Stockholm Resilience Centre
Research for Governance of Social-Ecological Systems
Master’s Thesis, 60 ECTS
Ecosystems, Governance and Globalisation Master’s programme, 120 ECTS
Impacts of Agriculturally-driven Regime Shifts on Ecosystem Services
and Human Well-being
Christine Hammond
Impacts of Agriculturally-driven Regime Shifts on Ecosystem Services and Human Well-being
Christine Hammond
Supervisors: Oonsie Biggs and Garry Peterson
ABSTRACT
Regime shifts are large, abrupt, persistent changes in the structure and function of ecosystems that may have substantial consequences for human well-being. In agricultural ecosystems, examples of regime shifts include soil salinization, lake eutrophication and bush encroachment.
Here, a novel, adaptable scoring system was developed using ecosystem services and human well-being as framed by the Millennium Ecosystem Assessment to: 1) quantify the impact of twelve agriculturally-driven regime shifts on ecosystem services and human well-being; and 2) estimate the effect that agriculturally-driven regime shifts have on different user groups. Key results include: 1) Ecosystem services and human well-being indices are impacted negatively by nearly all shifts from less to more anthropogenically impacted regimes; 2) The relative difference in ecosystem service amount between alternate regimes is much larger for regime shifts with more negative impacts than those with positive impacts; and 3) All user groups were impacted negatively by nearly all regime shifts, with industrial farmers being impacted least negatively and subsistence farmers being impacted most negatively. These findings can facilitate a better- informed assessment of the potential risks, benefits and costs associated with taking action to avert or precipitate agriculturally-driven regime shifts.
INTRODUCTION
Large-scale anthropogenic modifications to the Biosphere are increasing the likelihood of large, sudden, persistent ecosystem shifts that could have substantial consequences for humans and ecosystems (Lenton et al., 2007; MA, 2005; Scheffer, 2009a). For example, fertilizer application to agricultural lands contributes to freshwater eutrophication and hypoxia, which degrade water quality for drinking and recreation, and may lead to extensive fish kills (Carpenter, 2003).
Agriculture is the most expansive anthropogenic land modification, covering over 38% of the Earth’s ice-free land surface (Foley et al., 2011), and drives many important ecosystem shifts (Folke et al., 2004; MA, 2005). This study aims to assess the impacts of these so-called regime shifts on ecosystem services and human well-being.
Regime shifts are defined as sudden, persistent, large-scale reorganizations of the structure, function and feedbacks of ecosystems (Scheffer et al., 2001). They are distinguished from other ecosystem changes in that they involve a fundamental reorganization of the underlying structure and dynamics of an ecosystem. The concept of regime shifts originates from dynamical systems theory, which has produced mathematical models that show how complex adaptive systems can organize and fluctuate around different attractors. These attractors represent different regimes in which systems tend to remain for extended periods of time, relative to the time spent between regimes (Beisner et al., 2003). Each regime is maintained by a set of reinforcing feedbacks that maintain the characteristic structure and dynamics of a particular regime.
A regime shift involves the shift of a system from one attractor or self-organizing configuration to another (Biggs et al., 2012). Regime shifts occur when drivers such as nutrient accumulation gradually weaken system feedbacks, until a threshold is reached at which point a new set of feedbacks become dominant and pull the system toward a distinct alternate attractor (Andersen et al., 2009). Often, regime shifts are associated with intense, short term disturbances, such as a fire or a drought, that tip the system over a threshold toward an alternate regime.
For example, the risk of a shift to saline soil increases with rising groundwater table levels.
Long-term irrigation, an agricultural driver, gradually brings water levels closer to the soil surface. When water levels rise above about 2m below the water surface, a new feedback in the form of capillary action draws water to the soil surface and deposits salts throughout the topsoil layer, with detrimental impacts on plants (Walker and Salt, 2006). Once the groundwater table is close to the 2m threshold, even a relatively small storm can push the system over the threshold where the new feedbacks are triggered, and lead to salinization of the topsoil.
Regime shifts have varying degrees of reversibility. They are often described in the direction from a less anthropogenically-impacted regime to a more anthropogenically-impacted regime, such as non-saline to salinized agricultural land. In many cases, this is a shift to a more degraded condition. As a result, many regime shifts are associated with negative environmental impacts.
However, the concept itself is value-neutral and can apply to shifts where humanity has benefited without significantly compromising ecosystems (Biggs et al., 2012). For example, the
introduction of effective pesticides has resulted in the global suppression of locust plagues with negligible side-impacts (Magor et al., 2008).
Agriculturally-driven regime shifts have substantial impacts on ecosystems, human economies and societies (Gordon et al., 2008; MA, 2003). The frequency of regime shifts and their associated impacts are expected to rise as both agricultural drivers and the frequency of system shocks are increasing as a result of global anthropogenic influence (Carpenter et al., 2001;
Rockström et al., 2009; Tilman et al., 2001). Much current research on regime shifts therefore focuses on improving knowledge of underlying ecological dynamics to better inform
environmental management and policy to prevent, avoid, precipitate or reverse regime shifts (Biggs et al., 2009; Brock et al., 2005; Lenton et al., 2007; Scheffer et al., 2009b). This study focuses on the impacts of regime shifts on ecosystems and people. Such knowledge can enable a more informed assessment of the potential risks, benefits and costs associated with regime shifts.
It can also draw policy attention to societal groups that benefit from or are particularly vulnerable to the impacts of particular regime shifts.
Major challenges to evaluating impacts of regime shifts are that they span various types and scales of ecosystem types and temporal scales (Gordon et al., 2008), that the relative condition of
alternate regimes are difficult to quantify, and that regime shifts have differential impacts across different sectors of society (Carpenter, 2003; Walker et al., 2010). In order to address these challenges, this study builds on the framework developed by the Millennium Ecosystem
Assessment (MA) for assessing the condition of ecosystems and their impacts on human society.
This framework provides a classification of the benefits that humans extract from ecosystems (ecosystem services) and the requirements humans have to live a good life (human well-being).
These indices provide a relatively simple, clear means for assessing the condition of a social- ecological system, and as such can be used to compare ecosystems services and human well- being levels associated with different system regimes.
The MA divides ecosystem services into four categories: provisioning, regulating, supporting and cultural (MA, 2005). Provisioning services are the products obtained from ecosystems (e.g., food, water), regulating services are the benefits obtained from the regulation of ecosystem processes (e.g., climate regulation), cultural services are the non-material benefits people obtain from ecosystems (e.g. hiking), and supporting services are the ecosystem processes that underlie the other three categories (e.g, soil formation). In agricultural ecosystems, examples of
provisioning services are crops, of regulating are the climate regulation, of cultural are heritage sites, and of supporting are nutrient cycling. Ecosystem services across categories often cluster into distinct bundles depending on the management situation (Raudsepp-Hearne et al., 2010a).
Similarly, human well-being is a multifaceted concept and includes nutrition, health, security, livelihood, and good social relations. Freedom of choice underlies human well-being, which may be experienced and perceived differentially, depending on culture, situation, geography and ecological circumstances. Human well-being is at the same time distinct from and dependent on ecosystem services (MA 2005). For example, food crops are considered to be a provisioning ecosystem service in that ecosystems have varying degrees of potential to produce crops.
Meanwhile, food nutrition is an indicator of human well-being, as it describes the social process whereby food produced by ecosystems is converted into human nutrition.
In general, agro-ecosystems are managed for the provisioning of food, fiber and bio-energy, often at the expense of the other categories of ecosystem services. Many studies have shown that
enhancing provisioning services leads to declines in regulating and cultural services (Bennett et al., 2009; Raudsepp-Hearne et al., 2010a; Rodriguez et al., 2006) When trade-offs are taken into account, the net benefits of improvements to provisioning services are often smaller than initially believed (MA, 2005). To counter trade-offs, environmental managers look for synergies - actions intended to create win-win situations that conserve ecosystem services across multiple categories (Foley et al., 2011; Pretty et al., 2006; Swinton et al., 2007; Tallis et al., 2008).
Positive synergies often occur between regulating, cultural and supporting services, and with biodiversity conservation.
Although measuring ecosystem services and human well-being offers a good representation of the condition of a social-ecological system as a whole, it does not take into account the unequal distribution of the benefits and costs to different societal groups. Different groups rely on different ecosystem services to different extents (Engel et al., 2008). Therefore, when
anthropogenic modifications lead to trade-offs between ecosystem services, these impacts are felt differentially between groups, creating winners and losers (Crépin et al., in prep). Areas with high levels of poverty are particularly vulnerable to ecosystem change because people lack protection from natural hazards and are highly dependent on agriculture, grazing and hunting for their livelihoods (Carpenter et al., 2009; MA, 2005). It has recently been suggested that
researchers disaggregate poor stakeholders from the rest of society to account for the unequal distribution of resources, and to improve relevance of research to poverty alleviation (Daw et al., 2011).
This study presents an innovative method to evaluate the impacts of regime shifts on social- ecological systems, using ecosystem services and human well-being as indicators. It also undertakes a novel exploration of the impacts of agriculturally-driven regime shifts on iconic users of ecosystem services. In doing so this study aim to address the following two research questions:
Q1. How do agriculturally-driven regime shifts impact ecosystem services and human well- being?
Q2. How are different user groups impacted by agriculturally-driven regime shifts?
METHODS
A simple, adaptable coding system was developed to qualitatively evaluate the impacts of regime shifts on ecosystem services and human well-being, based on peer-reviewed literature. Data was then analyzed quantitatively to compare the distribution of impacts across regime shifts, as well as the relative difference in ecosystem service availability in alternate regimes. Finally, six major categories of users of ecosystem services were defined to explore the differential impact of regime shifts on user groups.
Choice of ecosystem services and human well-being indices for analysis
The Regime Shifts Database (www.regimeshifts.org) was the primary data source for identifying agriculturally-driven regime shifts that impact ecosystem services and human well-being. The database provides examples of different types of regime shifts that have been documented in social-ecological systems. The information in the database is based on an assessment and synthesis of the literature, and most of the entries have been reviewed by experts. Twelve regime shifts were selected for this study (Table 1). The criteria used to select regime shifts are that they are driven by agricultural activities, that they impact ecosystem services, and that feedbacks can be identified that keep the system in each alternative regime.
The Regime Shifts Database was used to extract a brief overview of the impacts of these regime shifts on ecosystem services. Further literature searches were conducted to gain a deeper insight into a wider range of impacts, as well as to confirm the findings in the database. To conduct the literature search, keywords including a regime shift title and ecosystem service or human well- being index, for example “eutrophication, water purification” were entered into google scholar.
Search results were then filtered for breadth of evidence, date of publication and number of citations. At least two recent, peer-reviewed journal articles were identified to support the relationship between each regime shift and its impact on ecosystem services and human well- being. A suite 18 of ecosystem services and 6 human wellbeing indices were chosen for
investigation across the 12 regime shifts (Table 2). Focus was placed on ecosystem services that are present in agro-ecosystems or impacted by agricultural drivers.
Q1. Impacts of agriculturally-driven regime shifts on ecosystem services and human well-being
A scoring system was developed for categorizing the impacts of regime shifts on ecosystem services and human wellbeing. First, ecosystem services were categorized as either inside or outside the regime shift system boundaries (Table 1). Next, ecosystem services that are present within the system boundaries were evaluated for whether or not they are directly impacted by the regime shift. Last, ecosystem services which were determined to be directly impacted were evaluated for being impacted positively, negatively or both for each regime shift.
The boundaries of the system impacted by each of the regime shifts were defined in order to determine which ecosystem services are present within those boundaries (Table 1). For example, fisheries are included as an ecosystem service for the shift from normoxic to hypoxic coast, but are excluded for the shift from forest to savanna because the boundaries of “forest” or “savanna”
do not include aquatic systems where fisheries exist. For terrestrial regime shifts, the spatial boundary is the landscape. A landscape comprises the visible features of an area of land, including landforms, bodies of water, vegetation cover and climate. The spatial scale varies for the aquatic regime shifts. For the shift from normoxic to hypoxic coast, the boundary is larger, encompassing regional or even subcontinental areas. For the shift from a clear to eutrophic lake, the boundary includes the lake as well as the surrounding cropland landscape. For the shift from submerged to floating plants, the spatial boundary is limited to the lake or pond in question.
Next, the ecosystem services present within the boundaries for each system were determined to identify those that were directly impacted by the regime shift. For an ecosystem service to be considered directly impacted, the regime shift had to result in a direct increase or decrease or both of the ecosystem service. For example, pollinators are present within the landscape boundaries of the shift from a clear to eutrophic lake, but they are not directly impacted by this shift. Perhaps breeding grounds of some pollinators may be impacted, but this is not
generalizable. Water purification would be a more directly impacted regulating service for this regime shift.
Directly impacted ecosystem services were scored according to the impact regime shifts have on ecosystem service amount, availability or potential. For example, the amount of fish is directly impacted by hypoxic conditions, the availability of recreation activities are directly impacted by bush encroachment, and the potential for hydropower is directly impacted by a shift in river channel position. Impacts were scored as an increase, a decrease, or both an increase and decrease in ecosystem services (Table 3). Plus/minus scores usually applied to sub-sections of an ecosystem service where one component increases while the other decreases. For example, in the shift from forest to cropland, the livelihoods category of human well-being both increases due to increased agriculture, and decreases due to decreased forestry.
Scores were assigned based on information in the Regime Shifts Database and additional literature searches. Scores were then assigned number values as indicated in Table 3. The sum was calculated for each ecosystem service and human well-being category, as well as for the total across all ecosystem service categories. Totals were then normalized from +1 to indicate the most positive possible impact to -1 to indicate the most negative possible impact.
The resulting normalized impact values were assembled in column charts to compare between ecosystem service and human well being categories. They were also assembled into a colour- coded table to present a visual overview of the relative magnitude of impact. Column charts were created to display a break-down of the impacts of each ecosystem service category and human well-being index.
In addition to evaluating the direction and magnitude of impact of regime shifts, a sub-analysis was undertaken to compare the suite of ecosystem services present in alternate regimes. A system of assigning relative value to ecosystem services in alternate regimes was created, as shown in Table 3. Values were assigned to each ecosystem service in the alternate regimes of all 12 regime shifts, and presented as petal charts. The sum of the values within ecosystem service categories and also the total across all three categories was calculated for each alternate regime, normalized between -1 and 1, and compared between categories using scatter plots. The
difference between regimes of the same shift were calculated and presented in a bar chart.
Q2: Impacts of agriculturally-driven regime shifts on user groups
An exploratory analysis was undertaken to assess how different user groups are impacted differentially by agriculturally-driven regime shifts. Six iconic user groups were defined according to the local landscape ecosystem they occupy, their degree of dependence on their local landscape ecosystem for well-being, and their degree of access to social or technological alternatives to ecosystem services (Table 4).
Three broad landscape types were chosen to define the user groups: urban, cultivated and wild.
Each landscape type has a primary user group resident, with additional user groups residing at the interfaces between the landscape types (Figure 1).
To determine which ecosystem services are essential to each user group, they were first assessed for the range of human well-being values they acquire from their local landscape ecosystem (Table 4). The same six human well-being indices in previous analyses were used (nutrition, health, livelihoods, security of housing, cultural values, and security from conflict).
Generalizations were made to account for the majority of the user group population. For example, some urban dwellers derive their livelihoods from the local landscape ecosystem (landscapers, urban gardeners), but the majority do not, therefore urban dwellers’ livelihood was taken as not dependent on their local landscape ecosystem (Table 5).
Next, the human well-being indices acquired from local landscape ecosystems were linked to relevant ecosystem services to identify which ecosystem services were acquired from the local landscape. For example, security of infrastructure is indicated as acquired from the local landscape ecosystem of subsistence farmers. Therefore, the protection of infrastructure against natural disasters is an important ecosystem service acquired from the local landscape ecosystem for subsistence farmers (Table 5).
Finally, ecosystem services that are acquired from the local landscape were confirmed as essential to the user group if no social or technological alternatives to the ecosystem service are available. For example, pollination services are indicated as essential for horticulturists and
subsistence farmers, but not for industrial farmers, even though these user groups may share the same landscape. This is because industrial farmers will often import bees for pollination or grow crops that have been bred to be self-fertile, making insect pollination unnecessary (Table 5).
Many different rationales could be used to define which ecosystem services as are essential to different user groups. The analysis presented here is exploratory, and intended to provide a first analysis of regime shift impacts across several user groups.
Each essential ecosystem service and human well-being index was assigned a value according to how it was impacted by each of the 12 regime shifts. Positively impacted essential ecosystem services were assigned a value of 1, negatively impacted essential ecosystem services were assigned a value of -1, and ecosystem services that were not impacted, outside the system or were impacted both positively and negatively were assigned a value of 0 (Table 3). The sum for all three ecosystem service categories and the human well-being category was calculated, then normalized against the number of services or indices within the category.
Results for total ecosystem services were tabulated and colour-coded separately to visually compare the impact of regime shifts on user groups. The normalized impact value column for total ecosystem services was added to the table for reference. A bar chart was designed to visualize the relative impact of essential ecosystem for each user group.
RESULTS
Key results found were: 1) Ecosystem services and human well-being indices are impacted negatively by nearly all regime shifts; 2) The relative difference in ecosystem service amount between alternate regimes is much larger for regime shifts with more negative impacts than those with positive impacts; and 3) User groups were impacted negatively by nearly all regime shifts, with industrial farmers being impacted least negatively and subsistence farmers being impacted most negatively. These results are discussed in more detail below.
Q1. Impacts of agriculturally-driven regime shifts on ecosystem services and human well-being
Impacts of regime shifts on ecosystem services and human well-being are first presented as a table displaying each score as determined by literature search. Next, the data is summarized in a bar chart showing the distribution of impact types for each ecosystem service across all regime shifts, as well as a compilation of the data into categories and total ecosystem services. A colour-coded figure then presents the relative impact of each regime shift on ecosystem service categories and human well-being. The scores that were adapted according to Table 3 to
represent availability of ecosystem service categories in alternate regimes are displayed as petal charts for individual ecosystem services, and as a bar chart for change in ecosystem service categories. Finally, the relationships between ecosystem service categories in alternate regimes are compared using scatter plots.
Scores for impact of the 12 regime shifts on each ecosystem service and human well-being indices are presented in Table 6. This data serves as a foundation for subsequent analyses.
General findings are that shifts from less to more anthropogenically-impacted regimes led to declines across the vast majority of ecosystem services and human well-being indices, and not simply a change in the set of services or well-being values. Provisioning services tend to increase (13%) or fall outside of system boundaries (26%) more often than other categories, regulating services are more often indirectly impacted than other categories (38%), and nearly all cultural services are impacted negatively by all regime shifts (90%). Most human well-being
indices decrease (67%), though a significant portion both increase and decrease as a result of regime shifts (11%) (Table 6).
The distribution of impact types for ecosystem services, biodiversity and human well-being across all regime shifts from less to more anthropogenically-impacted regimes are presented in Figure 2. Provisioning services that declined the most were freshwater and wild products.
Provisioning services that increased the most were crops and livestock. The provisioning services fisheries, timber and hydropower were found outside the boundaries for many regime shifts. Regulating services that were most negatively impacted were water purification,
regulation of soil erosion and pest regulation. In one regime shift (Locust plagues to outbreaks), the regulating services climate regulation, regulation of soil ersion, pest and disease regulation and natural hazard regulation were enhanced. The regulating services air quality, climate regulation, pollination and natural hazard regulation were usually not impacted directly by regime shifts. Cultural services declined in nearly all regime shifts. Biodiversity was impacted negatively by nearly all regime shifts. The majority of each human well-being index declined, with particularly negative impacts on cultural values and security from conflict. Food and nutrition was found to be enhanced most often, though small increases in livelihood and security from conflict were also noted. Security of infrastructure and health were indirectly impacted by many regime shifts (Figure 2).
Figure 2 also displays columns that aggregate the distribution of impact types across all regime shifts into each ecosystem service category, total human well-being indices, as well as total ecosystem services. From the ecosystem services that were directly impacted, cultural services fared worst at 90% decline, followed by regulating services, of which 88% decline, then
provisioning services, of which 74% decline. Provisioning servies increased in 19% of cases, regulating services increased in 10% of cases cultural services increased in 4% of cases.
Provisioning services both increase and decrease (+/-) in 7% of cases, regulating services both increase and decrease in 2% of cases, and cultural services both increase and decrease in 7 % of cases. Total ecosystem services that were directly impacted decreased in 83 % of cases, increased in 12% of cases, and both increased and decreased in 5 % cases. The distribution of
impact types for total human well-being was similar to total ecosystem services, having 77%
decrease, 10% increase, and 13% both increase and decrease (Figure 2).
A colour-coding system was applied to the relative degree of impacts across ecosystem service categories for each regime shift, as shown in Figure 3. The figure is presented in order of least impacted total ecosystem services to most impacted total ecosystem services, as shown in the left column (Figure 3). The only exception to this order is that the shift from undammed to dammed, which is impacted less than the shift from plagues to outbreaks in absolute value (ie. without taking into account whether the value is positive or negative). The shift from locust plagues to outbreaks was the only regime shift to have positive impacts across all ecosystem service categories and human well-being indices, and for this reason is presented above the shift from undammed to dammed.
Figure 3 highlights that the regime shift locust plagues to outbreaks had more positive and fewer negative impacts on both ecosystem services and human well-being. This shift is an example where the less anthropogenically-impacted regime (infrequent, large scale plagues) is associated with fewer ecosystem services than the more anthropogenically-impacted regime (frequent, small scale outbreaks). The regime shifts from high to low soil organic matter, normal to saline soil, original to new river channel position and vegetated to desert landscape had very negative impacts on both ecosystem services and human well-being. The regime shifts forest to cropland and forest to savanna had significantly fewer negative impacts on human well being and
provisioning services. Each human well-being index was impacted negatively in the shifts from normal to saline soil, original to new river channel and vegetated to desert.
The original impact data in Table 6 was adapted as shown in Table 3 to reflect the suite of ecosystem services available in alternate regimes, and is displayed as petal charts in Figure 4.
This figure shows that regime shifts which lead to enhanced ecosystem services in more
anthropogenically-impacted regimes tend also to have higher numbers of ecosystem services that are not impacted by the shifts, and regime shifts that have enhanced ecosystem services in less anthropogenically-impacted regimes tend to have lower numbers of ecosystem services that are not impacted by the shifts (Figure 4). Provisioning services tend to be enhanced in the more
anthropogenically-impacted regimes of the shifts from plagues to outbreaks, undammed to dammed, forest to savanna and forest to cropland, and enhanced in the less anthropogenically- impacted regimes of the shifts from original to new river channel and vegetated to desert (Figure 4). Regulating services tend to be enhanced in the more anthropogenically-impacted regimes of the shifts from plagues to outbreaks, undammed to dammed river, and grassy to bushy savanna, and enhanced in the less anthropogenically-impacted regimes of the shifts from forest to
savanna, high to low soil organic matter and vegetated to desert. Cultural services recreation and aesthetic value were enhanced in the more anthropogenically-impacted regime of the shift from plagues to outbreaks, and underwent no change in the shift from undammed to dammed. The remaining cultural services were enhanced in the less anthropogenically-impacted regime for all regime shifts, with the exception of spiritual values, which underwent no change in the shift from plagues to outbreaks (Figure 4).
The following ecosystem services tend to decline in more anthropogenically-impacted regimes:
pest and disease regulation, water purification, wild food and products, educational and spiritual (Figure 4). The few ecosystem services that are enhanced in more anthropogenically-impacted regimes are crops, livestock, and hydropower, mainly in the shifts from locust plagues to outbreaks, undammed to dammed river, forest to savanna and forest to cropland (Figure 4).
These increases in provisioning services are associated with declines in pollination and educational values in the shift from undammed to dammed, declines in educational, spiritual, pollination, disease, soil erosion and climate regulation in the shift from undammed to dammed, and declines in all regulating and provisioning services in the shifts from forest to savanna and forest to cropland. Overall enhancements to crops, livestock and hydropower are outweighed by declines in other ecosystem services in all shifts except the shift from locust plagues to outbreaks (Figure 4).
The availability of ecosystem services in alternate regimes were compiled by ecosystem service category, and the difference was calculated between the regimes to show the regime shift impact, as presented Figure 5. In nearly all cases, the shift from less to more anthropogenically-impacted regimes led to either increases or decreases across all three ecosystem service categories
together. The shift from locust plagues to outbreaks increased across all three categories, while
the remainder of the shifts decreased across all three categories. The only exception was the shift from undammed to dammed, where there was an increase in provisioning services, with a decrease in regulating and cultural services. Cultural and provisioning services tend to undergo more change from Regime 1 to Regime 2 than do regulating services. This is likely due to the relatively high number of provisioning services that are indirectly impacted by regime shifts.
The difference in availability of ecosystem service categories between alternate regimes was found to be less for regime shifts with more positive impacts on ecosystem services and more for regime shifts with very negative impacts on ecosystem services (Figure 5). For example, the increase in ecosystem services in the shift from locust plagues to outbreaks is modest, when compared with the declines in ecosystem services in the shifts from normal to saline soil, original to new river channel, high to low soil organic matter and vegetated to desert (Figure 5).
The availability of ecosystem services in alternate regimes, as well as for total ecosystem services and total human well-being, were compared by category and are shown in scatter plots (Figure 6). All combinations of categories compared indicate that regimes tended to cluster with regime 1 being high in both indices and regime 2 low in both indices. Exceptions to this trend were found in regime shifts that were more positively impacted (plagues to outbreak, undammed to dammed). Clustering was found to be stronger when comparing provisioning or regulating services with cultural services than when comparing provisioning services with regulating services (Figures 6a-c), though the strength is attributed a calculation artifact due to cultural services having the same value. There is a relationship when comparing total ecosystem services with human well being (Figure 6d).
A weak, but significant relationship was observed between regulating and provisioning services (Figure 6a) (R2=0.3634, p value=0.0014, n=24), whereby regime 1 tended to be high in both provisioning and regulating services, and regime 2 was low in both provisioning and regulating services. That is to say the 36% of the variation in provisioning services was due to variation in regulating services, and that there is a 0.14% probability that these results could be observed if no relationship existed. An exception to this trend was observed in the shift from plagues to outbreaks, where both provisioning and regulating are lower in regime 1 and higher in regime 2.
Another exception is the shift from undammed to dammed, where regulating services are high in regime 1 and low in regime 2.
Similarly, a decline in provisioning services was associated with a decline in cultural services, while an increase in provisioning services occurred together with an increase in cultural services in most regime shifts (Figure 6b ) (r2=0.5994, p=<0.0001, n=24). Two exceptions were observed; one is the shift from plagues to outbreaks, where both
provisioning and cultural services are lower in regime 1 and higher in regime 2, and the other is the shift from undammed to dammed, where provisioning services are lower in regime 1 and higher in regime 2.
Following suit with the preceding analyses, regulating and cultural services have higher values in regime 1 and lower values in regime 2 (Figure 6c) (R2=0.7779, P=<0.0001, n=24). The exception to this pattern is the shift from plagues to outbreaks, where both provisioning and cultural
services are low in regime 1 and high in regime 2.
A relationship was identified between total ecosystem services and human well-being. Regime 1 tended to be high in both total ecosystem services and human well-being while regime 2 tended to be low in both total ecosystem services and human well-being (Figure 6d) (r2=0.9199, p value=<0.0001, n=24). The only exception was found in the shift from locust plagues to
outbreaks where total ecosystem services and human well-being were low for regime 1 and high for regime 2.
Q2. Impacts of agriculturally-driven regime shifts on user groups
Nearly all user groups were impacted negatively by nearly all regime shifts (Figure 7).
Exceptions were the shift from locust plagues to outbreaks, which positively impacted all groups, and the shift from undammed to dammed rivers, which had a positive impact on horticulturists and neither positive nor negative impacts on industrial farmers and urban dwellers. The strongest possible impact is shown in the right column of Figure 7, as total impact across all
ecosystem services from Figure 3, whereas user impacts are the subset that are essential to eact user group.
The average impact on total ecosystem services over all regime shifts was least negative for industrial farmers and most negative for subsistence farmers. Horticulturists were impacted nearly twice as much as industrial farmers, urban dwellers were impacted over twice as much as industrial farmers, tourists and hunter-gatherers were impacted three times more than industrial farmers, and subsistence farmers were impacted over four times more than industrial farmers (Figure 7).
Disaggregating total ecosystem service impact on user groups into each category shows the same rank order for provisioning and cultural services. However, for regulating services, the
following impact order was observed, from least to most negatively impacted: industrial farmers, urban dwellers and tourists (tie), hunter-gatherers, horticulturists, and subsistence farmers
(Figure 9). Cultural services had relatively large impacts on urban dwellers, tourists, hunter- gatherers and subsistence farmers, whereas regulating services had relatively large impacts on industrial farmers and horticulturists (Figure 8).
DISCUSSION
This study has developed an innovative, adaptable method to evaluate the impacts of
agriculturally-driven regime shifts on ecosystem services and human well-being. It also assessed the impacts of these shifts on different user groups, based on which locally-derived ecosystem services are essential to their well-being.
Q1. Impacts of agriculturally-driven regime shifts on ecosystem services and human well- being
The findings of this study indicate that most shifts from less to more anthropogenically-impacted regimes lead to declines in ecosystem services and human well-being, when considering only the direction (and not the magnitude) of change in individual services (Figure 2). Theoretically, one might expect a more equitable distribution of positive and negative impacts in different regimes, given that they represent different configurations of an ecosystem which are not a priori better or worse (Biggs et al., 2012). However, our results indicate that, when considering only the
direction of change, more anthropogenically-impacted regimes are associated with a general loss across different types of ecosystem services, rather than a different bundle of ecosystem services.
If the magnitude of change for each individual ecosystem service had been taken into account, it would have helped understand whether this general loss of different services was associated with a large increase in specific services (e.g. food production).
Although most shifts from less to more anthropogenically-impacted regimes led to declines in ecosystem services and human well-being, some regime shifts can lead to an increases across these measures, as is demonstrated by the shift from locust plagues to outbreaks (Figure 3). This suggests that not all anthropogenic interventions lead to ecosystem degradation; rather, some can improve ecosystem services and human well-being (Folke et al., 2004; Scheffer and Carpenter, 2003). However, the number of ecosystem services that increase in the shift from locust plagues to outbreaks is substantially less than in regime shifts where ecosystem services and human well- being decrease (Figure 3). This suggests that improvements brought about by human
interventions may generally be much smaller than the negative consequences of human impacts on ecosystems (Ellis, 2011).
Regime shifts which lead to enhanced ecosystem services in more anthropogenically-impacted regimes tend also to have higher numbers of ecosystem services that are not impacted by the shifts, compared with regime shifts that have enhanced ecosystem services in less
anthropogenically-impacted regimes, which tend to have lower numbers of ecosystem services that are not impacted by the shifts (Figure 4). This suggests that improvements brought about by human intervention tend to be focused on a few ecosystem services and do not impact a wide range of ecosystem services (Foley et al., 2005).
In nearly all shifts examined in this study, all categories of ecosystem services increase or decrease together, with no clear trade-offs between categories (Figure 5). It may be that the trade-offs noted in previous work (Bennett et al., 2009; Power, 2010; Rodriguez et al., 2006) arise as a result of changes to magnitude of ecosystem services, which were not accounted for in this study. Another explanation for the lack of trade-offs between ecosystem service categories in this study is that regime shifts could account for lag effects that may not be apparent in
shorter-term studies. Regimes represent the “equilibrium” condition of social-ecological systems either before a shift is initiated or after change has stabilized, and include slow effects that may not be apparent during the shift (Scheffer, 2009a). It is possible that shorter-term studies are looking at ecosystems that are in transition between regimes, where fast responses such as increases in provisioning services and declines in regulating services are observed, but slower responses, such as the impact of the decline in regulating services on provisioning services, have not yet been realized.
Although trade-offs were not identified, it was found that increases in the provisioning services crops and livestock were associated with declines in pollination and the regulation of climate, pests, and soil erosion, as well as with declines across all cultural services (Figure 4). This suggests that these individual services are particularly sensitive to activities associated with crop and livestock production. Declines in wild food and products, water purification, pest and disease regulation, educational and spiritual services were observed across all regime shifts (Figure 4),
suggesting that these services are sensitive to more general anthropogenic interventions (Power, 2010; Swinton et al., 2007).
The distribution of types of regime shift impacts was similar for total ecosystem services and total human well-being indices (Figure 2). This differs from findings of the MA (2003), which suggest that human well-being has increased despite declines in ecosystem services. Some research has found that in addition to the influence of provisioning services and technology on human well-being, time lags separate the impact of declining ecosystem services on human well- being (Raudsepp-Hearne et al., 2010b). The time lags hypothesis described above to explain the lack of trade-offs in ecosystem service categories, may also account for the similarity between impact type distribution in total ecosystem services and total human well-being found in this study. Another explanation for the similarity in distribution of impact types across ecosystem services and human well-being is that some evidence gathered to support relationships between regime shifts and ecosystem services was also applied to relationships between regime shifts in human well-being. These methods were used most notably with the human well-being indices food and nutrition and cultural values.
Q2. Impacts of agriculturally-driven regime shifts on user groups
For each user group, the average impact across all regime shifts showed a decline in total ecosystem services (Figure 7). This differs from literature suggesting that most changes in ecosystem services translate into distinct winners and losers (Daw et al., 2011, Engel et al., 2008). In this study, no clear winners were observed, although some groups were impacted less negatively than other groups. In general, negative impacts on ecosystem services led to negative impacts across all user groups.
Industrial farmers were impacted least negatively by changes to ecosystem services (Figure 7).
This suggests that industrial farmers have relatively less dependence on a diversity of ecosystem services compared to the other user groups. This may help to explain why industrial farmers, whose practices often drive regime shifts, are less inclined to change practices for the sake of
ecosystem services (Rodriguez et al., 2009). If the actual magnitude of change in ecosystem services was considered in this study, it may be that the gains in food production services to industrial farmers outweigh the losses in other ecosystem services, and lead to overall benefits.
Over all ecosystem services, horticulturists were impacted more negatively than industrial farmers, and less negatively than urban dwellers, tourists, hunter-gatherers and subsistence farmers (Figure 7). When only considering regulating services, however, horticulturists were impacted more negatively than industrial farmers, urban dwellers, tourists and hunter-gatherers, and less negatively than subsistence farmers (Figure 8). This suggests that horticulturists are particularly dependent on regulating services, including pollination and pest suppression, which decline in anthropogenically-impacted regimes (Björklund et al., 1999; Ricketts et al., 2008).
The remaining four groups tended to experience stronger negative impacts. Of these four, urban dwellers experienced relatively fewer negative impacts related to provisioning services (Figure 8), mainly because most provisioning services used by urban dwellers are imported from outside their local landscape ecosystem. Surprisingly, two very different groups: tourists and hunter- gatherers, were impacted similarly across all ecosystem service categories (Figure 8). This highlights the importance of wild and cultural services to these two groups. Subsistence farmers experienced the largest declines of all groups, pointing to the strong dependence of this group on both wild and cultivated landscapes (Costanza et al., 1997; DeFries et al., 2004).
Reflection on methods
This work studies a wide range of different ecosystem changes occurring on multiple scales.
Although using multiple ecosystem services paints a broad picture of “before and after” changes that are policy relevant (Turner et al., 2003), there is a risk of being overly-inclusive, and
missing the details that are available through case study (Tallis et al., 2008) or spatial analysis (Raudsepp-Hearne et al., 2010a). This study takes into account the differential impact of regime shifts on different user groups making the results more relevant to poverty alleviation (Daw et
al., 2011), but it does not go so far as to engage stakeholders in participatory research (Reyers et al., 2009) or become embedded in social processes for implementation (Cowling et al., 2008).
This study contributes a simple, innovative method for summarizing qualitative data across different regime shifts and then analyzing the data quantitatively. The concepts used to define ecosystem change and impacts on ecosystems and humans, namely regime shifts, ecosystem services and human well-being, are based on well-established literature, and provide an effective framework for defining spatial and temporal boundaries of ecosystem change and for classifying the benefits people derive from ecosystems and their requirements for living a good life. The method appears to be robust, in that it can be used to analyze data in various ways and result in congruent findings, as shown in ecosystem service availability in alternate regimes.
However, there are some important challenges and weaknesses associated with the method developed in this paper. First, the method assigns each ecosystem service or human well being index equal value, leading to results that show the direction rather than the magnitude of change in ecosystem services or human well-being in each category. If magnitudes had been attached to each ecosystem service, it would for example have been possible to conclude that crops increase by a factor of 7, while pest regulation decreases by a factor of 3 and recreational value decreases by a factor of 2. However, since the direction of change to individual ecosystem services is used without values attached, one can only say that crops increased, pest regulation decreased and recreational value decreased. It then becomes necessary to use ecosystem service categories to draw further conclusions. What then follows is that the number of services in a category
influences the impact outcome. For example, if 3 out of 4 cultural services decline, this category is reduced by 75%, but if 3 out of 7 regulating services decline while others are indirectly
impacted, the category is only reduced by 42.8%. The results in this study therefore relate only to the range or number of different ecosystem services that have declined, and should not be used to draw conclusions about the magnitude of change.
A second challenge of the study was that the literature search yielded either no evidence or weak evidence to support relationships between some regime shift - ecosystem service pairs. This was less of a problem for provisioning services, which are readily quantifiable, than for regulating
and cultural services, which are difficult to quantify. For regulating services, low availability of evidence to support relationships with regime shifts led to a relatively high number of services being scored as indirectly impacted. This was due to the availability of relatively weak evidence, making direct links between regime shifts and many regulating services impossible to establish.
For cultural services, low availability of evidence to support relationships with regime shifts resulted in many services being scored as negatively impacted. Studies that were available supporting relationships between some regime shifts and declines in cultural services were applied across regime shifts with the same system boundaries. Different approaches to
challenges concerning lack of evidence would have impacted results differently. The approach used here led to regulating services being presented as changing less than other categories from one shift to another (Figure 5), and cultural services being presented as strongly negative (Figure 3), with resultant negative skew on total ecosystem services (Figure 3).
Finally it is important to point out that, although effective, the concepts used here attempt to simplify what is inherently complex. Ecosystem services are interconnected, humans do not fit into neat user groups, and the same regime shifts occur in vastly different social-ecological circumstances. Attempts to understand this complexity requires simplification, and the potential consequences of this simplification should be kept in mind when interpreting the results.
Future research directions
This study suggests that, when studying ecosystem change in the form of regime shifts,
ecosystem services tend to be impacted uni-directionally across all categories, without significant trade-offs between categories. These impacts are felt differentially by user groups who depend on different clusters of ecosystem services, with users that contribute more to regime shifts being impacted less by them.
These findings can be challenged or supported by further inquiry. The finding that ecosystem services are generally impacted negatively by shifts from less to more anthropogenically-
impacted regimes could be challenged by assigning estimating the relative magnitude of change
to each ecosystem service. This would better highlight cases where the main change is not a change in the set of services, but rather large changes in quantity of particular services. Findings regarding change in ecosystem services over several regime shifts could then be applied to the user groups to determine whether or not all impacts remain negative over all ecosystem services, and whether the rank of impact between user groups changes or stays the same. In addition, a larger suite of intentional regime shifts similar to the shift from locust plagues to outbreaks should be evaluated to further investigate whether the magnitude of change in shifts that lead to overall increases in ecosystem services is less than the magnitude of change in shifts that lead to overall declines in ecosystem services. User groups could be defined according to the ecosystem services that they require as well as to the degree to which they contribute to ecosystem re- organization to investigate any possible links between users contributing to and being impacted by regime shifts.
The method outlined in this study could be applied to regime shifts in other systems or that are driven by other anthropogenic activities (such as overfishing or clear-cutting). They could also potentially be used to compare ecosystem services in contexts not related to regime shifts, for instance between different ecosystem types or different locations, provided that the system boundaries are well-defined.
For future studies, it would be advisable to take care in choosing ecosystem services for analysis.
Since results are impacted by the direction rather than the magnitude of ecosystem service, the number of ecosystem services should strike a balance between being as close as possible to equal between ecosystem service categories for comparison and having a large number to prevent overrepresentation of a few ecosystem services. It is also important to choose an appropriate suite of ecosystem services, tailored to the social-ecological system that is under investigation.
For example, if the study presented here had included a range of wild services, the impacts would have skewed resulting in hunter-gatherers faring worse than subsistence farmers.
CONCLUSION
This study introduces a method for evaluating the impacts of regime shifts on ecosystem
services, human well-being and ecosystem service user groups. Results suggest that, in the long term, changes in ecosystem services usually co-vary in the same direction, rather than having strong trade-offs between them, as is evident in shorter-term studies. These results suggest that, in addition to balancing ecosystem service trade-offs and seeking synergies between them in the shorter-term, long-term prevention and reversal of regime shifts with negative impacts is of utmost importance. The knowledge provided by this study enables a more informed assessment of the potential costs and benefits associated with regime shifts, and draws attention to societal groups such as subsistence farmers that are especially vulnerable to the impacts of regime shifts.
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TABLES & FIGURES
Table 1. Regime shifts selected for investigation, with alternate regimes and system boundary descriptions.
Regime Shift Regime 1 (less
anthropogenically impacted regime)
Regime 2 (more anthropogenically impacted regime)
System Boundary
Forest to Cropland Forest-dominated
landscape
Cropland- dominated landscape
Landscape
Normal Salinity to Saline Soil Vegetated landscape with non-saline topsoil
Landscape with unproductive saline soil
Landscape
Locust Plagues to Locust Outbreaks Occasional large locust plagues
Frequent small locust outbreaks
Landscape
Undammed to Large Dammed Rivers Unaltered river hydrology
Altered river hydrology
Landscape + human communities Clear to Eutrophic Lake Clear water, high
O2
High algae, low O2 Lake +
surrounding farms Normoxic to Hypoxic Coast Normal sea life on
coast
Oceanic dead zones
Regional- Subcontinental Grassy to Bushy Savanna Intact Grassland Bushy savanna,
high soil erosion
Landscape
Forest to Savanna Forest landscape Savanna
landscape
Landscape
Vegetated to Desert Landscape Vegetated landscape
Desert landscape Landscape
Original to New River Channel Position
Original channel position
New channel position
Landscape + human communities Submerged Plants to Floating Plants Submerged plants
dominate, clear water
Floating plants, poor light penetration
Individual bodies of water
High Soil Organic Matter to Low SOM Productive cropland
Unproductive cropland
Landscape
Table 2. Ecosystem services and human well-being indices chosen for analysis, adapted from the Millennium Ecosystem Assessment.
Ecosystem Service Description
Provisioning Services Freshwater Quantity / Accessibility
Freshwater Crop Yield / Ability of landscape to produce crops Crops Livestock Yield / Ability of landscape to support livestock Livestock Fishery Yield / Ability of aquatic ecosystem to support fisheries Fisheries Wild Product Yield / Ability of ecosystem to support Wild Life Wild products Timber or Woodfuel Yield / Ability of Ecosystem to support
timber
Hydropower Quantity of Hydropower / Presence of waterway suitable for dam Regulating Services Benefits Obtained Through Regulation of Ecosystem Processes Air Quality regulation Increase in ecosystem factors that promote air quality / decrease
in factors that reduce air quality
Climate regulation Increase in ecosystem factors that promote stable climate / decrease in factors that reduce climate stability
Water purification Increase in ecosystem factors that promote clean water/
decrease in factors that reduce water purity
Soil erosion regulation Increase in ecosystem factors that promote soil quality / decrease in factors that promote soil erosion
Pest and disease regulation Increase in ecosystem factors that control pests and diseases / decrease in factors that support pests and diseases
Pollination Increase in ecosystem factors that support pollinators / decrease in factors that threaten pollinators
Natural hazard regulation Increase in ecosystem factors that protect against natural hazards/ decrease in factors that increase vulnerability to natural hazards
Cultural Services Non-Material Benefits Humans Obtain from Ecosystems Recreation Suitability / Accessibility of Ecosystem for Human Leisure
Activities
Aesthetic Natural Beauty of Ecosystems
Spiritual and inspirational Ecosystems regarded as sacred, inspire human reflection or connection with nature
Cognitive and educational Ecosystem qualities that underlie human knowledge systems Human Well-being Indices Requirements for a Good Life
Food and Nutrition Availability / Affordability of Nutritious Food
Health Availability / Affordability of Protection from and Treatment for Disease
Security of Infrastructure Availability / Affordability of Adequate Housing and Infrastructure Livelihoods Sufficient Economic Activity to Support Individual Freedom Cultural values Freedom to Enjoy Life through Recreation, Reflection, Education Security from conflict Personal Security and Good Social Relations
Table 3. Scoring system used to evaluate impacts of regime shifts on ecosystem services and human well-being, relative value of ecosystem services in alternate regimes, and ecosystem services essential to user groups.
Ecosystem Service Status
Score Symbol
Regime Shift Value
Regime 1 Value
Regime 2 Value
Essential for User Group
Outside the system out 0 0 0 0
Not impacted directly ind 0 0 0 0
Increase + 1 -1 1 1
Decrease - -1 1 -1 -1
Both increase and decrease
+/- 0 0 0 0
