How Bali’s Water Temples Teach Smart Teamwork

Picture your dorm’s shared kitchen. If everyone cooks at 7 p.m., the stove line explodes and dinner’s late. If nobody cleans at the same time, pests show up. The fix is simple: agree on a rhythm—stagger the cooking, sync the clean-up. Lansing and Kremer describe a real-world version of this on Bali’s terraced rice fields, where farmers face two opposite problems at once: sharing limited water and keeping crop pests down. Their solution is to coordinate when fields are wet or fallow so pests lose their home, without making every farm demand water on the same day. That balance—neither “everyone goes solo” nor “everyone moves in lockstep”—is the heart of the story. 

According to Lansing and Kremer, Bali’s farmers use “water temple” networks to plan planting like a neighborhood schedule. These temples aren’t just spiritual sites; they’re meeting points where farmer groups set calendars. One example follows two systems on the same river. Downstream subaks planted together and even delayed their start by two weeks compared with their upstream neighbors so the heaviest water demand didn’t hit at once. Pests stayed minimal that season, harvests were solid, and the shared water—though tight—stretched further because the peak didn’t collide. Think of it as staggering shower times in a crowded house so the hot water lasts. 

To see how much coordination matters, Lansing and Kremer built a computer model of two rivers, mapping 172 farmer associations and simulating rain, river flow, crop stages, water stress, and pest growth. When they compared the model with real harvests, it matched well. Then they tested different ways of coordinating. If every group planted alone, pests soared; if everyone planted the same day, water stress spiked. The sweet spot—highest yields—looked like the actual temple network scale in between. In short: the right-sized team plan beats both free-for-all and one-size-fits-all. 

Here’s the coolest part for everyday life: when the researchers let groups “copy the best neighbor” year after year, coordinated clusters popped up on their own and average yields climbed. Those networks also bounced back faster from shocks like droughts or pest bursts—because a good rhythm makes the whole system tougher, not just one farm. The authors warn that random, every-group-for-itself changes (like chasing the newest crop without syncing with neighbors) keep results uneven across the region. The takeaway for your team, club, or flatmates is simple: set a shared cadence, borrow what works nearby, and plan breaks on purpose. That’s how you get more done with less stress—and recover quicker when life throws curveballs.

Reference:
Lansing, J. S., & Kremer, J. N. (1993). Emergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscape. American Anthropologist95(1), 97–114. https://doi.org/10.1525/aa.1993.95.1.02a00050

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You Don’t Just Fit Your World—You Help Build It

Imagine fixing up your room before exam week. You clear the desk, pin a schedule on the wall, and set a water bottle by your chair. A few days later, you’re studying longer, taking fewer breaks, and even sleeping better. Your tiny redesign didn’t just make the room nicer—it changed how you behave. Odling-Smee, Laland, and Feldman employ a similar concept for living things: organisms not only adapt to their surroundings, but also alter those surroundings in ways that matter for the future. They call this “niche construction,” and it means life is a two-way street between creatures and the environments they help shape.

According to the authors, animals and plants are constant remodelers. Worms mix and move soil so much that they alter its structure and chemistry over generations. Social insects build nests that later push the evolution of behaviors for keeping those nests safe, clean, and at the right temperature. Even plants tweak the world by shifting soil nutrients, humidity, or fire patterns, and some species evolve to rely on the very conditions they helped create. In everyday terms, it’s like generations of students leaving better notes, habits, or clutter for the next class—what’s left behind shapes what’s likely to happen next.

This remodeling has consequences that go beyond genes alone. Parents and ancestors can pass down “ecological inheritance”—not just DNA, but altered surroundings that change what traits are useful. Think of a cuckoo laying eggs in a host’s nest: that parental choice hands the chick a different set of challenges and advantages, which can steer which traits thrive. Sometimes there’s a delay: one set of genes changes the environment first, and only later do other genes catch up, creating “evolutionary momentum.” There are also indirect gene interactions: what one species does can change how another’s genes show up, like worms improving soil in ways that boost plant growth. For a human-scale analogy, a campus that adds more bike lanes may, over time, favor students who invest in cycling gear and habits—choices today shaping which skills and tools pay off tomorrow.

The big takeaway is practical: shaping your surroundings is part of shaping yourself. The authors even note that learned and cultural behaviors can initiate new selection pressures—such as birds learning to open milk bottles, which could make digestive or learning traits more valuable. Mutual “win-wins” can also start as by-products: animals that spread seeds while eating fruit help plants, nudging both sides to lean into the partnership. In daily life, curate your “niche” on purpose: set up study spaces that invite focus, pick routines that make healthy choices the easy default, and build group norms that future-you will inherit. Adaptation isn’t only about coping with what’s out there; it’s also about the feedback loops you create through what you build, protect, and pass on.

Reference:
Odling-Smee, F. J., Laland, K. N., & Feldman, M. W. (1996). Niche Construction. The American Naturalist, 147(4), 641–648. https://doi.org/10.1086/285870

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Smart Cities, Simple Choices: Why Your Daily Habits Matter

Think of a city as a living group chat. Every person sends signals—moving to a new neighborhood, getting a job, turning on a tap—and together those signals shape what the city becomes. Marquez et al. explain that researchers use simulations to test “what if?” ideas without risking real neighborhoods or budgets, pulling info from places like population counts, job surveys, and local water utilities to see the full picture of how a city grows. This approach combines big-picture math with street-level behavior: top-down models track overall trends, while bottom-up “agents” simulate everyday choices; cellular automata provide the map, illustrating how land use changes block by block. It sounds techy, but the idea is simple: small decisions add up fast.

Sustainability is the goal that keeps the chat from turning into chaos. It means balancing what people want today with what the city needs tomorrow across society, the economy, and nature. It is not perfection; it’s a direction. In practice, this can manifest as more effective public spending. For example, judging a water project solely by who can pay misses the bigger win—fewer illnesses, more time in school or at work, and a better quality of life for everyone. When planners compare the benefits and the hidden costs—such as traffic, pollution, and even crime—they get closer to making fair, long-term choices.

The case of Ciudad Juárez shows why this matters. The city is situated in a dry region, so most of its drinking water comes from an underground aquifer, rather than a river. For years, pumping has outpaced natural recharge by roughly five to one, meaning demand keeps draining the aquifer faster than rain can refill it. The team’s model warns that if this pattern holds, the aquifer will not meet the city’s needs in about two decades. Jobs also draw people in, which increases demand for housing, services, and—yes—more water, creating a loop that planners must manage with care.

So where do you fit in? Your choices ripple. Shorter showers and fixing leaks are obvious wins in a dry city, but so is supporting policies that fund basic services, because the benefits come back to you in improved health, increased time, and greater opportunities. Paying attention to how you move (carpooling, biking, or using transit), where you live, and where you work helps keep that group chat from overheating with traffic and pollution. And when you hear about “models” or “agents,” don’t tune out. These tools exist to make everyday life smoother, not more complicated. The message from Marquez et al. is clear: when we balance people, jobs, and nature—and when our individual actions align with smart plans—the city becomes stronger for everyone.

Reference:
Marquez, B. Y., Castañon-Puga, M., Castro, J. R., & Suarez, E. D. (2010). On the Modeling of a Sustainable System for Urban Development Simulation Using Data Mining and Distributed Agencies. In G. Kou, Y. Peng, F. I. S. Ko, Y.-W. Chen, & Tomoko Tateyama (Eds.), 2nd International Conference on Software Engineering and Data Mining (1st ed., Issues 23-25 June 2010, pp. i–xvi). IEEE.

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Simulating a City: How Computers Help Us Build Fair, Livable Places

When a city grows, it’s not just more people and buildings. It’s traffic, jobs, rents, parks, water, and the invisible rules tying them together. Marquez et al. explain how social simulation allows us to “test-drive” city decisions on a computer, rather than in real life, where mistakes are costly. They combine three tools that fit like puzzle pieces: dynamic systems to visualize big-picture trends over time, multi-agent systems to observe how many independent “actors” (such as households, firms, or agencies) interact, and cellular automata to map those changes on a grid that resembles an actual city. Put simply, it’s top-down, bottom-up, and on-the-map thinking working together, allowing us to explore what might happen before it actually occurs (Marquez et al., 2010).

Sustainability sits at the center of this approach. The authors describe it as aiming for a good life today without wrecking tomorrow, balancing social needs, the economy, and the environment. In cities, this means tracking how population growth and migration can boost innovation and services, but also bring congestion, unemployment, or pollution if planning is done poorly. Markets set many prices and wages, yet they don’t always account for “externalities,” like dirty air or clogged roads. That’s why planners use cost–benefit thinking that values public health and well-being, not just bills and fees. An easy example is water and sanitation: the benefits include fewer illnesses and more productive days, which matter even if a simple price tag doesn’t capture them all (Marquez et al., 2010).

To illustrate this, Marquez et al. examine Ciudad Juárez. It’s a fast-growing, desert-climate city where water demand rises with population and industry. Most drinking water comes from the Bolsón del Hueco aquifer, and extraction has exceeded natural recharge several times. Residential users account for the largest share of water, with commercial, industrial, and public uses making up the remainder. The authors simulate these pressures with NetLogo and find a worrying pattern: if current trends continue, the aquifer’s supply won’t meet the city’s needs within about two decades. Growth also ties the city to larger economic cycles because it serves as a border hub, which can amplify booms and downturns (Marquez et al., 2010).

Why should young people care? Because everyday choices connect to these systems. Taking a job across town can significantly impact travel patterns. Choosing where to live changes the demand for services. Supporting smarter water use and fair public investments helps your neighborhood stay healthy and affordable. The big message is hopeful: complex doesn’t mean helpless. By simulating cities as living systems—encompassing people, money, and nature together—we can test ideas, identify side effects, and strive for a city that functions effectively in real life, not just on paper (Marquez et al., 2010).

Reference:
Marquez, B. Y., Castañón-Puga, M., & Suarez, E. D. (2010). On the Simulation of a Sustainable System Using Modeling Dynamic Systems and Distributed Agencies. In 2010 6th International Conference on Networked Computing (INC) (1st ed., pp. 1–5). IEEE.

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This blog provides simplified educational science content, created with the assistance of both humans and AI. It may omit technical details, is provided “as is,” and does not collect personal data beyond basic anonymous analytics. For full details, please see our Privacy Notice and Disclaimer. Read About This Blog & Attribution Note for AI-Generated Content to know more about this blog project.