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"Gene diversity is still in the hands of the small farmers around the world." 

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"Gene diversity is still in the hands of the small farmers around the world." 

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Commercial farms mainly run off of GM seeds and even though so many countries have contributed to the world seed bank it is up to the small farmers who do not use GM seeds to save seed diversity.  The world seed bank has made a large effort to collect one of the world's most valuable natural resources there is still a lot more that has to be done. With many scientists trying to diversify seeds by adding in genes from the wild crop it is the duty of the small farmer to not only protect the wild crop but also the other forms that aren't as commercially popular but are still diverse (McCouch, 2013).

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We must mine the biodiversity in seed banks to help to overcome food shortages, urge Susan McCouch and colleagues.

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We must mine the biodiversity in seed banks to help to overcome food shortages, urge Susan McCouch and colleagues. Rent or Buy article Get time limited or full article access on ReadCube. All prices are NET prices. Subscribe to Journal Get full journal access for 1 year $199.00 only $3.90 per issue All prices are NET prices.

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"The modernization of agriculture has meant the loss of diversity." 

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"The modernization of agriculture has meant the loss of diversity." 

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Many seed companies have manufactured seeds that are resistant to disease and can produce their own insecticides and various other things. While this may have some benefits for commercial farming like increased yields and being able to use less fertilizer, it causes problems for seed diversity. All the seeds from big companies are genetically identical, killing seed diversity through mass use and cross contamination. The American Institute for Biological Sciences has reported that crop diversification is a rational and cost effective way to combat the negative effects climate change is creating (Lin, 2011).

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Abstract

Recognition that climate change could have negative consequences for agricultural production has generated a desire to build resilience into agricultural systems. One rational and cost-effective method may be the implementation of increased agricultural crop diversification. Crop diversification can improve resilience in a variety of ways: by engendering a greater ability to suppress pest outbreaks and dampen pathogen transmission, which may worsen under future climate scenarios, as well as by buffering crop production from the effects of greater climate variability and extreme events. Such benefits point toward the obvious value of adopting crop diversification to improve resilience, yet adoption has been slow. Economic incentives encouraging production of a select few crops, the push for biotechnology strategies, and the belief that monocultures are more productive than diversified systems have been hindrances in promoting this strategy. However, crop diversification can be implemented in a variety of forms and at a variety of scales, allowing farmers to choose a strategy that both increases resilience and provides economic benefits.

The observation that managed ecosystems often fail to respond smoothly to external changes and pressures has led to greater research on ecological regime shifts, thresholds, and resilience ( Folke et al. 2004). Although the idea of building resilience has been studied in a broad range of ecosystems, from coral reefs to forests ( Nyström et al. 2000, Chapin 2004), this idea has not been well studied in an especially important system to human society: the agroecosystem. The development of resilient agricultural systems is an essential topic of study because many communities greatly depend on the provisioning ecosystem services of such systems (food, fodder, fuel) for their livelihoods ( Altieri 1999). Many agriculture-based economies have few other livelihood strategies ( Tilman et al. 2002), and small family farms have little capital to invest in expensive adaptation strategies, which increases the vulnerability of rural, agricultural communities to a changing environment. The challenge for the research community is to develop resilient agricultural systems using rational, affordable strategies such that ecosystem functions and services can be maintained and livelihoods can be protected.

Environmental changes may affect many different aspects of agricultural production. With greater climate variability, shifting temperature and precipitation patterns, and other global change components, we expect to see a range of crop and ecosystem responses that will affect integral agricultural processes. Such effects include changes in nutrient cycling and soil moisture, as well as shifts in pest occurrences and plant diseases, all of which will greatly influence food production and food security ( Fuhrer 2003, Jones and Thornton 2003). These changes are expected to increase abiotic and biotic stress, forcing agricultural systems to function under greater levels of perturbation in the future.

Vandermeer and colleagues (1998) elucidated the main issues linking the role of diversity in agroecosystems to functional capacity and resilience. First, biodiversity enhances ecosystem function because different species or genotypes perform slightly different roles and therefore occupy different niches. Second, biodiversity is neutral or negative in that there are many more species than there are functions; thus, redundancy is built into the system. Third, biodiversity enhances ecosystem function because those components that appear redundant at one point in time may become important when some environmental change occurs. The key here is that when environmental change occurs, the redundancies of the system allow for continued ecosystem functioning and provisioning of services. These three hypotheses are not mutually exclusive and change over time and space; therefore, all linkages between diversity and function may be useful for the long-term maintenance of sustainable agricultural systems.

Because of the impacts that climate change may have on agricultural production, the need to consider diversified agricultural systems is ever more pressing. The following sections review the current knowledge about agricultural diversity and its ability to protect agriculture from the consequences of climate change, as well as the barriers that remain for its adoption as a climate change adaptation strategy. In the first section, I discuss the advantages of diversified agroecosystems under a future climate by looking at pest, disease, and plant physiological effects. The second section discusses the barriers to the adoption of diversified agriculture as an adaptation strategy, and the third section examines methods to help farmers optimize diversification strategies to improve resilience and protect agricultural production.

Advantages of diversified agroecosystems

Current knowledge suggests that climate change will affect both biotic (pest, pathogens) and abiotic (solar radiation, water, temperature) factors in crop systems, threatening crop sustainability and production. More diverse agroecosystems with a broader range of traits and functions will be better able to perform under changing environmental conditions ( Matson et al. 1997, Altieri 1999), which is important given the expected changes to biotic and abiotic conditions. The following are a few of the major ways that the greater functional capacity of diverse agroecosystems has been found to protect crop productivity against environmental change.

Pest suppression. Pest suppression is a perennial challenge to farmers, and it is a very important ecosystem service. In agricultural systems, as in natural ecosystems, herbivorous insects can have significant impacts on plant productivity. The challenges of pest suppression may intensify in the future as changes in climate affect pest ranges and potentially bring new pests into agricultural systems. It is expected that insect pests will generally become more abundant as temperatures rise as a result of range extensions and phenological changes. This abundance will be accompanied by higher rates of population development, growth, migration, and overwintering ( Cannon 1998, Bale et al. 2002). Changes in the distribution and abundance of species and communities are unlikely to occur at the same rates. Migrant pests are expected to respond more quickly to climate change than plants, and they may be able to colonize newly available crops and habitats ( Cannon 1998, Bale et al. 2002). However, there are a variety of barriers to range expansions, including such biotic factors as competition, predation, and parasitism from other species ( Patterson et al. 1999). Promoting such barriers to range expansion and pest viability will have an immediate negative impact on pest outbreaks and will help protect agricultural production.

Farmers may be able to assist in creating biotic barriers against new pests by increasing the plant diversity of their farms in ways that promote natural enemy abundance. The composition of the plant community, as determined by a farmer, may be described as the planned diversity of the system. Crop diversity is critical not only in terms of production but also because it is an important determinant of the total biodiversity in the system ( Matson et al. 1997). With greater plant species richness and diversity in spatial and temporal distribution of crops, diversified agroecosystems mimic more natural systems and are therefore able to maintain a greater diversity of animal species, many of which are natural enemies of crop pests ( Altieri 1999). Many examples of pest suppression have been shown within agricultural systems possessing diversity and complexity, especially in comparison with less-complex systems ( Cannon 1998). For example, in willow systems, insect pest outbreaks of the leaf beetle Phratora vulgatissima have been shown to be greater in willow monocultures than in natural willow habitats ( Dalin et al. 2009). However, in a review of specialist and generalist natural enemy responses to agricultural diversification, it was found that diversification may reduce natural enemy searching efficiency. Moreover, pest control by specialist enemies may be less effective in a more diverse agroecosystem because a lower concentration of host plants may reduce attraction or retention of these specialist enemies ( Sheehan 1986).

Habitat management is one method used within agricultural systems to alter habitats to improve the availability of the resources natural enemies require for optimal performance ( Landis et al. 2000). Such management techniques have been developed for use at within-crop, within-farm, or landscape scales, and some have been proven to be very economical for farmers. In one review examining pest management in agriculture ( Gurr et al. 2003), the authors found that many degrees of complexity exist in increasing biodiversity for pest management. Simply diversifying the plant age structure of a monoculture or strip-cutting fields such that natural enemies have a temporal refuge can improve in-field habitats for natural enemies. Larger-scale changes, such as integrating annual and perennial noncrop vegetation; increasing crop diversity within the field; or increasing farmwide diversification with silvoculture, agroforestry, and livestock may also provide a variety of other functions to the system ( table 1; Gurr et al. 2003).

In an example from a meta-analysis of the density response of natural enemies (invertebrate predators and parasitoids) to experimental changes in structural complexity, Langellotto and Denno (2004) found that increasing structural complexity led to a significant rise in natural enemy abundance at habitat and within-plant scales. Hunting and web-building spiders showed the strongest response to structural complexity, followed by hemipterans, mites, and parasitoids. Evidence of greater spider abundance in response to diversification has also been shown by Sunderland and Samu (2002), who found that abundance increased with structural complexity in 63% of the studies they examined. The central conclusion of this review was that spiders tend to concentrate in diversified patches, and greater diversification throughout the whole crop would offer the best prospect of improving pest control ( Sunderland and Samu 2000).

One example of a perennial system that exhibits a rich range of natural enemy pest control is the coffee agroforestry system, where there is a wide variety of spatial and temporal diversity determined by the shade trees planted within the cropping system. Greater natural enemy presence has been observed in the more diverse and shaded agroforestry systems, and increased bird diversity and density have been shown to reduce herbivore plant damage through greater insectivorous bird predation ( Perfecto et al. 2004). It has also been observed that predatory ground-dwelling ants are attracted to and prey upon the coffee berry borer, a major pest of coffee production, with greater efficiency in diversified coffee systems when compared with unshaded monocultures ( Armbrecht and Gallego 2007).

The integration of diversified systems into agriculture can have financial benefits for the farmer, as well. One financially beneficial type of habitat management that has been widely adopted at the within-field scale is the beetle bank, where native grasslands and refugia are maintained at the field margins to protect carabid beetle populations. In one analysis of the costs and benefits associated with pest suppression, the cost of establishing a beetle bank in a 20-hectare (ha) wheat field, combined with yield loss resulting from land removed from production, was calculated at $130 for the first year with subsequent costs and yield losses of $45 per year. However, the ability to keep aphid populations below a spray threshold through natural enemy suppression saved about $450 per year in labor and pesticide costs, and the prevention of aphid-induced yield loss saved about $1000 per year for the 20-ha field. These figures show that the loss in productive land for the establishment of the beetle banks was more than offset by the money saved from reduced pesticide use and aphid-induced yield loss (Thomas et al. 1991).

Although climate change may produce a shift in pest and natural enemy ranges, an agricultural system with greater plant biodiversity improves the system's resilience by harboring greater natural enemy biodiversity, thereby protecting crops from a large variety of potential future pests. Although natural enemies in a diverse system may be functionally redundant at the present, they may no longer prove redundant as future changes occur. The diversity of plant species within the agroecosystem therefore provides long-term pest suppression for agricultural systems by building up a bank of potential natural enemies for any future pest outbreaks in the system.

Disease suppression. Losses caused by pathogens can contribute significantly to declines in crop production, and changes in climate potentially could affect plant disease distribution and viability in new agricultural regions. From 2001 to 2003, 10% of the global crop losses in wheat, rice, and maize were shown to be a result of pathogens ( Oerke 2006).

The diversity of crop species in an agroecosystem has a much less predictable effect on microbial pathogens compared with crop pests, as microclimatic conditions play an important role in the development and severity of a disease ( Matson et al. 1997, Fuhrer 2003). The effect of climate change on disease prevalence is therefore much less certain. Climate change could have positive, negative, or no impact on individual plant diseases ( Chakraborty et al. 2000), but it is suspected that milder winters may favor many crop diseases, such as powdery mildew, brown leaf rust, and strip rust, whereas warmer summers may provide optimal conditions for other diseases, such as cercosporea lead spot disease ( Patterson et al. 1999). Global change is also predicted to alter the distribution and abundance of arthropod vectors that distribute viruses, thereby affecting the rates of and chances for crop transmission ( Anderson et al. 2004).

A central tenet of epidemiology is that both the number of diseases and the incidence of disease should increase proportionally to host abundance ( Tilman et al. 2002). In one grassland study, in which grassland plant species richness and composition were manipulated, the pathogen load was almost three times greater in the monoculture plots, where host abundance was at a maximum, than in the polyculture plots planted with 24 grassland species (an approximation of natural diversity; Mitchell et al. 2002). Eleven diseases were more severe at lower plant species richness, with most of the diseases correlating with host abundance, showing that the greater abundance of host species within lower-species-diversity plots increased disease transmission.

The loss of genetic diversity in crop production has led to a hypothesized increase in crop disease susceptibility as a result of higher rates of disease transmission. Many mechanisms reduce the spread of disease in agricultural systems with greater varietal and species richness. Barrier and frequency effects occur when other disease-resistant varieties or species block the ability of a disease or virus to transmit and infect a susceptible host ( Finckh et al. 2000). These effects increase with greater spatial and temporal diversity in the agricultural system, and intentional crop system diversity with greater barrier effects can significantly reduce pathogen impacts on crop production. Multiline cultivars and varietal mixtures have been used to effectively retard the spread and evolution of fungal pathogens in small grains and to control some plant viruses ( Matson et al. 1997).

One well-known example of barrier effects in rice production showed that genetic variation within species and within populations can increase the ability of an agricultural system to respond to pathogen diseases. Zhu and colleagues (2000) demonstrated that in-field genetic crop heterogeneity suppresses disease in rice crops suffering from rice blast. Disease-susceptible rice varieties, when planted in mixtures with resistant varieties over large tracts of land, had 89% greater yield and 94% reduced fungal blast occurrence than when planted in monoculture. Because of this experiment's success, fungicidal sprays were no longer applied to these fields after the trial. Rather, farmers grew rice in mixtures in order to improve the resilience of the systems while reducing economic costs. There have been few such large-scale experiments to study the efficacy of genetic heterogeneity to increase production, reduce chemical use, and potentially stabilize or even reduce food prices for a region, but these results do provide evidence that intraspecific crop diversification has the potential to effectively control fungal disease spread and protect against crop loss.

Increasing diversification of cereal cropping systems by alternating crops, such as oilseed, pulse, and forage crops, is another option for managing plant disease risk (Krupinsky et al. 2002). Disease cycles could be interrupted through crop rotation by interchanging cereal crops with broadleaf crops that are not susceptible to the same diseases. Reduced tillage could enhance soil biodiversity, leading to greater disease suppression, and stand densities could be adjusted to allow for better microclimatic adjustments to disease growth.

These examples show that farmers can take advantage of greater crop diversification to reduce disease susceptibility in agricultural systems, thereby limiting the amount of production loss as a result of crop diseases. Although changes in disease spread and severity are uncertain under climate change, greater genetic variation across space and time could potentially reduce adverse disease transmission impacts that may accompany climate change.

Climate variability buffering and mitigation. Diversified agroecosystems have become more important for agriculture as climate fluctuations have increased. Research has shown that crop yields are quite sensitive to changes in temperature and precipitation, especially during flower and fruit development stages. Temperature maximums and minimums, as well as seasonal shifts, can have large effects on crop growth and production. Greater variability of precipitation, including flooding, drought, and more extreme rainfall events, has affected food security in many parts of the world ( Parry et al. 2005).

Such observed agricultural vulnerabilities to changes in temperature and precipitation point to the need to develop resilient systems that can buffer crops against climate variability and extreme climate events, especially during highly important development periods such as anthesis. There are a variety of ways that diversified agricultural systems exemplify that more structurally complex systems are able to mitigate the effects of climate change on crop production.

Agroforestry systems are examples of agricultural systems with high structural complexity. Although the primary crop of interest (e.g., coffee, cacao) is sometimes grown in more intensively managed systems with little shade cover, the more structurally complex systems have been shown to buffer crops from large fluctuations in temperature ( Lin 2007), thereby keeping crops in closer-to-optimal conditions. The more shaded systems have also been shown to protect crops from lower precipitation and reduced soil water availability ( Lin et al. 2008) because the overstory tree cover reduces soil evaporation and improves soil water infiltration.

Agroforestry systems also protect crops from extreme storm events (e.g., hurricanes, tropical storms) in which high rainfall intensity and hurricane winds can cause landslides, flooding, and premature fruit drop from crop plants. In one example from Mexico, greater farming intensity of coffee agroforestry systems was correlated with the percentage of farm area lost to landslides and the amount of coffee production lost to premature fruit drop ( Philpott et al. 2008). In another example of diverse agriculture systems and hurricanes, a study of Nicaraguan farms following Hurricane Mitch in 1998 showed that less intensively managed land, which exhibited greater diversity and structural complexity, suffered less erosion, had more vegetation, and experienced lower economic losses from hurricane damage ( Holt-Giménez 2002). Resistance patterns became more apparent in areas with high storm intensity, and complex interactions and thresholds exist, but are difficult to detect.

In a comparative study of farming systems in Sweden and Tanzania, two locations where agriculture has suffered from climate variation and extreme events, it was found that agricultural diversity increased the resilience of the production systems. Sweden suffered from cold-tolerance issues, whereas Tanzania suffered from problems of heat tolerance and irregular El Niño cycles. Both locations experienced greater seasonal drought. In these cases, research showed that successful management practices able to buffer systems from climate variation and protect production were those that were generally more ecologically complex, incorporating wild varieties into the agricultural system and increasing the temporal and spatial diversity of crops (Tengö and Belfrage 2004).

These examples present a potential long-term strategy for farmers experiencing patterns of reduced rainfall and growing temperature variability. Diversification of agricultural systems can significantly reduce the vulnerability of production systems to greater climate variability and extreme events, thus protecting rural farmers and agricultural production.

Barriers and challenges to the increased adoption of diversified agriculture

Although many recognize that diversity can improve the resilience of agricultural systems to environmental change, the adoption of increased diversification has been slow for a number of reasons. First, economic policy incentives for the production of monoculture row crops under intensive management have outweighed the perceived incentives to implement diversified farming systems, although this may change as climatic variations increase. Second, many of the efforts to adapt agriculture to climate change have focused on the development of biotech solutions to produce drought-resistant crops, pushing agriculture toward more expensive and intensive forms of management. Lastly, the mistaken belief that biomass production is substantially greater in monocropped systems than in multispecies systems has discouraged the move toward more diversified systems. Such barriers slow the rate of adoption of diversified agricultural systems as adaptation options and must be addressed in order to hasten the implementation of this strategy.

Farm price and income supports: A US example. In the United States, the economic incentives to intensify production in monoculture systems outweigh the incentives to diversify agriculture systems. Agricultural subsidies select mainly for five crops-corn, wheat, soybean, cotton, and rice-thereby incentivizing greater production of these few crops. Between 1995 and 2002, 89% of the $91.2 billion disbursed in commodity payments went to these crops in order to boost the income of crop and livestock farmers. Soybean and corn farmers alone received 56% of that money ( Boody et al. 2009). The commodity payment system encourages monocropping of select crops because payments are determined by acreage of crop produced, thereby incentivizing the maximum production of one or a few crops over large tracts of landscape. Such incentives favor greater production of fewer species planted in space and time, at the expense of ecosystem services and ecosystem function ( Altieri 1999, Tilman et al. 2002).

Incentives for the greater production of fewer crops have also been supported by the mechanization of many agricultural production practices (e.g., planting, harvesting). Mechanization is now the status quo in the United States and is necessary for this type of production system. The mechanization of crop species for maximum production, in general, is most efficient when only one crop is planted because management systems (e.g., planters, harvesters, chemical inputs, irrigation systems) can be designed for one crop type and one crop structure, thereby decreasing labor time and costs (Pimentel et al. 2008). In this sense, an agricultural system that selects mainly for one or two main crops and is highly mechanized can be very efficient and productive, and certainly this ability to scale up production and increase yield has had many advantages for food production and the maintenance of stable food prices in the past.

However, farm price and income supports were originally developed because farm households were financially disadvantaged compared with other US households, not to increase the production of specific crops. Current data show that farm household incomes have risen above those of the average nonfarm household ( Mishra and Sandretto 2002), and that much of the subsidy program does not support small farmers; rather, the majority of the money goes to large farms that own wide swaths of land ( Riedl 2007), thereby negating the original intent of the price- and income-support mechanisms. This brings into question the true economic benefit of subsidies for many small farmers, who will be most vulnerable to climate change-induced production losses in the future. Incentives that can increase economic productivity of farms by permitting the selling of ecosystem services, such as carbon sequestration, have the potential to increase the adoption of diversified farm systems such as terraces and agroforestry ( Antle et al. 2007). Developing policy that incentivizes the diversification of agricultural crops and landscapes may be a more rational strategy for developing resilient agricultural systems and protecting food production in the future under climate change ( Boody et al. 2009).

Biotech solutions. The recognition that agriculture will face challenges under climate change has brought about a major effort to adapt agriculture through technical means, primarily the research and development of drought-resistant biotech crops. The push for greater use of biotechnology that focuses on sole-crop agriculture has made some headway in protecting production yields for some farmers, but it has not succeeded in many situations, especially in developing nations ( Herdt 2006). Yet biotech continues to be a major focus in agricultural adaptation solutions to climate change. According to assessments by the Australian government, crops genetically engineered for drought tolerance have not been found to outperform traditional varieties ( Braidotti 2008), and in fact, many traits are most easily bred into crop systems using conventional breeding through crop genetic diversity ( USDA 2008). The authors of an International Water Management Institute report ( IWMI 2007) concluded that improvements in biotech products would have only a moderate impact over the next 15 to 20 years in making crops more efficient in using water. They also concluded that "greater, easier, and less contentious gains" could come from managing water supplies better, rather than trying to develop crops that can flourish with less water ( IWMI 2007).

Additionally, the speed of research and development of new biotech crops must be assessed in comparison with the speed of climate change effects on agriculture. A recent New York Times article ( Pollack 2008) that interviewed a researcher on Monsanto drought-tolerant corn stated that drought-tolerant varieties could reach American farmers in four years, with a 10% increase in yield. Other varieties could reach Africa by 2017 ( Pollack 2008). The difficulty with assessing such scenarios is the uncertainty in the rate of change that farmers will have to contend with in the next 5 to 10 years. Will the technology developed today be sufficient to protect farmers under the climate conditions of the future when it is launched in 5 to 10 years? For how long will the technology be useful? Such products may also be prohibitively expensive, which will pose a challenge for smallholder rural farmers who may want to pursue this adaptation option under climate change.

If there is indeed a temporal scale mismatch in the rate of development of adequate biotech lines and the rate and extent of climate change effects on agriculture, farmers will have to turn to other adaptation options to improve the resilience of their systems to climate change. The need to develop options for present and expected climate change and for those who will have no access to such technology remains a great problem for agricultural development and food security fields. Diversified agriculture in such cases remains a highly accessible adaptation option for many farmers.

Biomass production. The belief that monocultures and intensively managed systems are more productive than diversified agricultural systems is another challenge to moving agricultural systems toward more diversity. Maximizing biomass production of one or two specific crops is essentially the goal of the current modern agricultural paradigm. Although ecosystem functioning of such systems persists at much reduced capacity, outside infrastructure such as mechanization, chemical inputs, and irrigation systems can help replace the lost functionality ( Altieri 1999) to enable high production. However, the potential effects of climate change on agriculture stability will further complicate our predictions of production and pricing of goods from large-scale, monocropped systems.

In many regions of the world, the ability to use intensified production practices and products is limited by cost and transportation. Petroleum for mechanization techniques and chemical inputs can be prohibitively expensive. Even in regions with access to mechanization and chemical inputs, a lack of water resources can severely reduce production capacity. In such cases, diversified agricultural systems that are able to produce under extreme climate scenarios are preferable because many of the ecosystem functions that cannot be brought into the system through inputs and mechanizations can be provided through natural means. Such solutions support both biodiversity and community resilience to climate change by taking advantage of ecosystem functions and services, supporting high production yields in potentially adverse environmental conditions.

However, not all studies have shown that greater diversity leads to increased production yield. In one study, biodiverse rotational systems of three to six species produced 25% lower yield versus integrated monocropped grain systems, but the grain was of higher quality. The high-quality grain from the more biodiverse system must be of greater value to overcome the economic benefit of higher production in the lower-quality monoculture (Snapp et al. 2010).

Developing optimization strategies and win-win solutions for diversification

A major challenge for the implementation of diversified agricultural systems for farmers is finding the appropriate balance of diversification within the farm system to satisfy both production and protection values. Farmers and agricultural managers must consider the variety of ways that diversification can occur within the system and develop methods that best meet their specific needs of crop production and resilience. Of course, as climate change variability increases, the value of resilience will also increase, especially in production systems sensitive to climate variation. However, a farmer's decision to move toward diversified agricultural systems will be highly influenced by the ability of the diversification strategy to support the economic resilience of farms. Cost-cutting examples, such as the use of beetle banks to reduce pesticide costs ( Thomas et al. 1991) or the reduction of fungicide use in integrated rice systems ( Zhu et al. 2000), illustrate the significant possible economic benefits of greater biodiversity. Policy incentives that strongly promote adaptation are also necessary for transitioning agriculture to a long-term sustainable state. Finding win-win solutions that account for farmers' various production and protection goals is necessary to develop long-term, viable strategies.

Optimizing diversification strategies at various scales. Developing tools that can help managers understand best practices on a farm field or landscape scale can significantly enhance diversity in agricultural systems while increasing the resilience of systems to climate change and maintaining high yields.

However, it will greatly benefit future planning if there is greater development of extension and on-the-ground research staff who are able to assist in collecting relevant soil and plant development data and in modeling cropping strategies to specific location variables. Simulation analyses conducted on specific production scenarios are especially useful in improving decisionmaking (e.g., what crops should be planted, and when), particularly when performed in conjunction with local knowledge of potential environmental and socioeconomic challenges. The use of interdisciplinary research to consider the overall crop management system will allow for better adaptation method development and implementation (Stone and Meinke 2005).

Development of larger-scale diversified landscapes that support and improve ecological resilience in agricultural systems requires a more in-depth analysis of the farm business and landscape-level scenario modeling for on-farm diversity possibilities. For example, Boody and colleagues (2009) examined how two watersheds in Minnesota would fare under a variety of future land-use scenarios including (a) a continuation of current trends, (b) the application of best management practices (BMPs) over the landscape, (c) a mixture of agricultural uses that maximize diversity and profitability, and (d) a scenario increasing vegetative cover over the landscape ( Boody et al. 2009). The scenario that maximized on-farm diversity and profitability moved beyond BMPs alone and included organic cropland, five-year crop rotations, and intensive managed grazing. This diverse system increased profits and biodiversity while reducing environmental externalities (e.g., water quality, greenhouse gases, sedimentation, and flooding), thereby creating a win-win-win solution. Such scenario modeling of landscapes could be very useful for farmers making decisions about large tracts of land or in systems where there is a cooperative structure in land management. These types of modeling scenarios may also assist decisionmakers in long-term planning of landscapes.

Stakeholder involvement and participatory research. The adoption of sustainable agricultural options under climate change has been a challenge for many communities, as the idea of climate change adaptation can seem overwhelming. The ability and space to communicate adaptation options is very important to implementation success; discussing the risk and uncertainty of climate change is especially critical, as sound climate science is required to implement rational and useful strategies. Additionally, stakeholders must understand that adaptation options become fewer as climate variability increases; the cost and complexity of adaptation will increase, yet the benefits of adaptation will increase as well ( Howden et al. 2010).

Stakeholder involvement and participatory research are often very useful tools in developing adaptation options that will be adopted by a local community because these methods recognize that knowledge often lies with the farmers in the field, and that local considerations should be integrated into long-term planning ( Rivington et al. 2007). In Australia, the Commonwealth Scientific and Industrial Research Organisation engages with rural agricultural communities through agricultural stakeholder meetings to discuss the effect of climate variability on challenges and priorities for local farmers. Farmers are active participants in developing adaptation solutions, such as the modeling scenarios of on-farm crop mixtures and rotations. Because of stakeholder engagement, farmers develop ownership of solutions and therefore more readily adopt adaptation strategies onto their farms ( Gardner et al. 2009). Thus, partnerships among stakeholders (farmers and scientists) are necessary for the successful development and adoption of sustainable management, such as the use of simulation approaches to help farmers find optimal strategies.

Conclusions

It is abundantly clear that farmers are facing growing stress from climate change, and that the greater implementation of diversified agricultural systems may be a productive way to build resilience into agricultural systems. The challenges to increasing adoption of diversified agricultural management strategies are both scientific and policy based. In the scientific realm, the adoption of diversified agricultural systems could be bolstered if farmers had a better idea of how to optimize a diversified structure to maximize production and profits. Crop and landscape simulation models that can model a range of climate scenarios and landscape modeling with farm profitability scenarios would help farmers find optimal strategies for maintaining production and profit. Stakeholder-based participatory research would also be highly beneficial, as researchers could model strategies that seem plausible to farmers.

In the policy realm, diversification within agricultural systems could potentially increase in the United States through the adjustment of the farm income support systems to incentivize more diverse cropping systems that support small farmers. Internationally, diversified agriculture can have a large role in protecting food security and production in regions where farmers have little access to chemical, structural, or technological resources. Diversified farming strategies are supported by international research efforts, including the International Assessment on Agricultural Knowledge, Science and Technology for Development, a global report of more than 400 scientists that concluded that locally adapted seed and ecological farming better addressed the complexities of climate change, hunger, poverty and productive demands on agriculture in the developing world. The report also showed that the ecological processes of these more complex systems could be used to protect farmers from climatic change and improve food security.

Understanding the potential of increasing diversity within farm systems is essential to helping farmers adapt to greater climate variability of the future. By adopting farm systems that promote ecosystem services for pest and disease control and resilience to climate change variability, farmers are less at risk to production loss and are more generally resilient to environmental change.

Acknowledgments

I thank the Berkeley Environmental Institute, Claire Kremen, and Miguel Altieri for spurring me to develop this topic. I also thank Ivette Perfecto, John Vandermeer, Miguel Altieri, and three anonymous reviewers for their comments in improving this manuscript.

This publication was developed under Cooperative Agreement no. X3 83232801 awarded by the US Environmental Protection Agency (EPA) to the American Association for the Advancement of Science. It has not been formally reviewed by the EPA. The views expressed in this document are solely my own and do not necessarily reflect those of the agency. The EPA does not endorse any products or commercial services mentioned in this publication.

References cited

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Resilience in Agriculture through Crop Diversification: Adaptive Management for Environmental Change | BioScience | Oxford Academic

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Recognition that climate change could have negative consequences for agricultural production has generated a desire to build resilience into agricultural systems. One rational and cost-effective method may be the implementation of increased agricultural crop diversification.

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"Where there is the most diversity there is the most history, the seeds have evolved for the climate and culture." 

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"Where there is the most diversity there is the most history, the seeds have evolved for the climate and culture." 

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In this portion of the documentary they were looking at the potato farmers in the highlands of Peru. This a community that relies heavily on the different potato crops and has for centuries. With climate changes pushing their planting higher and higher into the mountain side the community is scared they will not be able to grow enough to survive. The Proceedings of the National Academy of Sciences in the United States claims that the modern day potato originates from this South American region and if the region was no longer able to grow the crop many people would starve and any connection to the potato's wild ancestor could be lost (Spooner, 2005).

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Abstract

The cultivated potato, Solanum tuberosum, ultimately traces its origin to Andean and Chilean landraces developed by pre-Colombian cultivators. These Andean landraces exhibit tremendous morphological and genetic diversity, and are distributed throughout the Andes, from western Venezuela to northern Argentina, and in southern Chile. The wild species progenitors of these landraces have long been in dispute, but all hypotheses center on a group of ≈20 morphologically very similar tuber-bearing ( Solanum section Petota) wild taxa referred to as the S. brevicaule complex, distributed from central Peru to northern Argentina. We present phylogenetic analyses based on the representative cladistic diversity of 362 individual wild (261) and landrace (98) members of potato (all tuber-bearing) and three outgroup non-tuber-bearing members of Solanum section Etuberosum, genotyped with 438 robust amplified fragment length polymorphisms. Our analyses are consistent with a hypothesis of a "northern" (Peru) and "southern" (Bolivia and Argentina) cladistic split for members of the S. brevicaule complex, and with the need for considerable reduction of species in the complex. In contrast to all prior hypotheses, our data support a monophyletic origin of the landrace cultivars from the northern component of this complex in Peru, rather than from multiple independent origins from various northern and southern members.

Materials and Methods

Plant Materials. We sampled 362 individual wild (261) and landrace (98) members of tuber-bearing relatives of potato ( Solanum section Petota) and three sister group representatives in Solanum section Etuberosum ( S. etuberosum and S. palustre). These accessions came from the United States Potato Genebank ( www.ars-grin.gov/nr6) and the Commonwealth Potato Collection of the Scottish Crop Research Institute ( www.scri.ac.uk/cpc). They were identified mostly from living accessions planted at the genebank by visiting potato taxonomists (mainly Jack Hawkes and Carlos Ochoa) over 30 years. The 264 wild species accessions are mostly members of the S. brevicaule complex and are largely the same ones used in prior morphological ( 21) and molecular ( 22) studies of the complex, and are labeled as those species. We included tetraploid S. stoloniferum to have a data set comparable to the prior morphological and molecular studies. The members of the S. brevicaule complex are so similar that their identities have frequently changed, and we mostly use the identities from these prior studies for consistency. We add additional cultivated accessions and wild species to represent the entire four-clade diversity of section Petota from Spooner and Castillo ( 26), and they included members of the Phureja Group (diploid, Andean), Stenotomum Group (diploid, Andean), Andigenum Group (tetraploid, Andean), and Chilotanum group (tetraploid, lowland Chile). Our study included 230 diploids (2 n = 2 x = 24), 120 tetraploids (2n = 4x = 48), and 12 hexaploids (2 n = 6 x = 72). S. gourlayi included its diploid and tetraploid cytotypes, and S. oplocense included its tetraploid and hexaploid cytotypes. Designations of ploidy and classes of species (cultivated, S. brevicaule group north, S. brevicaule south, outgroups, and ploidy) are presented in Fig. 1.

AFLP Genotyping. Plants were grown in the glasshouse, and DNA was extracted from frozen plant leaf tissue taken from single plants by using the DNeasy Plant DNA Extraction kit (Qiagen, cat. no. 69181). AFLP assays were performed by using a modification of the protocol of Vos et al. ( 27), using the 6-bp cutting enzymes PstI and EcoRI and the 4-bp cutting enzyme MseI. The six AFLP primer combinations used were EAAC + MCCA, EACA + MCAC, PAC + MACT, PAG + MACC, PAT + MAAC, and PCA + MAGG. PCR reactions were set up on 384-well plates by using a Beckman Biomek 2000 liquid handling device. Electrophoresis was carried out on the Bio-Rad Sequi-Gen GT system on 5% acrylamide and 7 M urea in 1× TBE buffer (100 mM Tris/100 mM boric acid/2 mM EDTA). A dual buffer system of 1× TBE and 1× TBE supplemented with 0.5 M NaOAc was used to create an ionic gradient, which resulted in better separation of the larger fragments. A Promega fmol DNA Cycle Sequencing system (Promega Q4100) marker (prepared according to the protocol but using only d/ddT Nucleotide Mix) was run to estimate fragment sizes. Gels were dried onto paper and visualized by exposure to x-ray film (Kodak BIOMAX MR). Gels were scanned by using a standard flat-bed scanner at 300 dpi and 8-bit grayscale format. The TIFF images were then imported into aflp-quantar software supplied by Keygene (Wageningen, The Netherlands). To enable automatic positioning of marker bands, a standard genotype was run on each gel. The AFLP data matrices are published as supporting information on the PNAS web site.

paup Phylogenetic Analysis. Phylogenetic reconstructions were performed by using * 4.0b8 ( 28), using Wagner parsimony ( 29). The non-tuber-bearing species S. etuberosum and S. palustre (section Etuberosum) were designated as the outgroup, but members of these species, and clades 1, 2, and 3 of Spooner and Castillo ( 26), fall at the base of the tree and are listed as outgroups in Fig. 1; all remaining wild and cultivated species are members of clade 4. To find multiple tree islands, we used a four-step search strategy, modified from Olmstead and Palmer ( 30). ( i) One million replicates initially were run by using random order entry starting trees with nearest-neighbor interchange. ( ii) The shortest trees from this analysis were used individually as starting trees with the tree-bisection-reconnection (TBR) method. ( iii) The resulting trees were searched with nearest-neighbor interchange, retaining all most parsimonious trees (MULPARS). ( iv) The resulting trees were searched with TBR and MULPARS. The last two analyses were terminated at 10,000 trees. The resulting trees were used to compute a strict consensus tree. A bootstrap analysis was conducted on 500 replicates with TBR and MULPARS. The above analyses were done twice, once with the entire data set and again only with the diploids.

AFLP data were also analyzed by neighbor-joining using ntsys-pc R 2.02k ( 31). The program simqual was used to compute similarity matrices using the "Jaccard" option, which ignores shared absent bands, and which is an appropriate algorithm for AFLPs scored as dominant markers.

Concordance Tests Among the Present AFLP Data to the Prior Restriction Fragment Length Polymorphism (RFLP), Randomly Amplified Polymorphic DNA (RAPD), and Morphological Studies. We tested concordance among our new AFLP results to the morphological ( 21) and single- to low-copy RFLP and RAPD data ( 22) of the S. brevicaule complex. For each data set, we constructed parallel matrices containing accessions in common between studies. We then made pairwise distance matrices for all four data sets. For the AFLP and RAPD data, we used the Jaccard matrix, for the RFLP data we used a simple-matching coefficient, and for the morphological data we used the distance algorithm, all present in ntsys-pc R 2.02k ( 31). We then performed pairwise comparisons of these matrices with the Mantel test ( 32) as performed in ntsys-pc R. This statistic varies from 0 (no correspondence of matrices) to 1 (perfect correspondence).

Results and Discussion

Cladistic Results. The six AFLP primer combinations produced 438 characters of which 3.6% of the data matrix had missing values, caused by occasional failed reactions or faint bands. Wagner parsimony analysis of all 362 accessions ( Fig. 1) produced 10,000 (our designated upper tree limit) most parsimonious 13,672-step trees with a consistency index of 0.033 and a retention index of 0.571, and a rescaled consistency index of 0.019. The topology of the entire data set is very similar to the four clade cladistic structure of Spooner and Castillo ( 26). S. etuberosum and S. palustre form a monophyletic basal outgroup, sister to S. bulbocastanum, S. polyadenium, S. stenophyllidium, and S. tarnii (clades 1 and 2), sister to S. acroscopicum, S. andreanum, S. chilliasense, S. pascoense, and S. paucissectum (clade 3); this clade also includes two accessions of S. acroscopicum and two accessions of S. multidissectum, members of the S. brevicaule group. The bootstrap analysis ( Fig. 1) showed >50% support for the basal clades of sect. Etuberosum and clades 1-3, and in some internal branches of clade 4, but poor support (<50%) in the external branches of clade 4. Wagner parsimony analysis of the 230 diploid accessions (data not shown) produced 177 most parsimonious 8,393-step trees with a consistency index of 0.0534, and a retention index of 0.5617 and a rescaled consistency index of 0.0300; bootstrap support was similar to the total taxon tree. The topology of the entire data set and the reduced data set of the diploids differs very little.

The topology of the entire data set is in concordance with the morphological ( 21), RAPD, and RFLP results ( 22) in defining a northern (species from Peru, together with S. achacachense from northern Bolivia) and southern (species from Bolivia and northern Argentina) clade of the S. brevicaule complex. This geographic split does not exactly follow country borders, but very closely so. For example, the northern clade contains S. achacachense PI 558032 from the department of La Paz, Bolivia bordering Peru, and the southern clade contains S. leptophyes PI 458378 from the department of Puno bordering Bolivia.

Also in concordance with prior results, the AFLP data fail to resolve many species in the complex. Species that fail to form clades in the northern S. brevicaule group are S. abancayense, S. bukasovii, S. canasense, S. leptophyes, S. marinasense, S. multidissectum, and S. multiinterruptum, whereas S. candolleanum and S. pampasense form clades. Species that fail to form clades in the southern complex are S. ambosinum, S. brevicaule, S. canasense, S. leptophyes, S. oplocense, S. sparsipilum, and S. sucrense, whereas S. avilesii, S. hoopesii, S. incamayoense, S. spegazzinii, S. ugentii, S. vernei, and S. vidaurrei [diploid] (to the exclusion of one accession of S. gourlayi [tetraploid]) form clades.

The AFLP data support a monophyletic origin of all of the cultivars. S. bukasovii 568954 and S. acroscopicum 230495, however, fall within the cultivated clade. Accession 230495 was labeled in the genebank as S. acroscopicum (a diploid species), but chromosome counts show it to be tetraploid and likely to be a misidentified cultivated species. S. bukasovii 568954 could be a progenitor or an unrecognized cultivated diploid species.

Hosaka ( 10) showed that S. tarijense was a likely maternal contributor in the origin of landraces of the Chilotanum group, because they share a 241-bp chloroplast deletion. Our examination of three accessions of S. tarijense, and the related species S. arnesii, S. berthaultii, and S. chacoense, show them to form a clade, separate from the cultivars.

Phenetic Results. Because AFLPs are dominant and anonymous marker data, a case has been made that they should be analyzed with phenetic methods ( 33). The neighbor-joining tree (data not shown) outlines nearly the same set of species groups including the northern and southern S. brevicaule groups, places the cultivated species as a single group, and places the outgroup distant to the tuber-bearing species. A phenogram could represent the phylogeny when similarities are mainly due to shared derived characteristics ( 34). In our case, conclusions are the same with cladistic or neighbor-joining procedures, and controversies of proper methods to use are therefore moot.

Concordance of the Present AFLP Data to Prior Morphological and Molecular Data in the S. brevicaule Complex. The Mantel tests showed high correlations ( r) of the present AFLP results to the prior RAPD and single- to low-copy nuclear RFLP results of the S. brevicaule complex ( 22) ( r = 0.740-0.845) ( Table 1) and much lower correlations to the morphological data ( r = 0.204). Despite much lower correspondence of AFLP, RFLP, and RAPD results to the morphological results ( Table 1), the morphological data still showed a north-south partitioning by a canonical variates analysis ( 21).

The utility of AFLPs to examine relationships of closely related species has been documented elsewhere. For example, Powell et al. ( 35) showed AFLPs and nuclear RFLPs to be significantly correlated in diversity studies of cultivated soybean ( Glycine max [L.] Merrill) and its progenitor species G. soja Hort.; Milbourne et al. ( 36) showed good correlations between AFLPs and RAPDs in S. tuberosum; and Russell et al. ( 37) showed good correlations of AFLPs and nuclear RFLPs in Hordeum. Such correlations, and the concordance of AFLP to nuclear RFLP, RAPD, and morphological results reported here, support the utility of AFLPs for examining relationships of S. tuberosum and the S. brevicaule complex.

Single Domestication for Potato. All cladistic and phenetic analyses, of both the diploids and tetraploids, show all landrace populations to form a monophyletic clade, derived from the northern members of the S. brevicaule complex. These S. brevicaule northern group member "species" are poorly defined, and ongoing studies may reduce them to a single species, with the earliest valid name of the group being S. bukasovii. The conclusions of a single origin of cultivated potato from the northern species of the S. brevicaule group differs from all conventional domestication hypotheses ( 9, 13, 15, 19- 21, 23- 25) in two fundamental respects: ( i) a single origin is here supported, rather than a series of multiple independent origins; and ( ii) the origin is confined to the northern component of the S. brevicaule complex, rather than to other southern complex species that are commonly mentioned as progenitors, such as S. sparsipilum or S. vernei (e.g., refs. 9 and 23). A "single" origin is here supported to mean an origin from a single species, or its progenitor ( S. bukasovii), in the broad area of southern Peru. Because landrace potatoes are currently spread throughout the Andes and Chile, they clearly were diffused from Peru both north and south, assuming present-day distributions of the original cultivars.

The single origin of potato parallels results suggesting single origins of other crops including barley ( 38), cassava ( 39), maize ( 40), einkorn wheat ( 41), and emmer wheat ( 42). This differs from multiple origins of common beans ( 43), cotton ( 44), millet ( 45), rice ( 46), and squash ( 47). Allaby and Brown ( 48) criticize the use of "anonymous" marker data of any type (including AFLPs) to infer single crop origins. Results of computer simulations have led these authors to postulate that monophyletic origins can be erroneously inferred when using dominant marker data analyzed by neighbor-joining methods. They assume that pairs of markers, on average, are unlinked and simulate different scenarios for cereal crops. Authors of some of the original studies have replied, suggesting that the "intrinsic quality" of their data outweighs any doubts through use of simulated data ( 49). It is clear that further, more sophisticated simulations are required, using information on known marker linkage relationships. Moreover, Allaby and Brown ( 48) do not comment on the applicability of their studies to predominantly outbreeding, clonally propagated crops, such as potato.

Diamond ( 50) discusses single vs. multiple crop origins in a geographic perspective. He suggests that crops that spread east and west (as einkorn wheat and emmer wheat in the Fertile Crescent), rather than north and south (as squash and cotton in the Americas), have a competitive advantage in rapid diffusion because they take less time to adapt to new habitats. He further contends that such rapid diffusion preempts adoption of competing crops and favors single crop origins, in contrast to multiple origins of crops spread north and south. His paper was written when maize ( 51, 52) and potato (present results) were thought to have multiple origins. The widespread north and south diffusion of maize and potatoes, and their monophyletic origin, prompts a reconsideration of his geographic interpretation of single and multiple origins.

Reconsideration of the Taxonomy of the S. brevicaule Complex. The data strongly suggest that ( i) considerable reduction of species is needed in the S. brevicaule complex and ( ii) the complex is polyphyletic. AFLP data suggest that some of the species in the complex, however (mentioned above), may be valid. AFLP data also suggest, as do the RAPD and nuclear RFLP data, that some accessions of S. multiinterruptum are part of the distinctive clade 3 (series Piurana) ( 22). Taxonomic changes in species circumscriptions are underway as part of a broader-scale taxonomic revision of the entire genus Solanum ( 53). Poor support for the traditionally circumscribed S. brevicaule complex species suggests that designations of species-specific progenitors of the landrace cultivars with this outdated taxonomy ( 9, 25) are futile. Rather, our results suggest that the Andean landrace cultivars arose from the northern component of the S. brevicaule complex. S. bukasovii is the earliest taxonomic name possessing priority as this progenitor.

Acknowledgments

We thank the U.S. Department of Agriculture Foreign Agricultural Service and the Scottish Executive Environment and Rural Affairs Department for financial support.

Footnotes

↵ † To whom correspondence should be addressed. E-mail: dspooner{at}wisc.edu .

Abbreviations: AFLP, amplified fragment length polymorphism; RAPD, randomly amplified polymorphic DNA; RFLP, restriction fragment length polymorphism.

View Abstract

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A single domestication for potato based on multilocus amplified fragment length polymorphism genotyping

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The cultivated potato, Solanum tuberosum , ultimately traces its origin to Andean and Chilean landraces developed by pre-Colombian cultivators. These Andean landraces exhibit tremendous morphological and genetic diversity, and are distributed throughout the Andes, from western Venezuela to northern Argentina, and in southern Chile.

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"The biggest and most immediate, most pressing need to conserve diversity was going to be climate change." 

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"The biggest and most immediate, most pressing need to conserve diversity was going to be climate change." 

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In this quote Cary Fowler was talking about a speech he had given to some of the workers at the seed bank in Norway stating that genetic diversity is a climate change issue. With temperatures rising some seeds are not adapted to handle the sudden change. To address this issue experts have turned to plants' wild ancestors to find genes that will allow the plant to withstand a hotter environment. The Proceedings of the National Academy of Sciences in the United States reports that because of climate change, especially the change in temperature and moisture, some European plant species have become severely threatened (Thuiller, 2007).

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Abstract

Climate change has already triggered species distribution shifts in many parts of the world. Increasing impacts are expected for the future, yet few studies have aimed for a general understanding of the regional basis for species vulnerability. We projected late 21st century distributions for 1,350 European plants species under seven climate change scenarios. Application of the International Union for Conservation of Nature and Natural Resources Red List criteria to our projections shows that many European plant species could become severely threatened. More than half of the species we studied could be vulnerable or threatened by 2080. Expected species loss and turnover per pixel proved to be highly variable across scenarios (27-42% and 45-63% respectively, averaged over Europe) and across regions (2.5-86% and 17-86%, averaged over scenarios). Modeled species loss and turnover were found to depend strongly on the degree of change in just two climate variables describing temperature and moisture conditions. Despite the coarse scale of the analysis, species from mountains could be seen to be disproportionably sensitive to climate change (≈60% species loss). The boreal region was projected to lose few species, although gaining many others from immigration. The greatest changes are expected in the transition between the Mediterranean and Euro-Siberian regions. We found that risks of extinction for European plants may be large, even in moderate scenarios of climate change and despite inter-model variability.

Methods

Data Sources. Species' distribution data are available for 2,294 plants ( 20), comprising ≈20% of the total European flora, sampled between 1972 and 1996. Modeling was conducted by using available data for Europe on a 50 × 50 km grid. The mapped area comprises western, northern and southern Europe, but excludes most of the eastern European countries where recording effort was both less uniform and less intensive ( 21). After removing species with <20 records, we considered range responses of 1,350 plant species of Europe. We assume this sample can be taken as representative of the responses of European plant species to climate change because it includes most of the life forms and phytogeographic patterns found among plant species in Europe.

Climate data were obtained from the Climatic Research Unit ( www.cru.uea.ac.uk) and included mean annual, winter, and summer precipitation, mean annual temperature and minimum temperature of the coldest month (MTC), growing degree days (>5°) and an index of moisture availability ( 22). These variables were chosen because of their strong link with the physiology and growth of plant species ( 23, 24). For instance, MTC discriminates species based on their ability to assimilate soil water and nutrients, and continue cell division, differentiation and tissue growth at low temperatures (lower limit), and chilling requirements for processes such as bud break and seed germination (upper limit). The moisture index discriminates species through processes related to phenology, rooting strategy, leaf morphology, and xylem vulnerability to cavitation. However, because there is surprisingly little experimental work for any particular species to guide the choice of bioclimatically limiting variables, the variables are generic and represent a hypothetical minimum basic set for niche-based modeling. Climate data were averaged for the 1961-1990 period. The data were supplied on a 10-foot (1 ft = 0.3 m) grid covering Europe. They were aggregated by averaging to 50 × 50 km Universal Transverse Mercator (UTM) to match the species data grid. Niche-based models were calibrated on the 50 × 50 km UTM grid, and modeled species distributions were projected back onto the 10′ grid for current and future climate.

Future projections were derived by using climate model outputs made available through the Intergovernmental Panel on Climate Change (IPCC) Data Distribution Centre ( ipcc-ddc.cru.uea.ac.uk). ‡‡ The modeled climate anomalies were scaled based on four scenarios proposed by the IPCC ( 12). The A1 scenario describes a globalized world with rapid economic growth and global population that peaks in mid-century and declines thereafter and assumes rapid introduction of new and more efficient technologies. Concentrations of CO ₂ increase from 380 ppm in 2000 to 800 ppm in 2080, and temperature rises by 3.6 K ( 12). The A2 scenario describes a heterogeneous world with regionally oriented economic development. Per capita economic growth and technological change are slower than in the other scenarios. Global concentrations of CO ₂ increase from 380 ppm in 2000 to 700 ppm in 2080, and temperature rises by 2.8 K. The B1 scenario describes a convergent world with global population that peaks in mid-century and declines thereafter, as in A1, but with a rapid change toward a service and information economy and the introduction of clean and resource-efficient technology. Concentrations of CO ₂ increase from 380 ppm in 2000 to 520 ppm in 2080, and temperature rises by 1.8 K. The B2 scenario describes a world in which the emphasis is on local solutions to socioeconomic and environmental sustainability. It is a world with continuously increasing global population (at a rate lower than A2), intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 scenarios. Concentrations of CO ₂ increase from 380 ppm in 2000 to 550 ppm in 2080, and temperature rises by 2.1 K ( 12).

We did not assess the impacts of land-use change, even though this factor will potentially compound the effects of climate change on species distributions ( 25). However, given the spatial extent and resolution of our data and the magnitude of climate change in most projections, the effect of land use would be most likely overridden by climate ( 26, 27).

Niche-Based Models of Species Climatic Envelops. We used the biomod framework, which capitalizes on several widely used niche-based modeling techniques (generalized linear models, generalized additive models, classification tree analysis, and artificial neural networks) to provide alternative spatial projections ( 13). For each climate change scenario, models relating species distributions to the seven bioclimatic variables were fitted by using biomod and projected into the future. Then, a consensus principal component analysis was run to explore central tendencies in projections and select the niche-based model representing the greatest commonality among projections ( 8).

There is increasing evidence that model projections can be extremely variable, and there remains a need to test the accuracy of models and to reduce uncertainties ( 8, 28, 29). One recent analysis has however provided the first test of the predictive accuracy of such models by using bird observed species' range shifts and climate change in two periods of the recent past ( 30). This work provides validation of niche-based models under climate change and demonstrated how uncertainty can be reduced by selecting the most consensual projections, as done in this study. We are therefore confident that this strategy provides a robust and defensible approach to species range projections for the purposes of conservation planning and biodiversity management.

To evaluate species extinction risks, we summed the number of pixels lost, potentially gained (under universal migration), or stable by each species for the different climate-change scenarios. We assigned each species to an International Union for Conservation of Nature and Natural Resources (IUCN) threat category (IUCN 2001). Those that were not listed were classified as lower risk, depending on the projected reduction in range size from present to 2080. Present and future range sizes (area of occupancy) were estimated from the number of pixels where species occurred. Loss in range size was calculated by subtracting future potential range size from present potential range size. In line with IUCN Red List criterion A3(c), the following thresholds were then used to assign a species to a threat category (IUCN 2001). Extinct is a species with a projected range loss of 100% in 50 or 80 years, critically endangered has a projected range loss of >80%, endangered has a projected range loss of >50%, and vulnerable has a projected range loss of >30%. Although this Red Listing approach is simplistic and considers only the effects of climate change, it provides a synthetic overview of species-specific threats due to climate change.

To evaluate the percentage of extinctions for a given area, we summed the number of species lost ( L) by pixel and related it to current species richness by pixel. The procedure was the same to assess the percentage of species gained ( G) by pixel (under assumptions that species could reach a new suitable climate space). Percentage of species turnover by pixel, under the assumption of universal migration, is then given by T = 100 × ( L + G)/( SR + G) where SR is the current species richness.

Results and Discussion

Many European species could be threatened by future climate change ( Fig. 1). Under the assumption of no migration, more than half of the species we considered become vulnerable or committed to extinction by 2080. The impacts of climate change are, naturally, less under the universal migration because of the possibility for species to move across landscapes. Under the no-migration assumption and the most severe climate change scenario (A1-HadCM3), 22% of the species become critically endangered (>80% range loss), and 2% extinct by 2080. These numbers decrease for the other scenarios and climate models. Under the universal migration assumption, the results are, as expected, less severe. Under tA1-HadCM3, 67% of species would be classified as low risk, whereas under B1-HadCM3, 76% of the species would be at low risk.

Our results coincide with the direction of predictions made by Thomas et al. ( 11), although the magnitude of the risks we project is less [and note that we project distributions to 2080, whereas Thomas et al. ( 11) only projected to 2050].

Niche-based modeling does not address the proximate causes of species extinction. Nevertheless, any reduction in the potential geographic range of a species is likely to lead to an increased risk of local extinction ( 11). This conclusion is, in fact, the rationale for building IUCN Red Lists ( 31). A decrease in range size implies that smaller stochastic events affect a larger proportion of the species' total population, especially in fragmented landscapes. If a species becomes restricted to a few sites, then local catastrophic events (such as droughts or disease outbreaks) or an increase of land transformation by humans could easily cause the extinction of that species ( 32).

Rates of species' loss and turnover show great variation across scenarios ( Fig. 2). In A1-HadCM3, the mean European temperature increases by up to 4.4 K, leading to a mean species loss of 42% and turnover of 63%. This scenario provides the widest range of variability across Europe for both species loss (2.5-86%) and turnover (22-90%). The percentage of species loss could exceed 80% in some areas, such as northcentral Spain and the Cevennes and Massif Central in France. B1-HadCM3 gives the lowest expected mean percentage of species loss (27%), reflecting the fact that this scenario has the lowest rate of increase in CO ₂ and temperature by 2080 (mean European temperature increase of 2.7 K). Other scenarios show intermediate mean rates of species loss (≈30%) and turnover (≈50%).

The relationship between the modeled percentage of species loss and the anomalies for the two most significantly correlated bioclimatic variables, growing-degree days (representing accumulated warmth) and a moisture availability index, was used to uncover the potential causes of variations in predicted changes in plant diversity across regions within and across scenarios ( Fig. 3). The strong consistent linear relationship across scenarios indicates that projected species loss from our models could be estimated from these two predictors. The Spearman rank-correlation values for the separate univariate relationships were 0.73 and 0.65, respectively. Multiple-linear regression by using these two predictors explains 60% of the variance across scenarios. The temperature of the coldest month, although being an important predictor of distributions for many species ( 6), did not show a strong relationship with species loss overall and was therefore not used in this analysis.

Regional deviations from the inferred relationship (positive and negative residuals) can be interpreted as indications of particularly high or low species vulnerability, because of ecological and historical characteristics of the flora, and/or specific environmental conditions ( Fig. 4). An excess of species loss (red color) is shown for mountain regions (mid-altitude Alps, mid-altitude Pyrenees, central Spain, French Cevennes, Balkans, Carpathians). Severe climatic conditions have occurred in mountains over evolutionary times, promoting highly specialized species with strong adaptation to the limited opportunities for growth and survival ( 33). The narrow habitat tolerances of the mountain flora, in conjunction with marginal habitats for many species, are likely to promote higher rates of species loss for a similar climate anomaly than in any other part of Europe ( 34). By contrast, the southern Mediterranean and part of the Pannonian regions have a negative residual for species loss (gray color). Both regions are characterized by hot and dry summers and are occupied by species that tolerate strong heat and drought. Under the scenarios used here, these species are likely to continue to be well adapted to future conditions.

We finally present mean percentages of species loss and turnover by environmental zones (M. Metzger, unpublished data) with the A1-HadCM3 scenario of maximum change to best illustrate the spatial patterns ( Fig. 5). The major spatial patterns are similar over all scenarios. The northern Mediterranean (52%), Lusitanian (60%) and Mediterranean mountain (62%) regions are the most sensitive regions; the Boreal (29%), northern Alpine (25%), and Atlantic (31%) regions are consistently less sensitive. Species turnover shows a somewhat different pattern. The Boreal region could, in principle, gain many species from further south, leading to a high species turnover (66%). The Pannonian region could also theoretically gain eastern Mediterranean species and has a calculated turnover of 66%. Thus, these regions stand to lose a substantial part of their plant species diversity, and (in time) to show a major change in floristic composition. Projected species turnover peaks at the transition between the Mediterranean and continental regions ( Fig. 5) with extirpation of Euro-Siberian species and expansion for Mediterranean or Atlantic species. Southern Fennoscandia is also an area of high potential turnover with the loss of boreal species and gain of Euro-Siberian species.

These results cannot be taken as precise forecasts given the uncertainties in climate change scenarios, the coarse spatial resolution of the analysis ( 35), and uncertainties in the modeling techniques used ( 8, 29). The relatively coarse grid scale of our study may hide potential refuges for species and environmental heterogeneity that could enhance species survival, especially in mountain areas where our estimation of risks of extinctions could be overestimated. On the other hand, landscape fragmentation could increase the vulnerability of these refuges to fire or other disturbances, which in combination with the lack of propagule flow, could compromise the survival of remnant populations. There are also major uncertainties due to lags associated with biotic processes. The recognized time scales for assigning species IUCN Red List categories are not suited to evaluating the consequences of slow-acting but persistent threats. We have substituted a time scale of 80 years (instead of 20) for critically endangered, endangered and vulnerable, respectively, over which to assess declines. The extent of species losses may be overestimated, because the plasticity of species and the survival of species in favorable microhabitats is not considered. However, even if the numbers are overestimated, patterns across regions may stand (e.g., the ranking of region in terms of vulnerability to loss). Species loss does not necessarily imply the immediate loss of a species from a site, rather it may imply a potential lack of reproductive success and recruitment that will tend to extinction on a longer time scale ( 36). Migration rates are likely to be species-specific, and resulting biotic interactions in "no-analogue" assemblages may alter species' realized niches.

Land use and associated habitat fragmentation are likely to generally inhibit migration rates ( 19). Further, future species distributions will likely be influenced by other environmental factors than changing climate. The current atmospheric CO ₂ concentration exceeds any experienced during the past 20 million years ( 12). Plant physiological responses, including growth responses to increased atmospheric CO ₂ and changes in wateruse efficiency, are expected to ameliorate the response of some plant functional types to climate change ( 37). On the other hand, nitrogen deposition, the enhanced potential for invasion by exotic species, or the promotion of more competitive native species may change competitive interactions in plant communities, yielding novel patterns of dominance and ecosystem function ( 38).

Despite uncertainties, our findings provide illustration of the potential importance and the likely direction of climate change effects. From a conservation perspective, a proportion of European plant species could become vulnerable. The strong positive relationship between projected species loss and changes in bioclimatic variables implies that action to reduce greenhouse gas emissions would also mitigate climate-change effects on plant diversity. However, even under the least severe scenario considered, the risks to biodiversity appear to be considerable. Different regions are expected to respond differently to climate change, with the greatest vulnerability in mountain regions and the least in the southern Mediterranean and Pannonian regions. Recent observations ( 39) and predictions ( 9) corroborate our conclusion regarding the climatic sensitivity of species in European mountain areas. We have also identified a broad transition zone where the greatest species mixing is likely to occur. During the Quaternary period, this region acted both as a crossing point and a refuge zone for Boreo-alpine and Euro-Siberian species ( 40). This transition zone will be a strategic region for plant-species conservation in a changing climate.

Acknowledgments

M.B.A. thanks T. Lathi and R. Lampinen for providing a digital version of Atlas Florae Europaeae. We thank M. Erhard (Potsdam-Institute for Climate Impact Research, Potsdam, Germany) for repackaging and aggregating original climate data into the Atlas Florae Europaeae grid and M. Metzger for his environmental classification of Europe. This research was funded by the integrated projects of the European Commission's FP5 Advanced Terrestrial Ecosystem Analysis and Modeling (EVK2-CT-2000-00075) and FP6 Assessing Large-Scale Environmental Risks with Tested Methods (GOCE-CT-2003-506675).

Footnotes

↵ § To whom correspondence should be addressed. E-mail: thuiller{at}sanbi.org .

Author contributions: W.T. and S.L. designed research; W.T. performed research; W.T., S.L., M.B.A., M.T.S., and I.C.P. contributed new reagents/analytic tools; W.T. and M.B.A. analyzed data; and W.T., S.L., M.B.A., M.T.S., and I.C.P. wrote the paper.

This paper was submitted directly (Track II) to the PNAS office.

Abbreviation: IUCN, International Union for Conservation of Nature and Natural Resources.

↵ ‡‡ Mitchell, T. D., Carter, T. R., Jones, P. D., Hulme, M. & New, M. (2004) A Comprehensive Set of High-Resolution Grids of Monthly Climate for Europe and the Globe: The Observed Record (1901-2000) and 16 Scenarios (2001-2100) (Tyndall Centre for Climate Change Res., Norwich, U.K.), Working Paper 55.

Freely available online through the PNAS open access option.

View Abstract

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Climate change threats to plant diversity in Europe

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Climate change has already triggered species distribution shifts in many parts of the world. Increasing impacts are expected for the future, yet few studies have aimed for a general understanding of the regional basis for species vulnerability. We projected late 21st century distributions for 1,350 European plants species under seven climate change scenarios.

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"If one plant is susceptible the all of them all susceptible." 

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"If one plant is susceptible the all of them all susceptible." 

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With the loss of seed diversity and seed companies mass producing genetically identical seeds if something were to come up, like a new disease or a new insect, then it would leave all the plants vulnerable, because without genetic diversity there are no plants adapted for the new disease. The Nature Research Journal reports that some believe that the lack of seed diversity is not a problem because the seeds have been modified so much to be resistant to insects, weeds, and disease the chances of an entire crop being wiped out is unlikely (Tilman, 2002). Seeds are being modified to not need as much insecticide and to be resistant to disease but as shown in the video with the wheat, just because seeds are GM does not mean they are completely resistant to disease.

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Acknowledgements

We thank the National Science Foundation for support and N. Larson for assistance.

Author information

Affiliations

‖Center for Environmental Science and Policy, Stanford University, Stanford, California 94305, USA

Corresponding author

Correspondence to David Tilman.

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