Earth is in the midst of a biodiversity crisis that is expected to worsen into the future. Scientists are scrambling to study how species interactions are responding to climate and ecosystem change, but often lack long-term, large-scale datasets that help determine which processes are most relevant in a given ecosystem. In a new paper, members of the LTER Metacommunity Dynamics and Community Responses to Disturbance Synthesis Working Group describe how researchers can overcome this limitation with the help of coordinated research and observation networks, whose datasets provide ecological information at spatial and temporal scales greater than any single research group could accomplish.
The evolution of coordinated research networks like the LTER, as well as the Long-Term Agroecosystem Research Network (LTAR), the Nutrient Network, the National Ecological Observatory Network (NEON), and others, provides a largely underutilized collection of long-term studies with spatial replication that could be synthesized to gain valuable knowledge on metacommunities and biodiversity trends, especially when historical contexts are known and infrastructure enables long-term field experiments. Based on insights the working group made while curating LTER data for metacommunity analyses, lead author Sydne Record and fellow working group members identify four challenges towards gathering and synthesizing these data and present recommendations for addressing each challenge.
Challenge One – Scale Mismatch Among Data Sets in Synthesis Efforts
Synthesizing biodiversity datasets that represent varying spatial and temporal scales can present obvious difficulties. Record et al. give two recommendations to help monitoring programs address this; first, ensure that raw data are published with ample metadata for important context, and second, programs should work together to derive agreed upon standardized sampling protocols for particular taxa.
Challenge Two – Rare Species
Long-term data is essential in order to accurately understand the presence or absence of rare taxa in a given system, because local and short-term dynamics can influence community assembly over time. Record et al. suggest that observation networks balance temporal and spatial replication to better characterize the regional species pool, including rare taxa. Researchers could also implement adaptive cluster sampling to capture rare species, with the study area spatially partitioned into a grid and survey effort intensified around grid cells with higher counts of particular rare species. The authors also encourage working groups to develop strategies for monitoring and interpreting future trends of the rare taxa that might predict invasion or threshold responses in future climate scenarios.
Challenge Three – Economies of Scale
The authors recommend that scientific societies provide a hub for coordination among and between single-PI and large-scale observation networks to help identify opportunities where single-PI and observation network projects can fill complementary knowledge gaps, particularly across spatio-temporal scales . They suggest that researchers also take advantage of cross-project collaborative opportunities (such as the LTER All Scientists’ Meeting or Research Coordination Network working groups) and establish joint data collection priorities and standards that would better match data collection approaches with species life histories and spatial extents. Harmonized datasets will be key to this work.
Challenge 4 – Statistical Integration of Long-Term, Spatially Replicated Data With Theory
Integrating statistical data with theoretical concepts continues to be a challenge, even with the availability of long-term data. Record et al. point to the practice of cyclical data assimilation with model/theory refinement as a promising approach. Near term forecasting using process-based models can generate testable predictions with the potential to quickly refine theory and identify key gaps in knowledge and understanding.
The planet is rapidly losing biodiversity and associated ecosystem services, so understanding how spatial and temporal scales impact biodiversity change is fundamental for conservation and research efforts. By coordinating these efforts, ecologists can better document why species persist or disappear in space and time, and characterize how biodiversity patterns emerge across a diverse range of ecosystems and time frames.
Record Sydne, Voelker Nicole M., Zarnetske Phoebe L., Wisnoski Nathan I., Tonkin Jonathan D., Swan Christopher, Marazzi Luca, Lany Nina, Lamy Thomas, Compagnoni Aldo, Castorani Max C. N., Andrade Riley, Sokol Eric R. Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Data. Front. Ecol. Evol., 14 January 2021| https://doi.org/10.3389/fevo.2020.612794