To heal a river, you need more than good intentions

Rethinking rivers mini series, Post 3 of 3: If we want to conserve rivers, we need to think in networks, rhythms, and landscapes.

This is post three of a three-part series on some unique aspects of rivers and why they’re so challenging to manage. We’re exploring how rivers function as networks, their unique rhythms, and what that means for conservation and restoration. If you didn’t see them, here’s the first two posts:

The surprising similarity between rivers and trees

The music of rivers

Freshwater needs all the help it can get. By sharing these posts, you’re helping raise the visibility of ecosystems that are often overlooked — and increasingly at risk. Let’s get more people thinking about rivers not just as scenery, but as living systems worth protecting.

Cass River, Canterbury, NZ. Photo: J. Tonkin.

In the previous two posts, I talked about how rivers are connected as branching networks and how their rhythms shape life. Here, I want to ask the question: what does that mean for actually managing or restoring them?

The short answer: it’s complicated.

Let me show you two examples from my own work that highlight both the challenges — and the possibilities — of doing freshwater conservation well: river restoration and flow management. TL;DR — To bring life back, you need to think in networks, rhythms, and landscapes.

Challenge 1: Restoring habitat isn't enough

Did you ever see the 1980s Kevin Costner film The Field of Dreams? In short, Kevin Costner's character builds a baseball ground in his corn fields and baseball players from the past magically turn up and start playing.

Surprisingly, there's a connection to river restoration. In fact, it underpins one of the main reasons most river restoration efforts fail to meet their ecological goals. Unlike the film, if you build it, they won't actually come... unless they're nearby.

It worked for Costner, but for rivers, if you build it, they won't necessarily come — the species that is.

So, restoring habitat isn’t enough if species can’t get there. And that's exactly what we found in a study published in 2014.

We examined the chances of stream invertebrates turning up at dozens of river restoration sites across Germany and whether these were driven by the types of restoration approaches used or simply how near or common the species were found in the nearby river network. We sourced details of how long the restored stretches of river were, how much money was spent, when the sampling took place relative to the restoration event, and what type of approaches were used, like reconnecting channels, changing flow paths etc. We then threw data at this problem and used a machine learning approach to understanding what was going on.

We found that the success of restoration wasn’t about how much money was spent or how fancy the techniques were — it was about whether the species were common nearby and able to reach the site.

In other words, the success of restoration was constrained by dispersal of species. Despite their ability to fly as adults, the majority of aquatic insects still follow the river network during their dispersal events. So the network plays a role in determining how far species spread during these events. The river is their superhighway.

So to ensure river restoration is successful — beyond just beautifying rivers — you need to account for where it is in the river network and the availability of species to colonise it. Otherwise, you’re just restoring habitat, not ecosystems.¹

Connectivity isn’t just about water — it’s about the movement of organisms, opportunities for restoring ecological function, and the flow of energy.

Don't worry about everything going on here. On the left, just look at the 'Model3' panel, which shows that of all the predictors that went into the machine learning model, distance (how close the nearest occurrence of a species was) and taxon pool (how common a species was in the surrounding area) were by far the most important predictors (its relative influence in the model). On the right, these are called 'partial dependence plots' which show the response (here the presence of a species at a restored site) as a function of the top 6 predictors. The first two panels show what I've already mentioned: the more common you are in the surrounding river network, the more chance you have of turning up and the same for the nearer you are, particularly within the first 1.5km of river. Source: Tonkin et al. (2014) Freshwater Biology.

This is obviously a big problem. River restoration is a big industry. For instance, between 1990 and 2005, an estimated average of more than US$1 billion a year was spent restoration of streams and rivers in the continental United States alone. But here's the kicker. Most of the projects that were carried out during this period were not monitored sufficiently to understand whether or not they worked. Thankfully this has changed a bit since then, but I'd argue that most restoration efforts still do not sufficiently monitor for long enough to tell if the goals were met ecologically.

So it’s not just that projects aren’t meeting their ecological targets, it’s that we often don’t even know if they are or not, nor can we learn what works if we don’t monitor the outcomes. It’s imperative that they do to ensure projects get the best bang for their buck.

Restoring habitats is one part of the story. But even if a species gets there, they still depend on the rhythms of the river itself — and that’s where things get even more complicated.

Challenge 2: Restoring river rhythms is complicated

As I mentioned in the previous post, we’ve drained rivers of their vitality by slapping a great slab of concrete in their path and rationing out their flow. For these rivers, gone are the days of boom and bust, of musical rhythms, of mass migrations and spawning events. But there are levers we can pull to minimise the damage to species that want to hang around. Many think that the main impact of dams is by blocking the path for fish and other river organisms that move along them, but the disruption of these crucial rhythms is also paramount.

"Environmental flows" are one such tool. These are where water is released from a dam in a way that benefits downstream ecosystems. According to the 2018 Brisbane Declaration: “Environmental flows describe the quantity, timing, and quality of freshwater flows and levels necessary to sustain aquatic ecosystems which, in turn, support human cultures, economies, sustainable livelihoods, and well-being".

Yet, any management of river flow from a dam is centred around a critical trade-off: who gets the water or who benefits from the water. This trade-off is typically between the needs of humans (e.g. hydroelectric energy generation, water storage etc.) and the needs of the native ecosystem downstream. Every drop of water held back for irrigation or released in unnatural rhythms for energy is water not going to the ecosystem. Managing rivers is always, then, about choosing winners and losers — whether fish, city dwellers, or farmers.

The literature is rich with great examples of where human needs and ecosystem needs are traded off. For instance, designing flows to improve food security in the Lower Mekong Basin by improving fisheries yield in the Tonle Sap, which feeds millions of people, while maintaining hydropower needs. Or in targeting flow releases to benefit native fishes over nonnative fishes, while maintaining reservoir storage capacities for irrigation purposes.

However, these examples tend to prioritise one sector of the ecosystem (above, fisheries yield or native fish). In other cases things like cottonwood trees in the US or river red gums in Australia are targeted. But many other native species occupy rivers. As I showed previously,

we initiated a computer modelling study looking at the tradeoffs among river flows designed to benefit different components of the ecosystem. That is, what happens to the rest of the ecosystem when we prioritise flows designed to benefit cottonwood over other riparian trees? What about native fishes? What about flying insects (those that emerge for part of their lifecycle)?

What we found was that targeting any one sector of the ecosystem often had major consequences for other sectors. This is because, for instance, cottonwoods benefitted most from large floods every few years, but this hampered native fishes, which require regular flood events that they use as spawning cues or dispersal triggers. Unsurprisingly, the historical natural flow regime was most beneficial for the whole ecosystems. As you can see (figure below), the natural flow regime comprised a combination of the three frequencies and magnitudes of flow events that the three targeted 'designer' flows comprised. Each targeted group performed slightly worse under natural conditions, but not far off its optimal. Again, this makes sense, the biodiversity that inhabits a river has evolved over thousands of years to work with the natural signal it experiences.

Designing a flow regime for a particular target, benefited that target but other members of the ecosystem were negatively impacted. The historical natural flow regime met the needs of all and was only slightly suboptimal for each. There’s a lot going on here, but if you want the take-home: there are trade-offs when designing an environmental flow programme for a particular species or group for other members of the ecosystem; the natural flow regime meets the needs of all. Take from the paper: "The ecosystem-wide effects of designer and natural flow regimes. Each of the four figure sectors represents a particular flow regime and/or ecosystem component: the natural flow regime and three designer flow regimes (riparian vegetation, fishes, and invertebrates). The effects of designer flow regimes on each component are shown, both targeted (arrow returns to same figure sector; e.g. fish to fish) and non-targeted (arrow from one sector to another; e.g. fish to plants), as well as the natural flow regime. Arrow widths correspond to the relative effects of a particular flow scenario (source of arrow) on all other components (arrow endpoint; larger widths equal more positive responses). These values are shown as proportions of maximum in the outermost bars (1 = maximum; e.g. native fish biomass at 100% of carrying capacity). For instance, when designing flows to most benefit native fishes, fish respond strongly (large arrow and outer bar) but plants perform poorly (small arrow and outer bar). The inner bar (tracking the circumference of the center arrows) represents the difference between the natural and prescribed flow for the group in that sector (given in percentage). For example, under the natural flow regime, fish achieve 77% of the biomass achieved under the designer flow." Source: Tonkin et al. (2021) Frontiers in Ecology and the Environment.

So, we can manage river flows to minimise the damage of dam operations on downstream ecosystems, but there are no true win-wins. That's what the natural flow regime (the natural record of floods, droughts and all the bits in between) represents for biodiversity — it meets the needs of all.

You can’t restore a river’s function without restoring its rhythm.

And that represents a fundamental challenge: balancing ecological needs with human demand, but also balancing ecological needs when prioritising conservation and restoration efforts on a particular target.

So what?

Rivers are complex, dynamic systems. And if we want to conserve them, we need to think in networks, rhythms, and landscapes.

Rivers need to be treated like the wild entities they are, not bottled up, strangled in between mounds of dirt, and stripped of their vital essence. Managing for variability is a useful first principle to work from.

After all, rivers are very much alive.

If this series resonated, I’d love for you to subscribe, share, or leave a comment. Freshwater ecosystems are often overlooked — but they’re vital, vulnerable, and worth fighting for.

1. A paper by Chris Swan and Bryan Brown showed this nicely, with the outcomes of restoration differing between headwaters and sites further down the network.