Effective stream management extends beyond reach and mesohabitat scales. As humans, we want to fix what we can see. If banks are eroding, we slope them and plant trees. If the Smoky Mountain madtom is extirpated, we reintroduce it. If the dam blows out habitat, we install boulders. However, we must address the cause of the problem. Several papers (Fausch et al. 2002; Allan 2004) stress the importance of viewing stream ecosystems on a landscape scale. In this class, we learned that fixing one problem may not be enough to restore biotic communities. For example, fixing eroded banks in a stream reach downstream of a city, which reaches bankfull stage ten times more often that it should, may not restore the biotic community. As managers, we must make all efforts to restore every aspect of streams that we can. For example, on this stream that drains an urban landscape, bank stabilizaiton may help, but it does not address the cause of the problem.
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Another key principle:
2. Collect large amounts of continuous, accurate data—before and after projects. How many of our readings of case studies were negatively affected by a lack of data? Too many. Many stream restoration projects either have little or no pre-implementation data, or lack proper post-implementation evaluation. Naturally, stream management projects are limited by resources and time. Until the invention of the time machine, we can’t go back and collect pre-implementation data on completed projects. However, the time for collecting pre-implementation data on future projects is NOW. As people who pride themselves on protecting future resources, it is our responsibility to have the foresight to collect relevant data on degraded streams now so that we can assess the impacts of future projects. We must also collect post-implementation data in order to evaluate the successes and failures of current projects. As stream restoration is an emerging field, those who collect solid pre-implementation data, and then objectively evaluate the effects of a project, will be considered methodological pioneers within by future generations of stream managers.
Like Brandon stated in his first posting, I believe that focusing on the cause of the habitat degradation within a watershed and not the manifestation of the degradation at a specific site is an important principle of stream management. This is a principle that is applicable to all forms of conservation, restoration, or resource management and not just in the context of stream restoration. In addition to the examples that Brandon has provided, I would like to mention an example. Many rivers are heavily impacted by poor agricultural practices. These activities can lead to degradation at certain sites due to sedimentation, pesticide run-off and destruction of shoal habitat due to cows in a stream. Individually, each of these impacts can cause declines in mussel or fish populations and are problems that can be addressed on a site-by-site basis. But major factor impacting the watershed isn’t these individual, treatable “symptoms” but the agricultural practices in the watershed. In the end, the watershed will never be safe from degradation until the agricultural practices are improved. As managers, we need to acknowledge what the underlying problem with the system is, opposed to constantly attempting to treat the resulting symptoms of that problem.
Collaborative planning and adaptive management are key for healthy rivers
With the diverse needs and uses of water in modern society, there is always going to be a need for balance between the needs of stakeholders, whose needs include clean drinking water, industry, agriculture, navigation, electric power, recreational users, wildlife habitat, and cultural and aesthetic values. Collaboration in water planning is critical to creating sustainable use and management of water. We have learned from many of our readings about the utility of adaptive management and some suggestions for how to implement adaptive management into stream management (Anderson et al., 2003; Poff et al., 2003; Richter et al., 2003). We started the semester discussing in-stream habitat management, which is perhaps more opportunistic in time and space than projects such as flow management, but must be a collaborative effort between many stakeholders, including private landowners, state and federal agencies and non-profit organizations. By the end of the semester we were discussing both the effects of varied instream flow methodology and landscape-scale watershed management. All of these management paradigms are dependent on working collaboratively and being willing to adapt management to fit the needs of stakeholders, while keeping the needs of the natural system in mind.
UNCERTAINTY
So far as we remain human, and so far as technology advances, there is bound to be changes to concepts, methods and structures. I believe this should be firmly planted at the back of the mind of every player in the arena of stream habitat management - managers, scientists and other decision-makers alike. It is very common for most of these people to say they are performing their roles with posterity in mind, but that is easier said than done. The topics on dams and instream structures have been some of the most interesting to me from this class. Nevertheless, I have realized from the lectures and in-class discussions that most often when a dam or some other instream structure is found to be causing some form of harm, either to aquatic or human communities, stakeholders remain divided on solutions. This is simply because engineers in the past years never thought their set-pieces could ever be faulted. So they aimed at building perfectly permanent structures.
The best solution would have been to just change certain parts of these structures, but now in most cases, the only solution left is to completey remove, or replace them. Unfortunately, due to the huge cost involved in undertaking these projects the appropriate authorities would rather choose to ignore these structures, via repeated postponement of action. This is one major principle I have picked up from this class and even at this level, I have found myself either applying this principle on the field, or suffering later for not doing so.
I have realised that when we are myopic in data collection , we either lose the opportunity to be more versatile in our projects later (when a new software package shows up, etc), or lose a possible back-up plan. When we collected data from Stoney Creek for RSI measurements, little did I know that a whole lot more information was going to come from it. After we found out that our RSI values were more than just a little ridiculous, we had to find some other means of determining the stability of that stream. That is when I realised that certain data we took just for practice had become important. So I am convinced that constantly keeping the uncertain in mind, will save us lots of time, energy and money in the future.
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