When energy doesn’t add up: use of an energyshed framework in assessing progress towards renewable energy transitions

Global progress in energy transitions to support climate mitigation goals has been slower than anticipated; this has prompted shifts away from traditional paradigms of regulated energy ownership towards a model of energy democratization by local communities and individuals. For example, in the United States, local communities in over 250 cities, counties, and states have made pledges to reach 100% renewable electrification by target dates ranging from 2020 to 2050. However, the availability of infrastructure and the competition for renewable energy resources, as well as lack of awareness of these limitations, present significant barriers to overcome. In this study, we explored a subset of 31 of these cities to assess their current electricity generation and how much further they have to go to meet their goals. Through an energyshed framework, we estimated powerplant electricity allocation to each city assuming competition for power from various renewable and non-renewable resource types, as well as look at the ‘best case scenario’ assuming 100% allocation of renewable-sourced electricity for a handful of cities in order to understand the existing and planned energy mixes for 2021 and the following 20 years. It is likely most cities will meet 10% of their energy demand with renewable energy, with best cases scenarios reaching between 35% and 65% renewable penetration, within the next 20–30 years. This highlights the need for infrastructural development in the energy sector, as well as intentional planning efforts in order to make these energy goals a reality

A stream classification system to explore the physical habitat diversity and anthropogenic impacts in riverscapes of the eastern United States

<div><p>Describing the physical habitat diversity of stream types is important for understanding stream ecosystem complexity, but also prioritizing management of stream ecosystems, especially those that are rare. We developed a stream classification system of six physical habitat layers (size, gradient, hydrology, temperature, valley confinement, and substrate) for approximately 1 million stream reaches within the Eastern United States in order to conduct an inventory of different types of streams and examine stream diversity. Additionally, we compare stream diversity to patterns of anthropogenic disturbances to evaluate associations between stream types and human disturbances, but also to prioritize rare stream types that may lack natural representation in the landscape. Based on combinations of different layers, we estimate there are anywhere from 1,521 to 5,577 different physical types of stream reaches within the Eastern US. By accounting for uncertainty in class membership, these estimates could range from 1,434 to 6,856 stream types. However, 95% of total stream distance is represented by only 30% of the total stream habitat types, which suggests that most stream types are rare. Unfortunately, as much as one third of stream physical diversity within the region has been compromised by anthropogenic disturbances. To provide an example of the stream classification’s utility in management of these ecosystems, we isolated 5% of stream length in the entire region that represented 87% of the total physical diversity of streams to prioritize streams for conservation protection, restoration, and biological monitoring. We suggest that our stream classification framework could be important for exploring the diversity of stream ecosystems and is flexible in that it can be combined with other stream classification frameworks developed at higher resolutions (meso- and micro-habitat scales). Additionally, the exploration of physical diversity helps to estimate the rarity and patchiness of riverscapes over large region and assist in conservation and management.</p></div

Proportion of stream length having various levels of % agriculture or % urban land cover in their upstream watersheds according to stream classes.

<p>Proportion of stream length having various levels of % agriculture or % urban land cover in their upstream watersheds according to stream classes.</p

Measures of association between stream classes and disturbance classes.

<p>Disturbance classes are a categorical indication of the anthropogenic stressor, if present, inducing the largest influence on a stream and includes (in order of greatest to least influence): Impoundment, dam regulation, dam fragmentation, landscape alteration, and no disturbance.</p

Comparison of the total and rare typologies emerging from the simple typology versus those arising from scenarios assessing uncertainty in class membership.

<p>Rare types refer to stream typologies with cumulative lengths in the lowest 10^th percentile of all typologies. Layers do not consider substrate classes.</p

Disturbance regimes mapped to stream reaches.

<p>Disturbance regimes mapped to stream reaches.</p

Case study examining streams similar to Walker Branch, Tennessee, and the Lower Roanoke River, North Carolina.

<p>(A) Locations of Walker Branch and the Lower Roanoke River and associated Ecoregions. Study side maps of (B) Walker Branch watershed and (C) the Lower Roanoke River. Streams in the (D) Ridge and Valley and (E) Mid-Atlantic and Southeastern Plains were sequentially filtered based on whether they matched the same typology as Walker Branch and the Lower Roanoke River, respectively. Sequential filtering started with size classes, and then was followed by gradient, hydrology, temperature, confinement, and substrate (i.e., in order of hypothesized importance in structuring stream ecosystems). Total length of streams matching filters is provided.</p