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2.2: History of Conservation in Sub-Saharan Africa - Biology

2.2: History of Conservation in Sub-Saharan Africa - Biology


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2.2: History of Conservation in Sub-Saharan Africa

1. Introduction

The high-profile death of Cecil the lion has reinvigorated debates over the role of hunting and hunters in conservation. The combination of this event, a controversial auctioned black rhinoceros hunt in Namibia, and recent public and media outcry has generated renewed calls for increased regulation, supported and advocated by NGO campaigns (Di Minin et al 2016a). These calls have prompted policymakers from the USA and other Western countries to impose tighter restrictions or even complete bans on certain forms of recreational hunting (Goode 2015, Grijalva 2016), and have raised the profile of hunting in recent academic literature. Conservation scientists have expressed concerns that hunting constitutes a threat to African wildlife populations, notably megafauna, especially in tropical regions (Bennett et al 2002, Ripple et al 2016a, 2016b, Benítez-López et al 2017).

However, not all hunting is inimical to conservation. Appropriately managed at sustainable harvest levels, hunting may support efforts to conserve biodiversity, yielding potentially significant positive environmental and socio-economic benefits, both direct and indirect (Brown and Williams 2003, Leader-Williams 2009). Examples of such benefits include protein and revenues from animal products and hunting fees, which underpin the livelihoods of rural communities, provide essential income to landowners and conservation agencies, and support the maintenance of wildlife habitat in areas that would otherwise be converted to agricultural use. In extensive African wildland regions that are ill-suited to alternative uses such as ecotourism, hunting can and does provide critical economic support to sustain conservation management (Lindsey et al 2006).

Nonetheless, the Cecil incident has highlighted that hunting regulation is a complicated matter. Public calls to restrict recreational hunting are motivated in part by emotional responses and ethical concerns relating to the welfare of non-human animals, against which conventional economic and consequentialist arguments may be regarded as less persuasive (Nelson et al 2016, Macdonald et al 2016a). Recent discussions on the acceptability of trophy hunting as a conservation tool have become highly polarized (Muposhi et al 2016). Influential international environmental groups increasingly oppose all forms of hunting and actively challenge arguments that support it 1 .

Given these conflicting world views and changing socio-ecological contexts in Africa, what are the implications for future hunting regulation and associated conservation impacts? Related to this question, Macdonald et al (2016b) ask whether existing models of conservation financing that depend on lion trophy hunting revenues can be replaced effectively by a global conservation governance regime that does not. Others question whether hunting bans will protect wildlife and wildlands or simply devalue them and lead to their demise. This article proposes that the answers to such questions are illuminated by analysing the nature of evolving and interacting institutions, informed by contemporary institutional and governance theory.

Building on this notion, and embedded in a complex adaptive socio-ecological systems framework, this contribution explores the interplay between regulatory institutions of African conservation governance and the consequent incentives of hunters to comply with them. It posits that the effectiveness of regulations depends on the socio-ecological context in which they are established 2 . To explore this proposition and gain deeper insights into the effectiveness of various regulatory measures, I draw on two case studies, namely rhino hunting and lion hunting, in an Africa-wide context. My analysis introduces institutional perspectives by employing principles identified in the emerging field of evolutionary institutional economics (Potts 2007, Beinhocker 2007).


1 INTRODUCTION

In tropical Africa, the consumption of wild meat, or bushmeat, by rural communities who live alongside protected areas is a major issue for the conservation of protected and threatened species (Tranquilli et al., 2014 ). Consumer demand for bushmeat can drive species to extinction (Milner-Gulland & Bennett, 2003 Ripple et al., 2016 ), largely because species with higher body mass are generally the most heavily hunted, but also tend to have low reproductive rates (Tuomi, 1980 ) and are therefore particularly at risk of going extinct because of demand for their meat (Ripple et al., 2016 Wilkie et al., 2016 ). With a growing global human population, particularly rapidly in sub-Saharan Africa (United Nations, 2019 ), the demand for wild meat will continue to increase to the detriment of wild species if current consumption figures do not abate (Wilkie et al., 2016 ).

Evidence shows that hunting of wildlife can be sustainable (a) in areas where human population density is ≤1 person per km 2 , (b) when hunted wildlife species have high reproductive rates, and (c) when hunting is almost exclusively for consumption by the hunter's family and relatives rather than for the market (Robinson & Bennett, 2004 Wilkie et al., 2016 ). For example, hunting for household consumption in some parts of the Congo Basin where hunters target fast reproducing species like rodents is likely to be sustainable (Wilkie & Carpenter, 1999 ). However, hunting to supply large urban markets like in West Africa has been shown to severely deplete wildlife populations (e.g., Brashares et al., 2004 Covey & Scott, 2014 Cronin et al., 2015 ).

In addition to being a conservation issue, wildlife consumption, hunting, and trade have also been the cause of zoonotic disease outbreaks that not only affect the human health of local populations (Karesh & Noble, 2009 ), but can also impact people across vast regions, as experienced with Ebola (Marí Saéz et al., 2015 ), Covid-19 (Contini et al., 2020 ), and other severe acute respiratory syndrome outbreaks (Hu et al., 2017 ).

Makira Natural Park, located in northeastern Madagascar, is one of the largest terrestrial protected areas in the country, and is home to the fossa and 17 species of lemurs, 14 of which are threatened with extinction. Past studies have revealed that in some villages along the park border up to 52% of households consumed lemur meat, albeit infrequently (Golden, 2009 ). Because the human population density in Makira Natural Park's buffer zone is 37 individuals per km 2 and lemur species and fossa have low reproductive rates, hunting of these species is considered to be unsustainable (Golden, 2009 ).

This study was conducted to measure the prevalence of lemur and fossa meat consumption in rural communities living within and around Makira Natural Park using the UCT. We compare estimates obtained from the UCT with those from direct questioning methods. As part of an ongoing integrated conservation and development program, the estimated prevalence of lemur and fossa meat consumption will be used to design a behavior change campaign at the appropriate scale, and repeated measures over time will enable us to assess the program's expected impact on reducing the consumption of these species.


2 STATUS OF SPECIFIC FISH SPECIES IN LAKE VICTORIA

Based on the experience of Arksey and O'Malley ( 2005 ), a literature search was conducted for various databases including, but not limited to, the Directory of Open Access Journals, Google Scholar, Web of Science and many other databases. As presented below, the materials on the fish species of concern were reviewed, and those containing similar information and facts were clustered together. Based on analysis of articles with differing opinions and facts, logical conclusions were reached and recommendations for enhancing the status of specific Lake Victoria fish species were developed.

2.1 The cyprinids

Lake Victoria once supported an array of Cyprinid species, some of which are endangered or have disappeared completely, based on catches in the recent years. The severe reduction of Labeo victorianus (locally known as ‘Ningu’), the only Labeo in Lake Victoria and its catchment, was particularly prominent. A general decline in the catch of L. victorianus, a potamodromous fish species, was observed around 1979 (Table 2), coinciding with the replacement of weirs and barriers by beach seins and small mesh size nets set at the river mouths. This is hypothesized to have led to a further decline in the population of this fish in subsequent years (Kibaara, 1981 ). The contribution of L. victorianus to the fish catches in the 1960s was 595 tonnes in 1968 and 467 tonnes in 1969, respectively (Kibaara, 1981 ). The catch decreased in the late 1980s from 204 fish/ha to <1/ha in the 1990s and later years (Balirwa et al., 2003 ). Despite this magnitude of its decline, catches were reported for some rivers (Nyando Mara Yala personal observation), although the numbers were considerably reduced, as was the length of the fish at maturity. This situation could be a survival tactic in response to an overfishing pressure, a situation documented for Nile tilapia in Lake Victoria (Njiru, Okeyo-Owuor, Muchiri, & Cowx, 2004 ).

The decline in the number of Labeo in the Kenyan waters of Lake Victoria can be attributed to such fishing practices as the use of fish traps at the river mouths during their migration, resulting in catching mature fish before spawning. This hinders the chances for the gravid fish to contribute to the next generation, leading to a decreased number of fish (Rutaisire & Booth, 2004 ). Labeo victorianus is on IUCN Red List of Threatened species (Maithya, Charo, Wangila, Ouma, & Orinda, 2003 ), indicating an urgent need for more research on the biology, ecology and potential propagation of this fish in captivity and culture. Such activities will not only reduce pressures on the wild fisheries, but also help boost their population in the wild through the re-introduction of the hatchery-bred fingerlings into the lake and the rivers flowing into it. Attempts to breed Labeo in captivity in Kenya (Maithya et al., 2003 ) and Uganda (Rutaisire & Booth, 2004 ) have been tried with significant success, enhancing the possibility of saving this endangered species.

Barbus altinialis is another cyprinid whose numbers have decreased considerably in the catches around the lake. The species is also listed in the IUCN Red List of Threatened Species. Though still caught in some rivers (Migori Mara personal observation), they are rarely seen in other rivers and commercial landings (personal communication by fishermen). The contribution of this fish to the fish landings around the lake has declined from 8,173 tons in the 1980s to 152 tons in the late 1990s and early 2000 (Balirwa et al., 2003 ). There could have been a further decrease in the numbers, since the fish has seldom been observed in current catches. Recent studies in the basin reported the presence of this species in the mid- and lower reaches of Kenyan rivers flowing into the lake (Mwangi, Ombogo, Amadi, Baker, & Mugalu, 2012 ).

2.2 Haplochromine cichlids

The upsurge of the introduced Nile perch, compounded with reduced water quality attributable especially to eutrophication, has negatively impacted the number of haplochromine species in Lake Victoria (Darwall et al., 2005 ). Most Haplochromine species have decreased significantly in number except for a few species such as Haplochromis pyrrhocephalus, which have undergone some morphological changes to overcome pressures from Nile perch (Witte et al., 2008 ). Katunzi, Zoutendijk, Goldschmidt, Wanink, and Witte ( 2003 ) observed that H. pyrrhocephalus changed feeding behaviour from predominantly fish to include shrimps and molluscs as a tactic to reduce niche overlap with Nile perch. Although most haplochromine cichlids of Lake Victoria are known for exhibiting rapid evolution, with an estimation of over 500 endemic species having evolved over the last 100,000–400,000 years, eutrophication pushed most of them to near extinction (Awiti, 2011 ). It is estimated that out of over 500 haplochromine species within the lake before the introduction of Nile perch, nearly 200 are now extinct (Goudswaard, Witte, & Katunzi, 2008 ). Simo, Freire, and Simberloff ( 2009 ) observed that resource competition could be the most probable mechanism for the impacts of the introduced species, other than predation. Nile perch were observed to fed mainly on haplochromine cichlids, and it is reported this led to a rapid decline in the number of haplochromines in the lake (Kitchell, Schindler, Ogutu-Ohwayo, & Reinthal, 1997 ). In the 1970s, for example, the contribution of haplochromines to the Lake Victoria fish catches was 22,464 tonnes (28.8%) and 32,552 tonnes (40.6%) in 1975 and 1976, respectively (Witte & Oijen, 1990 ). This contribution decreased sharply to 128 tonnes in 1980s, and further to four tonnes in the 1990s and 3 tonnes in 2000 (Balirwa et al., 2003 Goudswaard & Witte, 1997 ).

Most haplochromines are trophic specialists with a strict choice of diet, maturing at a small size and low productive potential due to their small clutch sizes. They also have extended parental care, making them vulnerable to most environmental and ecological changes, especially predation (Goudswaard et al., 2008 ). Haplochromines are known to spend more time and energy protecting their young ones, which sometimes leads to their capture by predators. The rate and sequence of haplochromine decline within the lake were determined by their relative abundance and their adult size, as well as their habitat overlap with Nile perch (Witte et al., 1992 ). As Nile perch are both better competitors and a predator of the haplochromines, the habitat overlap is disadvantageous to haplochromines since it increases their interactions with each other (Outa, Mungai, & Keyombe, 2019 ). The rate of disappearance differed among the different feeding guilds. The relatively large piscivores, insectivores and molluscivores were the first to disappear from the catches. The small detritivores and zooplanktivores declined at lower rates (Seehausen et al., 1997 Witte et al., 2007 ). This could be largely attributable to the size, noting larger fish are easier to spot and pursue by the predatory Nile perch. The exotic Nile tilapia is also suspected of having negative impacts on haplochromine cichlid biodiversity through hybridization, overcrowding, competition for food and the introduction of parasites and diseases from their native environments (Awiti, 2011 ). Some satellite lakes (e.g., Lake Kanyaboli Yala Swamp) have been hypothesized to be refugia of haplochromine species.

2.3 The African catfishes

Catfishes in Lake Victoria have been declining, with the numbers of these indigenous fish having decreased drastically since the beginning of the 1980s (Dadzie & Ochieng-Okach, 1989 Goudswaard & Witte, 1997 ). The overall catfish stock in Lake Victoria is estimated to be 90 tonnes, with the standing stock of Bagrus docmak estimated to be 2,788, 22,131 and 14,766 tonnes in the 1970s in the Kenyan, Tanzanian and Ugandan portions of Lake Victoria, respectively. Yearly catches fluctuated between 500 and 17,000 tonnes, but decreased to <200 in 1988. About 1,000–1,800 tonnes were landed annually in the Kenyan waters of Lake Victoria until 1983, followed by a decline (Goudswaard & Witte, 1997 Kudhongania & Cordone, 1974 ), being attributed to the introduction of Nile perch and the ecological changes taken place within the lake over the years, including deoxygenation of the deeper waters and a decline in the haplochromine cichlids that constituted an important food source for this fish. As an example, the 1980s B. docmak was known to feed predominantly on haplochromines. However, the diet changed to Ratrineobola argentea and oligochaetes in the recent years, most likely because of the decline in the number of haplochromines in the lake. Before the establishment of the predatory Nile perch, the 1980s B. docmak, Clarias gariepinus and Schilbe intermedius were the top predators within the lake (Goudswaard & Witte, 1997 ).

The Xenoclarias eupogon biomass was estimated to be 447 tonnes in Lake Victoria in the early 1970s. The catch rates have declined over the years from 18, 0.6 and 0.3 (number of fish caught) per hectare in 1984, 1985 and 1986, respectively (Goudswaard & Witte, 1997 ), and the fish is currently thought to have gone extinct. Synodontis victoriea and Synodontis afrofischeri are still present in small numbers in shallow areas of the lake (Bwanika, Chapman, Kizito, & Balirwa, 2006 ), being considered mostly as bycatches in the fishery of R. argentea, the latter being a dominant cyprinid within the lake. Schilbe intermedius and C. gariepinus are the least affected of the catfishes in the lake, possibly attributable to a smaller habitat overlap with Nile perch than the other catfish species. Schilbe intermedius is partly pelagic, while C. gariepinus live in water bodies surrounding the lake and, therefore, can return to the lake through river inflows, thereby boosting their numbers within the lake (Goudswaard & Witte, 1997 ). Schilbe intermedius was estimated to comprise 646 tonnes in the 1969–1970 period (Table 1), with the number continuing to decline over the years. The catches of these fish are occasionally included in the catch data, as they were considered to be of low commercial value, making their estimation rather difficult. The other threat facing most African catfish species, especially S. intermedius and S. victoriea, is the gill net fishing in the river mouths, especially during the rainy seasons. This practice leads to the elimination of the gravid male and female fish migrating upstream to spawn. Goudswaard & Witte, ( 1997 ) argue, however, that there is no indication overfishing has led to the decline in catfishes in Lake Victoria, especially in the deeper waters.

2.4 The African lungfish (Protopterus aethiopicus)

The African lungfish (Protopterus aethiopicus ‘Kamongo’ in Luo) is a special kind of fish, especially among the communities living around the lake. With its snake-like appearance and strong taste, coupled with the lower bone-to-flesh ratio, it occupies a particular category for fishermen and consumers. The decrease in the number of African lungfishes could be a result of the conversion of most wetlands, which served as their refugia to agricultural fields. Harvesting of nest-guarding male lungfish also could have contributed to the decreased recruitment of the young ones, leading to a decline in their numbers in Lake Victoria (Goudswaard, Witte, & Katunzi, 2002 ). Other possible reasons for their decline could be the impacts of the Nile perch, declining food abundance and habitat degradation. Goudswaard, Witte, and Katunzi ( 2002 ) reported a decline in the catch of lungfish from 67.5 to 5.5 kg/ha between 1973 and 1986, while the catches decreased from 0.3 to 0.07 tonnes (Table 1) between 1986 and 1990. Little research has been conducted on the culture and propagation of lungfish in captivity, indicating a need to protect and manage their dwindling populations within Lake Victoria.

1973 1984 1985 1986 1987 1988 1989 1990 2000
Bagrus docmak 23 37 12 2 1 0 0
Synodontis afrofisheri 10 33 6 6 5 1 1
L. victorianus 67 163 80 0 0 0 0
Schilbe intermedius 46 89 72 54 26 12 62
Lungfish 67.5 5.5 0.07
Oreochromis variablis 26 15 2 2 0 0 0
Oreochromis esculentus
Haplochromines From 1955 to 128 3 4
Labeo victorianus From 204 to 20 0 0

2.5 The tilapiines

Some indigenous tilapiines to Lake Victoria and its affluent rivers (e.g., Oreochromis variabilis) have also come under serious threat (Maithya et al., 2003 ). This species, together with the native Oreochromis esculentus, was a lucrative fishery within the lake in the early 1960s, but has significantly declined over the decades because of various changes within the lake, such as predation from the introduced Nile perch, as well other environmental and ecological changes over the years (Goudswaard, Witte, & Katunzi, 2002 ). The number of tilapiines decreased in the 1970s and increased in the late 1990s and around 2000 (Table 1 and 2). This could be attributable to the introduced Nile tilapia, which also resulted in a decreased O. variabilis and O. esculentus populations, and an increase in the landings of the tilapiines in general. The contribution of O. variabilis decreased from 26 fish/ha in the early 1970s to less <1 fish/ha in the late 1980s and subsequent years. Although data on these two species are sparse, fish landings around the lake exhibited a decline in their numbers.

Taxa 1966–1967 1976–1977 1986–1987 2000
Tilapiines 17,747 2,480 5,772 30,530
Bagrus 6,646 4,645 8,173 152
Protopterus 2,627 2,035 309 469
Barbus 813 330 85 0
Synodontis spp 122 305 28 127
Haplochromines 1,955 1,280 3 4
Labeo 204 20 0 0

According to Sitoki, Kurmayer, and Rott ( 2012 ), eutrophication has resulted in increased blue-green algae biomass that has replaced the diatoms, which are the preferred diet of O. variabilis (Maithya, Njiru, Okeyo-Owuor, & Gichuki, 2012 ). Nile tilapia (Oreochromis niloticus) was introduced into the lake in the 1950s to enhance the declining tilapiine fishery, and as with the Nile perch, the ecological effects of this introduction were taken into consideration (Njiru et al., 2004 ). Being a superior competitor, O. niloticus has gradually replaced O. variabilis and O. esculentus (Aloo, 2003 Awiti, 2011 Njiru, Waithaka, Muchiri, Knaap, & Cowx, 2005 ). The introduction of O. niloticus and Tilapia zillii has resulted in the replacement of the endemic species (O. esculentus and O. variabilis) with possible hybridization as speculated by Lowe-Mc Connell ( 2009 ). It was observed that the contribution of these two fish species begins declining gradually to a point of disappearance in the catches within the lake since establishment of the two introduced species (Lowe-Mc Connell, 2009 ). Other reasons cited for the decline in the numbers of O. esculentus in the lake (apart from competition from Nile tilapia) are replacement of Aulacoseira by the less nutritious blue-green algae (Sitoki et al., 2012 ). The replacement is attributed to eutrophication, since blue-green algae can tolerate high nutrient conditions, in contrast to the former, which is sensitive to nutrient enrichment.


3 RESULTS

3.1 Part A: Normative belief structures in Kenya and Zimbabwe

To understand regional variation in normative beliefs, we compared belief structures in Kenya and Zimbabwe. Our survey recorded participants' responses to normative statements such as “my community feels I should bring my livestock into a boma every night.” Factor analysis of the Kenyan data revealed that normative questions mapped onto four factors (see Table 2). Factor analysis was then performed on the Zimbabwean data, with the analysis was constrained to produce four factors. A Tucker coefficient test showed a similarity of 0.95 between the two factor structures. This is highly similar, and these livestock management normative belief structures can be considered virtually identical. The same analytical approach was carried out using control beliefs, and yielded a Tucker coefficient of 0.79, so control belief structures between the two sites have no measurable similarity. We conclude that normative belief structures are unusually conserved, and therefore approaches using norms to promote effective livestock management may be highly transferrable.

Factor Description Example
Factor 1 Herding and perceptions of community management People expect I will herd my livestock every day.
Factor 2 Perceptions of livestock management locally, regionally, and nationally Community elders think it is very important for me to manage my livestock well.
Factor 3 Boma use norms My community feels my livestock should be brought into a Boma every night.
Factor 4 Perceived behavior of loved ones The people I care about herd their livestock every day.
  • Note: Factor mapping of normative livestock management behavior questions, using all Kenyan data. Each factor represents a distinct attitude dimension, onto which a set of specific questions map.

3.2 Part B: Normative belief clusters in Kenya and Zimbabwe

Individual normative beliefs are not homogenous within a community we used cluster analysis to understand whether our respondents could be classified into groups of like-minded individuals. Compiling all normative beliefs from Zimbabwe and Kenya, our cluster analysis revealed six relatively distinct clusters, each with different normative beliefs (see Figure 1). To understand the factors that most differed across the clusters, we ran a univariate analysis. All terms, including demographic, social, and normative terms (n = 21) emerged as significant (p < .05) however, predator killing (both subjective and descriptive terms), country, sex, leadership, and access to food were all highly significant (p < .001). Due to the statistical favorability of a smaller number of factors, the "country” term should be viewed proxy for all the social and cultural differences between Kenya and Zimbabwe which are otherwise unaccounted for. In individual clusters, terms had varying importance in their ability to characterize the group. We compared cluster characteristics and performed t-tests to understand how these salient characteristics differed by cluster.

3.2.1 Cluster 1: Kenyan traditionalist leaders

Slightly older, mostly Kenyan men (92.1% male, vs 76.0% in the overall data, t test: p < .001 98.4% Kenyan 12.1% of respondents 69–81, vs 7.4% in the general data), often in positions of leadership (46.3% vs 31.4% in overall data, t-test: p < .001). These individuals strongly agreed with all predator-killing norms (e.g., 96.3% agreed or strongly agreed that “my community feels I should kill any predators that kill livestock” vs. 51.3% overall, t-test: p < .001). All predator-killing norms were statistically stronger in this cluster than the general population. This cluster may represent individuals who practice traditional Maasai pastoralism and predator control, who may often be in positions of local esteem.

3.2.2 Cluster 2: Educated modernists

This cluster had an approximately even number of Zimbabweans and Kenyans (Zimbabweans = 55.9%). This group was relatively educated, and only 20.6% of members had never attended school (compared to 38.1% in the general population t-test: p < .001) there was also a greater instance of higher education, with 28.7% of respondents having attended secondary school (vs 21.0% overall t-test: p < .001), and 6.6% having attended university (2.5% overall t-test: p = .03). However, despite this, they hold relatively few leadership roles (19.9%, vs 31.4% overall t-test: p < .001). They were cautious in their judgement of livestock production standards, and agreed less than average with statements such as “Kenyans/Zimbabweans carry out good livestock management” (p < .001). They were also less accepting of predator control norms than average for example, only 11% of respondents agreed or strongly agreed that “people expect that I will kill any predators that kill my livestock,” compared to 45.7% at large. All predator control norms were less supported by this group than the overall population (all t-test: p < .001). We believe this cluster represents individuals with somewhat educated, modern values, who place relatively little value on traditional livestock management, and may understand the benefits wildlife—including predators—can bring to communities.

3.2.3 Cluster 3: Disadvantaged defenders

This cluster was Kenya- and male-skewed (95.4% men, compared to 75.6% overall t-test: p < .001), with lower education levels (71.1% never attended school, compared to 35.6% at large t-test: p < .001). This group had very strong beliefs that local, regional, and national livestock management are of high standard: 93.4, 89.5, and 90.1% thought that all members of each respective group “manage their livestock well”, compared to the general population results of 43.5, 33.1, and 36.3%, respectively (all t-test: p < .001). In a perhaps related component of their psychology, this cluster also exhibited strong support for predator killing, strongly agreeing with the injunctive (should: 87.5%), descriptive (do: 80.9%), and subjective (key people/groups: 71.1%) norms regarding “kill[ing] predators that kill livestock,” compared to 31.4, 26.8, and 25.8% of the sample overall. Although similar to Cluster 1, this group did not benefit from the advantages of the first group, for example, leadership roles. With their strong normative traditional practices, we characterize this group as typical male community members in traditional roles, who are defensive of their way of life, and may be unable access to other opportunities.

3.2.4 Cluster 4: Alternative livelihoods

This group had a near-even split between Zimbabweans (56.2%) and Kenyans. Despite few members being in positions of leadership (17.1% vs 31.4% overall t-test: p < .001), members of this cluster experienced significantly fewer incidences of food shortage than participants overall (20 vs 51.7% t-test: p < .001), but lower livestock ownership rates (12.4% had no livestock at all, vs 3.8% overall t-test: p < .001) this may indicate that they produce their own crops, or have secure alternative sources of employment. They were broadly against predator control, and in answer to the same questions regarding injunctive, subjective, descriptive, and norms about predator killing, only 26.7, 6.7, and 1.0% of people respectively strongly agreed with normative statements, compared to 31.4, 25.8, and 26.8% in across all the data (all differences t-test: p < 0.001). These individuals are similar to those in Cluster 2, but overall have lower educational levels, higher food security, and lower levels of livestock ownership.

3.2.5 Cluster 5: disadvantaged and disgruntled

This group had a higher than expected proportion of women (37.5 vs 24% overall t-test: p < .001), were slightly younger than average (mean age group of 3.6, rather than 3.8 t-test: p = .12), and experienced elevated food shortages (69.1 vs 51.7% overall p < .001). Their normative beliefs regarding livestock management practices and standards were less strict than the overall results. For example, strong agreement with the injunctive statements such as “my community feels my livestock should be brought into a boma every night” (22.0%), or descriptive norms such as “people expect I will herd my livestock every day” (11.3%) were much lower than on the overall sample (which supported these examples at 71.8 and 63.0%, respectively). All herding and boma use statements (n = 6) had statistically significantly less support from this group (t-tests, all p < .001). We suggest that this cluster has relatively weak ties to, but are necessarily still reliant on, traditional livestock management. They have similarities with Cluster 3 in terms of social disadvantage, but showed relatively less defense of their existing lifestyles, so may be more open to alternative employment or management approaches.

3.2.6 Cluster 6: Educated, skeptical women

With the highest proportion of women of all clusters (42.6 vs 24.0%) and a similarly elevated proportion of Zimbabweans (64.8 vs 24.6% overall), this group was highly distinct. They were overall more educated (school was bracketed mean of 2.3 vs 1.9 overall t-test: p < .001) than the respondents at large. Similarly to Cluster 5, they showed low confidence in local livestock management practices, and all norms were less strict (e.g., low agreement with statements such as “my community feels my livestock should be herded every day”) than in the overall population (all t-test: p < .001). They also had low confidence in management standards, with significantly lower estimates of the proportion of individuals who carried out good livestock management locally, regionally, and nationally than the overall survey population (t-test: p < .001). They also showed less acceptance or support for predator killing norms than expected, with only 13.9, 13.0, and 6.5% agreement with injunctive, descriptive, and subjective predator-killing norms, versus 51.3, 45.7, and 42.3%, respectively, for the entire sample (t-tests, all p < .001). This group condemned local livestock management the most strongly of all clusters with high education levels and more female participants, we suggest this group may be modern in outlook, and may either wish to have greater support in their livestock management, or find livelihood alternatives.


4 DISCUSSION

4.1 Discussion of results and implications for environmental assessments

In this paper, we present the first high-resolution (5 arcminute) global dataset of present-day CA distribution. The dataset expands on the work of Kassam et al. ( 2015 ) and Derpsch et al. ( 2010 ). Our downscaled, present-day maps show that only a limited amount of the global cropland area (up to

15%) is currently managed under CA. The baseline estimate is broadly consistent with the Kassam et al. ( 2015 ) data at the national scale, with the exception of Europe, where we included additional data from the SAPM survey (EUROSTAT, 2010 ). However, there is a considerable lack of knowledge about the extent of “good quality CA” (i.e., the implementation of all three CA principles). For example, Kassam et al. ( 2015 ) question if large soybean mono-cropping areas in South America should be regarded as good quality CA, as long as the only management practice implemented is no/minimum tillage. Similarly, Derpsch et al. ( 2010 ) mention several million hectares of “direct seeding” in Russia and the countries of the former Soviet Union, where the seeding equipment still causes large soil disturbance and thus reduces the benefits of real CA systems. Kassam et al. ( 2015 ) include in their data all arable land on which no-tillage or reduced-tillage management (disturbing less than 25% of the cropped area and leaving behind at least 30% of crop residues) is applied, while crop rotations are not a prerequisite to be counted toward CA. Moreover, Carmona et al. ( 2015 ) found that farmers and even national monitoring programs often refer to CA, although only direct seeding (without considering cover crops and residue management) is implemented. Thus, our baseline estimate might be a rather optimistic estimate of present-day CA adoption. To depict some of these uncertainties, we also provide a low and high estimate of present-day CA adoption, which can be interpreted as a distinction of different states of CA implementation. The lower end of the range depicts areas with a more integrated system of permanent no-tillage, crop residue management and crop rotations, while the high estimate includes a wider range of areas primarily devoted to temporary no-tillage, reduced tillage, or conservation tillage operations. Conservation tillage, however, can still include substantial disturbance to the soil and does not necessarily include crop residue management and crop rotations, which may result in different impacts on environmental processes such as soil carbon storage or changes in evapotranspiration patterns.

In general, based on the present-day adoption rates, there is a large potential for converting further agricultural land to more sustainable practices in both of our scenarios. Derpsch et al. ( 2010 ) and Kassam et al. ( 2015 ) report some history of CA adoption in countries where the adoption rates are high at present day (Table S4). They show, once initiated, the adoption process can speed up within a few years, for example, in Brazil or Argentina, where the CA areas increased tenfold within a decade. However, Giller et al. ( 2009 ) emphasize that high adoption rates in South America do not imply similar developments elsewhere and argue that, in sub-Saharan Africa, CA adoption outside of extension programs is basically zero. Such regional differences appear also in our CA potential maps. Low adoption indices mainly appear in Africa and Southeast Asia, resulting in limited potentials to large-scale CA adoption in the future (Table 5). In contrast, the highest potentials are located in Europe, North America and Oceania, where economic barriers to CA adoption are lower (Soane et al., 2012 ), consistent with claims from CA organizations working in the field (ECAF, 2017 ).

This regional diversity in present-day and future CA adoption patterns may have implications for environmental assessments regarding agricultural management. For example, to calculate global carbon sequestration potentials in agricultural soils, empirically derived GHG mitigation rates are applied to the global cropland area (Smith et al., 2008 UNEP, 2013 ). Despite limitations in process understanding (Baker et al., 2007 Govaerts et al., 2009 Powlson et al., 2014 ) such calculations may overestimate the mitigation potential due to two reasons. First, as our potential CA maps show, even under optimistic assumptions (bottom-up scenario), there might be barriers to the adoption of CA that prevent 100% conversion of the global cropland area. Second, large areas, for example, in South America are already managed under CA, sometimes for decades (Derpsch et al., 2010 ). Due to the saturation effect in soil carbon accumulation rates (Paustian et al., 2016 ), these areas may not contribute to additional mitigation, lowering the global mitigation potential. Moreover, Smith et al. ( 2008 ) report highest mitigation potentials in warm-moist climates. Large areas of both limited CA potential (e.g., Southeast Asia, Central Africa) and already high adoption rates (e.g., South America) are located in such climatic environments (Figure 4). Similarly, the few studies looking at biophysical effects of no-till farming may overestimate effects on climatic indicators by the assumption that all agricultural land can be managed under sustainable techniques such as CA (Davin et al., 2014 Hirsch et al., 2017 Wilhelm et al., 2015 ).

It is not surprising that tillage and crop residue management (both incorporated within our CA representation) has recently been identified as one of the key land management variables for global change research with severe knowledge gaps in process understanding and data availability (Erb et al., 2017 ). At the same time, CA, no-till farming, and additional climate-smart management techniques receive increasing attention in the climate change mitigation and adaptation literature. Our maps, implemented in climate, vegetation, and integrated assessment models can contribute to explore interactions and feedbacks between sustainable cropland management and the climate system. Together with advances in the plot-scale understanding of soil carbon storage upon CA adoption, improved and more realistic quantification of climate mitigation potentials may be derived. Additionally, the maps provide a useful input to land surface models and coupled Earth System models to assess the impacts of changes in the agricultural management strategy on biophysical surface characteristics (e.g., albedo and evapotranspiration) and associated climate variables.

4.2 Discussion of methods and outlook

Some uncertainties remain related to definitions of management practices, input data, and assumptions in the mapping process. First, CA has been defined only recently as a set of management practices that have been practiced already before (FAO, 2008 ). Estimates of the amount of agricultural area that is devoted to CA thus depend on what the authors actually include into the framing of the term (see discussion in the previous section). We represent this source of uncertainty by providing a range of estimates (low, baseline, high). Moreover, CA areas not reported due to the lack of sufficient reporting mechanisms in countries not covered in the baseline map may add further, although relatively small, uncertainty. Second, our mapping approach relies on the assumption that a combination of biophysical and socioeconomic indicators determine the adoption of CA at the grid scale. While this is a common assumption in economic theory, the knowledge about these relationships is still incomplete (Knowler & Bradshaw, 2007 ) and requires further research, especially focusing on spatial variation due to differences in socioeconomic and biophysical conditions as well as the farming systems. Furthermore, this approach may miss additional socioeconomic, institutional, and cultural factors that determine CA adoption at the regional to local scales due to data limitations and insufficient process understanding (Supporting Information Appendix S2). The aforementioned uncertainty is further amplified by the dependency on spatial proxy data for many factors, instead of implementing the driving factors directly in the mapping. Indeed, direct measures representing socioeconomic conditions, for example, extension work, availability of technology, or policies facilitating access to the required knowledge to implement CA, would increase the accuracy of the CA distribution map. However, unlike indicators of the biophysical state of the land surface, socioeconomic data are often constrained to national-level resolution, omitting the spatial variation in socioeconomic conditions within national boundaries (Otto et al., 2015 ) and a paradigm shift in the social sciences toward harmonized subnational or gridded databases is still in its infancy (Azzarri, Bacou, Cox, Guo, & Koo, 2016 ).

In this global mapping approach, we were therefore not able to include the full detail of local to regional varying drivers promoting and preventing CA adoption (Supporting Information Appendix S2). Nevertheless, our mapping approach provides a useful synthesis of the available data and knowledge of the potential adoption of CA helpful to target further assessments, in particular in the context of climate and land-model experiments.


Discussion

The effect of Lantana on ecosystems

While native to the Americas, Lantana was brought to Europe in the 16th century and since that date it has been subjected to horticultural improvement through selection of traits and hybridisation, leading to the creation of 630 named cultivars and variants. This genetically diverse artificial species complex was the source of introductions to India, Australia and South Africa [6]. This plasticity has enabled it to adapt to a wide variety of habitats – from sea level to 1800 m or more [43], [44]. Lantana grows in tropical, subtropical and temperate climates, with mean annual rainfall of <1000–>4000 mm [45]. Lantana can also aggressively compete for surface-soil nutrients and water [46], is allelopathic and hinders seedling recruitment and growth of other plants in its vicinity [47]–[50], it produces abundant seed that is dispersed large distances by birds and water, and is able to form dense stands under favourable conditions, enabling it to quickly dominate native vegetation [8], [51], [52]. These properties have made Lantana one of the most successful weeds, which can dramatically transform ecosystems. Studies suggest that Lantana invasion affects local biodiversity and all four categories of ecosystem services – provisioning, regulating, supporting and cultural [53]. For example, Lantana is known to pose serious threat to biodiversity in several World Heritage sites and Endangered Ecological Communities in Australia (e.g. rainforest of northern Queensland, Fraser Island and the Greater Blue Mountains), the Fynbos of South Africa, and biodiversity hotspots in India (e.g. the Western Ghats and Eastern Himalayas) [12], [54], [55]. Furthermore, Lantana is toxic to livestock and harbours the tsetse fly, the vector of African sleeping sickness, and malarial mosquito [12]. It is also known to affect economic viability of 14 major crops around the world including coffee, tea, rice, cotton, oil palm, coconut and sugarcane, in part due to its allelopathic properties, which reduce productivity of crop plants [22].

Invasion trajectory and management effort

Our results suggest that Lantana has continued an upward trajectory of spread and invasion in Australia, India and South Africa. One striking feature of this invasion trajectory is its spread despite intensive management. For example, in the early 1980s Lantana had invaded about 2.2 million hectares of forest plantations, watercourses and savannah in South Africa and mechanical and chemical control had little effect on this invasive species [43]. Similarly, in India all efforts using biological control in the mid-1980s had failed and Lantana was still spreading [38]. In an assessment of invasive species in Queensland, Australia in 2003 Lantana was ranked the most invasive weed [56]. It is also evident that considerable resources were spent on Lantana control and management in all three countries while the invasion trajectory continued to rise upwards. In 1973, for example, the cost of Lantana control in Queensland, Australia was estimated at c.A $1 M (US $1 M) per year [57]. In South Africa, the cost of chemical poisoning to control Lantana was estimated at R 1.7 M (US $ 250,000) per year in 1999 [58]. Estimates from India suggest that the present cost of Lantana control is approximately INR 9000 (US $ 200) per hectare [59]. In addition, substantial opportunity costs of Lantana invasion are reported in the literature for example, Lantana's global infestation of millions of hectares of grazing land [22], [60]. A study of the grazing sector in Queensland, Australia suggested that in 2007 this sector incurred opportunity costs of A $ 121 M (US $ 121 M) due to Lantana invasion [61] in comparison with A $ 3 M (US $ 3 M) per year loss recorded for the same sector in 1985 [60]. Similar concerns have also been reported from India [22].

Rate of change and drivers of spread

Our invasion trajectories of Lantana across three continents suggest that there were episodes of rapid change. In Australia, Lantana was first introduced to the old Botanical Gardens in Adelaide, South Australia, and due to its popularity as garden plant multiple introductions followed, mainly in New South Wales and Queensland [62], [63]. In India, Lantana is known to have been introduced in 1807 in Kolkata botanical gardens [64] while in the Nilgiris, where we focused our investigation, Lantana was mentioned for the first time by Hough in 1829 [24]. In South Africa, the first introduction did not take place until 1858, when it was introduced to Cape Town [25], [65]. The invasion trajectory of Lantana in Australia and India shows a rapid rate of change around mid-1920s. This was shortly after the end of World War I, when a period of post-war economic depression occurred [66]. Both Australia and India experienced rapid land use change, mining and exploitation of other natural resources at this time [67]. This might have triggered the spread of Lantana on both continents. Paradoxically, reports of Lantana control in India from the 1910s and 1920s suggest that this is also the time when the greatest effort to control Lantana was made and a variety of control measures were used (Fig. 3). South Africa did not experience such a rapid rate of change at that time possibly because Africa was still relatively isolated from extractive resource industries and large-scale intensive agriculture, e.g. [68]. South Africa, however, experienced three episodes of rapid rate of change following World War II (between 1950 and 1970). Australia also experienced a similar increase in the 1960s. Both these increases might be related to post-war land use change in these countries [69], [70]. Such a rise is not apparent in India, possibly because the land tenure and land use in the Nilgiris, where our data comes from, has not witnessed any major changes since the 1950s [71], [72]. Reports on Lantana control suggest that it was in the 1970s in Australia and South Africa that the greatest effort to control Lantana was invested (Fig. 3). While the South African trajectory continued to rise at a steady rate of change between 1970s and 2000s (possibly evidence that some of the control measures were working), Australia and India experienced another surge in 2000s (Fig. 2B). This might be a consequence of recent land use pressure on expanding agricultural sectors in both countries and consequent land use change [73], [74]. These episodes of increase in the rate of change indicate the change in land use as possible driver of Lantana spread [75], [76]. Lantana is a shade intolerant plant [8] and therefore any increase in the intensity of land management, e.g. increase in farmland area or opening up of forests, would have facilitated its spread. Similarly, any lapse in land management would have led to an increase in marginal lands where Lantana could have invaded as it is known to colonise rapidly after fire or to invade cleared grazing areas and forest plantations [7], [77]–[79].

Role of Lantana in providing ecosystem function and livelihoods

The rapid spread of Lantana is evident from its invasion trajectory, but does this mean that its spread has always had detrimental effects on the ecosystems and the local communities who depend on them? Lantana has several negative impacts on ecosystems, but its positive role has also been documented. For example, while Lantana is known to compete with forestry species and reduce their productivity [52], it can also increase the regeneration of some non-timber forest products [12]. In addition while the presence of Lantana, a bee-pollinated plant [80], reduces pollinator load of native plants [81], it makes a useful honey plant [82]. Lantana's toxic effects on livestock and its allelopathic effects on other plants are also well documented [47]–[50], however, its alkaloids are also known to have anti-bacterial, anti-microbial, anti-inflammatory, anti-tumour, and anti-AIDS properties that have the potential for use in medicine [83]. In comparison with grass-covered surfaces, Lantana cover can increase water run-off and, therefore, surface soil erosion, but it has also proven useful to prevent soil erosion on barren mountain slopes and in deforested areas [84], [85]. Interestingly, in India, many forest managers now accept Lantana as a naturalised plant that plays an important role in the functioning of ecosystems by, for example, providing cover to carnivores, food for birds as well as some wild herbivores in addition to the livelihood benefits that Lantana provides to the local communities [86]. As such, they only aim to manage or control Lantana rather than attempting to eradicate it. Thus the change in management strategy from eradication to control and acceptance of Lantana reflects not only a realisation of the futility of eliminating Lantana altogether, but also increasing cognisance of its ecosystem effects, both positive and negative.

From eradication to adaptive management

The focus of Lantana management thus far has been on its control and eradication. As indicated by the increase in the number of reports on Lantana control in the 1970s, substantial effort was made to control and eradicate Lantana in Australia and South Africa around this time [39], [40]. While the emphasis in Australia was on biocontrol [41], in South Africa mechanical removal was a preferred option [42]. Although these reports indicate substantial weed management efforts, they seem to have had little effect on the spread of Lantana [38], [43] and it still remains a major concern in Australia, India and South Africa [22]. The rapid invasion of Lantana has even instigated legislation for its control in Australia and South Africa [26], [87]. This legislation restricts its import and outlines rules for its eradication. In Australia, for example, Lantana is a declared Noxious Weed under the New South Wales Noxious Weeds Act 1993. All Lantana species are declared Class 3 plants under the Land Protection (Pest and Stock Route Management) Act 2002. Lantana species cannot be sold or distributed and landholders may be required to control these plants if they pose a threat to an environmentally significant area in Australia [88]. Similarly in South Africa, Lantana is a proclaimed noxious weed under the Weeds Act (No 42, 1937), and the owner or occupier of the property is obliged to eradicate Lantana when such a notice has been served [30]. The Conservation of Agricultural Resources Act (1983) in South Africa has subsequently declared Lantana as Category 1 invasive species, which must be eradicated or effectively controlled on farm units (The Conservation of Agricultural Resources Act – Act No 43, 1983). In comparison to Australia and South Africa no such legislation exists in India, but evidence suggests that instead local communities have adapted to the presence of Lantana. For example, a whole new cottage industry has sprung up in areas where Lantana is now abundant. This includes its use in basketry making rubbish bins, flower pots and fruit plates thatching roofs weaving hedges and making toys and furniture [22], [89]. On a more industrial scale, Lantana pulp is used for making paper in India [90]. Adaptive management is an iterative, ongoing process of learning and responding to environmental conditions while acknowledging their dynamics, uncertainty, and changes over time [91]. The adaptations to Lantana in India represent both autonomous and planned attempts by human groups to innovate and diversify their livelihoods in response to the increasing abundance of Lantana. Further investigations are currently underway in the Western Ghats to see what other adaptation pathways, including practical measures of control, are being pursued by various groups in response to Lantana.

It is apparent that Lantana is an invasive plant that has adapted very well to the ecosystems it has invaded, often transforming their natural state. Furthermore, its bioclimatic niche and therefore potential for its expansion might include much more land area in Australia, India and South Africa than it has currently invaded (Fig. 4). While legislation and management have aimed at controlling the density and spread of Lantana, there is limited evidence for success of such control measures. The focus of legislation and management so far has been on Lantana's ‘ecosystem dis-services’, but there is also evidence that it provides certain ecosystem services and livelihoods. Furthermore, much of the recent scientific evidence suggests that invasive species are here to stay [1], [15], [16], [92]. For example, a long-term data set of naturalized plant species on islands [92] demonstrates that the mean ratio of naturalized to native plant species across islands has changed steadily for nearly two centuries, indicating that these new species assemblages have created novel ecosystems. In the future, conservationists and managers will need to grapple with the novel ecosystems that invasive species (such as Lantana) give rise to. In some areas, however, there will always be the need to control Lantana as it is a competitive weed, but these control measures need to be well defined and realistic. Given that the success of the eradication and management of Lantana has been limited thus far, better tools are needed to manage Lantana, possibly including more effective biological control agents. However, where such control measures are not practical, one way forward might be to embrace this pan-global invasive species and to find ways for its adaptive management.

Conclusion

Calls have been made recently for conservationists to focus on the functional role of species in ecosystems rather than their origins: “Nearly two centuries on from the introduction of the concept of nativeness, it is time for conservationists to focus much more on the functions of species, and much less on where they originated” [1], p.154. We show that in Australia, India and South Africa, despite measures to control Lantana, its spread and invasion have continued. We do this by developing a quantitative scale for comparison of invasion trajectories across three continents. These invasion trajectories display rapid rates of change in the 1920s, between the two World Wars, possibly due to large-scale land use changes. Even though efforts to control Lantana peak in India in the 1910s and in Australia and South Africa in the 1970s, this has little effect on its invasion. For most invasive species, quantitative data on historical drivers of spread are lacking and therefore development of such quantitative scale can provide a better handle on drivers of their spread. Our long-term view of Lantana invasion across three continents suggests that the future management of invasive species will require an adaptive management approach to their invasion. Policymakers will need to find innovative and diverse approaches to such adaptive management whilst being prepared to embrace the novel ecosystems that invasive species create and to respond to future changes in social-ecological conditions that may evolve as a result of their presence. Such an adaptive management response will be most effective to improve the resilience of both ecosystems and societies to the presence of invasive species. In the future, therefore, managers will be much better off finding new ways to adapt to invasive species rather than fighting a losing battle to eradicate them.


Anthropology - MA, PhD

Biological Anthropology (by Research) - MSc

Ethnobiology (by Research) - MSc, PhD

Forensic Osteology and Field Recovery Methods - MSc

Social Anthropology (suspended) - MA

Social Anthropology - Humanitarian and Environmental Crises - MA


Author information

Verena J. Schuenemann and Alexander Peltzer: These authors contributed equally to this work.

Affiliations

Institute for Archaeological Sciences, University of Tübingen, Tübingen, 72070, Germany

Verena J. Schuenemann, Beatrix Welte, Anja Furtwängler, Christian Urban, Ella Reiter, Michael Francken, Katerina Harvati & Johannes Krause

Senckenberg Centre for Human Evolution and Palaeoenvironment, University of Tübingen, Tübingen, 72070, Germany

Verena J. Schuenemann, Katerina Harvati & Johannes Krause

Integrative Transcriptomics, Center for Bioinformatics, University of Tübingen, Tübingen, 72076, Germany

Alexander Peltzer & Kay Nieselt

Department for Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, 07745, Germany

Alexander Peltzer, Chuan-Chao Wang, Wolfgang Haak, Stephan Schiffels & Johannes Krause

Division of Archaeology, University of Cambridge, Cambridge, CB2 3DZ, UK

Museum and Institute of Zoology, Polish Academy of Sciences, Warsaw, 00-679, Poland

Berlin Society of Anthropology, Ethnology and Prehistory, Berlin, 10997, Germany

DFG Centre for Advanced Studies ‘Words, Bones, Genes, Tools: Tracking Linguistic, Cultural and Biological Trajectories of the Human Past’, University of Tübingen, 72070 Tübingen, Germany

School of Biological Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia


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