Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two ...decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision‐support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision‐support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next‐generation tools to support agroecosystem management through the 21st century.
Core Ideas
Managers and researchers need monitoring data that are directly connected to models and decision‐support tools.
Standardized monitoring protocols present an opportunity to understand cross‐scale agroecosystem dynamics.
The Landscape Data Commons provides data harmonization, data access, and model connections.
Standardized data and modeled indicators enable managers to leverage quantitative data in decision‐support tools.
Shared data and model infrastructure can support collaborative adaptive management on agroecosystems globally.
The Landscape Data Commons enables researchers and managers to better understand agroecosystem dynamics by harmonizing and aggregating standardized monitoring data, facilitating connections to models, making data and model outputs available to users through a data portal and API, and providing links to analysis and decision support tools.
Background
Soil properties have important effects on fire occurrence and spread, but soils are often overlooked in fire prediction models. Quantifying soil−fire linkages is limited by information in ...conventional soil maps, but digital soil mapping products (
e.g.,
detailed soil property maps) could improve both wildfire prediction models and post-fire management decisions.
Results
Of our estimated 3.7 Mkm
2
of rangeland in the continental US and Alaska, an average of 38 000 km
2
burned per year between 2008 and 2017. To highlight the role of soils in fire ecology, we present 1) a conceptual framework explaining why soil information can be useful for fire models, 2) a comprehensive suite of literature examples that used soil property information in traditional soil survey for predicting wildfire, and 3) specific examples of how more detailed soil information can be applied for pre- and post-fire decisions.
Conclusions
Digital soil mapping can improve fire prediction models and inform post-fire management decisions.
Agricultural systems are enormously variable in space and time. New and developing artificial intelligence (AI)-based tools can leverage site-based science and big data to help farmers and land ...managers make site-specific decisions. These tools are improving information about soils and vegetation that forms the basis for investments in management actions, provides early warning of pest and disease outbreaks, and facilitates the selection of sustainable cropland management practices. Continued progress with AI will require more observational data across a wide range of agricultural settings, over long time periods.
Question
Plant communities are structured by both equilibrium and non‐equilibrium dynamics, which interact at different spatiotemporal scales. The influence of external factors on internal regulation ...processes might depend on ecological state, and thus, on system resilience. We asked if well‐conserved (reference) states have higher resilience to external factors than degraded states, considering the greater capacity for self‐regulation expected of reference states.
Location
Graminous–subshrubby steppes of northern Patagonia, Argentina.
Methods
During four years, we assessed the influence of an external factor (rainfall variability) on internal regulation processes (seedling recruitment, growth of main perennial species, and three resilience proxies) in two alternative states (one reference and another degraded) of graminous–subshrubby steppes of northern Patagonia (Argentina). Specifically, we assessed the response of alternative states to simulated high rainfall events (irrigation).
Results
The degraded state was more sensitive to rainfall variability than the reference state. Specifically, in the degraded state the density of surviving seedlings, the growth of shrubs and Papostipa speciosa’s relative tiller production and cover increased in response to irrigation; whereas seedling emergence and survival, and grass growth were low or even null without irrigation. Finally, resistance and elasticity were lower whereas malleability was greater in degraded than in reference states.
Conclusions
The degraded state was less resilient (low resistance and elasticity; high malleability) to stochastic weather events (in response to either increases or decreases in water availability. In contrast, the reference state had a great capacity to respond to rainfall variability. However, demographic processes such as seedling recruitment and vegetative growth were compensated by competition and mortality, suggesting a lower sensitivity to external drivers, and thus, a greater stability. By influencing the balance between equilibrium and non‐equilibrium dynamics, degradation might affect the resilience and stability of the ecosystem. Thus, to prevent rangeland degradation, management plans should anticipate climatically favorable and unfavorable periods.
Our work focused on the study of the ecological resilience to drivers of alternative states in steppes of Patagonia (Argentina). Resilience is the ability of an ecosystem to absorb or recover after disturbances caused either by environmental events (e.g. climatic) or anthropic use (e.g. livestock overgrazing). We evaluated the resilience of alternative states to weather events (wet years and droughts). We found that better conserved states have very stable dynamics associated with high resilience to disturbance factors. On the other hand, states with intermediate degradation are unstable against environmental and anthropic factors, and are very likely to continue degrading. Finally, highly degraded states become very stable, because three reasons: (i) they have already lost a lot of soil and vegetation (they cannot continue degrading), (ii) species resistant to drought and/or grazing dominate, and (iii) they are very difficult to recover. In a context of global change, where extreme weather events will be increasingly frequent, it is essential that we design management and/or restoration strategies that strengthen the resilience and foster the stability of our ecosystems.
How is an ecosystem supposed to be? The answers determine how millions of dollars are spent and how ecosystems are transformed (or ignored), with effects lasting centuries. Conflict over this ...question used to be between industry and environmentalists. Now ecologists are doing battle with one another too.
1. The distribution, ecology, and behaviour of ants (Hymenoptera: Formicidae) is profoundly influenced by environmental stress and competition. As in plants, trade-offs in adaptations to these ...factors are the basis for functional classifications of ant taxa and communities at a global scale. 2. Theory predicts a trade-off between stress tolerance and competitive dominance in both plants and ants. In ants, low temperature is thought to be stressful, so I hypothesized that there would be a positive relationship between temperature and behavioural dominance. I evaluated this relationship in a South American, Chaco ant community. 3. The activity and behaviour of ground-foraging, omnivorous ants were examined at baits in open and closed, forested habitats during different seasons and times of day to characterize the responses of ant taxa to variation in microclimate and competitors. 4. Behaviourally dominant ants were most active at moderately high temperatures, whereas subordinate species were active at extreme temperatures, when they had virtually exclusive access to resources. 5. The patterns presented here and those observed in other studies suggest that there is a general trade-off between behavioural dominance and thermal tolerance in ants. This trade-off creates a linear relationship between temperature use and dominance for ants up to ≈ 35⚬C, but extremely high temperatures may also be stressful such that the full relationship is actually unimodal
Resilience-based frameworks, including state-and-transition models (STM), are being increasingly called upon to inform policy and guide ecosystem management, particularly in rangelands. Yet, multiple ...challenges impede their effective implementation: (1) paucity of empirical tests of resilience concepts, such as alternative states and thresholds, and (2) heavy reliance on expert models, which are seldom tested against empirical data. We developed an analytical protocol to identify unique plant communities and their transitions, and applied it to a long-term vegetation record from the Sonoran Desert (1953-2009). We assessed whether empirical trends were consistent with resilience concepts, and evaluated how they may inform the construction and interpretation of expert STMs. Seven statistically distinct plant communities were identified based on the cover of 22 plant species in 68 permanent transects. We recorded 253 instances of community transitions, associated with changes in species composition between successive samplings. Expectedly, transitions were more frequent among proximate communities with similar species pools than among distant communities. But unexpectedly, communities and transitions were not strongly constrained by soil type and topography. Only 18 transitions featured disproportionately large compositional turnover (species dissimilarity ranged between 0.54 and 0.68), and these were closely associated with communities that were dominated by the common shrub (burroweed,
Haplopappus tenuisecta
); indicating that only some, and not all, communities may be prone to large compositional change. Temporal dynamics in individual transects illustrated four general trajectories: stability, nondirectional drift, reversibility, and directional shifts that were not reversed even after 2-3 decades. The frequency of transitions and the accompanying species dissimilarity were both positively correlated with fluctuation in precipitation, indicating that climatic drivers require more attention in STMs. Many features of the expert models, including the number of communities and participant species, were consistent with empirical trends, but expert models underrepresented recent increases in cacti while overemphasizing the introduced Lehmann's lovegrass (
Eragrostis lehmanniana
). Quantification of communities and transitions within long-term vegetation records presents several quantitative metrics such as transition frequency, magnitude of accompanying compositional change, presence of unidirectional trajectories, and lack of reversibility within various timescales, which can clarify resilience concepts and inform the construction and interpretation of STMs.
•The use of science to inform conservation practices is limited by broad generalities generated from limited sampling alongside narrow ecosystem service perspectives.•Collaborative science approaches ...featuring “social-ecological system” perspectives are being used as a means to improve the utility of science.•We review our approach to collaborative science to improve brush management outcomes in rangelands in the Chihuahuan Desert.•Expanding the use and utility of collaborative science requires stable support via targeted funding and technical expertise, as well as web-based tools and mobile applications that link specific locations to science information and conservation practice guidelines.
Interpretation of assessment and monitoring data requires information about how reference conditions and ecological resilience vary in space and time. Reference conditions used as benchmarks are ...often specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially observed in an area based on soil and climate. State-and-transition models (STMs) coupled to ecological sites specify indicators of ecological resilience and thresholds. Although general concepts surrounding STMs and ecological sites have received increasing attention, strategies to apply and quantify these concepts have not. In this paper, we outline concepts and a practical approach to potential-based land classification and STM development. Quantification emphasizes inventory techniques readily available to natural resource professionals that reveal processes interacting across spatial scales. We recommend a sequence of eight steps for the co-development of ecological sites and STMs, including 1) creation of initial concepts based on literature and workshops; 2) extensive, low-intensity traverses to refine initial concepts and to plan inventory; 3) development of a spatial hierarchy for sampling based on climate, geomorphology, and soils; 4) stratified medium-intensity inventory of plant communities and soils across a broad extent and with large sample sizes; 5) storage of plant and soil data in a single database; 6) model-building and analysis of inventory data to test initial concepts; 7) support and/or refinement of concepts; and 8) high-intensity characterization and monitoring of states. We offer a simple example of how data assembled via our sequence are used to refine ecological site classes and STMs. The linkage of inventory to expert knowledge and site-based mechanistic experiments and monitoring provides a powerful means for specifying management hypotheses and, ultimately, promoting resilience in grassland, shrubland, savanna, and forest ecosystems.
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