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Agriculture and the exploitation of natural resources have transformed tropical mountain ecosystems across the world, and the consequences of these transformations for biodiversity and ecosystem functioning are largely unknown1-3. Conclusions that are derived from studies in non-mountainous areas are not suitable for predicting the effects of land-use changes on tropical mountains because the climatic environment rapidly changes with elevation, which may mitigate or amplify the effects of land use4,5. It is of key importance to understand how the interplay of climate and land use constrains biodiversity and ecosystem functions to determine the consequences of global change for mountain ecosystems. Here we show that the interacting effects of climate and land use reshape elevational trends in biodiversity and ecosystem functions on Africa's largest mountain, Mount Kilimanjaro (Tanzania). We find that increasing land-use intensity causes larger losses of plant and animal species richness in the arid lowlands than in humid submontane and montane zones. Increases in land-use intensity are associated with significant changes in the composition of plant, animal and microorganism communities; stronger modifications of plant and animal communities occur in arid and humid ecosystems, respectively. Temperature, precipitation and land use jointly modulate soil properties, nutrient turnover, greenhouse gas emissions, plant biomass and productivity, as well as animal interactions. Our data suggest that the response of ecosystem functions to land-use intensity depends strongly on climate; more-severe changes in ecosystem functioning occur in the arid lowlands and the cold montane zone. Interactions between climate and land use explained-on average-54% of the variation in species richness, species composition and ecosystem functions, whereas only 30% of variation was related to single drivers. Our study reveals that climate can modulate the effects of land use on biodiversity and ecosystem functioning, and points to a lowered resistance of ecosystems in climatically challenging environments to ongoing land-use changes in tropical mountainous regions.

Future rainfall dynamics in the Kilimanjaro region will mainly be influenced by both global climate and local land-cover change. An increase in rainfall is expected, but rising temperatures are also predicted for the ecosystem. In situ rainfall of five stations is analyzed to determine seasonal variability and multidecadal trends in the lowlands and lower elevations of the Kilimanjaro region. Monthly rainfall totals are obtained from the Tanzanian Meteorological Agency, from two mission stations, and from a sugar cane plantation. The datasets of the two mission stations cover time spans of 64 and 62 years, starting in 1940 and 1942, while rainfall data obtained from the Tanzanian Meteorological Agency and from the sugar cane plantation start in 1973 and 1974 and thus cover 40–41 years. In one out of five stations, a significant weak negative linear long-term trend in rainfall is observable, which is also evident in the other locations but is not significant. However, humid and dry decades are evident and seasonality has changed, especially during the long rains between March and May. El Niño–Southern Oscillation (ENSO) in combination with positive Indian Ocean dipole (IOD) leads to enhanced rainfall during the year of ENSO onset and the following year. During La Niña years, rainfall increases in the following year, while during the onset year rainfall patterns are more diverse. Positive IOD leads to enhanced rainfall amounts.

This study introduces the set-up of a new meteorological station network on the southern slopes of Kilimanjaro, Tanzania, since 2010 and presents the recorded characteristics of air temperature, air humidity and precipitation in both a plot-based and area-wide perspectives. The station set-up follows a hierarchical approach covering an elevational as well as a land-use disturbance gradient. It consists of 52 basic stations measuring ambient air temperature and above-ground air humidity and 11 precipitation measurement sites, with recording intervals of 5 min. With respect to precipitation observations, the network extends the long-term recordings of A. Hemp who has installed and maintained up to 117 multi-month accumulating rainfall buckets in the region since 1997. The meteorological characteristics of the study region based on the derived data since 2010 are mostly in line with previous studies, although we see increased precipitation amounts at higher elevations during these years when compared with long-term means. We furthermore identify a mean annual condensation level at about 2300 m a.s.l. which has not been reported before. Finally, this is the first study to provide high resolution maps of mean monthly and mean annual temperature, humidity and precipitation for Kilimanjaro, which are of great value for geographically oriented meteorological or ecological investigations. Detailed performance statistics of the geo-statistical and machine learning techniques used for the gap filling of the recorded meteorological time series and their regionalization to the Kilimanjaro region indicate that the presented data sets provide reliable measurements of the meteorological reality at Kilimanjaro.

Spatially high resolution climate information is required for a variety of applications in but not limited to functional biodiversity research. In order to scale the generally plot-based research findings to a landscape level, spatial interpolation methods of meteorological variables are required. Based on a network of temperature observation plots across the southern slopes of Mt. Kilimanjaro, the skill of 14 machine learning algorithms in predicting spatial temperature patterns is tested and evaluated against the heavily utilized kriging approach. Based on a 10-fold cross-validation testing design, regression trees generally perform better than linear and non-linear regression models. The best individual performance has been observed by the stochastic gradient boosting model followed by Cubist, random forest and model averaged neural networks which except for the latter are all regression tree-based algorithms. While these machine learning algorithms perform better than kriging in a quantitative evaluation, the overall visual interpretation of the resulting air temperature maps is ambiguous. Here, a combined Cubist and residual kriging approach can be considered the best solution.

Agriculture and the exploitation of natural resources have transformed tropical mountain ecosystems across the world, and the consequences of these transformations for biodiversity and ecosystem functioning are largely unknown

Large-herbivore migrations occur across gradients of food quality or food abundance that are generally determined by underlying geographic patterns in rainfall, elevation, or latitude, in turn causing variation in the degree of interspecific competition and the exposure to predators. However, the role of top-down effects of predation as opposed to the bottom-up effects of competition for resources in shaping migrations is not well understood. We studied 30 GPS radio-collared wildebeest and zebra migrating seasonally in the Serengeti-Mara ecosystem to ask how predation and food availability differentially affect the individual movement patterns of these co-migrating species. A hierarchical analysis of movement trajectories (directions and distances) in relation to grass biomass, high-quality food patches, and predation risk show that wildebeest tend to move in response to food quality, with little attention to predation risk. In contrast, individual zebra movements reflect a balance between the risk of predation and the access to high-quality food of sufficient biomass. Our analysis shows how two migratory species move in response to different attributes of the same landscape. Counterintuitively and in contrast to most other animal movement studies, we find that both species move farther each day when resources are locally abundant than when they are scarce. During the wet season when the quality of grazing is at its peak, both wildebeest and zebra move the greatest distances and do not settle in localized areas to graze for extended periods. We propose that this punctuated movement in high- quality patches is explained by density dependency, whereby large groups of competing individuals (up to 1.65 million grazers) rapidly deplete the localized grazing opportunities. These findings capture the roles of predation and competition in shaping animal migrations, which are often claimed but rarely measured. Fil: Hopcraft, J. Grant. University Of Glasgow; Reino Unido. Frankfurt Zoological Society; Tanzania Fil: Morales, Juan Manuel. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; Argentina Fil: Beyer, H. L.. The University Of Queensland; Australia Fil: Borner, Markus. University Of Glasgow; Reino Unido. Frankfurt Zoological Society; Tanzania Fil: Mwangomo, Ephraim. Tanzania National Parks; Tanzania Fil: Sinclair, A. R. E.. University Of British Columbia; Canadá Fil: Olff, Han. University Of Groningen; Países Bajos Fil: Haydon, Daniel T.. University Of Glasgow; Reino Unido

The factors determining gradients of biodiversity are a fundamental yet unresolved topic in ecology. While diversity gradients have been analysed for numerous single taxa, progress towards general explanatory models has been hampered by limitations in the phylogenetic coverage of past studies. By parallel sampling of 25 major plant and animal taxa along a 3.7 km elevational gradient on Mt. Kilimanjaro, we quantify cross-taxon consensus in diversity gradients and evaluate predictors of diversity from single taxa to a multi-taxa community level. While single taxa show complex distribution patterns and respond to different environmental factors, scaling up diversity to the community level leads to an unambiguous support for temperature as the main predictor of species richness in both plants and animals. Our findings illuminate the influence of taxonomic coverage for models of diversity gradients and point to the importance of temperature for diversification and species coexistence in plant and animal communities., Explaining species richness patterns is a key question in ecology. Peters et al. sample diverse plant and animal groups across elevation on Mt. Kilimanjaro to show that, while disparate factors drive distributions of individual taxa, diversity overall decreases with elevation, mostly driven by effects of temperature.

The results of 10 years of monitoring water quality and quantity during the period 1996-2006 in the three rivers (Mbalageti, Grumeti and Mara) draining the Serengeti ecosystem are presented, together with river gauging data starting in 1948, rainfall data starting in 1960, and animal population data starting in 1960. Water quality remained unchanged in the Mbalageti and Grumeti rivers; these rivers are seasonal and they dry out during a drought. The Mara River is perennial and is vital to maintain the ecosystem during a drought. Its quality has changed, with increased contribution from groundwater, with higher pH and visibility and decreasing salinity. The flow rate during a drought has decreased by 68% since 1972. This is attributed to deforestation of its upper catchment in the Mau forest in Kenya and to extraction of water for irrigation in Kenya upstream of the ecosystem. Hydrological modeling suggests that the Mara River would now dry out for two months and one month respectively if the 1949-1952 and the 1972-1973 severe droughts occurred again. Ecohydrologic modeling suggests that this would in turn lead to the collapse of the herbivore population from the lack of drinking water. This model also suggests that providing drinking water to the animals at artificial water holes spread throughout the ecosystem would lead to decadal time-scale booms and busts of the herbivore population. The Serengeti ecosystem stability is maintained by the annual migration that partitions the ecosystem in seasonally used compartments. It is thus necessary to restore the natural hydrology of the Mara River in Kenya, and this requires remediation measures in Kenya. If that does not occur, disaster prevention measures are needed by providing water in weirs, dams, and artificial wetlands along the Mara River in the Serengeti National Park, as well as extending by 5 km the western edge of the park so as to reach Lake Victoria to provide acces to permanent water.

The dissolved oxygen concentration (DO) was sampled during a diurnal cycle in three water holes heavily used by wildlife and with distinctive biological features along the Seronera River. The DO fluctuated widely (by up to 11.5 mg l−1) as a function of time, mechanical stirring and aeration by animals, and the presence of fringing wetlands. The DO cycle was successfully modeled (within 0.3 mg l−1) by assuming that the four dominant processes were photosynthesis and respiration by algae near the surface, trapping by wetlands, decomposition of dead organic matter on the bottom, and stirring/aeration by hippos. The rate of DO decline from the decay of dead organic matter was equal to the rate of DO removal by algal respiration at night.

The distribution of temperature, salinity, visibility and dissolved oxygen was sampled from 1996 to 2002 at sites along the Seronera River. The minimum temperature decreased with distance upstream. The salinity increased up-river where occasionally hypersaline conditions prevailed. Dissolved oxygen was highly variable spatially and temporally, depending on both the level of eutrophication by animal dung and the presence of wetlands that help filter the excess nutrients. During the study period, fringing, freshwater wetlands have generally been degraded and in some cases destroyed, and this has been accompanied by significantly decreased oxygen levels, sometimes nearing anoxic conditions. Also during this period, saltwater wetlands have increased, and since wildlife impacted these wetlands little, dissolved oxygen levels remained high throughout. Visibility was highest in areas fringed by wetlands.

The conservation of migratory species can be problematic because of their requirements for large protected areas. We investigated this issue by examining the annual movements of the migratory wildebeest, Connochaetes taurinus, in the 25000 km2 Serengeti-Mara Ecosystem of Tanzania and Kenya. We used Global Positioning System telemetry to track eight wildebeest during 1999–2000 in relation to protected area status in different parts of the ecosystem. The collared wildebeest spent 90% of their time within well-protected core areas. However, two sections of the wildebeest migration route – the Ikoma Open Area and the Mara Group Ranches – currently receive limited protection and are threatened by poaching or agriculture. Comparison of current wildebeest migration routes to those recorded during 1971–73 indicates that the western buffer zones appear to be used more extensively than in the past. This tentative conclusion has important repercussions for management and needs further study. The current development of community-run Wildlife Management Areas as additional buffer zones around the Serengeti represents an important step in the conservation of this UNESCO World Heritage Site. This study demonstrates that detailed knowledge of movement of migratory species is required to plan effective conservation action.