Global environmental change, including climate change, is undoubtedly a pressing issue of global concern in recent times (Naeem et al., 2009; Bulkeley and Newell, 2010; Hussein, 2011). This in part is due to a rise in extreme events and associated threats to humanity, species and habitats (Birkmann et al., 2014; Allen and Allen, 2017; Ma et al., 2018). Climate variability and change in particular alters plant phenology because temperature tends to influence the timing of development, singularly and through interactions with other cues, such as photoperiods (Partanen et al., 1998; Fitchett et al., 2015; Suonan et al., 2019). In tropical regions and ecosystems, phenology dynamics are often less sensitive to temperature and photoperiods but more aligned to seasonal shifts in precipitation (Reich, 1995). These phenology patterns are attuned to environmental conditioning including the associated seasonality patterns (Cleland et al., 2007; Puppi, 2007). Shifts in plant phenology offers compelling evidence of ecosystem interactions with climatic patterns as well as with other components of global environmental change including the accumulation of atmospheric carbon dioxide (Cleland et al., 2007; Stocker et al., 2013). Phenology dynamics have important implications for biophysical and biogeochemical feedbacks to the climate system (Piao et al., 2019). Further, plant reproduction, population-level interactions, community dynamics and plant evolution and adaptations often influence ecosystem functions and services (Isbell et al., 2011; Maestre et al., 2012). These can, however, be altered by shifts in plant phenology (Peñuelas et al., 2013; Suonan et al., 2019).

Phenology examines organism-environment relationships using critical life cycle phenomena as the primary window (Liang and Schwartz, 2009). In situations where vegetation phenology varies at a scale relevant to the movements of individuals (e.g., dispersal or foraging ranges), such knowledge is essential to understanding processes and dynamics within such ecosystems (Cole and Sheldon, 2017). Analysis of phenology dynamics at landscape level is relevant because seasonal vegetation dynamics (including spatial and temporal patterns) within heterogeneous biophysical environments is critical for understanding the complex functioning of ecosystems. This includes the interactions of primary producers with seasonal and inter-annual environmental variability across landscapes (Liang and Schwartz, 2009). These heterogeneous phenological dynamics at regional and landscape-level are also important for animal populations (Haddad et al., 2011; Simms, 2013). This is because variation within a wide range of abiotic factors (e.g., soil moisture and nutrients, temperature, precipitation) often can cause plants at different locations to initiate growth at different times (Zheng et al., 2016). Evidence available indicates that plants and animals exhibit seasonal patterns in their activities. This is attributed to the fact that there is a seasonality in the suitability of their environment (Visser and Both, 2005).

In the Serengeti plains of Tanzania and Kenya, population viability of some grazers is directly influenced by access to patches of grassland that are varied in phenology as a result of spatial heterogeneity (Fryxell et al., 2005). Thus, plant phenology is an important parameter for showing long-term and seasonal variations in development patterns for both annual, biannual and perennial plants across different landscapes (Primack and Gallinat, 2017; He et al., 2018; Hegazy et al., 2018). Changes in phenological patterns of vegetation such as the rate and duration of photosynthetic activities, onset of greenness (OGT), end of greenness time (EGT) and duration of greenness (DOG) have the potential to serve as indicators of change in environmental quality including impacts on plant production (Vrieling et al., 2016; Ibrahim et al., 2018). Further, it is vital in detecting spatio-temporal variations in plant health and productivity (Tottrup and Rasmussen, 2004; Boke-Olén et al., 2016).

It is apparent that spatial heterogeneity in resources at landscape scale allows mobile consumers to compensate for temporal variability in resource availability at local scale (Fryxell et al., 2005). This is an important landscape characteristic of relevance to herbivores because it confers nutritional benefits by extending the foraging time as well as resource access at landscape level (Coogan et al., 2012). In water limited ecosystems especially semi-arid and arid areas, plant phenology is seldom synchronized across the landscape. However, it tends to vary asynchronously as a result of spatial and temporal variation in elevation, aspect, and weather (Chen and Pan, 2002; Hobbs et al., 2008). In these landscapes, wild herbivores, pastoralists and their livestock respond to gradients and pulses in forage quality and quantity by matching their distribution to spatially variable peaks and gradients in forage quality (Scoones, 1995; Hebblewhite et al., 2008). Responses occur in varying forms and at varying spatial and temporal scales. One adaptation strategy used by pastoral groups in response to this variability is to move across the landscape in search of abundant and nutritious forage (Ellis and Swift, 1988). These movements are key to sustaining the foraging and nutritional needs of livestock (Turner and Schlecht, 2019). They are critical for traditionally guided plant inflorescence-phenological dynamics (Dunning et al., 2016). They also form the basis for the ecological resilience of both pastoral livelihoods and rangeland ecosystems (Boles et al., 2019).

Accelerated environmental changes in pastoral landscapes in East Africa have been registered in the last two decades (Little, 1996; Boles et al., 2019). These changes include increased extreme weather events especially drought and flash floods (Ayal et al., 2018; Kimaro et al., 2018), land use land cover change and habitat fragmentation (Kimiti et al., 2018). These changes in part reflect policy shifts driven by outsiders that have historically viewed pastoralism as working against both environmental and development goals (Turner and Schlecht, 2019). In pursuit of “development,” restrictions on pastoral mobility were imposed and at the same time significant promotion of sedentarisation and crop farming in much of Karamoja sub-region (Krätli, 2010; Egeru, 2016). Restrictions were imposed following the need to bring “peace” by controlling livestock theft within Karamoja and with neighboring communities and across Kenya, Uganda and South Sudan. In essence, the traditional pastoral Karamojong was “quarantined” to graze within the sub-region without being able to explore the traditional grazing pathways. Such restrictions of mobility of people and animals prevents herbivores and pastoralists from matching their distribution to the resources they require to survive and reproduce (Hobbs et al., 2008). Such interruptions on migratory pathways lead to profound effects such as landscapes becoming unsuitable to support people and animals (Fryxell et al., 2005) and localized degradation (Egeru et al., 2019).

Amidst these environmental changes, political orientations and re-orientations to what constitutes “development” in Karamoja and climate variability and change remain unresolved (Gray, 2000; Jabs, 2005; Krätli, 2010; Egeru et al., 2019). The intensity, frequency and shortened return time of extreme events (especially drought) is more pronounced today (Mubiru et al., 2018; Nsubuga and Rautenbach, 2018). Neighboring pastoralists from Kenya (Turkana, Pokot) have recently had to spend longer grazing time on the Uganda side than in previous grazing cycles. By spending a longer grazing time in Karamoja, they impose an additional challenge to people whose mobility is restricted. Accordingly, a paucity of information exists on vegetation dynamics in the region and how it might be able to support the internal mobility of pastoral groups within Karamoja as well as the external grazing pressure from Kenya and South Sudan. This study assessed savannah vegetation phenology with the aim of identifying spatio-temporal dynamics of plant activity in Karamoja sub-region. In doing so, we hold the assumption that the pastoral groups from within and outside the sub-region have only been able to maintain their livestock herds because of an inherent landscape heterogeneity. Further, Turner and Schlecht (2019) have opined that pastoral transhumance responds more to seasonal variabilities and spatial heterogeneities that display some predictable regularities across the landscape.

Karamoja sub-region is located in north-eastern Uganda and covers a total land area of 27,319 square kilometers. The sub-region is located between latitude 1°31′ to 4°N and longitude 33°30′ to 35°E. It is constituted by seven districts including: Kotido, Abim, Moroto, Amudat, Napak, Kaabong, and Nakapiripirit (Figure 1A). The sub-region consists of plains that rise toward the hilly terrain in the eastern parts of the region bordering the escarpment along the border with Turkana District of Kenya. The Kidepo Valley National park is part of the open grassland and woodland savannah ecosystems that predominate in the northern parts of sub-region. The landscape opens to the plains and low lands of central to western Karamoja, interrupted by Mt. Napak and isolated inselbergs and mountainous rises of the Iriri and Alekilek Mounts toward the border with the Teso sub-region to its west. In southern Karamoja in parts of Nakapiriti, occurs the Kadam Mountains that later open to the plains and flats in Namaalu with lush grassland ecosystem. This sub-region in Uganda is classified as semi-arid region and is known for its rainfall variability and intermittent droughts. Rainfall in the sub-region on average is about 800 mm with a non-uniform distribution ranging from 300 to 1200 mm in some parts of the sub-region (Egeru et al., 2014). Temperatures are considerably high and range from 28 to 32.5°C (maximum temperature) and from 15 to 18°C (minimum temperature) making evaporation rates in the sub-region similarly high.

The high evaporation rate in addition to the area sloping to the west leads to limited retention of water in the area as runoff rapidly accumulates in the lowland-wetlands of Teso, Lango, and Acholi sub-regions. The sub-region has had a marked irregularity in rainfall since the 1920s through 1940s and 1950s and intense droughts in the 1980s (Gulliver and Dyson-Hudson, 1967). This irregularity and unpredictability of rainfall patterns has exacerbated the fragility of local pastures and has required flexible and knowledgeable day-by-day herding decisions of pastoral households in the sub-region (Filipová and Johanisova, 2017). As a result, changes in the livelihood and lifestyle sources have occurred. For example, the International Organisation for Migration indicated that 40% of households in the sub-region now rely on natural resource extraction. Wood is used for charcoal production, topsoil is used to make bricks, and quarrying stone is used as a primary source of income and livestock management. Livestock, once dominant, is now a primary source of income for only 17% of the households in the sub-region. Despite this perceived income allocation sources, livestock remains a key livelihood asset and strategy as many households are striving to rebuild their livestock herds. In fact, Krätli (2010) indicated that the persistent food insecurity challenge in Karamoja is a livestock crisis indicator.

Traditionally, the Karamojong moved their livestock in a transhumant manner to manage grazing resources heterogeneity at landscape level. However, after the accumulation of guns in 1911 and pacification by the colonial administration from 1921, restrictions on movement in and out of Karamoja were imposed. These restrictions prevented the Karamojong from being able to freely graze their livestock within their traditional grazing lands (Knighton, 1990; Filipová and Johanisova, 2017). Most recently in the post disarmament exercise in 2007, a total ban on livestock from Karamoja leaving the sub-region was imposed. As a result, the pastoral households have had to manage their livestock numbers within the sub-region which has also had to accommodate the transhumant Turkana (herders from Kenya) who come to the sub-region as a dry season grazing ground (Egeru, 2016; Figure 1B). These dynamics have shaped resource use, governance and power relations. Where failure and competition for resources has been intense, violence and conflict over grazing lands and watering resources have been registered. This makes it critical to monitor vegetation dynamics in the sub-region.

Considering the range of savannah vegetation phenological characteristics, the onset of greenness NDVI threshold value was set to 20% of the distance between minimum and maximum NDVI during the rising levels (Zhang et al., 2015). The end of greenness was also determined in a similar manner (Song et al., 2011). The 20% threshold accounts for noise in the NDVI data and prevents the identification of false starts and/or end of greenness time (Van Leeuwen et al., 2010).

The maximum NDVI (NDVI_max) with in the year was obtained, thereafter, during the NDVI rising stage, minimum NDVI (NDVI_min) was obtained and a 20% of the difference between NDVI_max and NDVI_min was set as the threshold (NDVI_threshold). Time of onset of greenness was defined as the date when NDVI reaches NDVI_threshold. The date when NDVI reaches to NDVI threshold for the first time was defined as time of onset of greenness. Time of end of greenness was defined in the same way during the descending stage (Appendix 1) for all vegetation types in the region as illustrated in 2001 for grassland vegetation (Appendix 1). Therefore, a threshold value of 0.1 NDVI as computed and obtained by several scholars (Lloyd, 1990; Reed et al., 1994; Jönsson and Eklundh, 2004; Song et al., 2011) was determined. This threshold was applied to all land cover types during the analysis.

In this study, we assessed the phenology of savannah vegetation to identify the spatio-temporal dynamics of plant activity in the Karamoja sub-region. We observed variability in phenological metrics of the four savannah vegetation cover types, namely bushland, grassland, woodland and thicket and shrub. Both intra-annual and inter-annual dynamics in phenology were evident across the Karamoja landscape. The observed intra and inter-annual variations point to the existence of different physiological mechanisms of plant growth, nutrient cycling, and abiotic processes including those influenced by geomorphology, soil fertility, climate, and disturbances such as fire which is commonly associated with semi-arid landscapes (Myoung et al., 2013). Fire as a disturbance in semi-arid areas plays an intrinsic role in shaping biophysical attributes of savannah ecosystem by limiting biomass below its climatically determined potential (Singh et al., 2018). In addition to other biotic and abiotic factors, above-ground phytomass disturbance and variable plant responses to fire, leads to differences in the dynamics of plant phenology across semi-arid areas landscapes (Snyman, 2004; Tokura et al., 2018; Richter et al., 2019). These disturbances appear to have been responsible for a lower signal strength in the sub-region in 2009. This lower signal strength in 2009 is traceable to the 2009/2010 drought episode. Using satellite-based indices derived from NDVI, Nakalembe (2018) identified extreme drought in 2009 over the sub-region.

Whereas we anticipated to find intra and inter-annual variability in vegetation phenology primarily because of the inherent climate variability (Egeru et al., 2014, 2019) in the sub-region, the specific metrics such as OGT, EGT, and DOG posited unique patterns within each of the main vegetation types. However, all of these savannah vegetation types showed OGT signals within late March and early April with a probability ranging between 67 and 75%. This falls within the main rainfall period in the sub-region and in most of the semi-arid areas of Uganda. Variability in the onset for the March-May rainfall and green-up has been observed to be variable across most of Uganda from year to year and in several occasions has been observed with some delays of even up to 30 days, thus starting in mid-April instead of mid-March (Mubiru et al., 2012). Such variability appears to have been captured by the vegetation greenup signals in the current study. This study has further demonstrated that savannah vegetation responds to rainfall signals but at varying levels which is demonstrated by lag-time of nearly 3 weeks observed in this study.

The variability observed in OGT with respect to vegetation types could perhaps be explained by specific vegetation response to climate parameters especially rainfall (Kang et al., 2018). Thus, the lag-time seen in this study between the different vegetation types within a 3 week range could indicate a critical threshold required for the vegetation to grow leading to the commencement of the OGT between the thicket and shrubs, grassland and woodland. Previous studies have shown that vegetation grows when a critical threshold is met based in part on cumulative rainfall, the proportion of annual average rainfall and relative soil moisture index (Lyamchai et al., 1997; White et al., 1997; Tao et al., 2017). This is particularly important in semi-arid regions of Africa where cumulative rainfall stimulates vegetation green-up. The Onset observed in this study corresponds to earlier analysis of vegetation phenology over the Horn of Africa in which Zhang et al. (2005) observed a first set of onset occurring in April, with a second one in September. Further, Vrieling et al. (2013) have suggested that a delayed onset of green-up is logical because there is often a lag time between the onset of rainfall and green-up. It is however important to note that contrary to the expectations that grassland would experience an early OGT, it was the thicket and shrubs and woodland that had an early sprouting. We attribute this development to a pre-rain green-up that has previously been documented in African savannahs (Adole et al., 2018). It also strengthens the understanding that vegetation growth onset in semi-arid regions is more often than not biome-dependent. This was stressed earlier by Pau and Still (2014) who pointed out that the length of the growing season varied between different vegetation types.

Although we observed a nearly consistent pattern in onset in this study, the intra-vegetation cover type variability was a stronger signal for heterogeneity of livestock grazing resources in the sub-region. The strong varied spatial occurrence of green-up within and across vegetation cover types within the early, normal and late green-up delivers grazing resources at different periods of time and at different locations in the sub-region. This is vital for differentiated pastoral utilization of landscapes. For example, we have shown that woody vegetation cover (woodland, thicket and shrub, and bushland) generally have earlier green-up compared to grassland. In parts of the Horn of Africa that are semi-arid, it has already been shown that even within a dry-spell, vegetation and especially trees and shrubs, remains green and abundant (Vrieling et al., 2013). According to Ellis and Swift (1988) pastoralists have relied on these varying forms of vegetation response and at varying spatial and temporal scales to graze their livestock across landscapes and have thus formed a strong basis for the resilience of pastoral livelihoods and rangeland ecosystems (Boles et al., 2019).

Variability is inherent in the sub-region's phenology. We have observed varied commencements for EGT to occur between July-November. Taken across the vegetation cover types, we did not find this EGT significantly different from each other however the intra-vegetation cover type variability was pronounced. A late EGT for grassland (49%), thicket and shrub (87%) and woodland (58%) provides support for the idea that heterogeneity in livestock resources exists across the landscape. It has been observed that woody vegetation with leafy fodder is often more reliable for livestock nutrition than grasses (Opiyo et al., 2015). In this study, both thicket and shrub and woodland tended to have a late EGT thereby becoming important grazing points during dry conditions. Further, this variability often dictates seasonal movements between base locations observed by Turner and Schlecht (2019) among pastoral communities in sub-Saharan Africa.

We also observed varying duration of greenness time (DOG) which occurred as a direct result of the patterns of OGT and EGT. Accordingly, while thicket and shrubs green up much earlier, the woodland had a longer duration of greenness (DOG) compared to all other vegetation types. In their study in southern Africa, Dekker and Smit (1996) observed similar patterns with grassland having short life cycles. Grassland have also been shown to be less adaptive to periods of moisture deficits (Puppi, 2007; Rather et al., 2018). We have also seen that the DOG appears to partition the sub-region into three key areas namely eastern, central and western Karamoja corridors with the western areas generally having a longer DOG occurrence, followed by central and eastern having a shorter DOGs for most of the vegetation cover types. These observed patterns do align with the rainfall dynamics and gradients in the sub-region. For example, locations in the western to southern Karamoja that exhibit a longer DOG correspond to lowlands and some highland areas of Mt. Labwor, Mt. Napak and Mt. Kadam that receive relatively higher rainfall in the sub-region (Egeru et al., 2019). Similarly, patches observed in eastern Karamoja occur around Mt. Moroto area as well as in the Mt. Morungole highlands of northern Karamoja. These areas have also traditionally served as important dry season grazing grounds in the sub-region (OCHA, 2010; see Figure 1B). Owing to these patterns, these areas have through historical time served as dry season grazing landscapes for the Karamoja sub-region. Throughout historical times, these areas of supposed resource abundance have dictated relationships, alliances, power and conflict in the sub-region (Ocan and Ocan, 1994). Given recent developments in the sub-region which restrict the outward mobility from Karamoja to neigbouring sub-regions for grazing, the locations with extended duration of greenness have become increasingly important grazing locations.

We analyzed the phenological dynamics of the Karamoja sub-region using a suit of phenological metrics across four vegetation types (bushland, grassland, woodland, and thicket and shrub). We observed intra and inter-annual variability in key metrics including OGT, EGT, and DOG during the period of analysis. There was an apparent consistency in the onset of greenness time around late March and first week of April across the study area. However, woodland and the thicket and shrubs showed a relatively earlier OGT in the sub-region which was most pronounced around the districts of Napak and Nakapiripirit. This could point to a pre-rain green-up that has also been previously documented in other studies associated with savannah ecosystems across Africa. Within the variable DOG, we found that grassland vegetation was associated with a shorter DOG while woodland had a longer DOG across the sub-region. The highland areas in Karamoja region experienced longer periods of greenness compared to low-lying areas. Longer and shorter DOG was associated with longer and shorter length of growing season, respectively. Owing to the inherent variability in space and time observed in the sub-region, we confirm that the sub-region has an inherent heterogeneity. This heterogeneity could be important to livestock herders in the sub-region particularly because the EGT is spread variably across different landscapes and vegetation types. This could be aiding pastoral mobility and supporting their ability to meet their livestock nutrition across the year. Based on apparent variability and consistencies-regularities observed in this study, a practical direction should be to understand how these patterns are shaping pastoral mobility patterns in the sub-region. Further, an examination of how local institutions (both state and non-state) are helping to support mobility within a complex system of variability and heterogeneity, statehood, competing land uses, alliances and a rapidly evolving yet dangerous notion of modernization by eliminating mobility in the sub-region, are requisite conversations.

The datasets generated for this study are available on request to the corresponding author.

AE and JM conceptualizing. AG and BB providing technical back stopping on data analysis and imagery. AE, JM, DK, and AS imagery processing and drafting manuscript. JN overall project coordination. AE funds sourcing and field activity arrangements. All authors contributed to the article and approved the submitted version.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.