allows no herbivores >15 kg, ‘W’ allows mesoherbivore wildlife >15 kg, but no cattle or megaherbivores, and ‘MWC’ allows megaherbivores, mesoherbivore wildlife and cattle). Long-term patterns of dung deposition in the KLEE plots indicate that 1) treatments are >90% effective at excluding targeted species, and 2) experimental fences do not deter wild herbivores from using the plots intended to be accessible to them (see Young et al. 1998 for more details). </div><div><br></div><div>Herded groups of 100-120 head of cattle are grazed in C, WC and MWC plots for several hours on each of two to three consecutive days, typically 3-4 times per year. The precise number of grazing days and timing of grazing largely depends on forage availability, but plots rarely experience more than 16 weeks without cattle grazing. This grazing regime reflects typical cattle management strategies for both private and communal properties in the region – where livestock graze in one general area for several days at a time until forage is depleted, then move on to a different area until the forage recovers. The landscape is not fenced into paddocks, but rather herders guide livestock so that the entire range undergoes similar episodic grazing throughout the year. The stocking rate of plots is similar to the moderate overall ranch stocking rate (0.10-0.14 cattle/ha; Odadi et al. 2007).  Fire has not been an active part of this ecosystem since the 1960s (R.L. Sensenig, personal communication).  </div><div><br></div><div><div>Site description: </div><div>The Kenya Long-term Exclusion Experiment (KLEE) is located at the Mpala Conservancy (3652’E, 017’N) in Laikipia County, Kenya. The study area is underlain with ‘black cotton’ soils, poorly drained vertisols with high  (>50%) clay content (Ahn and Geiger 1987). Black cotton savannas are widespread in East Africa, covering hundreds of thousands of km2. Ninety-seven percent of the tree canopy cover in KLEE is Acacia drepanolobium Sjost. (Young et al. 1998), and total tree canopy cover averages 15-25%. Five grass species (Pennisetum mezianum Leeke, P. stramineum Peter, Themeda triandra Forssk., Lintonia nutans Stapf., and Brachiaria lachnantha (Hochst.) Stapf) make up 85% of herbaceous cover (Porensky et al. 2013). The site is located on virtually flat topography at an elevation of 1810m asl. The absence of distinct runoff or run-on areas, coupled with the relatively low plant diversity, makes this an ideal system to examine the effects of different herbivores on plant production independent of other factors.</div><div>Mpala Conservancy is managed for both wildlife conservation and livestock production, with mean stocking rates of 0.10-0.14 cattle/ha. Wild ungulates commonly found at the study site include the mesoherbivores plains zebra (Equus burchelli Gray), Grant’s gazelle (Gazella [Nanger] grantii Brooke), hartebeest (Alcelaphus buselaphus Pallas), eland (Taurotragus oryx Pallas), and oryx (Oryx gazella beisa L.), as well as the megaherbivores elephant (Loxodonta africana Blumenbach), and reticulated giraffe (Giraffa camelopardalis L.). Total biomass-density (kg /  km-2) of large wild ungulates is approximately one third of cattle biomass-density, and large wild ungulate biomass density is split almost evenly between megaherbivores and mesoherbivore wildlife (Veblen et al. 2016). In addition to these larger herbivores, one small antelope, steinbuck (Raphicerus campestris Thunberg), a strict browser, occurs in the area and is able to access all experimental treatment plots (Young et al. 2005). Wildlife in this region are present year-round and do not undergo large seasonal migrations. </div><div><br></div><div>Descriptions of datasets available for download</div><div>1.Rainfall </div><div>2.Dung</div><div>3.Acacia drepanolobium density and size</div><div>4.Plot locations</div><div>5.Vegetation dataset</div><div><br></div><div>Additional datasets available upon request</div><div><br></div><div>1.Rainfall</div><div><br></div><div>Methods and description: Rainfall measurements were recorded from manual rain gauges located along the fence lines of KLEE. There are a total of three rain gauges. Each KLEE block has one manual rain gauge. Exact GPS locations are located in the “GPS locations” sheet of this document. Rainfall dates are recorded and gauge measurements are taken as soon as possible after rainfall events. </div><div>This Excel worksheet has rainfall data from each of the three replicate KLEE blocks since 2003. There are separate worksheets for daily rainfall, monthly rainfall (since 1996), and yearly rainfall (since 1996). Additional monthly and yearly rainfall data since 1996 are available upon request. Measurements are taken in millimeters. Columns North, Central, and South refer to gauge readings taken in the north, central, and south blocks of KLEE. </div><div></div><div>2.Dung</div><div><br></div><div>Methods and description: Starting in 2006, we have conducted biennial (roughly March and October) dung surveys along six-4 m x100 m permanent transects within each of the 18 KLEE plots and three control transects outside of the KLEE plots. This Excel worksheet features dung count data for each KLEE plot. Count data is broken down by herbivore species. To avoid recounting the same dung piles during subsequent surveys, we crush all recorded dung piles during each session. For animals that defecate in middens (such as steinbuck and Grant's gazelle), we used the number of dung pellets and differences in shape and color to estimate the number of separate defecation events. Dung piles for all major herbivore species could be positively identified to species in the field, with two exceptions. The dung of cattle and buffalo could not be distinguished, and we lumped them. The dung of plains and Grevy's zebras also could not be distinguished from each other; hence we grouped them as “zebra”. However, plains zebra far outnumber Grevy’s, so effectively we consider these to be plains zebra dung.</div><div><br></div><div><br></div><div>3.Acacia drepanolobium density and size survey</div><div><br></div><div>Methods and description: A. drepanolobium makes up approximately 97% of the woody cover in this system. This Excel file contains Acacia drepanolobium density and size distributions in each of the of the 18 KLEE plots. Surveys were conducted in 2011. Trees were surveyed along three 4 m x 100 m transects within each KLEE plot. Each row represents data from one transect. Columns indicate experimental block, plot, number of trees in each of five size classes, and total number of trees for each transect. Additional data for non-drepanolobium woody species, as well as a newly updated 2015 tree survey, are available upon request. </div><div></div><div>4.Plot locations</div><div><br></div><div>Methods and description: This zip file contains 18 .kml files. Each file corresponds with one KLEE plot and is named according to its block (first letter) and treatment (following letters). We collected GPS points from the corners of each of the 18 experimental plots using a Trimble Juno 3B GPS unit with meter-level accuracy. Points were imported into QGIS and used to created polygons of each experimental plot. Polygons were then saved as Google Earth .kml files. </div><div><br></div><div>5.Vegetation dataset</div><div><br></div><div>Methods and description: Herbaceous vegetation in all 18 KLEE plots has been sampled biannually (in February and June) or annually (in June) since 1995.  Sampling periods follow rainy periods that are similar in terms of average rainfall. Due to improvements in species identification, pre-1999 surveys are not fully comparable to later data. Each of the eighteen 4 ha KLEE treatment plots contains a central hectare that is divided into a 10 x 10 m grid of 100 sampling stations. Aerial plant cover and composition are assessed at these stations by counting the number of pins hit by each species over a ten-point pin frame (with vertical pins separated by 5 cm; maximum one hit per pin per species). All 100 grid points were sampled 1999-2005, and every fifth grid point (20 per plot) was sampled from 2006 to 2013 (see Fig. 2 for current vegetation sampling layout). This Excel datasheet contains vegetation data from 1999 – 2013. Later surveys have also been conducted and are available upon request. </div></div><div><br></div><div><br></div