Predicting vulnerability of forest patches to invasion by non-native plants for landscape scale management.

As a leading cause of forest health degradation, non-native invasive plant species are a key focus for many forest management and conservation efforts. These efforts come at a high price for resource-limited agencies and organizations making cost-effectiveness an important objective of invasion response plans. In this paper, we present an approach to guide the prioritization of locations for invasion management using species distribution models that account for the non-equilibrium of invasive species distributions and use readily available land use data as the primary explanatory variables. This approach takes advantage of the relatively high spatial resolution, as well as the broad, continuous geographic coverage, of land use data to provide results at a landscape scale relevant to practitioners responsible for invasive species management. In our example from northern Virginia, we simultaneously modeled a suite of invasive plant species to identify common indicators of invasion. We found that the proportions of surrounding non-forested land use types (grasses, crops, and development) were the most common and strongest indicators of invasion risk. These outcomes can guide managers of large protected areas to focus on major divides between forest and non-forest land over linear disturbances. We also found useful species-specific traits that can inform specific management actions. Additionally, we demonstrate through a case study how organizations that manage multiple smaller properties can take advantage of the projected distribution maps when considering acquiring or administering properties.

Counting the Capital's cats: Estimating drivers of abundance of free-roaming cats with a novel hierarchical model.

Free-roaming cats are a conservation concern in many areas but identifying their impacts and developing mitigation strategies requires a robust understanding of their distribution and density patterns. Urban and residential areas may be especially relevant in this process because free-roaming cats are abundant in these anthropogenic landscapes. Here, we estimate the occupancy and density of free-roaming cats in Washington D.C. and relate these metrics to known landscape and social factors. We conducted an extended camera trap survey of public and private spaces across D.C. and analyzed data collected from 1483 camera deployments from 2018 to 2020. We estimated citywide cat distribution by fitting hierarchical occupancy models and further estimated cat abundance using a novel random thinning spatial capture-recapture model that allows for the use of photos that can and cannot be identified to individual. Within this model, we utilized individual covariates that provided identity exclusions between photos of unidentifiable cats with inconsistent coat patterns, thus increasing the precision of abundance estimates. This combined model also allowed for unbiased estimation of density when animals cannot be identified to individual at the same rate as for free-roaming cats whose identifiability depended on their coat characteristics. Cat occupancy and abundance declined with increasing distance from residential areas, an effect that was more pronounced in wealthier neighborhoods. There was noteworthy absence of cats detected in larger public spaces and forests. Realized densities ranged from 0.02 to 1.75 cats/ha in sampled areas, resulting in a district-wide estimate of ~7296 free-roaming cats. Ninety percent of cat detections lacked collars and nearly 35% of known individuals were ear-tipped, indicative of district Trap-Neuter-Return (TNR) programs. These results suggest that we mainly sampled and estimated the unowned cat subpopulation, such that indoor/outdoor housecats were not well represented. The precise estimation of cat population densities is difficult due to the varied behavior of subpopulations within free-roaming cat populations (housecats, stray and feral cats), but our methods provide a first step in establishing citywide baselines to inform data-driven management plans for free-roaming cats in urban environments.

Warm springs alter timing but not total growth of temperate deciduous trees.

As the climate changes, warmer spring temperatures are causing earlier leaf-out1-3 and commencement of CO2 uptake1,3 in temperate deciduous forests, resulting in a tendency towards increased growing season length3 and annual CO2 uptake1,3-7. However, less is known about how spring temperatures affect tree stem growth8,9, which sequesters carbon in wood that has a long residence time in the ecosystem10,11. Here we show that warmer spring temperatures shifted stem diameter growth of deciduous trees earlier but had no consistent effect on peak growing season length, maximum growth rates, or annual growth, using dendrometer band measurements from 440 trees across two forests. The latter finding was confirmed on the centennial scale by 207 tree-ring chronologies from 108 forests across eastern North America, where annual ring width was far more sensitive to temperatures during the peak growing season than in the spring. These findings imply that any extra CO2 uptake in years with warmer spring temperatures4,5 does not significantly contribute to increased sequestration in long-lived woody stem biomass. Rather, contradicting projections from global carbon cycle models1,12, our empirical results imply that warming spring temperatures are unlikely to increase woody productivity enough to strengthen the long-term CO2 sink of temperate deciduous forests.

Joint effects of climate, tree size, and year on annual tree growth derived from 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 test effects of climate, tree size, and other drivers on individual growth. This has limited the potential to test ecologically relevant hypotheses on tree growth sensitivity to environmental drivers and their interactions with tree size. Here, we develop and apply a new method to simultaneously model nonlinear effects of primary climate drivers, reconstructed tree diameter at breast height (DBH), and calendar 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 maximum temperature, over ≤3-month seasonal windows), with concave-down responses in 63% of relationships. Climate sensitivity commonly varied with DBH (45% of cases tested), with larger trees usually more sensitive. Trends in ring width at small DBH were linked to the light environment under which trees established, but basal area or biomass increments consistently reached maxima at intermediate DBH. 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.

Global patterns of forest autotrophic carbon fluxes.

Carbon (C) fixation, allocation, and metabolism by trees set the basis for energy and material flows in forest ecosystems and define their interactions with Earth's changing climate. However, while many studies have considered variation in productivity with latitude and climate, we lack a cohesive synthesis on how forest carbon fluxes vary globally with respect to climate and one another. Here, we draw upon 1,319 records from the Global Forest Carbon Database, representing all major forest types and the nine most significant autotrophic carbon fluxes, to comprehensively review how annual C cycling in mature, undisturbed forests varies with latitude and climate on a global scale. Across all flux variables analyzed, rates of C cycling decreased continuously with absolute latitude-a finding that confirms multiple previous studies and contradicts the idea that net primary productivity of temperate forests rivals that of tropical forests. C flux variables generally displayed similar trends across latitude and multiple climate variables, with no differences in allocation detected at this global scale. Temperature variables in general, and mean annual temperature or temperature seasonality in particular, were the best single predictors of C flux, explaining 19%-71% of variation in the C fluxes analyzed. The effects of temperature were modified by moisture availability, with C flux reduced under hot and dry conditions and sometimes under very high precipitation. Annual C fluxes increased with growing season length and were also influenced by growing season climate. These findings clarify how forest C flux varies with latitude and climate on a global scale. In an era when forests will play a critical yet uncertain role in shaping Earth's rapidly changing climate, our synthesis provides a foundation for understanding global patterns in forest C cycling.

Leaf turgor loss point shapes local and regional distributions of evergreen but not deciduous tropical trees.

The effects of climate change on tropical forests will depend on how diverse tropical tree species respond to drought. Current distributions of evergreen and deciduous tree species across local and regional moisture gradients reflect their ability to tolerate drought stress, and might be explained by functional traits. We measured leaf water potential at turgor loss (i.e. 'wilting point'; πtlp ), wood density (WD) and leaf mass per area (LMA) on 50 of the most abundant tree species in central Panama. We then tested their ability to explain distributions of evergreen and deciduous species within a 50 ha plot on Barro Colorado Island and across a 70 km rainfall gradient spanning the Isthmus of Panama. Among evergreen trees, species with lower πtlp were associated with drier habitats, with πtlp explaining 28% and 32% of habitat association on local and regional scales, respectively, greatly exceeding the predictive power of WD and LMA. In contrast, πtlp did not predict habitat associations among deciduous species. Across spatial scales, πtlp is a useful indicator of habitat preference for tropical tree species that retain their leaves during periods of water stress, and holds the potential to predict vegetation responses to climate change.

Tree height and leaf drought tolerance traits shape growth responses across droughts in a temperate broadleaf forest.

As climate change drives increased drought in many forested regions, mechanistic understanding of the factors conferring drought tolerance in trees is increasingly important. The dendrochronological record provides a window through which we can understand how tree size and traits shape growth responses to droughts. We analyzed tree-ring records for 12 species in a broadleaf deciduous forest in Virginia (USA) to test hypotheses for how tree height, microenvironment characteristics, and species' traits shaped drought responses across the three strongest regional droughts over a 60-yr period. Drought tolerance (resistance, recovery, and resilience) decreased with tree height, which was strongly correlated with exposure to higher solar radiation and evaporative demand. The potentially greater rooting volume of larger trees did not confer a resistance advantage, but marginally increased recovery and resilience, in sites with low topographic wetness index. Drought tolerance was greater among species whose leaves lost turgor (wilted) at more negative water potentials and experienced less shrinkage upon desiccation. The tree-ring record reveals that tree height and leaf drought tolerance traits influenced growth responses during and after significant droughts in the meteorological record. As climate change-induced droughts intensify, tall trees with drought-sensitive leaves will be most vulnerable to immediate and longer-term growth reductions.

Mapping carbon accumulation potential from global natural forest regrowth.

To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy.

Growing season moisture drives interannual variation in woody productivity of a temperate deciduous forest.

The climate sensitivity of forest ecosystem woody productivity (ANPPstem ) influences carbon cycle responses to climate change. For the first time, we combined long-term annual growth and forest census data of a diverse temperate broadleaf deciduous forest, seeking to resolve whether ANPPstem is primarily moisture- or energy-limited and whether climate sensitivity has changed in recent decades characterised by more mesic conditions and elevated CO2 . We analysed tree-ring chronologies across 109 yr of monthly climatic variation (1901-2009) for 14 species representing 97% of ANPPstem in a 25.6 ha plot in northern Virginia, USA. Radial growth of most species and ecosystem-level ANPPstem responded positively to cool, moist growing season conditions, but the same conditions in the previous May-July were associated with reduced growth. In recent decades (1980-2009), responses were more variable and, on average, weaker. Our results indicated that woody productivity is primarily limited by current growing season moisture, as opposed to temperature or sunlight, but additional complexity in climate sensitivity may reflect the use of stored carbohydrate reserves. Overall, while such forests currently display limited moisture sensitivity, their woody productivity is likely to decline under projected hotter and potentially drier growing season conditions.

ForC: a global database of forest carbon stocks and fluxes.

Forests play an influential role in the global carbon (C) cycle, storing roughly half of terrestrial C and annually exchanging with the atmosphere more than five times the carbon dioxide (CO2 ) emitted by anthropogenic activities. Yet, scaling up from field-based measurements of forest C stocks and fluxes to understand global scale C cycling and its climate sensitivity remains an important challenge. Tens of thousands of forest C measurements have been made, but these data have yet to be integrated into a single database that makes them accessible for integrated analyses. Here we present an open-access global Forest Carbon database (ForC) containing previously published records of field-based measurements of ecosystem-level C stocks and annual fluxes, along with disturbance history and methodological information. ForC expands upon the previously published tropical portion of this database, TropForC (https://doi.org/10.5061/dryad.t516f), now including 17,367 records (previously 3,568) representing 2,731 plots (previously 845) in 826 geographically distinct areas. The database covers all forested biogeographic and climate zones, represents forest stands of all ages, and currently includes data collected between 1934 and 2015. We expect that ForC will prove useful for macroecological analyses of forest C cycling, for evaluation of model predictions or remote sensing products, for quantifying the contribution of forests to the global C cycle, and for supporting international efforts to inventory forest carbon and greenhouse gas exchange. A dynamic version of ForC is maintained at on GitHub (https://GitHub.com/forc-db), and we encourage the research community to collaborate in updating, correcting, expanding, and utilizing this database. ForC is an open access database, and we encourage use of the data for scientific research and education purposes. Data may not be used for commercial purposes without written permission of the database PI. Any publications using ForC data should cite this publication and Anderson-Teixeira et al. (2016a) (see Metadata S1). No other copyright or cost restrictions are associated with the use of this data set.

Role of tree size in moist tropical forest carbon cycling and water deficit responses.

Drought disproportionately affects larger trees in tropical forests, but implications for forest composition and carbon (C) cycling in relation to dry season intensity remain poorly understood. In order to characterize how C cycling is shaped by tree size and drought adaptations and how these patterns relate to spatial and temporal variation in water deficit, we analyze data from three forest dynamics plots spanning a moisture gradient in Panama that have experienced El Niño droughts. At all sites, aboveground C cycle contributions peaked below 50-cm stem diameter, with stems ≥ 50 cm accounting for on average 59% of live aboveground biomass, 45% of woody productivity and 49% of woody mortality. The dominance of drought-avoidance strategies increased interactively with stem diameter and dry season intensity. Although size-related C cycle contributions did not vary systematically across the moisture gradient under nondrought conditions, woody mortality of larger trees was disproportionately elevated under El Niño drought stress. Thus, large (> 50 cm) stems, which strongly mediate but do not necessarily dominate C cycling, have drought adaptations that compensate for their more challenging hydraulic environment, particularly in drier climates. However, these adaptations do not fully buffer the effects of severe drought, and increased large tree mortality dominates ecosystem-level drought responses.

Tree Circumference Dynamics in Four Forests Characterized Using Automated Dendrometer Bands.

Stem diameter is one of the most commonly measured attributes of trees, forming the foundation of forest censuses and monitoring. Changes in tree stem circumference include both irreversible woody stem growth and reversible circumference changes related to water status, yet these fine-scale dynamics are rarely leveraged to understand forest ecophysiology and typically ignored in plot- or stand-scale estimates of tree growth and forest productivity. Here, we deployed automated dendrometer bands on 12-40 trees at four different forested sites-two temperate broadleaf deciduous, one temperate conifer, and one tropical broadleaf semi-deciduous-to understand how tree circumference varies on time scales of hours to months, how these dynamics relate to environmental conditions, and whether the structure of these variations might introduce substantive error into estimates of woody growth. Diurnal stem circumference dynamics measured over the bark commonly-but not consistently-exhibited daytime shrinkage attributable to transpiration-driven changes in stem water storage. The amplitude of this shrinkage was significantly correlated with climatic variables (daily temperature range, vapor pressure deficit, and radiation), sap flow and evapotranspiration. Diurnal variations were typically <0.5 mm circumference in amplitude and unlikely to be of concern to most studies of tree growth. Over time scales of multiple days, the bands captured circumference increases in response to rain events, likely driven by combinations of increased stem water storage and bark hydration. Particularly at the tropical site, these rain responses could be quite substantial, ranging up to 1.5 mm circumference expansion within 48 hours following a rain event. We conclude that over-bark measurements of stem circumference change sometimes correlate with but have limited potential for directly estimating daily transpiration, but that they can be valuable on time scales of days to weeks for characterizing changes in stem growth and hydration.