Henry B. Glick

Positive biodiversity-productivity relationship predominant in global forests.

Global biodiversity and productivity The relationship between biodiversity and ecosystem productivity has been explored in detail in herbaceous vegetation, but patterns in forests are far less well understood. Liang et al. have amassed a global forest data set from >770,000 sample plots in 44 countries. A positive and consistent relationship can be discerned between tree diversity and ecosystem productivity at landscape, country, and ecoregion scales. On average, a 10% loss in biodiversity leads to a 3% loss in productivity. This means that the economic value of maintaining biodiversity for the sake of global forest productivity is more than fivefold greater than global conservation costs. Science, this issue p. 196 Global forest inventory records suggest that biodiversity loss would result in a decline in forest productivity worldwide. INTRODUCTION The biodiversity-productivity relationship (BPR; the effect of biodiversity on ecosystem productivity) is foundational to our understanding of the global extinction crisis and its impacts on the functioning of natural ecosystems. The BPR has been a prominent research topic within ecology in recent decades, but it is only recently that we have begun to develop a global perspective. RATIONALE Forests are the most important global repositories of terrestrial biodiversity, but deforestation, forest degradation, climate change, and other factors are threatening approximately one half of tree species worldwide. Although there have been substantial efforts to strengthen the preservation and sustainable use of forest biodiversity throughout the globe, the consequences of this diversity loss pose a major uncertainty for ongoing international forest management and conservation efforts. The forest BPR represents a critical missing link for accurate valuation of global biodiversity and successful integration of biological conservation and socioeconomic development. Until now, there have been limited tree-based diversity experiments, and the forest BPR has only been explored within regional-scale observational studies. Thus, the strength and spatial variability of this relationship remains unexplored at a global scale. RESULTS We explored the effect of tree species richness on tree volume productivity at the global scale using repeated forest inventories from 777,126 permanent sample plots in 44 countries containing more than 30 million trees from 8737 species spanning most of the global terrestrial biomes. Our findings reveal a consistent positive concave-down effect of biodiversity on forest productivity across the world, showing that a continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The BPR shows considerable geospatial variation across the world. The same percentage of biodiversity loss would lead to a greater relative (that is, percentage) productivity decline in the boreal forests of North America, Northeastern Europe, Central Siberia, East Asia, and scattered regions of South-central Africa and South-central Asia. In the Amazon, West and Southeastern Africa, Southern China, Myanmar, Nepal, and the Malay Archipelago, however, the same percentage of biodiversity loss would lead to greater absolute productivity decline. CONCLUSION Our findings highlight the negative effect of biodiversity loss on forest productivity and the potential benefits from the transition of monocultures to mixed-species stands in forestry practices. The BPR we discover across forest ecosystems worldwide corresponds well with recent theoretical advances, as well as with experimental and observational studies on forest and nonforest ecosystems. On the basis of this relationship, the ongoing species loss in forest ecosystems worldwide could substantially reduce forest productivity and thereby forest carbon absorption rate to compromise the global forest carbon sink. We further estimate that the economic value of biodiversity in maintaining commercial forest productivity alone is

Mapping tree density at a global scale

166 billion to

Wyoming's Aging Agricultural Landscape: Demographic Trends Among Farm and Ranch Operators, 1920–2007

490 billion per year. Although representing only a small percentage of the total value of biodiversity, this value is two to six times as much as it would cost to effectively implement conservation globally. These results highlight the necessity to reassess biodiversity valuation and the potential benefits of integrating and promoting biological conservation in forest resource management and forestry practices worldwide. Global effect of tree species diversity on forest productivity. Ground-sourced data from 777,126 global forest biodiversity permanent sample plots (dark blue dots, left), which cover a substantial portion of the global forest extent (white), reveal a consistent positive and concave-down biodiversity-productivity relationship across forests worldwide (red line with pink bands representing 95% confidence interval, right). The biodiversity-productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, showing that continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone—US

Spatially-explicit models of global tree density

166 billion to 490 billion per year according to our estimation—is more than twice what it would cost to implement effective global conservation. This highlights the need for a worldwide reassessment of biodiversity values, forest management strategies, and conservation priorities.

Patterns in stream greenhouse gas dynamics from mountains to plains in northcentral Wyoming

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.30 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.66 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

Modeling the Effects of Horizontal Positional Error on Classification Accuracy Statistics

On the Ground Across the United States, farmers and ranchers are getting older, and fewer young operators are entering the agricultural workforce than in the past. We statistically and cartographically explored demographic trends among farm and ranch operators in Wyoming to see if and how the agricultural community was aging. Census records indicate that Wyomings agricultural community is in fact aging, and that the relative proportions of younger operators are dwindling rapidly. With a changing local agricultural community, we face risks associated with loss of local knowledge, loss of tradition, and loss of investment that stem from a deep-rooted sense of place. We face a fundamental challenge in inspiring young agriculturalists to take up residence in the state to help replace those of retirement age. This might be accomplished through shifts in education, public policy, economic incentives, or through targeted cultivation of personal connections to the land.

Improving the Reliability of Mixture Tuned Matched Filtering Remote Sensing Classification Results Using Supervised Learning Algorithms and Cross-Validation

Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.

Predicting Global Forest Reforestation Potential

Quantification of stream contributions to global carbon cycling is key to understanding how freshwater streams transmit and transform carbon between terrestrial and atmospheric pools. To date, greenhouse gas emissions of carbon dioxide and methane from freshwaters, particularly in mountainous regions, remains poorly characterized due to a lack of direct field observations. Using a unique longitudinal approach, we conducted field surveys across two ecoregions (Middle Rockies and Great Plains) in the Clear Creek watershed, a sub-watershed of Wyomings Powder River Basin. We took direct measurements of stream gases using headspace sampling at thirty sites (8 June - 23 October). We observed the lowest and most variable concentrations in headwaters, which flow through a federally designated alpine wilderness area. By contrast, the Great Plains exhibited 1.45 and 4 times higher pCO2 and pCH4 concentrations and the relative contributions of methane increased downstream. Fluxes during snowmelt were 45% and 58% higher for CO2 and CH4 than during baseflow but overall were lower than estimates for other systems. Variability for pCO2 was highest during late summer and in the uppermost sections of the headwaters. The high heterogeneity and common undersaturation observed through space and time, especially in the mountains, suggests downscaled regional estimates may fail to capture variability in fluxes observed at these smaller scales. Based on these results, we strongly recommend higher resolution time series studies and increased scrutiny of systems at near equilibrium, inclusive of winter storage and ice-off events, to improve our understanding of the effects of seasonal dynamics on these processes.

Corrigendum: Mapping tree density at a global scale

Abstract Using a concept proposed by Stehman and Czaplewski (1997), we implemented spatially-explicit Monte Carlo simulations to test the effects of manually introduced horizontal positional error on standard inter-rater statistics derived from twelve classified high-resolution images. Through simulations we found that both overall and kappa accuracies decrease markedly with increasing error distance, varying greatly across distances relevant to practical application. The use of ground reference sites falling solely in homogeneous patches significantly improves inter-rater statistics and calls into question the use of kernel-smoothed data in one-time accuracy assessments. Our simulations offer insight into the scale of both structural and cover type heterogeneity across our landscapes, and support a new method for minimizing the effects of positional error on map accuracy. We recommend that analysts use caution when applying traditional accuracy assessment strategies to categorical maps, particularly when working with high-resolution imagery.

Modeling cougar habitat in the Northeastern United States

Mixture tuned matched filtering (MTMF) image classification capitalizes on the increasing spectral and spatial resolutions of available hyperspectral image data to identify the presence, and potent ...