By Alma Mendoza, Colosio Fellow with the IIASA Ecosystems Services and Management Program
Changes in land use cover can have a crucial impact on the environment in terms of biodiversity and the benefits that ecosystems provide to people. Assessing, quantifying, and identifying where these changes are the most drastic is especially important in countries that have high biodiversity along with high rates of natural vegetation loss. Socioeconomic pressures often drive land use change and the impacts are expected to increase due to population growth and climate change.
To better understand the possible impacts of land use change in Mexico over the short, medium, and long term, my colleagues and I used the Shared Socioeconomic Pathways–a set of pathways that span a wide range of feasible future developments in areas such as agriculture, population, and the economy–together with a set of climatic scenarios known as the Representative Concentration Pathways. We focused on Mexico, because the country is large enough to encompass different ecosystems, socioeconomic characteristics, and climates. In addition, Mexico is characterized by high deforestation rates, huge biodiversity, and a large number of communities with contrasting land management practices. Incorporating all these features, allowed us to take the complexity of socioecological systems into account.
We designed a model to test how socioeconomic and biophysical drivers, like slope or altitude, may unfold under different scenarios and affect land use. Our model includes 13 categories of which eight represent the most important ecosystems in Mexico (temperate forests, cloud forests, mangroves, scrublands, tropical evergreen and -dry forests, natural grasslands, and other vegetation such as desert ecosystems or natural palms), four represent anthropogenic uses (pasture, rainfed and irrigated agriculture, and human settlements), and one constitutes barren lands. We set two plausible scenarios: “Business as usual” and an optimistic scenario called the “green scenario”. We projected the “business as usual” scenario using medium rates of vegetation loss based on historical trends and combined it with a medium population and economic growth with medium increases in climatic conditions. For the “green scenario”, we projected the lowest rates of native vegetation loss and the highest rates of native vegetation recovery with a low population and medium economic growth in a future with low climatic changes.
Our results show that natural vegetation will undergo significant reductions in Mexico and that different types of vegetation will be affected differently. Tropical dry and evergreen forests, followed by ‘other’ vegetation and cloud forests are the most vulnerable ecosystems in the country. For example, according to the “business as usual” scenario, tropical dry forests might decrease in extent by 47% by the end of the century. This is extremely important considering that the most recent rates, for the period 2007 to 2011, were even higher than the medium rates we used in this scenario. In contrast, the “green scenario” allowed us to see that, with feasible changes of rate, this ecosystem could increase their distribution. However, even 80 years of regeneration would not be enough to reach the extent these forests had in 1985, when they accounted for around 12% of land cover in Mexico. Moreover, the expansion of anthropogenic land cover (such as agriculture, pastures, and human settlements) might reach 37% of land cover in the country by 2050 and 43% by 2100 under the same scenario. In terms of CO2 emissions due to land use cover change we found that Mexico was responsible for 1-2% of global emissions that are the result of land use cover change, but by 2100 it could account for as much as 5%.
Our findings show that conservation policies have not been effective enough to avoid land use cover change, especially in tropical evergreen forests and drier ecosystems such as tropical dry forests, natural grasslands, and other vegetation. Cloud forests have also been badly affected. As a biologically and culturally rich country, Mexico is responsible for maintaining its diversity by implementing a sustainable and intelligent management of its territory.
Our study identified hotspots of land use change that can help to prioritize areas for improving environmental performance. Our project is currently linking the hotspots of change with the most threatened and endemic species of Mexican terrestrial vertebrates (mammals, amphibians, reptiles, and birds) to provide useful results that can help prioritize ecosystems, species, or municipalities in Mexico.
Mendoza Ponce A, Corona-Núñez R, Kraxner F, Leduc S, & Patrizio P (2018). Identifying effects of land use cover changes and climate change on terrestrial ecosystems and carbon stocks in Mexico. Global Environmental Change 53: 12-23. [pure.iiasa.ac.at/15462]
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Marcia MacNeil, Blogger at the International Food Policy Research Institute (IFPRI), on a new comprehensive review by IFPRI and IIASA researchers
The world’s agricultural monitoring systems provide up-to-date information on food production to decision makers that is crucial to global and national food security. When prices become dangerously volatile—as they did during the food price crisis of 2007-2011—these systems spread critical information quickly that can reduce the risks of market and supply upheavals.
Monitoring is now better than ever, with improved access to the latest high-resolution satellite imagery and remote-sensing based products. But fundamental gaps remain, and no system currently provides the quantitative crop area and production forecasts ideally needed for food security interventions, according to a comprehensive review by experts including IFPRI Senior Research Fellow Liangzhi You, and led by IIASA researchers in the Ecosystems Services and Management Program
Using questionnaires and discussions with monitoring systems staff, the study measured the gaps in input data and models used, outputs produced, the role of the analysts, interaction with other systems, and the geographical scale at which the systems operate.
Figure 1. Agricultural Systems. Comparison of global and regional scale agricultural monitoring systems in terms of number of sources of input data used.
They found that although each system is tailored to meet the needs of different customers, there are many similarities between the systems. For example, nearly all the reviewed systems reported that cropland maps, crop calendars, and meteorological data were their most important sources.
The most glaring gaps among the systems were found in the data used for crop calendars and crop type maps.
Crop calendars list planting and harvesting dates for the crop types in a particular area. This information is key for keeping tabs on crop conditions, estimating farming area, forecasting yields, and more. It’s used to make decisions to mobilize food aid and move commodities to market, reducing food waste. But this data comes in many different, at-times incompatible forms.
Some data comes from household surveys and censuses, some from expert opinions, and some from satellites. This lack of consistent, validated data results in poor representation of geographic diversity and variability in location and timing in sowing and harvesting dates. Maps of crop types, another important source of data for monitoring systems, suffer from a similar lack of consistent data.
The world’s crop monitoring systems would benefit from greater data sharing, the study concludes—such as a shared repository of datasets. Opportunities for more precise data collection abound. The rapid rise in the use of smart phones and social media, even in once-inaccessible rural areas, offers opportunities for farmers to self-report geo-located crops and information such as planting dates, fertilizer application, irrigation, and expected yields.
Climate change raises the risks to crop production, and these monitoring systems are increasingly critical for decision making and early warning to head off future food crises. More, and better high-quality data will help ensure they can quickly and accurately produce potentially life-saving information.
Figure 2. An image from the USAID Famine Early Warning Systems Network (FEWS NET) shows areas of acute near-term food insecurity. Such systems are crucial to monitoring and responding to potential food crises, but gaps remain, particularly for certain crops.
by Rastislav Skalsky, Ecosystems Services and Management Program, International Institute for Applied Systems Analysis
As growers, we know soil is important. It supports plants, and provides nutrients and water for them to grow. But do we all appreciate how crucial the role of soil is in continuously supplying plants with water, even when it hasn’t rained for a few days or even weeks, even without extra water being added via watering?
Soil is like a sponge. It can retain rain water and, if it is not taken up by plants, soil can store it for a long time. We can feel the water in soil as soil moisture. Try it — take and hold a lump (clod) of soil — if it is wet it will leave a spot on your palm. If it’s only moist then it will feel cold — cooler than the air around. And if the soil is dry, it will feel a little warm.
Soil moisture not only can be felt, but it can also be measured — in the lab, or directly in the field with professional or low-cost soil moisture sensors.
Soil moisture in general indicates how much water is contained by the soil. But it is not always the case that soil which feels moist or wet is able to support plants. It could happen that, despite feeling moist, the soil simply does not hold enough water, or holds the water too tightly for the plants to extract it. Or the opposite, soil can sometimes contain too much water. To understand how this works, one has to learn more about how water is stored in the soil.
Water is bound to soil by physical forces. Some forces are too weak to hold water in the plant root zone and water percolates to deeper layers, where plants can no longer reach it. Other forces can be too strong, preventing water from being retrieved by the roots.
If soil moisture is measured at one place over time, it can reveal its seasonal dynamics. Having estimated important soil water content thresholds (FS — full saturation, FC — field capacity, PDA — point of decreased availability, and WP — wilting point) for that particular site, e.g. based on soil texture test or measurement, one can easily interpret if the measured soil moisture and say if there was enough water or not to fully support plants with water and air. In this particular case of sandy 0–30 cm deep topsoil from Slovakia, it was never wet enough to cause oxygen stress for plants, — in fact it never reached state of all capillary voids filled with water (FC). On the other hand, each summer the topsoil moisture dropped below the point of decreased availability (PDA), even got close to the wilting point or went through (WP), which means that during those periods plants suffered drought conditions.
Thresholds In order to describe this behavior in more useful terms, plant ecologists and soil hydrologists came up with couple of important soil water content thresholds (Figure 1). These thresholds, also called “soil moisture ecological intervals”, define how easily plants can get the water out of the soil.
We speak about full saturation of soil when all empty spaces (pores/voids) are completely filled with water. Full saturation of the soil with water prevents air entering into the soil. Yet there is no force holding water in the soil. Roots need air as well as water so, if this situation continues, it eventually causes oxygen stress for most of the common plants because roots simply cannot breathe.
Soil also has different types of pores. Larger ones, which are called “gravitational pores”, are filled with water only when the soil is saturated and otherwise drains freely, and smaller ones called “capillary pores” which are small enough in size to prevent water from percolating down the soil profile by gravitation. These smaller pores can hold water even in well-drained soils and make it available for plants to extract. There are also even smaller pores where the water is held so tightly that plants cannot extract it.
When all gravitational pores/voids are empty of water and it is present only in so called capillary pores/void we speak about the field water capacity — which is considered to be the best soil moisture status of the soil — enabling plants to retrieve the water they need, whilst leaving enough air for roots to breathe. If no new water is added into the soil, the soil dries as water is used by plants or evaporates. As soil dries less water is available to plants until the point of decreased availability when water remains only in the smallest capillary pores/voids. But this water is bound to soil particles so strongly that most plants are not able to extract it suffer from drought. Ultimately, all the available water is used up by plants, and the remaining water is inaccessible. Soil reaches the so-called wilting point and water is not available for the plants anymore. Plants permanently wilt and eventually die.
How Soil Characteristics Relate to Moisture The tricky thing with soil moisture however is that the same amount of water (volumetric percent of the total soil column volume) can, in different soils, represent different amount of water available for plants. How big this difference could be is defined by many soil characteristics.
The most important is the soil texture — a blend of all fine-earth soil mineral constituents (sand, silt, clay) and stones in various rates. In general, the finer the texture is (i.e. more clay, less sand) the more water is bound in the soil too tightly to be retrieved by plants. Even if the soil feels moist, plants can permanently wilt in clay soils. In contrast, those soils with coarse texture (i.e. more sand, less clay) can support plants with nearly all the water they can hold. Although the soil looks dry, plants can still effectively take the water out of it. The drawback here is that in coarse textured, sandy, soil nearly all water drains down the gravitational pores and therefore such a soil cannot support plants for very long time. That is also why medium textured soils (loam, silty loam, clay loam) are considered best for holding and providing the water for plants. Medium textured soils can effectively drain excess water, yet hold much water in capillary pores/voids for a long time, and still, only a relatively small amount of water remains unavailable for the plants.
A practical implication of this behavior of soil with different soil texture could be that one has to apply slightly different strategies to maintain soil moisture in the way that it can effectively supply plants with water. Sandy soils will require more frequent watering with smaller amount of water. It would not make any practical sense to try build-up a storage of water in these soils. All extra water added will simply drain out of the topsoil. Clay rich soils can absorb big amounts of water but a lot is bounded too strongly to the soil particles and thus not available for the plants. Therefore one should water even if the soil looks moist or wet — and if dry a lot of water must be added to recharge the topsoil so that it can support plants effectively. With loamy soils it is possible to be more relaxed with watering frequency, simply because one can build solid storage of water in such soils. Adding a bit more water than is necessary is perfectly fine with these soils because the water is effectively kept in the soil profile and it can be used later on.
Interested in learning more? Why not sign up for GROW Observatory’s next free online course – Citizen Research: From Data to Action – to discover how citizen-generated data on soils, food and a changing climate can create positive change in the world. Starts 5th November.
By Marcus Thomson, researcher, IIASA Ecosystems Services and Management Program
While living in Cairo in 2010, I witnessed first-hand the human toll of political and environmental disasters that washed over Africa at the end of the last century. Unprecedented numbers of migrants were pressing into North Africa, many pushed out of their homelands by conflict and state-failure, pulled towards safer, richer, less fragile places like Europe. Throughout Sub-Saharan Africa, climate change was driving up competition for scarce land and water, and raising pressure on farmers to maintain the quantity and quality of their crops.
It is a similar story throughout the developing world, where many farmers do without the use of expensive chemical fertilizer and pesticides, complex irrigation, or boutique seed varieties. They rely instead on traditional land management practices that developed over long periods with consistent, predictable conditions. It is difficult to predict how dryland farmers will respond to climate change; so it is challenging to plan for various social, economic, and political problems expected to develop under, or be exacerbated by, climate change. Will it spur innovation or, as has been argued for the Syrian civil war, set up conflict? A major stumbling block is that the dynamics of human social behavior are so difficult to model.
Instead of attempting to predict farmers’ responses to climate change by modelling human behavior, we can look to the responses to environmental changes of farmers from the past as analogues for many subsistence farmers of the future. Methods to fill in historical gaps, and reconstruct the prehistoric record, are valuable because they expand the set of observed cases of societal-scale responses to environmental change. For instance, some 2000 years ago, an expansive maize-growing cultural complex, the Ancestral Puebloans (APs), was well established in the arid American Southwest. By AD 1000, members of this AP complex produced unique and innovative material culture including the famed “Great Houses”, the largest built structures in the United States until the 19th century. However, between AD 1150 and 1350, there was a profound demographic transformation throughout the Southwest linked to climate change. We now know that many APs migrated elsewhere. As a PhD student at the University of California, Los Angeles, I wondered whether a shift to cooler, more variable conditions of the “Little Ice Age” (LIA, roughly AD 1300 to 1850) was linked to the production of their staple crop, maize.
I came to IIASA as a YSSP in 2016 to collaborate with crop modelers on this question, and our work has just been published in the journal Quaternary International. I brought with me high-resolution data from a state-of-the-art climate model to drive the crop simulations, and AP site information collected by archaeologists. Because AP maize was quite different from modern corn, I worked with IIASA soil scientist Juraj Balkovič to modify the crop simulator with parameters derived from heirloom varieties still grown by indigenous peoples in the Southwest. I and IIASA economic geographer Tamás Krisztin developed a statistical technique to analyze the dynamical relationship between AP site occupation and simulated yield outcomes.
We found that for the most climate-stressed high-elevation sites, abandonments were most associated with increased year-to-year yield variability; and for the least stressed low-elevation and well-watered sites, abandonment was more likely due to endogenous stressors, such as soil degradation and population pressure. Crucially, we found that across all regions, populations peaked during periods of the most stable year-to-year crop yields, even though these were also relatively warm and dry periods. In short, we found that AP maize farmers adapted well to gradually rising temperatures and drought, during the MCA, but failed to adapt to increased climate variability after ~AD 1150, during the LIA. Because increased variability is one of the near certainties for dryland farming zones under global warming, the AP experience offers a cautionary example of the limits of low-technology adaptation to climate change, a business-as-usual direction for many sub-Saharan dryland farmers.
This is a lesson from the past that policymakers might take note of.
 Kelley, C. P., Mohtadi, S., Cane, M. A., Seager, R., & Kushnir, Y. (2015). Climate change in the Fertile Crescent and implications of the recent Syrian drought. Proceedings of the National Academy of Sciences, 201421533.
 Thomson, M. J., Balkovič, J., Krisztin, T., MacDonald, G. M. (2018). Simulated crop yield for Zea mays for Fremont Ancestral Puebloan sites in Utah between 850-1499 CE based on temperature dailies from a statistically downscaled climate model. Quaternary International. https://doi.org/10.1016/j.quaint.2018.09.031
by Melina Filzinger, IIASA Science Communication Fellow
Ecosystems worldwide are changed by the influence of humans, often leading to the extinction of species, for example due to climate change or loss of natural habitat. But it doesn’t stop there: as the different species in an ecosystem feed on each other and are thereby interconnected, the loss of one species might lead to the extinction of others, which can even destabilize the whole system. “In nature, everything is connected in a complex way, so at first glance you cannot be sure what will happen if one species disappears from an ecosystem,” says IIASA postdoc Mateusz Iskrzyński.
This is why the IIASA Evolution and Ecology (EEP) and Advanced Systems Analysis (ASA) programs are employing food-web modeling to find out which properties make ecosystems particularly vulnerable to species extinction. Food webs are stylized networks that represent the feeding relationships in an ecosystem. Their nodes are given by species or groups of species, and their links indicate how biomass cycles through the system by means of eating and being eaten. “This type of network analysis has a surprising power to uncover general patterns in complex relationships,” explains Iskrzyński.
Every one of these food webs is the result of years of intense research that involves both data collection to assess the abundance of species in an area, and reconstructing the links of the network from existing knowledge about the diets of different species. The largest of the currently available webs contain about 100 nodes and 1,000 weighted links. Here, “weighted” means that each link is characterized by the biomass flow between the nodes it connects.
Usually, food webs are published and considered individually, but recently efforts have been stepped up to collect them and analyze them together. Now, the ASA and EEP programs have collected 220 food webs from all over the world in the largest database assembled so far. This involved unifying the parametrization of the data and reconstructing missing links.
The researchers use this database to find out how different ecosystems react to the ongoing human-made species loss, and which ones are most at risk. This is done by removing a single node from a food web, which corresponds to the extinction of one group of species, and modeling how the populations of the remaining species change as a result. The main question is how these changes in the food web depend on its structural properties, like its size and the degree of connectedness between the nodes.
From the preliminary results obtained so far, it seems that small and highly connected food webs are particularly vulnerable to the indirect effects of species extinction. This means that in these webs the extinction of one species is especially likely to lead to large disruptive change affecting many other organisms. “Understanding the factors that cause such high vulnerability is crucial for the sustainable management and conservation of ecosystems,” says Iskrzyński. He hopes that this research will encourage more, and more precise, empirical ecosystems studies, as reliable data is still missing from many places in the world.
As a next step, the scientists in the two programs are planning to understand which factors determine the impact that the disappearance of a particular group of organisms has. They are going to make the software they use for their simulations publicly available, together with the database they developed.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
By Sandra Ortellado, 2018 Science Communication Fellow
China is the world’s biggest producer of both wild and farmed fish, yet the massive commercial fishing industry threatens thousands of years of tradition in ocean and freshwater fishing, as well as the livelihoods of coastal fishing communities.
In the past decade, some coastal ecosystems and environments have been destroyed and polluted in the process of industrialization. Millions of tons of fish are caught in Chinese territorial waters each year, such that overfishing of high value commercial species has led to a drastic decline of some native fisheries resources and species.
In response, the Chinese government released a five-year plan for protecting marine ecosystems and restoring wild capture fisheries. The plan promotes an agenda of “ecocivilization,” which emphasizes land–sea coordination, green development, and social–ecological balance.
It also calls for the introduction of additional output control measures, which directly limit the amount of fish coming out of a fishery. Existing input control measures restrict the intensity of gear used to catch fish, but they may not be sufficient to protect ecosystems.
Yi Huang, a member of this year’s YSSP cohort, has made it her goal to figure out how social ecological balance can be achieved even as fishery regulations shift towards increased input and output control.
Given the size of China’s fishing industry, large scale change requires the abstract concepts of “ecocivilization” to be translated into action, compliance, and enforcement at the local level. That means engaging with individual fishers, their communities, and their way of life, says Huang.
“If you want to control overfishing; the object of fishery management policy are fishers. So you need to understand human behavior to help you control overfishing.”
Huang’s project investigates how changes in fishery management will affect demographic, geographic, and socioeconomic trends in the Chinese fisher population. With the guidance of her supervisors, she’s also developing a bioeconomic model to analyze how output control measures like catch limits will affect ecological and socioeconomic conditions.
“I just want to figure out how to improve enforcement of this kind of policy and see if we can use it to solve the overfishing problem at the same time as giving those in the fishing industry a better life,” says Huang.
Current input control measures like licensing systems, vessel buyback programs, closed seasons, restricted areas, and fisher relocation programs are meant to discourage overfishing and transition towards more sustainable practices. Nevertheless, a decline in fishing vessels and restricted fishing seasons only resulted in an increase in total vessel engine power and large spikes in fishing activity just prior to the closed season.
According to the Chinese fishery statistical yearbook, the number of people employed in the fishing industry proliferated to 13.8 million in 2016, so in recent years the government has issued subsidies encouraging fishers not to fish in the off-season and to change vocation. Older fishers are hesitant to abandon an identity that has been passed down from generation to generation in their families. However, younger generations with access to higher education are lured by the prospect of more stable work outside of their fishing communities, which could really change the socioeconomic and demographic structure of coastal villages.
With the potential for increased output controls to incur drastic changes in coastal communities, it’s more important than ever that regulations are carefully designed with both socioeconomic and ecological factors in mind.
Huang hopes her research will help inform the process of policy development, which involves balancing the needs of both vulnerable fisheries labor and delicate ecosystems.
“When policymakers want to use output control in fishery management, maybe they will think more about the fisher or the socioeconomic aspect of the resolution,” says Huang.
“My research is at the national level, but when they design a regulation it’s at the local level, so my research can teach them how socioeconomic surveys at the local level can be used together with ecological research when they are preparing for regulations.”
Huang, who studied sociology at the Ocean University of China before starting as a PhD student in Marine Affairs at Xiamen University, has spent the past ten years researching coastal fishing communities. She has a deep fondness for the people she surveyed, who welcomed her into their homes and showed her the beauty of the environment that sustained them.
“I want to protect the ocean and the people that connect with it,” says Huang.
A sociological perspective has given Huang an eye for nuance and an appreciation for things that don’t turn out quite how you expect, as they often don’t in scientific research—especially when it attempts to explain human behavior.
For example, Huang says that although fishers may look like countryside people, they act very differently from farmers.
“The ocean has a lot more risk involved than planting on land,” explains Huang.
Because Chinese fishery regulation is currently focused almost exclusively on analyzing resources from an ecological perspective, she thinks sociology and anthropology research could add another revealing dimension to the approach.
“After doing surveys and analyzing the data, I will find maybe I’m wrong or maybe there is something more. That’s why I’m really interested in this kind of research,” says Huang.
As her research project develops, Huang says she’s grateful for the feedback of her supervisors and peers at IIASA, who both challenge and encourage her.
“Even when they have some critical comments on my research, I feel more confident that my research is meaningful, that they support me, and that they’re really interested in my research,” says Huang. “That’s what I can feel every day.”