Tag Archives: livestock

Livestock production: the limits of extensive systems in Zimbabwe

As the previous blog described, the communal area sites we have been studying in Masvingo rarely produced sufficient crops to cover even subsistence needs, and then if so only very occasionally, as with the Mwenezi experience in 2016-17. So what about livestock production?

Given its drought-prone nature, Masvingo province is known as cattle-keeping country. Many of the former white-owned farms were large ranches, often covering vast areas with very few stock. Communal area people were able to make use of this to poach graze and supplement the limited grazing in their own areas. Now with resettlement farms surrounding them, communal areas are more hemmed in. Although in the early 2000s there was surplus grazing in the new resettlements as people settled and carved out fields, this is much less the case now. Indeed, in responses to questions about interactions with nearby resettlement areas, conflicts over grazing (and also thatch grass and fuelwood) came top in the ranking by our communal area respondents.

This means that extensive livestock production is constrained in communal areas, perhaps even more so than in the past. Before the 2000 land reform sometimes negotiations were made with nearby (white) farmers, especially during drought, for access to grazing, but more often herders risked poach grazing, and occasionally suffered the consequences of the confiscation of herds and arrests. However, given the scarcity of grazing in the communal areas, it was worth it.

What happens now? Of course poach grazing persists, hence the recording of frequent conflicts, but also there are quite a few loan arrangements that facilitate access to grazing as animals are loaned to relatives or friends in the resettlements. They then have the benefit of the draft power, manure and milk, and (sometimes) the occasional offspring in exchange, while the owner keeps the animals alive and breeding. This was a very common pattern in the first decade of resettlement after 2000; however as settlers have built up their own herds, and the connections to their ‘home’ areas have faded, they are increasingly reluctant to take on communal area livestock. From our sample, loaning out was absent in the two Gutu sites, but still persisting in Mwenezi.

As the table below shows, with the exception of Mwenezi, our communal area sites could not be described as major livestock production areas. Indeed, over a third of households hold no cattle at all, and are reliant on sharing of others’ for draft power (see previous blog). Outside Mwenezi, smallstock holdings are small, and donkeys, pigs and broilers are rare.an purchase regularly. This was only 6-9% of households in the sites outside Mwenezi, where 23% had purchased cattle in the previous five years.

  Mwenezi Chivi Gutu West Gutu North
Cattle held per household (N) 7.6 4.0 3.1 3.7
Loaned in (N) 1 0.5 0.5 0.4
Loaned out (N) 1.7 0.2 0 0
Above zero cattle (%) 64 66 51 61
Above ten cattle (%) 22 8 6 7.3
Cattle purchased in last 5 years (% of households) 23 8 6 9
Cattle sold in last year (%) 41 6 14 15
Cattle milk sales (%) 24 2 0 0
Goat (N) 7.9 1.8 2 2
Sheep (N) 0.8 0.1 0.5 0
Smallstock sold in last year (% of households) 44 8 14 5
Donkey (N) 1.3 0.3 0.2 0.1
Pig (N) 0.9 0 0.1 0.1
Broiler % 2 9 5 0
Broiler contract (% of households) 1 0 0 0
Herding labour hire (%) 7 4 1 2
Feed inputs (%) 7 0 5 19
Vet inputs % 30 20 23 19

 

Perhaps only Mwenezi could be described as a livestock system based on production, with a relatively large average cattle (7.6, ranging from zero up to 105) and goat (7.9, ranging from 0 to 60) holdings, and regular sales and purchases. Although more than the other sites, there is still very limited labour hired explicitly for herding (only 7% of households). Cattle milk sales are also recorded here from those with larger breeding herds. This is not surprising given the dry conditions of the area, and the extensive, relatively high quality sweet grazing available. While the bumper sorghum harvest in the years of our study was unusual, livestock production can provide a regular income.

This contrasts with all the other sites where average cattle holdings averaged 3-4; just about enough to maintain a draft span, and provide some transport, manure and milk, but sales and purchase are comparatively much lower. When sales occur, these are usually emergency sales for school fees, medical expenses or a funeral. Replacements are by-and-large through births within the herd, and these are infrequent because of the small herd size and the age/sex composition, which is geared towards older oxen for draft rather than a breeding herd.

Limited intensification

You might expect, with constrained grazing, there would be a shift to more intensified production – for example stall feeding with purchased feed. There is some evidence this is happening to a small extent in Gutu North, where 19% are purchasing feed, but most of this is at a very small level, and largely supplements. In other areas, this is not a phenomenon except for a few who will buy in to support calves or pregnant cows. Contract arrangements for livestock production have not taken off in these areas, which would be another way of financing feed and other inputs for a more intensified alternative. Only a few in Mwenezi are linked to a contract broiler arrangement with a local farm.

With the collapse of state veterinary services in recent years, and the poor quality of dipping chemicals, there has been a rise in tick diseases across the country. This has meant that those with resources purchase spray dip chemicals for private spraying. Some also recorded buying veterinary medicines for sick animals. A quarter to a third of households – those with larger, more valuable herds and flocks – invest in this way, and have learned to cope without state services. The rest remain vulnerable and deaths from a variety of tick-borne diseases are regularly recorded, especially in wetter years.

In sum, outside Mwenezi, despite Masvingo’s former reputation, these are largely not livestock production areas today. Cattle are kept for multiple uses, notably as inputs to agriculture which, despite poor results, is still seen as the core activity. Land areas are constrained in the communal areas with notional grazing areas often occupied by settlements and farms, or very heavily used and so degraded. This is very different to the situation in the past, and in other parts of the country further west in Matabeleland and southern Midlands, where a more livestock-based economy exists, more akin to that found in Mwenezi and the Lowveld areas.

Contrasts with the resettlement areas?

The A1 resettlement areas nearby are not that different. Here cattle are kept primarily as an input to agriculture, for draft power and manure, with milk, meat and live sales being bonuses, and sales key for emergencies. The herd is seen a stable savings account, which, given the volatility of the economy, makes much sense. Yet the herd size is mostly too small to allow for the possibility of making a regular living. In the A1 resettlement areas too, pressure on land is increasing. In 2000, there was plenty of spare grazing, but now more people have arrived, lands have been subdivided and grazing areas are being encroached. With more fields and settlement, the need to for herding labour during the cropping season increases, but labour is scarce and expensive, and relatively few invest in dedicated herding labour, as with the communal area sites. In other words, unlike for crop agriculture, livestock production in the resettlement and communal areas is more similar.

The big exception is broiler production, which, as a project for younger family members and women, has taken off across the new resettlements. Sometimes this is supported by contracting arrangements, but usually it is independent, financed by surplus income from agriculture and off-farm sources. The difference here is the availability of cash for investment. In the communal areas this is rare, and many are living hand to mouth. Occasionally an aid project will come along, but these are sporadic and often last just a few years. For most communal area households usually there’s not enough surplus to do much more than keep going. This is different in a significant proportion (not all by any means – see other blogs) of resettlement households, where accumulation from agriculture can be invested elsewhere and investment drives further investment in process of stepping out (diversifying) and up (accumulating) of livelihoods.

Once again, land redistribution and the opportunities for accumulation that this offers provides the basis for enhanced livelihoods. But this is constrained for land extensive production activities such as with livestock. Former white farmers had hundreds if not thousands of hectares and managed to make a reasonable (but not always very good) living from livestock ranching. With a more equitable distribution of land this is no longer an option, and more intensive approaches to production – broilers, piggeries, stall-feeding and so on – become the priorities outside the areas like Mwenezi with good grazing and land surplus. Such investments, though, need cash, and this is in very short supply, with limited other options in the communal areas as the next blog will discuss.

This post is the fifth in a series of nine and was written by Ian Scoones and first appeared on Zimbabweland.

This field research was led by Felix Murimbarimba and Jacob Mahenehene. Data entry was undertaken by Tafadzwa Mavedzenge

Photo credit: Tapiwa Chatikobo

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Models for integrated resource assessment: biases and uncertainties

What are the most appropriate ways of understanding changes in natural resource change in rural areas, particularly in the context of climate change? How can we make use of data that is patchy and uncertain? How can models help decision-making about future management?

These questions are at the heart of three recently published journal articles on Zimbabwe. The three papers focus respectively on climate impacts on livestock feed (in Nkayi), land use intensity patterns (in Wedza) and the prevalence of grass fires (in Mazowe). What connects them is the use of remotely-sensed data on land use with an integrated modelling approach, aimed at policy prescriptions for resource management.

This style of research on natural resource use has become more and more common in recent years, as increasingly detailed data derived from satellite systems has become freely available. Integrated assessment models, modelling everything from climate impacts to crop production to land-use to water scarcity, can be linked to geo-referenced spatial data and parameterised with field-based data collection.

As a style of inquiry, integrated modelling approaches have a number of advantages. Diverse data sources can be combined, and predictions made around key policy issues. But there are also problems – and, in different ways, these three papers illuminate some of them.

Five problems with integrated resource assessment modelling

First, models are always framed by assumptions around problems and solutions. Each of these studies adopts a particular stance, resulting in recommendations for interventions to address the highlighted problem. So, climate change results in feed gaps for livestock, which can be solved by ‘climate smart’ adaptation measures in Nkayi. High land use intensity – excessive extraction of primary production – means that ‘hot spots’ of land degradation ‘externalities’ can be identified for intervention measures in Wedza. Increasing fire frequencies are assumed to be universally a bad thing, not a necessary consequence land clearance or a reflection of natural cycles in savannah dynamics, as fuel load builds up. Instead, recommendations, including the deployment of fire teams, creating fire-breaks and developing monitoring systems, are put forward for Mazowe.

Second, the uncertainties embedded in complex models are legion, meaning that any predictions have to be heavily qualified. These papers all acknowledge important uncertainties. In the assessment of land use intensity against a baseline of net primary production in Wedza, these arise, for example, from problems of estimating primary production in the baseline case, especially below-ground. Linking biomass harvesting to specific areas when livestock move is also recognised as a source of uncertainty. In the analysis of climate impacts on fodder management options in Nkayi, the uncertainties surrounding climate predictions across scenarios is acknowledged, and the model in turn is developed with parameters that are constrained within a ‘reasonable range of uncertainty’. Yet, by the end of the papers, important uncertainties are seemingly put aside in the desire to reach a definitive conclusion for the way forward. The apparent need for prediction, directions for ‘decision-making’ and control-oriented intervention are all-consuming.

Third, the style of argument too often leads to a closing down of discussion of more diverse options. All three papers are structured in the standard way of scientific papers, with propositions tested according to a set of methods, leading to results and conclusions. In the methods section, the qualifications, imperfections and uncertainties are duly noted. But, by the time the results are presented, around a particular quantitative model, such difficult issues are quietly put to the background. By the time of the conclusions, they have all but disappeared, and much stronger causal, predictive statements offer a definitive way forward, frequently hinted at by the original framing. For example, a model of land use intensity Wedza, focused on the extraction of net primary productivity, inevitably side-steps questions of how landscapes are understood, and how future resource use is seen by different groups of people. The social and political dynamics of change are not part of the storyline, despite the attempt to link resource use with different wealth groups.

Fourth, models are only models – simplified ways of thinking about the world – and they certainly can be helpful in thinking through options. But sometimes the assumptions just don’t make sense. Models to have any purchase need some ground-truthing, and some stress-testing with reality. The paper on grass fires shows clearly that there are no statistically significant differences across tenure types in fire frequency and extent. In other words, land reform farmers cannot be blamed, but without field based data, the paper is unable to explain the patterns, and instead uses a model that extrapolates future patterns from the past. In respect of fire, this is rather unlikely – fires due to land clearing will decline as farms and fields are established, while hunting will decline as game animal populations are eliminated. As a result, the regression-based models become detached from likely future realities. Instead, the regressions play a political role: by extrapolating increases in fires, they justify a set of externally-defined interventions.

Finally, the rush to a definitive recommendation for policy too often results in missing out on complex system dynamics, histories and contexts. The paper in this trio on livestock fodder systems, for example, assumes that the ‘feed gap’ will be filled by improved fodder quantity and quality, including the growing of fodder crops and the application of fertiliser to crops to improve stover. And this in dryland Nkayi? Surely not. The paper acknowledges that past attempts at improved fodder management have consistently failed, but does not probe why in the rush to provide an intervention-friendly recommendation aligned with a ‘climate-smart’ intervention narrative.

Styles of science: how to broaden out inquiry and open up debate

All three of these papers make important arguments and present significant data. They all have been peer-reviewed in respectable journals (Agricultural Systems, Ecological Economics and Geocarto International). The data is (mostly) of high quality, the models are consistent (if problematic) and the arguments are clearly made (although open to challenge). But reading these (and these are only exemplars of many, many others, perhaps rather unfairly singled out), the five wider concerns raised above kept coming back.

It makes me uneasy when a style of science closes down debate. Uncertainties are not embraced and alternative interpretations are not given space. An assumption that the end-point must be a science-based ‘smart’ intervention means other possibilities – more social, political for example – are not countenanced. This is less a critique of the particular methods and models, but more the style of policy-oriented science, centred on integrated assessment modelling, now central to a huge industry of ‘global change’ research.

What might an alternative approach look like? Modelling that takes uncertainty seriously would not close down to definitive solutions, but would aim to open debates up. Models that are interrogated with deep, field-based data, thus triangulating between modelling approaches, result in greater robustness and wider interpretation. When reading the papers, I had to ask: are there alternatives to new fodder regimes and crop fertilisation to address the consequences of climate change on livestock production in Nkayi? Of course there are! Does fire management have to be focused always on fire prevention; are fires always bad? Of course not! But such alternatives were not debated.

Suggesting diverse, alternative options for the future – different interpretations and solutions from an open approach to data, evidence and integrated assessment modelling – allows for an engaged, inevitably political debate, about what makes sense for whom. This would make for papers that are less neat, but perhaps ultimately more useful.

This is the fourth of a short series of blogs profiling recent papers on Zimbabwe.

This post was written by Ian Scoones and first appeared on Zimbabweland. Photo credit: Ian Scoones

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Food security in Zimbabwe: why a more sophisticated response is needed

food-aid-1

The food security situation in Zimbabwe – and indeed across large swathes of southern Africa – is serious. El Niño has struck hard and production levels this past season were well down. The UN estimates that in Zimbabwe alone 4.1 million people – 42% of the rural population – will be in need of support before the next season. Aid agencies are raising funds and are involved in a major humanitarian operation (see WFP and USAID, for example).

We are now entering the most difficult period. Between September and March, when early ‘green’ crops become available, the food situation will be tough, and many will be reliant on handouts and purchased imported food. Disposal of livelihood assets is already occurring and FEWSNET predicts that large parts of southern Zimbabwe will be in ‘emergency’ conditions, together with parts of Mozambique and Malawi.

There is little doubt that the harvests this year were really poor. And this was on the back of a bad season last year. This means that stocks are low and funds circulating in the local, rural economy limited. I do not want to question for a minute the severity of the situation, but I do want to challenge the way it is being portrayed, and ask whether this allows for the most effective targeting of those really in need.

Data challenges

For Zimbabwe the basic data comes from the annual ZimVac report, complemented by various crop surveys. ZimVac, as discussed on this blog before, is a major survey based on a sample of 14,434 rural households across 60 districts. Enumeration areas are chosen across districts and samples selected based  on population density estimates from the most recent population census. It assesses food production, cash income, livestock and so on, and comes up with a food access estimate, based on a daily 2100 k Calorie intake requirement during the consumption year to 31 March. Those unable to meet food needs through a range of sources are deemed to be in deficit and in need of support. This is where the 4.1 million figure comes from – the number of people estimated to be in this situation at the end of March 2017 (even if just for a day).

But as discussed before on this blog, these estimates may miss out on certain aspects. For example, In April, when visiting field sites in some areas hit badly by drought, I was surprised how much maize was being produced in home gardens and around settlements this year. While the main field crop had failed, more intensive production near the home. Sometimes involving supplementary irrigation, and certainly higher inputs of organic fertiliser, home garden areas were producing maize, including substantial quantities of green mealies. These crops rarely get noticed in the larger censuses as they focus on the main field crop, but added up these can be significant, although of course totals are way down on other years.

The other missing story relates to livestock. This year there were major concerns that the El Niño drought would decimate livestock. There were significant die-offs early on, but thankfully sporadic rains fell in February. This was too late for most crops, but it did replenish grass and water sources in many parts of the country, including those drought prone areas of Masvingo and Matabeleland that were suffering livestock mortalities. This turn-around will have had major impacts on food provisioning in these areas in the absence of harvests. There were entrepreneurs buying up animals in numbers and this was a ready source of cash for many. Many livestock were moved to resettlement areas where there is more plentiful grass due to (currently) lower population densities. The high livestock populations in resettlement areas, particularly in southern districts, adds to their food security resilience.

Livestock and their movement is often forgotten in food security assessments (ZimVac covers elements of this, but it’s complex, and difficult to capture in large surveys). Along with the importance of green mealies, other ‘famine’ crops, and the range of (often illegal) coping strategies that people employ mean that successful food provisioning is far more extensive than the UN agencies suggest.

While the data is broken down by district, it is not differentiated by the type land tenure and use. We do not get a sense of the differential vulnerabilities of, for example, communal area dwellers, those with A1 or A2 farms, villagised or self-contained, nor workers linked to such rural households. We know from extensive research that rural communities are highly differentiated, both within and between sites. At the moment we get a very blunt assessment, district by district. The report lists the ten best-off and worse-off districts, for example. Some of the districts where we work, where there was more land redistribution, both in the Highveld and further south, are in the better-off areas. Does this mean land reform areas are less food insecure? We cannot tell from ZimVac data as presented.

A more complex pattern: why land reform is not to blame

There are hints though that a more complex pattern sits below the aggregate numbers. The ZimVac summary report (p. 150) shows that nationally only 11% of households will be food secure this year based on their own cereal crop production. This is even lower in drought-prone areas, such as Masvingo, for example. On aggregate 58% of the national rural population will be food secure through the consumption season, but this is made up through access to income from a variety of sources, not just food production. How do these aggregate figures match up with data from the new resettlement areas?

We’ve been tracking food production in our study areas in Masvingo for some years. In our sites in Masvingo and Gutu districts for example across the harvest seasons from 2003 to 2013, between 44% and 69% of households produced enough for household consumption (estimated at 1 MT). In the Wondezo extension A1 site in Masvingo, farmers produced on average 2 MT in 2014 and over 6 MT in 2015, with 85% and 89% producing sufficient from maize alone for household consumption in those years. In our A1 resettlement sites in Mazowe, over 5 years between 2010 and 2014 seasons the average household maize production was 3.5 MT, declining over time as tobacco production increased. This means that on average 78% of households produced more than a tonne of maize in each year, and were food secure from own-farm production alone. This of course does not account for the significant cash income from tobacco in Mazowe (realising nearly $3000 per household on average across A1 farms between 2010 and 14), or vegetable production and livestock in Masvingo, along with other sources of income.

In other words, the ZimVac sample must be very different. 11 per cent this year (and higher but still low figures in other years) having sufficient food from own production is way lower than in our admittedly much smaller samples in the resettlements. In our areas, consistently over time and across sites, we do not see the level of food insecurity recorded by the ZimVac surveys – although of course it exists in pockets, among certain vulnerable people. There are of course communal areas nearby our A1 sites where the situation is quite different, and it is probably from here that the ZimVac data derives. Our comparisons with communal areas showed the contrasts, with resettlement areas outperforming communal areas across the board. But without any differentiated national food security data, it is difficult to make sense of the aggregates generated by standard crop assessments and livelihood surveys.

This food security crisis therefore is not the result of land reform as some would have it (as I keep telling journalists who ask; here’s an example from a Dutch daily that offered a more sophisticated take). Other countries in the region have suffered badly from the same drought, and Zimbabwe has before, long before the post 2000 land reform. In fact, land reform areas are an important part of why the actual underlying situation is better than it might be. My hunch – still not tested despite much encouragement – is that ZimVac’s sampling frame (appropriately for a national sample that is proportional to population density) is focused on communal areas. This means that the dynamics of the new resettlements in the food economy are being missed out on.

As reported many times on this blog, we see significant flows of food and other finance coming from the A1 resettlement areas, both to communal areas and to urban centres, through kin networks and labour migrancy. This is unrecorded and therefore not accounted for. My guess is that it is really significant in the overall food security story in the country, and taking account of land reform in the wider assessment would allow a redirection of effort by humanitarian and development agencies to support production for boosting local food security and economies, investing where the potential lies.

There is no reason for complacency though. Things could and should be much better, with proper investment. For example, the lack of irrigation infrastructure (and its state of repair, and its poor functioning due to intermittent electricity supplies) is a cause for major concern, and undermines resilience

The politics of food aid: why a more targeted approach is needed

Food aid is of course is highly political. It always has been, and accusations of partisan allocations have occurred again this year. Many are happy not to rely on the obligations and patronage that food aid implies – whether to the party-state or NGOs – and seek their own way. But there are some who are really destitute, without the networks that provide support. They are really needy and include a lot of people, but it’s certainly not 4.1 million. They include widows or older parents without living children, child-headed households, farm labourers, those with illness and disability, for example.

They all need help, as existing provisioning and coping strategies are insufficient. They are scattered all across the country – including in the high potential, richer areas within communities who are otherwise prospering, and are difficult to find. These are the people who need food, and would be a better focus for a more sophisticated, targeted approach to relief, which could combine with a more strategic developmental approach to increase production and market led economic development across communal, resettlement and urban areas.

This post was written by Ian Scoones and appeared on Zimbabweland

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The El Niño drought hits livestock hard in Zimbabwe

The El Niño drought is hitting hard this year. Livestock in particular are suffering, as grass and water are scarce. Some fear that it could be as bad as 1991-92 when around a million cattle died. To date some 7000 cattle mortalities have been recorded, the majority of which have been in Masvingo province, as well as Matabeleland. Government and aid agencies are encouraging farmers to destock, urging people to buy supplementary feed to save breeding stock. Drought task teams have been established in the affected provinces, and emergency feedlots are being established. It is a very serious situation. As perhaps the most valuable asset that most people have, losing herds can be devastating for livelihoods and recovery takes many years. Some small showers have recently improved grass conditions in some places, but the amount of fodder available is clearly grossly inadequate to see animals through the long dry season across the coming months.

Livestock in the 1991-92 drought

In this blog I again draw on work we carried out in 1991-92 in Chivi communal area, and is reported in the book, Hazards and Opportunities. During 1991-92 overall cattle survival among our sample was only 41%. This was the case for both large and small herd owners, with no significant relationships being shown between pre-drought herd sizes and survival rates. As now, it was a widespread drought, with all areas and all people affected. By the end of the drought 68% of households had no cattle at all, up from 55% before the drought. Drought recovery took years, and it was only by the late 1990s that herds had reached pre drought levels.

Herd composition is also affected by drought, and in turn affects the recovery dynamics. The table below shows the composition in the Chivi sample, pre and post 1991-92 drought. Cows were especially badly affected (particularly those with calves), although heifers survived better, and were the basis of post-drought recovery.

 

Cattle type Pre-drought (N = 583) % Post-drought (N = 247) %

 

Bull 8.1 6.5
Oxen 22.5 17.8
Cow 34.5 21.9
Steer 5.7 8.1
Heifer 20.8 37.7
Male Calf 2.7 2.4
Female Calf 5.8 5.7

 

 

The pattern of response among Chivi herds during 1991-92 is shown in the Table below. This differentiates between two phases of the drought: the early period before December 1992 and the later phase after this time and before the end of 1992.

RESPONSE Period 1 (N=64) % Period 2 (N=48) %
Illegal grazing 9.7 25.0
Movement out 29.0 35.4
Leasing 14.1 10.4
Commercial feed 16.1 14.6
Pods and hay 3.2 4.2
Cut & carry grass 12.5 4.3
Tree products 100.0 100.0
Crop residues 34.4 2.1

Movement out of the area was a vital strategy. However it took on a different form to earlier droughts. Data from the 1982-84 drought and the impact on cattle survival in Mazvihwa, Zvishavane district collected during my PhD studies (Scoones 1992), show how early movement was crucial to overall survival.

Strategy

 

Description of movement % survival N   (herds)
A Out of area (c. November 1982) 40.1 287
B Out of the area in the dry season (Aug-Oct 1993) 22.9 402
C No movement outside area 3.3 181

But by contrast to 1982-84, movement had less of an impact in 1991-92. Cattle were moved from Chivi to a variety of sites during late 1991. In the first part of the drought, 29% of herds were moved out of their home area to another site within the communal lands. By the second part of drought this had risen to over 35%. Illegal grazing outside the communal area (in resettlement areas or commercial farms) represented another type of movement. Nearly 10% of herds had been moved to such sites in the first period of drought and by the second period a quarter of all herds were using illegal grazing. However, the drought’s impact was so extensive and so dramatic that movement within a large radius was pointless. Animals that had been moved earlier got stranded, unable to benefit from the micro-management afforded to cattle resident at home kraals

During 1991-92, the largest cause of mortality was death due to starvation or extreme water shortage (47.7%). A significant number of animals were slaughtered just prior to death through poverty in order to salvage some meat for local consumption or sale (30.3%). Low nutritional status is linked with disease susceptibility and a number of animals died either directly from illness or were slaughtered because of disease (4.5%). Extensive searching for food required animals to wander far. This meant that a number were permanently lost; either they died while out foraging or they were stolen (5.7%). Foraging also had to take place in dangerous places (road edges, mountains, river banks) and a number of cattle died due to accidents (7.2%). Only very few animals (4.5%) were purposefully slaughtered.

The pattern observed during 1991-92 parallels that in previous droughts. Due to the fact that cattle are considerably more valuable live (for draft power, manure, milk etc.) than dead (sale value), there are very strong incentives to try and maintain live stock. Destocking is a risky option as the terms of sale during drought and repurchase following drought are not favourable to the herd owner. The costs of not having animals available to plough in the rainy season (assuming rains came) is so high that most farmers retain their stock as long as possible. No matter how much the government or the NGOs beseeched livestock owners to destock, they didn’t, and the rationale was clear.

The 1991-92 drought mortalities meant that much restocking during the 1990s was with mixed breeds, or animals purchased from commercial ranches. During the land reform, breeds got mixed even more, with the hardy indigenous Shona, Tuli and other breeds being diluted in the nation’s genetic stock. Indigenous breeds are well known to be able to survive off mixed diets of grass and browse and can survive without water for long periods. By contrast the larger, grass-dependent ‘improved’ breeds’ condition quickly deteriorates when grazing and water is scarce. In many respects, Zimbabwe’s cattle herds are less resilient than they were before.

What lessons can be drawn?

First, flexible movement is key, and restrictions imposed by veterinary controls can result in major increases in mortality. However illegal movement to underutilised commercial ranches is now not possible, nor is lease grazing on ranches. Most of these areas are now resettled as part of the land reform. Movement to the new resettlements from the communal areas has been a regular feature of the past 15 years, as have new relationships being struck with A2 farms. Relief grazing on state land is also vital, and so making access to state farms, military land and national partks will be important. These strategies will be crucial for herd survival in the coming months, and need to be encouraged and facilitated.

Second, access to water is almost as important as grazing, and in the past many animals perished from thirst rather than starvation (although usually a combination). A focused public works programme that invested in rehabilitating water sources, including pumping from dry rivers, establishment of mifuku, and so on, could be a highly productive investment.

Third, supplementary feeding is vital, especially for maintaining a core breeding herd. In the early 1990s there were not so many agrodealers, and certainly very few out in the rural areas. This has changed, and means that the purchase of blocks and other supplementary feeds has become much easier. People also have experience of using such sources of feed now, and will likely make much more use of them this year than in the past. Ensuring market supply, and offering subsidised options, may be a good investment.

Fourth, encouraging people to sell animals early as part of a destocking campaign has been a failure in the past, and is likely to be so again. While some richer A2 and A1 farmers, with other sources of income, and no reliance on draft animals for ploughing, may opt for destocking sales, most will only sell when animals are already virtually dead. Those with access to land, water and feed may take advantage of such poverty sales and buy up animals for rehabilitation and later fattening. Here the role of A2 farmers may become important, compared to the past.

The costs of losing herds is devastating as we saw in the early 1990s. The impacts are felt for years, undermining agricultural production and livelihoods. Ensuring that mortalities are reduced, and that animals survive is essential, but it seems the efforts being invested now are too little, too late; and sadly making the same mistakes of the past.

This post was written by Ian Scoones and first appeared on Zimbabweland

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The crop bias in resettlement: why pastoralists in Matabeleland are losing out

Discussion of livelihoods after land reform in Zimbabwe has been dominated by studies from Mashonaland, focusing particularly on crop production. Few studies have explored land reform in Matabeland, particularly in the pastoral livestock-keeping areas of Matabeland South. This is why the work of Clifford Mabhena is really important. His 2010 Fort Hare thesis, ‘Visible Hectares, Vanishing Livelihoods’ was based on extended fieldwork in Gwanda and Umzingwane districts. He argues that by focusing on settlement and crop production – the Mashonaland model – resettlement has availed more land, but not improved livelihoods, especially of pastoral livestock owners. A paper in the Journal of Contemporary African Studies came out last year which summarises the story.

Since the 1980s, resettlement has not seen huge success in the dry zones of Matabeleland (see Joss Alexander’s 1991 paper, The unsettled land). The sign-up for 1980s ‘Model A’ schemes was limited, and the attempt to design a livestock-oriented approach through the Model D scheme was largely a failure. Planners simply did not understand the nature of local livestock systems – the importance of seasonal transhumance (lagisa), loaning systems, and how livestock were managed across households, for example. The imposition of the ‘rectangular grid’ of standard settlement schemes – with the echoes of colonial planning – were widely resented and resisted, as Steve Robins described in the 1990s. Fences were cut and paddock grazing abandoned in favour of more flexible systems.

In the pastoral settings of southern Matabeleland there is perhaps an even greater, but rather different, pattern of livelihood differentiation, with (male) livestock keepers sometimes with huge herds, being the really ‘big men’ of local society, while others – younger men, women and poorer non-livestock owners – sought out other livelihoods, involving migration, mining and collection of wild products, as well as crop farming when the rains were good. In the past, the narrow ownership of livestock had benefits more broadly through kin and village connections, as well as offering employment through herding. But these benefits were mediated through complex social relations, involving sharing and loaning, that have declined and were never seen as being embedded in resettlement models. These were based instead on the notion of the individual plot holder and mixed farmer, settled permanently in villages, and without the need to move and access grazing in distant places.

As pastoral studies across the world have shown, in dry areas with variable rainfall, flexible movement is essential, as are ‘key resources’ that allow dry season grazing to sustain herds in times of dearth (see the book I edited in 1994 – Living with Uncertainty – for example) . Just as in the classic examples of transhumant and nomadic pastoralism of East and West Africa, in Matabeleland there had always been a locally adapted version based on the same principles of flexibility and mobility. Over time, as so many other places, this had been undermined, as land was removed and barriers to movement imposed. But nevertheless Matabeleland pastoralists made use of key resource grazing along the Shashe and Thuli rivers, and moved to gain relief grazing in ranches and wildlife areas. With the violence of the 1980s in the region, many large scale ranches were abandoned releasing grazing for those with large herds in the communal areas. As many pointed out, the problem in the communal areas was not too many people, but too many livestock, so the demand was for more grazing, that many were able to gain through various forms of leasing and poaching – all allowing some form of grazing flexibility to be maintained.

The post 2000 resettlements changed this. The ranches were carved up into A1 and A2 plots and handed out to beneficiaries. In the A2 plots, well connected people often benefited but the areas were too small for really effective livestock farming in such a harsh climate. In A1 areas, land was handed to often poorer people from the communal areas, with the intention that they become crop farmers. The farms however have often not flourished due to drought, and compared to the increasingly crowded communal areas, there are few livestock.

As Mabhena argues, there has been a mismatch between local needs and the design of resettlement models. The one-size-fits-all model from Mashonaland has not worked. He argues “the obsession of the Mugabe government with the redistribution of land as an end in itself rather than with the creation of viable rural livelihood options for rural people has led to a collapse of policymaking in the rural sector, especially in relation to the pastoral economy”. As Mr Nkomo, one of Mabhena’s informants from the communal areas explained:

“We used to lease graze or even grazed our livestock freely during the dissidentsera in some of these farms… but the state has settled people there. Where do they expect us to graze our livestock? Furthermore most of those resettled are strangers and own very few livestock”.

 The JCAS paper concludes:

 “Land redistribution is a programme capable of enhancing rural livelihoods if the state identifies the interests of beneficiaries before deciding on the peoplesinterests brings a danger of embarking on programmes and projects that do not address the needs of the local people and are not sustainable. People of southern Matabeleland are pastoralists and therefore could enhance their livelihoods if more land is made available for grazing than for village settlement distribution model. Misreading the landscape and misrepresenting peoplesinterests brings a danger of embarking on programmes and projects that do not address the needs of the local people and are not sustainable….There is a real desire at the local level to make agrarian livelihoods work better but the states one size fits allland reform programme focusing on agrarian reform through crop production has impacted negatively on livestock production and other livestock related livelihoods”.

 The crop bias in agricultural extension and land use planning in Zimbabwe has existed for decades. It has marginalised a vitally important element of the production system, and resulted in the imposition of measures that rarely work in the context of complex livestock production systems – whether attempts at ‘improved breeding’ or ‘paddocked grazing schemes’. This huge blindspot has major consequences in the drier parts of the country, and particularly Matabeleland where livelihoods are based on pastoral production. There clearly is a need for a major rethink of resettlement models for Matabeleland: a lesson that really should have been learned years ago through past failures resulting from inappropriate impositions.

This post was written by Ian Scoones and appeared first on Zimbabweland

 

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Zimbabwe is food secure this season, but more questions raised

The annual ZimVac assessment based on a national sample survey of over 10,000 households and carried out in May came out a month or two back. Unlike last year, when alarm bells were rung over a potential food security catastrophe, this year the prognosis was good. Excellent rains, including in some of the drier and usually more food insecure parts of the country, resulted in a bumper harvest.

Last year I critiqued the use of the headline figure from the assessment as potentially misleading. The same limitations of the survey apply, but the media reporting is more balanced this year (with some extreme exceptions – see comment string in an earlier blog). The survey is based on the 2012 Zimstat sampling frame and covers a large number of enumeration areas across the country, sampled proportional to population densities. Annoyingly the report still doesn’t separate out communal areas and resettlement areas, and my guess is that there remains some sampling bias. More on this below. Last year fortunately the dire predictions were not borne out. In part this was because the rains came, and a green crop filled the hunger period, but also I hypothesised in an earlier blog that the production from new resettlement areas was being undercounted. I suspect this remains the case.

Anyway, I thought blog readers would like a quick summary of the report, as without an impending disaster the media has largely ignored it. You can read the powerpoint report in full, which covers all sorts ranging from nutrition to sanitation. I will concentrate on agricultural production and food security, and draw text directly from the report.

The Ministry of Agriculture, Mechanisation and Irrigation Development estimates that the country will have a cereal harvest surplus of 253,174 MT in the 2014/15 consumption year from a total cereal harvest of 1,680,293MT.

Maize remained the major crop grown by most households (88%) compared to 80% for 2012/13, while groundnuts were the second most grown crop. Generally, the proportion of households growing crops increased except for cotton which showed a decline (due to the collapse in prices) and soya beans which remained unchanged.

Nationally, average household cereal (maize and small grains) production was 529.5kg. This was higher than last season (346kg). In Masvingo maize production averaged 339.7 kg and small grains 126 kg, given a total of 525.7 kg per household. Overall, average household cereal production was highest in Mashonaland West and lowest in Manicaland, and the contribution of small grains to total household cereal production was significant in Masvingo, Matabeleland North and Matabeleland South.

While improvements, these average figures are still low. And compared to the production levels from new resettlement households minute. Our studies in Masvingo, even in the poor rainfall years of between 2010 and 2012, show much higher averages (although with variations). Gareth James’ studies from Mashonaland shower higher outputs still. Again in the poorer rainfall years, he recorded average outputs of maize some 12 times these average national figures for all cereals for the good rainfall year of the past season. Of course the new resettlements have proportionately fewer people and so appropriately in a national representative sample this should be reflected. But, without data broken down and without indications of variation, the ZimVac study still fails to capture this story. As I have argued before (many times!), this is important for policy, and for thinking about national food security.

The ZimVac survey showed that for the 2013/2014 agricultural season approximately 45.2% of the households benefited from the Government Input Support Scheme, which was the main source of inputs. The proportion of households accessing maize inputs through purchase remained unchanged (39%) from 2013. About 2.3% of the households accessed their maize inputs from NGOs which was a decrease from 4.0% in the 2012/13 season.

Given the higher levels of production, the national average maize price was $0.37/kg down from $0.53/ kg during the same period last year. This pattern was also reflecting at the provincial level. Matabeleland South recorded the highest maize price ($0.65/kg). This was the same pattern during the same period last year.

Livestock (cattle, sheep and goats) were in a fair to good condition when the survey took place. Grazing and water for livestock were generally adequate in most parts of the country save for the communal areas, where it was, as is normal, generally inadequate. However, the report notes, there are marginal parts of Matabeleland North and South, Midlands, Manicaland and Masvingo provinces which had inadequate grazing which may not last into the next season.

According to the report, around 60% of the households reported not owning any cattle. Mashonaland East had the highest proportion of households not owning any cattle and Matabeleland South had the least. Nationally, only 14% of the households owned more than 5 cattle with Matabeleland South and Matabeleland Matabeleland North having a higher proportion of households owning more than 5 cattle.

Like the cereal production data, these national and provincial figures are very different to what we have found (and Gareth and others) in the new resettlements. Here cattle ownership is far higher, reflecting the richer, more capitalised form of farming found. Of course the ZimVac study may suffer from under-reporting, as in many large-scale surveys with huge samples, but the contrasts are interesting – and again potentially important.

In terms of food consumption, Masvingo had the highest proportion of households consuming an acceptable diet (75%) and Matabeleland North had the lowest (54%). This showed increased local availability of foodstuffs, and improved off-farm opportunities. However, nutritional indicators remained low, including a high prevalence of stunting. As commented on before, this mismatch between food intake and nutritional indicators remains puzzling.

So, following the food balance methodology the assessment adopts (see discussion of the methodology and its limitations in an earlier blog), the report estimates that for the 2014/15 consumption year at peak (January to March next year) is projected to have 6% of rural households food insecure. This is a 76% decrease compared to the (disputed) estimate the previous consumption year.

This proportion represents about 564,599 people at peak (which may of course be people suffering deficits for only a few days), not being able to meet their annual food requirements. Their total energy deficit is estimated at an equivalent of 20,890MT of maize; actually a very small amount, and not suggesting any urgent need for food aid, given the margins of error in the estimates. Matabeleland North (9.0%), Matabeleland South (8.3%) and Mashonaland West (7.7%) were projected to have the highest proportions of food insecure households. By contrast, Manicaland (2.7%) and unusually Masvingo (3.4%) provinces were projected to have the least proportions of food insecure households.

So in sum, a good harvest results in a good food security situation. This is of course good news, and no surprise. But the report and the analysis still raise many questions. I hope that those working on food and farming in Zimbabwe can join forces and think harder about questions of sampling, the contributions of the new land reform areas to production, and the complex dynamics at the heart of the food economy that underpins food insecurity prevalence and distribution. The ZimVac annual survey is a major contribution, but with some thought and adaptation it could be contributing much more to our understanding of changing livelihoods and food economies in the post-land reform era.

This post was written by Ian Scoones and originally appeared on Zimbabweland

 

 

 

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Are livestock destroying the planet?

Livestock are essential to rural economies and livelihoods across Africa. On Zimbabweland there have been many blogs on this theme focusing on Zimbabwe’s livestock and marketing systems. But are these animals contributing to planetary destruction through greenhouse gas emissions?

A special issue of the Proceedings of the National Academy of Sciences on livestock and global change late last year offered some new data, and generated a minor storm of controversy thanks in large part to the Economist weighing into the debate. The Economists’ summary of a paper by Mario Herrero from CSIRO in Australia and colleagues from IIASA and ILRI suggested that the solution to the high climate change impacts of traditional livestock rearing was to abandon free range pastoralism and shift to a form of intensive factory farming. The answer The Economist believes is “intensive livestock farming, which is more efficient and environmentally friendlier than small-scale, traditional pastoralism of the sort beloved by many greens”. Why is this position adopted? The Economist explains:

… More acres are given over to feeding animals than to any other single use. Meat accounts for a sixth of humanity’s calorific intake but uses roughly a third of its crop land, water and grain. Producing a kilogram of grain takes 1,500 litres of water; a kilo of beef takes 15,000 litres. A fifth of the world’s pasture has been spoilt by overgrazing….livestock farming produces 8-18% of greenhouse-gas emissions. It is the main contributor to the build-up of nitrogen and phosphorus in the world’s soils, producing too much ammonia (which is caustic), nitrous oxide (a greenhouse gas) and dead zones in oceans (the result of excess phosphorus). A fifth of the world’s pasture has been spoilt by overgrazing….

Extensive livestock production it seems is bad news. This was in part the argument of the FAO’s controversial book from 2006, Livestock’s Long Shadow. And it has been picked up by many since, including another FAO publication published recently that provided a rather more rounded perspective than its predecessor. So should Zimbabwe and other countries in Africa be abandoning livestock production to save the planet? Are intensive systems of ‘factory farming’ the answer?

The debate is actually hopelessly confused, and confusing. The data in the PNAS article is clear. Inefficient feed systems result in more greenhouse gases being produced during production than more intensive systems (essentially more belching and farting). And white meat (pigs and poultry) are better than red meat and milk in this regard.

But the assessment does not account for the costs of the other inputs of industrial farming, including fossil fuels used in feed production, housing, transport and so on. Traditional livestock systems are often very ‘low input’, with little fossil fuel dependency, and linked into markets not reliant on massively long supply chains.

Such systems make efficient use of marginal land and resources; as Tara Garnett puts it a ‘livestock on leftovers’ approach focused on adapting existing systems rather than the simple focus on efficiencies. The trouble with studies such as the PNAS one is that the results and conclusions depend crucially on what ‘the system’ is, and what is being compared with what. These choices are crucial and can inject fatal biases, or encourage wayward misinterpretations.

Simon Fairlie produced a brilliant book a few years back, Meat: a Benign Extravagance. It even got George Monbiot to change his views on meat eating. The book argues – with masses of data and careful argument – that meat production if done in an ecologically sensitive and humane manner is fine on a whole range of counts, and should not be discounted as a form of production and source of livelihood. It just depends on who produces it and how. The same applies in the great climate and environmental impact debate, a theme that is picked up in the book, and in a recent paper that questions many of the data assumptions used in FAO’s livestock climate assessments.

In the exchange of comments following the Economist article Mario Herrero distances himself from the claims made by the Economist, arguing that they never claimed that “we should get rid of pastoralism” (they didn’t!). Instead he argues that small-scale intensive systems are the best way forward, as part of a diversity of approaches.

This is all well and good, but how then can the extensive savannah grasslands of Africa be best used? This is not where intensive small-scale systems are likely to emerge. Should they be turned over for carbon sequestration as some argue, or wildlife, with people and their environmentally destructive animals forced off the range? What then happens to the many livelihoods of often very poor people who are dependent on livestock? And if livestock are not consuming the grass, fires or termites might result in less production and perhaps even larger emissions.

The problem with studies of this sort – and perhaps especially the media and policy commentary that follows – is the way that complex systems are simplified. First is the way the accounting is done, with often limited data and missing out key aspects. What is included in the model and how it is bounded makes a huge difference. In this case focusing only on food conversion efficiency gives a distorted picture of climate impacts of different livestock based production-marketing systems.

Second is the interpretation that focuses on the accounted for measure – in this case greenhouse gases – and excludes the complexity of the wider system. Any assessment of costs and benefits must look at the whole picture, including the array of opportunity costs and trade-offs, and so crucially must involve the people concerned who know these best.

Third is the way uncertainties are dealt with, often put to one side (or in very long appendices of supplementary data). In the case of aggregate global pictures across all livestock systems, uncertainties can be massive. Inadequate data plagues agricultural policymaking, and particularly for extensive livestock. Add to that the uncertainties associated with climate change predictions and the data problems are compounded.

And fourth is the way alternatives are defined as part of policy narratives that are developed through such modelling efforts. By defining (narrowly) a problem, a solution (again narrow) is defined. Too often dramatic alternatives to the status quo are recommended, without thinking about the consequences.

Pastoralism is a way of life adapted to dry non-equiibrium rangelands, and is a massive contributor to livelihoods and economies, as well as providing a route to land management. Our book, Pastoralism and Development in Africa, highlighted through many case studies the way pastoralism contributes to development in the Greater Horn of Africa. A similar case could be made for the livestock dependent areas of Zimbabwe, as I and many others have long argued.

Surely the most appropriate response is to seek out more climate-compatible forms of livestock development, based on existing systems, and working with people and their animals, rather than seeking a dramatic transformation that would result in increased poverty and growing inequality in already poor areas of the world. The models may help think through the options, but they are no replacement for engaging with the realities on the ground.

This post was written by Ian Scoones and originally appeared on Zimbabweland

 

 

 

 

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