CONTEXT: Published maps of global tree cover derived from Landsat data have indicated substantial changes in forest area from 2000 to 2012. The changes can be arranged in different patterns, with ...different consequences for forest fragmentation. Thus, the changes in forest area do not necessarily equate to changes in forest sustainability. OBJECTIVE: The objective is to assess global and regional changes in forest fragmentation in relation to the change of forest area from 2000 to 2012. METHODS: Using published global tree cover data, forest and forest interior areas were mapped in 2000 and 2012. The locations of forest interior change were compared to the locations of overall forest change to identify the direct (pixel level) and indirect (landscape level) components of forest interior change. The changes of forest interior area were compared to the changes of total forest area in each of 768 ecological regions. RESULTS: A 1.71 million km² (3.2 %) net loss of global forest area translated to a net loss of 3.76 million km² (9.9 %) of forest interior area. The difference in loss rates was consistent in most of the 768 ecological regions. The indirect component accounted for 2.44 million km² of the net forest interior change, compared to 1.32 million km² that was attributable to the direct component. CONCLUSION: Forest area loss alone from 2000 to 2012 underestimates ecological risks from forest fragmentation. In addition to the direct loss of forest, there was a widespread shift of the remaining global forest to a more fragmented condition.
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EMUNI, FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UL, UM, UPUK, VKSCE, ZAGLJ
Context
Pattern metrics drawn from image processing and remote sensing have been applied as descriptors of the texture of landscape gradient data. Like some classical pattern metrics in ecology, ...texture has several facets which are measured by examining an adjacency matrix—the frequencies of co-occurring pixel values on a map—in different ways.
Objectives
To improve the interpretation and application of such metrics in landscape ecology we reformulate and interpret several of them by analogy to traditional metrics used with categorical data.
Results and conclusions
1. Four of the eight classical texture metrics measure attraction—the tendency for the same or similar values to be adjacent. Four others measure dispersion—the diversity of adjacencies relative to the entire adjacency matrix, the diagonal of the matrix, or the origin of the matrix. 2. The attraction metrics (
dissimilarity
,
contrast
,
inverse difference
, and
homogeneity
) differ only in the algebraic weights applied to different parts of an adjacency matrix. 3. The dispersion metrics (
entropy
,
uniformity
,
difference entropy
, and
sum entropy
) can be made more comparable by rescaling them to their maximum possible values. 4. While the metrics may be applied to any adjacency matrix, the choices about the method used to create an adjacency matrix have subtle yet important implications for the use and comparability of some metrics.
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EMUNI, FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UL, UM, UPUK, VKSCE, ZAGLJ
The composition of tree species occurring in a forest is important and can be affected by global change drivers such as climate change. To inform assessment and projection of global change impacts at ...broad extents, we used hierarchical cluster analysis and over 120,000 recent forest inventory plots to empirically define forest tree assemblages across the U.S., and identified the indicator and dominant species associated with each. Cluster typologies in two levels of a hierarchy of forest assemblages, with 29 and 147 groups respectively, were supported by diagnostic criteria. Groups in these two levels of the hierarchy were labeled based on the top indicator species in each, and ranged widely in size. For example, in the 29-cluster typology, the sugar maple-red maple assemblage contained the largest number of plots (30,068), while the butternut-sweet birch and sourwood-scarlet oak assemblages were both smallest (6 plots each). We provide a case-study demonstration of the utility of the typology for informing forest climate change impact assessment. For five assemblages in the 29-cluster typology, we used existing projections of changes in importance value (IV) for the dominant species under one low and one high climate change scenario to assess impacts to the assemblages. Results ranged widely for each scenario by the end of the century, with each showing an average decrease in IV for dominant species in some assemblages, including the balsam fir-quaking aspen assemblage, and an average increase for others, like the green ash-American elm assemblage. Future work should assess adaptive capacity of these forest assemblages and investigate local population- and community-level dynamics in places where dominant species may be impacted. This typology will be ideal for monitoring, assessing, and projecting changes to forest communities within the emerging framework of macrosystems ecology, which emphasizes hierarchies and broad extents.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
As the future climate becomes hotter or drier, forests may be exposed to more frequent or severe droughts. To inform efforts to ensure resilient forests, it is critical to know which forests may be ...most exposed to future drought and where. Longer duration droughts lasting 2–3 years or more are especially important to quantify because forests are likely to experience impacts. We summarized exposure to 36‐month drought for forests across the conterminous United States using the Standardized Precipitation‐Evapotranspiration Index (SPEI) overlaid on forest inventory plot locations. Exposure was quantified under 10 scenarios that combined five modeled climates and two Representative Concentration Pathways (RCPs, 4.5 and 8.5) through 2070. Future projections indicate a tripling of the monthly spatial extent of forests exposed to severe or extreme drought—38% of forests were exposed on average by mid‐century as opposed to 11% during 1991–2020 (2041–2070). Increases in drought exposure were greatest under hotter (HadGEM2‐ES), drier (IPSL‐CM5A‐MR), and middle (NorESM1‐M) climate models, under either RCP. Projections agreed that forests in portions of the western United States, especially the southwestern United States, could face high levels of exposure. Forest types including pinyon/juniper, woodland hardwoods, and ponderosa pine were projected to be exposed to drought more than 50% of the time on average across all scenarios by mid‐century, when no forest type was exposed more than 25% of the time under any scenario during the recent period. Projections agreed less for the eastern United States, but in some scenarios, particularly under RCP 8.5, large portions of the East could be exposed to drought nearly as often as parts of the West. Moreover, a substantial portion of oak/hickory forests occur in eastern regions, where projections agree on increased drought exposure. This study provides novel insights about the changing conditions forests face in both the eastern and western United States. Our results can be combined with information about the sensitivities and adaptive capacities of forest ecosystems to prioritize drought adaptation efforts.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Context
Forest loss and fragmentation pose extreme threats to biodiversity. Their efficient characterization from remotely sensed data therefore has strong practical implications. Data are often ...separately analyzed for spatial fragmentation and disorder, but no existing metric simultaneously quantifies both the shape and arrangement of fragments.
Objectives
We present a fractal fragmentation and disorder index (FFDI), which advances a previously developed fractal index by merging it with the Rényi information dimension. The FFDI is designed to work across spatial scales, and to efficiently report both the fragmentation of images and their spatial disorder.
Methods
We validate the FFDI with 12,600 synthetic hierarchically structured random map (HRM) multiscale images, as well as several other categories of fractal and non-fractal test images (4880 images). We then apply the FFDI to satellite imagery of forest cover for 10 distinct regions of the Romanian Carpathian Mountains from 2000–2021.
Results
The FFDI outperformed its two individual components (fractal fragmentation index and Rényi information dimension) in resolving spatial patterns of disorder and fragmentation when tested on HRM classes and other image types. The FFDI thus offers a clear advantage when compared to the individual use of fractal fragmentation index and the Information Dimension, and provided good classification performance in an application to real data.
Conclusions
This work improves on previous characterizations of landscape patterns. With the FFDI, scientists will be able to better monitor and understand forest fragmentation from satellite imagery. The FFDI may also find wider applicability in biology wherever image analysis is used.
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EMUNI, FZAB, GEOZS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UL, UM, UPUK, VKSCE, ZAGLJ
The scale of investigation for disturbance-influenced processes plays a critical role in theoretical assumptions about stability, variance, and equilibrium, as well as conservation reserve and ...long-term monitoring program design. Critical consideration of scale is required for robust planning designs, especially when anticipating future disturbances whose exact locations are unknown. This research quantified disturbance proportion and pattern (as contagion) at multiple scales across North America. This pattern of scale-associated variability can guide selection of study and management extents, for example, to minimize variance (measured as standard deviation) between any landscapes within an ecoregion. We identified the proportion and pattern of forest disturbance (30 m grain size) across multiple landscape extents up to 180 km
2
. We explored the variance in proportion of disturbed area and the pattern of that disturbance between landscapes (within an ecoregion) as a function of the landscape extent. In many ecoregions, variance between landscapes within an ecoregion was minimal at broad landscape extents (low standard deviation). Gap-dominated regions showed the least variance, while fire-dominated showed the largest. Intensively managed ecoregions displayed unique patterns. A majority of the ecoregions showed low variance between landscapes at some scale, indicating an appropriate extent for incorporating natural regimes and unknown future disturbances was identified. The quantification of the scales of disturbance at the ecoregion level provides guidance for individuals interested in anticipating future disturbances which will occur in unknown spatial locations. Information on the extents required to incorporate disturbance patterns into planning is crucial for that process.
Conversion of natural land cover can degrade water quality in water supply watersheds and increase treatment costs for Public Water Systems (PWSs), but there are few studies that have fully evaluated ...land cover and water quality relationships in mixed use watersheds across broad hydroclimatic settings. We related upstream land cover (forest, other natural land covers, development, and agriculture) to observed and modeled water quality across the southeastern US and specifically at 1746 PWS drinking water intake facilities. While there was considerable complexity and variability in the relationship between land cover and water quality, results suggest that Total Nitrogen (TN), Total Phosphorus (TP) and Suspended Sediment (SS) concentrations decrease significantly with increasing forest cover, and increase with increasing developed or agricultural cover. Catchments with dominant (>90 %) agricultural land cover had the greatest export rates for TN, TP, and SS based on SPARROW model estimates, followed by developed-dominant, then forest- and other-natural-dominant catchments. Variability in modeled TN, TP, and SS export rates by land cover type was driven by variability in natural background sources and catchment characteristics that affected water quality even in forest-dominated catchments. Both intake setting (i.e., run-of-river or reservoir) and upstream land cover were important determinants of water quality at PWS intakes. Of all PWS intakes, 15 % had high raw water quality, and 85 % of those were on reservoirs. Of the run-of-river intakes with high raw water quality, 75 % had at least 50 % forest land cover upstream. In addition, PWS intakes obtaining surface water supply from smaller upstream catchments may experience the largest losses of natural land cover based on projections of land cover in 2070. These results illustrate the complexity and variability in the relationship between land cover and water quality at broad scales, but also suggest that forest conservation can enhance the resilience of drinking water supplies.
Display omitted
•Land cover and water quality were linked regionally and at public water intakes.•Nutrient and sediment concentrations decreased with increasing forest land cover.•Both intake setting and land cover were important determinants of water quality.•Small watersheds may experience the largest losses of natural land cover by 2070.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
Aim
We may be able to buffer biodiversity against the effects of ongoing climate change by prioritizing the protection of habitat with diverse physical features (high geodiversity) associated with ...ecological and evolutionary mechanisms that maintain high biodiversity. Nonetheless, the relationships between biodiversity and habitat vary with spatial and biological context. In this study, we compare how well habitat geodiversity (spatial variation in abiotic processes and features) and climate explain biodiversity patterns of birds and trees. We also evaluate the consistency of biodiversity–geodiversity relationships across ecoregions.
Location
Contiguous USA.
Time period
2007–2016.
Taxa studied
Birds and trees.
Methods
We quantified geodiversity with remotely sensed data and generated biodiversity maps from the Forest Inventory and Analysis and Breeding Bird Survey datasets. We fitted multivariate regressions to alpha, beta and gamma diversity, accounting for spatial autocorrelation among Nature Conservancy ecoregions and relationships among taxonomic, phylogenetic and functional biodiversity. We fitted models including climate alone (temperature and precipitation), geodiversity alone (topography, soil and geology) and climate plus geodiversity.
Results
A combination of geodiversity and climate predictor variables fitted most forms of bird and tree biodiversity with < 10% relative error. Models using geodiversity and climate performed better for local (alpha) and regional (gamma) diversity than for turnover‐based (beta) diversity. Among geodiversity predictors, variability of elevation fitted biodiversity best; interestingly, topographically diverse places tended to have higher tree diversity but lower bird diversity.
Main conclusions
Although climatic predictors tended to have larger individual effects than geodiversity, adding geodiversity improved climate‐only models of biodiversity. Geodiversity was correlated with biodiversity more consistently than with climate across ecoregions, but models tended to have a poor fit in ecoregions held out of the training dataset. Patterns of geodiversity could help to prioritize conservation efforts within ecoregions. However, we need to understand the underlying mechanisms more fully before we can build models transferable across ecoregions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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