Past, present, and future roles of long-term experiments in the LTER Network

Author Posting. © American Institute of Biological Sciences, 2012. This article is posted here by permission of American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 62 (2012): 377-389, doi:10.1525/bio.2012.62.4.9.The US National Science Foundation—funded Long Term Ecological Research (LTER) Network supports a large (around 240) and diverse portfolio of long-term ecological experiments. Collectively, these long-term experiments have (a) provided unique insights into ecological patterns and processes, although such insight often became apparent only after many years of study; (b) influenced management and policy decisions; and (c) evolved into research platforms supporting studies and involving investigators who were not part of the original design. Furthermore, this suite of long-term experiments addresses, at the site level, all of the US National Research Council's Grand Challenges in Environmental Sciences. Despite these contributions, we argue that the scale and scope of global environmental change requires a more-coordinated multisite approach to long-term experiments. Ideally, such an approach would include a network of spatially extensive multifactor experiments, designed in collaboration with ecological modelers that would build on and extend the unique context provided by the LTER Network.2012-10-0

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

Characterizing differences in precipitation regimes of extreme wet and dry years: implications for climate change experiments.

Climate change is intensifying the hydrologic cycle and is expected to increase the frequency of extreme wet and dry years. Beyond precipitation amount, extreme wet and dry years may differ in other ways, such as the number of precipitation events, event size, and the time between events. We assessed 1614 long-term (100 year) precipitation records from around the world to identify key attributes of precipitation regimes, besides amount, that distinguish statistically extreme wet from extreme dry years. In general, in regions where mean annual precipitation (MAP) exceeded 1000 mm, precipitation amounts in extreme wet and dry years differed from average years by ~40% and 30%, respectively. The magnitude of these deviations increased to >60% for dry years and to >150% for wet years in arid regions (MAP<500 mm). Extreme wet years were primarily distinguished from average and extreme dry years by the presence of multiple extreme (large) daily precipitation events (events >99th percentile of all events); these occurred twice as often in extreme wet years compared to average years. In contrast, these large precipitation events were rare in extreme dry years. Less important for distinguishing extreme wet from dry years were mean event size and frequency, or the number of dry days between events. However, extreme dry years were distinguished from average years by an increase in the number of dry days between events. These precipitation regime attributes consistently differed between extreme wet and dry years across 12 major terrestrial ecoregions from around the world, from deserts to the tropics. Thus, we recommend that climate change experiments and model simulations incorporate these differences in key precipitation regime attributes, as well as amount into treatments. This will allow experiments to more realistically simulate extreme precipitation years and more accurately assess the ecological consequences

Ambient changes exceed treatment effects on plant species abundance in global change experiments

The responses of species to environmental changes will determine future community composition and ecosystem function. Many syntheses of global change experiments examine the magnitude of treatment effect sizes, but we lack an understanding of how plant responses to treatments compare to ongoing changes in the unmanipulated (ambient or background) system. We used a database of long-term global change studies manipulating CO2, nutrients, water, and temperature to answer three questions: (a) How do changes in plant species abundance in ambient plots relate to those in treated plots? (b) How does the magnitude of ambient change in species-level abundance over time relate to responsiveness to global change treatments? (c) Does the direction of species-level responses to global change treatments differ from the direction of ambient change? We estimated temporal trends in plant abundance for 791 plant species in ambient and treated plots across 16 long-term global change experiments yielding 2,116 experiment-species-treatment combinations. Surprisingly, for most species (57%) the magnitude of ambient change was greater than the magnitude of treatment effects. However, the direction of ambient change, whether a species was increasing or decreasing in abundance under ambient conditions, had no bearing on the direction of treatment effects. Although ambient communities are inherently dynamic, there is now widespread evidence that anthropogenic drivers are directionally altering plant communities in many ecosystems. Thus, global change treatment effects must be interpreted in the context of plant species trajectories that are likely driven by ongoing environmental changes

Asynchrony among local communities stabilises ecosystem function of metacommunities

Abstract Temporal stability of ecosystem functioning increases the predictability and reliability of ecosystem services, and understanding the drivers of stability across spatial scales is important for land management and policy decisions. We used species-level abundance data from 62 plant communities across five continents to assess mechanisms of temporal stability across spatial scales. We assessed how asynchrony (i.e. different units responding dissimilarly through time) of species and local communities stabilised metacommunity ecosystem function. Asynchrony of species increased stability of local communities, and asynchrony among local communities enhanced metacommunity stability by a wide range of magnitudes (1–315%); this range was positively correlated with the size of the metacommunity. Additionally, asynchronous responses among local communities were linked with species’ populations fluctuating asynchronously across space, perhaps stemming from physical and/or competitive differences among local communities. Accordingly, we suggest spatial heterogeneity should be a major focus for maintaining the stability of ecosystem services at larger spatial scales

Asynchrony among local communities stabilises ecosystem function of metacommunities

Temporal stability of ecosystem functioning increases the predictability and reliability of ecosystem services, and understanding the drivers of stability across spatial scales is important for land management and policy decisions. We used species-level abundance data from 62 plant communities across five continents to assess mechanisms of temporal stability across spatial scales. We assessed how asynchrony (i.e. different units responding dissimilarly through time) of species and local communities stabilised metacommunity ecosystem function. Asynchrony of species increased stability of local communities, and asynchrony among local communities enhanced metacommunity stability by a wide range of magnitudes (1–315%); this range was positively correlated with the size of the metacommunity. Additionally, asynchronous responses among local communities were linked with species’ populations fluctuating asynchronously across space, perhaps stemming from physical and/or competitive differences among local communities. Accordingly, we suggest spatial heterogeneity should be a major focus for maintaining the stability of ecosystem services at larger spatial scales