Matthew A. Williamson

Uncertainty in Calculations of Net Primary Production for Grasslands

Net primary production (NPP) is a fundamental characteristic of all ecosystems and foundational to understanding the fluxes of energy and nutrients. Because NPP cannot be measured directly, researchers use field-measured surrogates as input variables in various equations designed to estimate ‘true NPP’. This has led to considerable debate concerning which equations most accurately estimate ‘true NPP’. This debate has influenced efforts to assess NPP in grasslands, with researchers often advocating more complex equations to avoid underestimation. However, this approach ignores the increase in statistical error associated with NPP estimates as a greater number of parameters and more complex mathematical functions are introduced into the equation. Using published grassland data and Monte Carlo simulation techniques, we assessed the relative variability in NPP estimates obtained using six different NPP estimation equations that varied in both the number of parameters and intricacy of mathematical operations. Our results indicated that more complex equations may result in greater uncertainty without reducing the probability of underestimation. The amount of uncertainty associated with estimates of NPP was influenced by the number of parameters as well as the variability in the data and the nature of the mathematical operations. For example, due to greater variability in the field-measured belowground data than aboveground data, estimates of belowground NPP tended to have more uncertainty than estimates of aboveground NPP. An analysis in which the input data were standardized allowed us to isolate the details of the calculations from the variability in the data in assessing the propagation of uncertainty. This analysis made clear that equations with product terms have the potential to magnify the uncertainty of the inputs in the estimates of NPP although this relationship was complicated by interactions with data variability and number of parameters. Our results suggest that more complex NPP estimation equations can increase uncertainty without necessarily reducing risk of underestimation. Because estimates can never be tested by comparison to “true NPP”, we recommend that researchers include an assessment of propagation of statistical error when evaluating the ‘best’ estimation method.

Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system.

Changes in Global Grassland Productivity during 1982 to 2011 Attributable to Climatic Factors

Open, Grass- and Forb-Dominated (OGFD) ecosystems, including tundra, tropical grasslands and savanna, provide habitat for both wild and domesticated large ungulate herbivores. These ecosystems exist across a wide temperature gradient from the Arctic regions to the Equator, but are confined to a narrow set of moisture conditions that range from arid deserts to forest-dominated systems. Primary productivity in OGFD ecosystems appears extremely sensitive to environmental change. We compared global trends in the annual maximum and mean values of the Normalized Difference Vegetation Index (NDVI) and identified the key bioclimatic indices that controlled OGFD productivity changes in various regions for the period from 1982 to 2011. We found significantly increased or decreased annual maximum NDVI values of 36.3% and 4.6% for OGFD ecosystems, respectively. Trends in the annual mean NDVI are similar for most OGFD ecosystems and show greater area decreases and smaller area increases than trends in the annual maximum NDVI in global OGFD ecosystems during the study period. Ecosystems in which the productivity significantly increased were distributed mainly in the Arctic, mid-eastern South America, central Africa, central Eurasia and Oceania, while those with decreasing trends in productivity were mainly on the Mongolian Plateau. Temperature increases tended to improve productivity in colder OGFD ecosystems; and precipitation is positively correlated with productivity changes in grassland and savannas, but negatively correlated with changes in the Arctic tundra. Simple bioclimatic indices explain 42% to 55% of productivity changes in OGFD systems worldwide, and the main climatic predictors of productivity differed significantly between regions. In light of future climate change, the findings of this study will help support management of global OGFD ecosystems.

Climatic change controls productivity variation in global grasslands.

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2–71.2% during 1982–2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms.

Assessing agreement among alternative climate change projections to inform conservation recommendations in the contiguous United States

Addressing uncertainties in climate vulnerability remains a challenge for conservation planning. We evaluate how confidence in conservation recommendations may change with agreement among alternative climate projections and metrics of climate exposure. We assessed agreement among three multivariate estimates of climate exposure (forward velocity, backward velocity, and climate dissimilarity) using 18 alternative climate projections for the contiguous United States. For each metric, we classified maps into quartiles for each alternative climate projections, and calculated the frequency of quartiles assigned for each gridded location (high quartile frequency = more agreement among climate projections). We evaluated recommendations using a recent climate adaptation heuristic framework that recommends emphasizing various conservation strategies to land based on current conservation value and expected climate exposure. We found that areas where conservation strategies would be confidently assigned based on high agreement among climate projections varied substantially across regions. In general, there was more agreement in forward and backward velocity estimates among alternative projections than agreement in estimates of local dissimilarity. Consensus of climate predictions resulted in the same conservation recommendation assignments in a few areas, but patterns varied by climate exposure metric. This work demonstrates an approach for explicitly evaluating alternative predictions in geographic patterns of climate change.

Assessment of the Conservation Measures Partnership's effort to improve conservation outcomes through adaptive management: Conservation Measure's Partnership

Conservation practice has demonstrated an increasing desire for accountability of actions, particularly with respect to effectiveness, efficiency, and impact to clearly identified objectives. This has been accompanied by increased attention to achieving adaptive management. In 2002, practitioners representing several prominent conservation nongovernmental organizations (NGOs) launched a community of practice called the Conservation Measures Partnership (CMP). The partnership CMP has worked to establish standards of conservation practice to improve accountability of conservation actions through adaptive management. The focal organizing framework for CMP has been the Open Standards for the Practice of Conservation (OS). We evaluated, through an online survey and personal interviews, the first decade of CMP and the OS. The CMP has garnered a positive reputation among agencies, NGOs, and funders and has succeeded in developing a large user base of the OS. However, CMP has not fully achieved its goal of making the OS standard operating procedure for the largest NGOs (e.g., The Nature Conservancy, World Wildlife Fund), despite it being widely used within these organizations. This lack of institutionalization is attributable to multiple causes, including an increase in the number of partially overlapping decision-support frameworks and challenges achieving full-cycle adaptive management. Users strongly believed the OS fosters better conservation practice and highly valued the OS for improving their practice. A primary objective of the OS is to assist practitioners to achieve full-cycle adaptive management to better integrate learning into improving the effectiveness and efficiency of actions. However, most practitioners had not yet achieved cycle completion for their projects. To improve the effectiveness of CMP, OS, and conservation practice in general, we recommend collaborative efforts among the proponents of multiple decision-support frameworks to foster strong institutional adoption of a common set of adaptive-management standards for conservation accountability.