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Remote sensing to model spatiotemporal distribution of functional diversity in the tundra

Periodic Reporting for period 1 - FUNDra (Remote sensing to model spatiotemporal distribution of functional diversity in the tundra)

Reporting period: 2018-11-01 to 2020-10-31

Functional diversity (FD) is an important quantifiable metric of ecosystem function. This is often measured during the growing season and the value is used to characterize an ecosystem. It is known, however, that functional traits change seasonally and so by definition, FD must fluctuate also. The temporal dynamics have not been previously examined. During the grant period, a severe drought in Europe gave the opportunity to study how traits respond to drought stress. The summer of 2018 brought a record-breaking heat wave and record low rainfall, resulting in a severe drought in much of northern and central Europe. In the following year, precipitation increased but, in many locations, remained below average. A temporal study that began in 2017 in a temperate evergreen forest in the Netherlands allowed the opportunity to examine the effects of this drought on functional traits before, during, and after the event. Understanding dynamics of FD is important because currently we only have one snapshot to characterize whole systems. Knowing how this metric changes seasonally and annually gives a better understanding of the functionality of these systems, allowing decision makers to valuate these areas more accurately. The trait-based approach gives an understanding of how species respond and therefore how we may better prepare for or mitigate their loss. The overall objectives were to determine the seasonal dynamics of functional diversity and compare a diverse and non-diverse system, determine the effect of drought on functional traits and diversity in Douglas Fir at the plot scale, and determine the effects of drought on forest functional traits at a landscape scale.
For the functional diversity study, field data was performed in two different ecosystems during the growing season. Field samples were collected from these locations approximately every two weeks. From the tropical location, 3 grass, 3 tree, and 3 vine species were sampled. From the temperate location only one species of tree was collected, from three different heights. Specific leaf area, leaf dry matter content, and total chlorophyll content were derived. These were used to derive four FD indices. A time series was created for each of these indices for each location. Changes were compared among the two ecosystems and looked at in terms of species diversity and abiotic differences. For the plot-scale study on drought effects, the same field and lab data was used as in the functional diversity study, with the addition of carotenoid analysis. Standard precipitation index (SPI) was calculated spanning 2017 to 2019. Times series of traits were examined with drought level to determine response to drought. For the landscape-scale drought study, the goal was to determine how the temperate forest responded to drought on a larger spatial scale in terms of resilience and resistance capabilities. The studied section of forest in the Netherlands covered 3,300 ha and primarily Douglas Fir. The duration of the drought was determined for this area by calculating SPI values spanning 2018 to 2020. Sentinel images of the study area from each month were downloaded and processed for particular traits and indices. Changes and patterns were analyzed in relation to the SPI time series. All time series of functional diversity indices in both locations showed significant changes throughout the season. The non-diverse site showed increasing correlation and uniformity of trait values. The species diverse area showed no indication of directionality and had relatively more normal distributions and independence of trait values. Overall, this shows that the species diversity provides more consistency in functional trait dynamics over the growing season. In the plot-scale drought study, chlorophyll and carotenoids had the largest responses to the drought in ways that indicated plant stress. Though Douglas Fir has been considered drought resistant, this study reveals that the intensity of the 2018 drought had an impact on its traits and its resilience without sufficient soil moisture relief in the following year. SPI in the study area indicated that 2017 ended in a drought which became a severe drought in 2018 and never fully recovered to “normal” in 2019. This points to the larger problem of ecosystems persisting in a chronic state of drought and the rapid change in precipitation regime. Normalized difference Vegetation Index dropped a small amount each year, showing a general resistance to drought. Leaf area index and fractional vegetation cover responded with a highly fluctuated pattern indicating weak resistance. Some results from the first two objectives have been disseminated in conferences (European Geophysical Union 2019 and 2020). Data has been shared with another Horizon 2020 project (MULTIPLY). Overall it can be concluded from this research that species diversity provides more consistency in FD dynamics over the growing season; and that it is not necessarily an extreme event that can irreparably damage an ecosystem, but rather these events paired with a lack of adequate recovery conditions that push ecosystems past their tipping point. These studies paint a picture of a temperate forest being pushed to its limits – a common situation for natural systems around the world. Tracking these systems’ response to stress gives insight into whether, how and into what they may transition. Mortality and transitioning to a more xeric ecosystem are likely outcomes for this forest if the below average precipitation pattern is to persist into the future.
Temporal studies on functional diversity, an important ecological indicator, have not been previously done. Studying our landscapes as dynamic and fluid systems gives us a more thorough understanding of our ecosystems and the services they provide. This will hopefully result in ecosystem services being more precisely valuated, as well as the natural landscape itself. This information can be critical to conservation efforts, as it points to the fact that we (humans) are the true beneficiaries of the services of in-tact ecosystems. Trait-based approaches are not new; however, they are often regarded as a static value. Recognizing and understanding their dynamics will be important for vegetation studies in the future, especially with understanding effects of climate change. The drought studies are an example of how to employ temporal trait data and how having a database of temporal data would benefit any future study for having a reference of baseline conditions. Tracking these systems’ response to stress gives insight into whether, how and into what they may transition. The landscape-scale study gives insight into ecosystem resilience and resistance on a large scale and therefore, what we can expect with future climate predictions. The findings at the trait level will allow the next step of finding out exactly which ecosystem services will be impacted; in other words, how this affects humans. The data will improve further modelling to estimate predictions about forest survival with climate change. These studies show the importance of temporal and long-term studies for understanding responses to climate change. As climate predictions inform society of what to expect, it is an important job for ecologists to also inform the scientific community and the public about what the changing climate means for our natural systems and the ecosystem services they provide.
research team collecting samples from a savanna-forest transition zone in Ghana
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