Geology topics

James A. Lutz

Publications and source records attributed to James A. Lutz.

16 recordsLinked to original sources

USGS2024

The relationship between maturation size and maximum tree size from tropical to boreal climates

The fundamental trade-off between current and future reproduction has long been considered to result in a tendency for species that can grow large to begin reproduction at a proportionately larger size. Due to the prolonged time required to reach maturity, estimates of tree maturation size remain unavailable and we lack a global view on the generality and the shape of this trade-off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree pecies spanning tropical to boreal climates. Results show that a species’ maturation size increases with maximum size, but in a non-proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation size were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. These findings on maturation size drivers are key to accurately represent forests’ responses to disturbance and climate change.

Ecology Letters↗

USGS2023

Masting is uncommon in trees that depend on mutualist dispersers in the context of global climate and fertility gradients

The benefits of masting (volatile, quasi-synchronous seed production at lagged intervals) include satiation of seed predators, but these benefits come with a cost to mutualist pollen and seed dispersers. If the evolution of masting represents a balance between these benefits and costs, we expect mast avoidance in species that are heavily reliant on mutualist dispersers. These effects play out in the context of variable climate and site fertility among species that vary widely in nutrient demand. Meta-analyses of published data have focused on variation at the population scale, thus omitting periodicity within trees and synchronicity between trees. From raw data on 12 million tree-years worldwide, we quantified three components of masting that have not previously been analysed together: (i) volatility, defined as the frequency-weighted year-to-year variation; (ii) periodicity, representing the lag between high-seed years; and (iii) synchronicity, indicating the tree-to-tree correlation. Results show that mast avoidance (low volatility and low synchronicity) by species dependent on mutualist dispersers explains more variation than any other effect. Nutrient-demanding species have low volatility, and species that are most common on nutrient-rich and warm/wet sites exhibit short periods. The prevalence of masting in cold/dry sites coincides with climatic conditions where dependence on vertebrate dispersers is less common than in the wet tropics. Mutualist dispersers neutralize the benefits of masting for predator satiation, further balancing the effects of climate, site fertility and nutrient demands.

Nature Plants↗

USGS2023

Linking seed size and number to trait syndromes in trees

Aim Our understanding of the mechanisms that maintain forest diversity under changing climate can benefit from knowledge about traits that are closely linked to fitness. We tested whether the link between traits and seed number and seed size is consistent with two hypotheses, termed the leaf economics spectrum and the plant size syndrome, or whether reproduction represents an independent dimension related to a seed size–seed number trade-off. Location Most of the data come from Europe, North and Central America and East Asia. A minority of the data come from South America, Africa and Australia. Time period 1960–2022. Major taxa studied Trees. Methods We gathered 12 million observations of the number of seeds produced in 784 tree species. We estimated the number of seeds produced by individual trees and scaled it up to the species level. Next, we used principal components analysis and generalized joint attribute modelling (GJAM) to map seed number and size on the tree traits spectrum. Results Incorporating seed size and number into trait analysis while controlling for environment and phylogeny with GJAM exposes relationships in trees that might otherwise remain hidden. Production of the large total biomass of seeds [product of seed number and seed size; hereafter, species seed productivity (SSP)] is associated with high leaf area, low foliar nitrogen, low specific leaf area (SLA) and dense wood. Production of high seed numbers is associated with small seeds produced by nutrient-demanding species with softwood, small leaves and high SLA. Trait covariation is consistent with opposing strategies: one fast-growing, early successional, with high dispersal, and the other slow-growing, stress-tolerant, that recruit in shaded conditions. Main conclusions Earth system models currently assume that reproductive allocation is indifferent among plant functional types. Easily measurable seed size is a strong predictor of the seed number and species seed productivity. The connection of SSP with the functional traits can form the first basis of improved fecundity prediction across global forests.

Global Ecology and Biogeography↗

USGS2022

Limits to reproduction and seed size-number trade-offs that shape forest dominance and future recovery

The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential.

Nature Communications↗

USGS2022

Globally, tree fecundity exceeds productivity gradients

Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data shows a 250-fold increase in seed abundance from cold-dry to warm-wet climates, driven primarily by a 100-fold increase in seed production for a given tree size. The modest (threefold) increase in forest productivity across the same climate gradient cannot explain the magnitudes of these trends. The increase in seeds per tree can arise from adaptive evolution driven by intense species interactions or from the direct effects of a warm, moist climate on tree fecundity. Either way, the massive differences in seed supply ramify through food webs potentially explaining a disproportionate role for species interactions in the wet tropics.

Ecology Letters↗

USGS2022

Crowding, climate, and the case for social distancing among trees

In an emerging era of megadisturbance, bolstering forest resilience to wildfire, insects, and drought has become a central objective in many western forests. Climate has received considerable attention as a driver of these disturbances, but few studies have examined the complexities of climate–vegetation–disturbance interactions. Current strategies for creating resilient forests often rely on retrospective approaches, seeking to impart resilience by restoring historical conditions to contemporary landscapes, but historical conditions are becoming increasingly unattainable amidst modern bioclimatic conditions. What becomes an appropriate benchmark for resilience when we have novel forests, rapidly changing climate, and unprecedented disturbance regimes? We combined two longitudinal datasets—each representing some of the most comprehensive spatially explicit, annual tree mortality data in existence—in a post-hoc factorial design to examine the nonlinear relationships between fire, climate, forest spatial structure, and bark beetles. We found that while prefire drought elevated mortality risk, advantageous local neighborhoods could offset these effects. Surprisingly, mortality risk ( P m ) was higher in crowded local neighborhoods that burned in wet years ( P m = 42%) compared with sparse neighborhoods that burned during drought ( P m = 30%). Risk of beetle attack was also increased by drought, but lower conspecific crowding impeded the otherwise positive interaction between fire and beetle attack. Antecedent fire increased drought-related mortality over short timespans (<7 years) but reduced mortality over longer intervals. These results clarify interacting disturbance dynamics and provide a mechanistic underpinning for forest restoration strategies. Importantly, they demonstrate the potential for managed fire and silvicultural strategies to offset climate effects and bolster resilience to fire, beetles, and drought.

California↗

USGS2021

Joint effects of climate, tree size, and year on annual tree growth derived using tree-ring records of ten globally distributed forests

Tree rings provide an invaluable long-term record for understanding how climate and other drivers shape tree growth and forest productivity. However, conventional tree-ring analysis methods were not designed to simultaneously account for the effects of climate, tree size, and other drivers on individual growth, which has limited the potential to use tree rings to understand forest productivity, its climate sensitivity, and its global change responses. Here, we develop and apply a new method to simultaneously model non-linear effects of primary climate drivers, reconstructed tree diameter (DBH), and year in generalized least squares models that account for the temporal autocorrelation inherent to each individual tree’s growth. We analyze data from 3811 trees representing 40 species at 10 globally distributed sites, showing that precipitation, temperature, DBH, and calendar year have additively, and often interactively, influenced annual growth over the past 120 years. Growth responses were predominantly positive to precipitation (usually over ≥ 3-month seasonal windows) and negative to temperature (usually over ≤ 3-month seasonal windows), with both included in 78% of top models, and with non-linear responses prevalent (63% of relationships). Climate sensitivity commonly varied with DBH (44% of cases tested). Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently peaked at intermediate DBH and declined thereafter. Accounting for climate and DBH, growth rate declined over time for 92% of species in secondary or disturbed stands, whereas growth trends were mixed in older forests. These trends were largely attributable to stand dynamics as cohorts and stands age, which remain challenging to disentangle from global change drivers. By providing a parsimonious approach for characterizing multiple interacting drivers of tree growth, our method reveals a more complete picture of the factors influencing growth than has previously been possible.

Indiana, Massachusetts, New Mexico, Nebraska, Utah↗

USGS2021

Is there tree senescence? The fecundity evidence

Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size–fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.

Proceedings of the National Academy of Sciences↗

USGS2021

Continent-wide tree fecundity driven by indirect climate effects

Indirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates.

Nature Communications↗

USGS2021

Determination of burn severity models ranging from regional to continental scales for the conterminous United States

Identifying meaningful measures of ecological change over large areas is dependent on the quantification of robust relationships between ecological metrics and remote sensing products. Over the past several decades, ground observations of wildfire and prescribed fire severity have been acquired across hundreds of wildland fires in the United States, primarily utilizing the Composite Burn Index (CBI) plot protocol. These observations have been coupled to spaceborne passive spectral reflectance indices (e.g. Landsat-derived variations of the Normalized Burn Ratio [NBR]) to produce regression models describing their relationship. Here we develop regression models by vegetation type for multiple vegetation classification systems representing a range of spatial scales, and a decision tree framework for evaluating these regression models. Our overall goals were to determine which scale of ecological classifications provided the best estimate of burn severity from Landsat data and how to choose the best regression model. We aggregated a total of 6280 CBI plots for 234 wildland fires that burned between 1994 and 2017 and produced Landsat-derived NBR and differenced NBR (dNBR) values for each plot. We then calculated best fit linear or higher order regression equations between CBI and NBR/dNBR for each landcover classification system from smallest to largest scale: LANDFIRE Biophysical Settings (BPS), National Vegetation Classification macrogroup (NVC) landcover classifications, Omernick III, II, and I ecoregions, LANDFIRE Fire Regime Groups (FRG), and the entire conterminous United States (CONUS) dataset. The CONUS regression model goodness of fit was moderate (R 2 = 0.55, P < 0.001) for dNBR and poor (R 2 = 0.30, P < 0.001) for NBR. Within landcover classifications, CBI was better fit by dNBR than NBR. Finer scale regional regression models including BPS (dNBR R 2 ¯ "> R2¯ = 0.56 and 0.00–0.83 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.43 and 0.00–0.82 R 2 range) and NVC (dNBR R 2 ¯ "> R(bar) 2 = 0.55 and 0.15–0.78 R 2 range; NBR R 2 ¯ "> R(bar) 2 = 0.41 and 0.00–0.79 R 2 range) were on average the same or better than the CONUS models for dNBR and NBR, with the strongest fit models exhibiting R 2 ≥ 0.70, whereas larger scale regional models R 2 ¯ "> R(bar) 2 ranged from 0.28 to 0.5. However, variation in accuracy among landcover types indicate that dNBR and NBR regression models could be used to effectively estimate CBI for future fires in certain regions, while for other regions models may require additional field observations or alternative spectral transformations. Our decision tree schema can be used to help users determine which scale is likely to produce the most accurate results using our models. The CBI regression models developed here, paired with the decision tree, provide users with a simple method to estimate burn severity in units of CBI for any fire within CONUS with moderate to high levels of confidence and provide a template for further development of models with new data going forward.

Conterminous United States↗

USGS2020

The distribution of woody species in relation to climate and fire in Yosemite National Park, California, USA

Background The effects of climate on plant species ranges are well appreciated, but the effects of other processes, such as fire, on plant species distribution are less well understood. We used a dataset of 561 plots 0.1 ha in size located throughout Yosemite National Park, in the Sierra Nevada of California, USA, to determine the joint effects of fire and climate on woody plant species. We analyzed the effect of climate (annual actual evapotranspiration [AET], climatic water deficit [Deficit]) and fire characteristics (occurrence [BURN] for all plots, fire return interval departure [FRID] for unburned plots, and severity of the most severe fire [dNBR]) on the distribution of woody plant species. Results Of 43 species that were present on at least two plots, 38 species occurred on five or more plots. Of those 38 species, models for the distribution of 13 species (34%) were significantly improved by including the variable for fire occurrence (BURN). Models for the distribution of 10 species (26%) were significantly improved by including FRID, and two species (5%) were improved by including dNBR. Species for which distribution models were improved by inclusion of fire variables included some of the most areally extensive woody plants. Species and ecological zones were aligned along an AET-Deficit gradient from cool and moist to hot and dry conditions. Conclusions In fire-frequent ecosystems, such as those in most of western North America, species distribution models were improved by including variables related to fire. Models for changing species distributions would also be improved by considering potential changes to the fire regime.

California↗

USGS2018

Individual species–area relationships in temperate coniferous forests

Questions What drives individual species–area relationships in temperate coniferous forests? Location Two 25.6‐ha forest plots on the Pacific Slope of North America, one in California, and one in Washington State. Methods We mapped all trees ≥1 cm in diameter and examined tree species diversity of their local neighbourhoods by calculating the individual species–area relationship for each species and for each of three diameter classes (saplings, mature trees and large‐diameter trees). Results In the California plot, small trees in four of the five major species occurred in neighbourhoods with higher levels of diversity than would be expected at random. In the Washington plot, small trees for four of five abundant species had neighbourhoods with lower than expected diversity at distances ≤5 m for small trees. However, at distances >5 m, all five species showed higher than expected diversity in their neighbourhoods. Larger trees at both plots tended to occur in neighbourhoods with lower than expected diversity, and no large‐diameter focal species had neighbourhoods with higher than expected diversity. Conclusion Diversity and co‐existence in temperate conifer‐dominated forests do not appear to be the result of random processes. Competitive interactions appear to dominate for the largest trees of most species, resulting in neighbourhoods with lower diversity. For smaller trees, we suggest that a positive response to environmental heterogeneity is the likely driver of neighbourhoods with higher than expected diversity, although we cannot rule out the possibility that facilitation or conspecific negative density dependence (CNDD) also play a role.

Journal of Vegetation Science↗

USGS2017

Fire and the distribution and uncertainty of carbon sequestered as above-ground tree biomass in Yosemite and Sequoia & Kings Canyon National Parks

Fire is one of the principal agents changing forest carbon stocks and landscape level distributions of carbon, but few studies have addressed how accurate carbon accounting of fire-killed trees is or can be. We used a large number of forested plots (1646), detailed selection of species-specific and location-specific allometric equations, vegetation type maps with high levels of accuracy, and Monte Carlo simulation to model the amount and uncertainty of aboveground tree carbon present in tree species (hereafter, carbon) within Yosemite and Sequoia & Kings Canyon National Parks. We estimated aboveground carbon in trees within Yosemite National Park to be 25 Tg of carbon (C) (confidence interval (CI): 23–27 Tg C), and in Sequoia & Kings Canyon National Park to be 20 Tg C (CI: 18–21 Tg C). Low-severity and moderate-severity fire had little or no effect on the amount of carbon sequestered in trees at the landscape scale, and high-severity fire did not immediately consume much carbon. Although many of our data inputs were more accurate than those used in similar studies in other locations, the total uncertainty of carbon estimates was still greater than ±10%, mostly due to potential uncertainties in landscape-scale vegetation type mismatches and trees larger than the ranges of existing allometric equations. If carbon inventories are to be meaningfully used in policy, there is an urgent need for more accurate landscape classification methods, improvement in allometric equations for tree species, and better understanding of the uncertainties inherent in existing carbon accounting methods.

California↗

USGS2017

Plant diversity increases with the strength of negative density dependence at the global scale

Theory predicts that higher biodiversity in the tropics is maintained by specialized interactions among plants and their natural enemies that result in conspecific negative density dependence (CNDD). By using more than 3000 species and nearly 2.4 million trees across 24 forest plots worldwide, we show that global patterns in tree species diversity reflect not only stronger CNDD at tropical versus temperate latitudes but also a latitudinal shift in the relationship between CNDD and species abundance. CNDD was stronger for rare species at tropical versus temperate latitudes, potentially causing the persistence of greater numbers of rare species in the tropics. Our study reveals fundamental differences in the nature of local-scale biotic interactions that contribute to the maintenance of species diversity across temperate and tropical communities.

Science↗

USGS2014

Assessing fire effects on forest spatial structure using a fusion of Landsat and airborne LiDAR data in Yosemite National Park

Mosaics of tree clumps and openings are characteristic of forests dominated by frequent, low- and moderate-severity fires. When restoring these fire-suppressed forests, managers often try to reproduce these structures to increase ecosystem resilience. We examined unburned and burned forest structures for 1937 0.81 ha sample areas in Yosemite National Park, USA. We estimated severity for fires from 1984 to 2010 using the Landsat-derived Relativized differenced Normalized Burn Ratio (RdNBR) and measured openings and canopy clumps in five height strata using airborne LiDAR data. Because our study area lacked concurrent field data, we identified methods to allow structural analysis using LiDAR data alone. We found three spatial structures, canopy-gap, clump-open, and open, that differed in spatial arrangement and proportion of canopy and openings. As fire severity increased, the total area in canopy decreased while the number of clumps increased, creating a patchwork of openings and multistory tree clumps. The presence of openings > 0.3 ha, an approximate minimum gap size needed to favor shade-intolerant pine regeneration, increased rapidly with loss of canopy area. The range and variation of structures for a given fire severity were specific to each forest type. Low- to moderate-severity fires best replicated the historic clump-opening patterns that were common in forests with frequent fire regimes. Our results suggest that managers consider the following goals for their forest restoration: 1) reduce total canopy cover by breaking up large contiguous areas into variable-sized tree clumps and scattered large individual trees; 2) create a range of opening sizes and shapes, including ~ 50% of the open area in gaps > 0.3 ha; 3) create multistory clumps in addition to single story clumps; 4) retain historic densities of large trees; and 5) vary treatments to include canopy-gap, clump-open, and open mosaics across project areas to mimic the range of patterns found for each forest type in our study.

California↗

USGS2013

Landscape-scale effects of fire severity on mixed-conifer and red fir forest structure in Yosemite National Park

While fire shapes the structure of forests and acts as a keystone process, the details of how fire modifies forest structure have been difficult to evaluate because of the complexity of interactions between fires and forests. We studied this relationship across 69.2 km2 of Yosemite National Park, USA, that was subject to 32 fires ⩾40 ha between 1984 and 2010. Forests types included ponderosa pine ( Pinus ponderosa ), white fir-sugar pine ( Abies concolor/Pinus lambertiana ), and red fir ( Abies magnifica ). We estimated and stratified burned area by fire severity using the Landsat-derived Relativized differenced Normalized Burn Ratio (RdNBR). Airborne LiDAR data, acquired in July 2010, measured the vertical and horizontal structure of canopy material and landscape patterning of canopy patches and gaps. Increasing fire severity changed structure at the scale of fire severity patches, the arrangement of canopy patches and gaps within fire severity patches, and vertically within tree clumps. Each forest type showed an individual trajectory of structural change with increasing fire severity. As a result, the relationship between estimates of fire severity such as RdNBR and actual changes appears to vary among forest types. We found three arrangements of canopy patches and gaps associated with different fire severities: canopy-gap arrangements in which gaps were enclosed in otherwise continuous canopy (typically unburned and low fire severities); patch-gap arrangements in which tree clumps and gaps alternated and neither dominated (typically moderate fire severity); and open-patch arrangements in which trees were scattered across open areas (typically high fire severity). Compared to stands outside fire perimeters, increasing fire severity generally resulted first in loss of canopy cover in lower height strata and increased number and size of gaps, then in loss of canopy cover in higher height strata, and eventually the transition to open areas with few or no trees. However, the estimated fire severities at which these transitions occurred differed for each forest type. Our work suggests that low severity fire in red fir forests and moderate severity fire in ponderosa pine and white fir-sugar pine forests would restore vertical and horizontal canopy structures believed to have been common prior to the start of widespread fire suppression in the early 1900s. The fusion of LiDAR and Landsat data identified post-fire structural conditions that would not be identified by Landsat alone, suggesting a broad applicability of combining Landsat and LiDAR data for landscape-scale structural analysis for fire management.

California↗