Remote sensing tracks daily radial wood growth of evergreen needleleaf trees

Relationships between gross primary productivity (GPP) and the remotely sensed photochemical reflectance index (PRI) suggest that time series of foliar PRI may provide insight into climate change effects on carbon cycling. However, because a large fraction of carbon assimilated via GPP is quickly returned to the atmosphere via respiration, we ask a critical question—can PRI time series provide information about longer term gains in aboveground carbon stocks? Here we study the suitability of PRI time series to understand intra‐annual stem‐growth dynamics at one of the world's largest terrestrial carbon pools—the boreal forest. We hypothesized that PRI time series can be used to determine the onset (hypothesis 1) and cessation (hypothesis 2) of radial growth and enable tracking of intra‐annual tree growth dynamics (hypothesis 3). Tree‐level measurements were collected in 2018 and 2019 to link highly temporally resolved PRI observations unambiguously with information on daily radial tree growth collected via point dendrometers. We show that the seasonal onset of photosynthetic activity as determined by PRI time series was significantly earlier (p < .05) than the onset of radial tree growth determined from the point dendrometer time series which does not support our first hypothesis. In contrast, seasonal decline of photosynthetic activity and cessation of radial tree growth was not significantly different (p > .05) when derived from PRI and dendrometer time series, respectively, supporting our second hypothesis. Mixed‐effects modeling results supported our third hypothesis by showing that the PRI was a statistically significant (p < .0001) predictor of intra‐annual radial tree growth dynamics, and tracked these daily radial tree‐growth dynamics in remarkable detail with conditional and marginal coefficients of determination of 0.48 and 0.96 (for 2018) and 0.43 and 0.98 (for 2019), respectively. Our findings suggest that PRI could provide novel insights into nuances of carbon cycling dynamics by alleviating important uncertainties associated with intra‐annual vegetation response to climate change.     

The facultative bimodal growth pattern in Quercus ilex – A simple model to predict sub-seasonal and inter-annual growth

In Mediterranean climates, bimodal growth patterns, corresponding to two peaks in radial increment during favorable seasons, have been described in several tree species. However, we lack a better mechanistic understanding of bimodality and its potential responses to the predicted warming and aridification trends. Filling this research gap is important since growth duration affects the capacity of trees to form wood and uptake carbon. Here we used an 11-year (1994–2004) long record of dendrometer data of the Mediterranean Holm oak (Quercus ilex) and compared how climate related to radial increment in trees from the south- and the north-facing slopes. We also related climate variables to tree-ring width and the production of intra-annual density fluctuations (IADFs), which reflects bimodality. In this paper, we introduce a model called VS-Lite2 to simulate tree-growth dynamics, which is a modified version of the process-based Vaganov-Shashkin Lite model. The VS-Lite2 model adequately reproduced the bimodal intra‐annual pattern of radial growth, IADFs, and annual tree growth. Trees from the south-oriented slope grew more, produced more IADFs and showed a more marked bimodal pattern than trees from the north-facing slope. These differences agree with the observation that late-summer drought constrained growth. Therefore, radial-growth models should consider plastic bimodality and micro-environmental conditions in areas subjected to seasonal droughts.     

The Impact of Annual and Seasonal Rainfall Patterns on Growth and Phenology of Emergent Tree Species in Southeastern Amazonia,Brazil

Understanding tree growth in response to rainfall distribution is critical to predicting forest and species population responses to climate change. We investigated inter‐annual and seasonal variation in stem diameter by three emergent tree species in a seasonally dry tropical forest in southeast Pará, Brazil. Annual diameter growth rates by Swietenia macrophylla demonstrated strong positive correlation with annual rainfall totals during 1997–2009; Hymenaea courbaril growth rates demonstrated weak positive correlation, whereas Parkia pendula exhibited weak negative correlation. For both Swietenia and Hymenaea, annual diameter growth rates correlated positively and significantly with rainfall totals during the first 6 mo of the growing year (July to December). Vernier dendrometer bands monitored at 4‐wk intervals during 3–5 yr confirmed strong seasonal effects on stem diameter expansion. Individuals of all three species expanded in unison during wet season months and were static or even contracted during dry season months. Stems of the deciduous Swietenia contracted as crowns were shed during the early dry season, expanded slightly as new crowns were flushed, and then contracted further during 3–5 wk flowering periods in the late dry season by newly mature crowns. The three species’ physiographic distribution patterns at the study site may partially underlie observed differences in annual and seasonal growth. With most global circulation models predicting conditions becoming gradually drier in southeast Amazonia over the coming decades, species such as Swietenia that perform best on the ‘wet end’ of current conditions may experience reduced growth rates. However, population viability will not necessarily be threatened if life history and ecophysiological responses to changing conditions are compensatory.     

A methodological framework to optimize models predicting critical dates of xylem phenology based on dendrometer data

Dendrometer measurements are a frequently used alternative to the laborious and time consuming microcoring to investigate intra-annual growth dynamics of trees. However, since dendrometer data not only comprise cambial growth, but also hydrological fluctuations, both signals need to be disentangled to derive critical dates of xylem phenology from dendrometer data. For this purpose, various approaches can be found in the literature, however a systematic comparison of the different options is still missing. In this study we present a methodological framework to evaluate the accuracy of different mathematical fittings to derive tree-ring phenology from dendrometer data and apply this approach to a data set comprised of three conifer species where high-resolution band dendrometer measurements and microcore sampling have been done in parallel. Based on our study we provide evidence that the most common approaches to derive onset and cessation of xylem cell enlargement from dendrometer data, i.e. applying absolute and relative thresholds to deterministic models fitted to dendrometer data, caused systematic deviations from the reference of xylogenesis observations, but could be improved by small adaptations. The most precise and unbiased predictions of xylem growth phenology were obtained by fitting the three-parameter Gompertz model to the dendrometer data and applying a relative threshold of 3.5% of annual increment to the model predictions for growth onset and an absolute threshold of 4.5 µm day^-1 based on the first model derivative for growth cessation. Our framework enables an improved usage of dendrometer data for the prediction of the onset and cessation of xylem cell enlargement, which are important ecological indicators to quantify the effects environmental changes on forest growth and the terrestrial carbon cycle.     

Extreme climatic events drive mammal irruptions: regression analysis of 100‐year trends in desert rainfall and temperature

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra‐annual rainfall had become more variable over time. Using long‐term live‐trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires.     

Refining the cheatgrass–fire cycle in the Great Basin: Precipitation timing and fine fuel composition predict wildfire trends

Larger, more frequent wildfires in arid and semi‐arid ecosystems have been associated with invasion by non‐native annual grasses, yet a complete understanding of fine fuel development and subsequent wildfire trends is lacking. We investigated the complex relationships among weather, fine fuels, and fire in the Great Basin, USA. We first modeled the annual and time‐lagged effects of precipitation and temperature on herbaceous vegetation cover and litter accumulation over a 26‐year period in the northern Great Basin. We then modeled how these fine fuels and weather patterns influence subsequent wildfires. We found that cheatgrass cover increased in years with higher precipitation and especially when one of the previous 3 years also was particularly wet. Cover of non‐native forbs and native herbs also increased in wet years, but only after several dry years. The area burned by wildfire in a given year was mostly associated with native herb and non‐native forb cover, whereas cheatgrass mainly influenced area burned in the form of litter derived from previous years’ growth. Consequently, multiyear weather patterns, including precipitation in the previous 1–3 years, was a strong predictor of wildfire in a given year because of the time needed to develop these fine fuel loads. The strong relationship between precipitation and wildfire allowed us to expand our inference to 10,162 wildfires across the entire Great Basin over a 35‐year period from 1980 to 2014. Our results suggest that the region's precipitation pattern of consecutive wet years followed by consecutive dry years results in a cycle of fuel accumulation followed by weather conditions that increase the probability of wildfire events in the year when the cycle transitions from wet to dry. These patterns varied regionally but were strong enough to allow us to model annual wildfire risk across the Great Basin based on precipitation alone.     

Understanding and predicting frost‐induced tropical tree mortality patterns

Extreme climatic and weather events are increasing in frequency and intensity across the world causing episodes of widespread tree mortality in many forested ecosystems. However, we have a limited understanding about which local factors influence tree mortality patterns, restricting our ability to predict tree mortality, especially within topographically complex tropical landscapes with a matrix of mature and secondary forests. We investigated the effects of two major local factors, topography and forest successional type, on climate‐induced tropical tree mortality patterns using an observational and modeling approach. The northernmost Neotropical dry forest endured an unprecedented episode of frost‐induced tree mortality after the historic February 2011 cold wave hit northwestern Mexico. In a moderately hilly landscape covering mature and secondary tropical dry forests, we surveyed 454 sites for the presence or absence of frost‐induced tree mortality. In addition, across forty‐eight 1 ha plots equally split into the two forest types, we examined 6,981 woody plants to estimate a frost‐disturbance severity metric using the density of frost‐killed trees. Elevation is the main factor modulating frost effects regardless of forest type. Higher occurrence probabilities of frost‐induced tree mortality at lowland forests can be explained by the strong influence of elevation on temperature distribution since heavier cold air masses move downhill during advective frosts. Holding elevation constant, the probability of frost‐induced tree mortality in mature forests was twice that of secondary forests but severity showed the opposite pattern, suggesting a cautious use of occurrence probabilities of tree mortality to infer severity of climate‐driven disturbances. Extreme frost events, in addition to altering forest successional pathways and ecosystem services, likely maintain and could ultimately shift latitudinal and altitudinal range margins of Neotropical dry forests.     

Linking drought legacy effects across scales: From leaves to tree rings to ecosystems

Severe drought can cause lagged effects on tree physiology that negatively impact forest functioning for years. These “drought legacy effects” have been widely documented in tree‐ring records and could have important implications for our understanding of broader scale forest carbon cycling. However, legacy effects in tree‐ring increments may be decoupled from ecosystem fluxes due to (a) postdrought alterations in carbon allocation patterns; (b) temporal asynchrony between radial growth and carbon uptake; and (c) dendrochronological sampling biases. In order to link legacy effects from tree rings to whole forests, we leveraged a rich dataset from a Midwestern US forest that was severely impacted by a drought in 2012. At this site, we compiled tree‐ring records, leaf‐level gas exchange, eddy flux measurements, dendrometer band data, and satellite remote sensing estimates of greenness and leaf area before, during, and after the 2012 drought. After accounting for the relative abundance of tree species in the stand, we estimate that legacy effects led to ~10% reductions in tree‐ring width increments in the year following the severe drought. Despite this stand‐scale reduction in radial growth, we found that leaf‐level photosynthesis, gross primary productivity (GPP), and vegetation greenness were not suppressed in the year following the 2012 drought. Neither temporal asynchrony between radial growth and carbon uptake nor sampling biases could explain our observations of legacy effects in tree rings but not in GPP. Instead, elevated leaf‐level photosynthesis co‐occurred with reduced leaf area in early 2013, indicating that resources may have been allocated away from radial growth in conjunction with postdrought upregulation of photosynthesis and repair of canopy damage. Collectively, our results indicate that tree‐ring legacy effects were not observed in other canopy processes, and that postdrought canopy allocation could be an important mechanism that decouples tree‐ring signals from GPP.     

Pattern of xylem phenology in conifers of cold ecosystems at the Northern Hemisphere

The interaction between xylem phenology and climate assesses forest growth and productivity and carbon storage across biomes under changing environmental conditions. We tested the hypothesis that patterns of wood formation are maintained unaltered despite the temperature changes across cold ecosystems. Wood microcores were collected weekly or biweekly throughout the growing season for periods varying between 1 and 13 years during 1998–2014 and cut in transverse sections for assessing the onset and ending of the phases of xylem differentiation. The data set represented 1321 trees belonging to 10 conifer species from 39 sites in the Northern Hemisphere and covering an interval of mean annual temperature exceeding 14 K. The phenological events and mean annual temperature of the sites were related linearly, with spring and autumnal events being separated by constant intervals across the range of temperature analysed. At increasing temperature, first enlarging, wall‐thickening and mature tracheids appeared earlier, and last enlarging and wall‐thickening tracheids occurred later. Overall, the period of wood formation lengthened linearly with the mean annual temperature, from 83.7 days at ?2 °C to 178.1 days at 12 °C, at a rate of 6.5 days °C^?1. April–May temperatures produced the best models predicting the dates of wood formation. Our findings demonstrated the uniformity of the process of wood formation and the importance of the environmental conditions occurring at the time of growth resumption. Under warming scenarios, the period of wood formation might lengthen synchronously in the cold biomes of the Northern Hemisphere.     

Tree growth variation in the tropical forest: understanding effects of temperature,rainfall and CO2

Tropical forest responses to climatic variability have important consequences for global carbon cycling, but are poorly understood. As empirical, correlative studies cannot disentangle the interactive effects of climatic variables on tree growth, we used a tree growth model (IBTREE) to unravel the climate effects on different physiological pathways and in turn on stem growth variation. We parameterized the model for canopy trees of Toona ciliata (Meliaceae) from a Thai monsoon forest and compared predicted and measured variation from a tree‐ring study over a 30‐year period. We used historical climatic variation of minimum and maximum day temperature, precipitation and carbon dioxide (CO₂) in different combinations to estimate the contribution of each climate factor in explaining the inter‐annual variation in stem growth. Running the model with only variation in maximum temperature and rainfall yielded stem growth patterns that explained almost 70% of the observed inter‐annual variation in stem growth. Our results show that maximum temperature had a strong negative effect on the stem growth by increasing respiration, reducing stomatal conductance and thus mitigating a higher transpiration demand, and – to a lesser extent – by directly reducing photosynthesis. Although stem growth was rather weakly sensitive to rain, stem growth variation responded strongly and positively to rainfall variation owing to the strong inter‐annual fluctuations in rainfall. Minimum temperature and atmospheric CO₂ concentration did not significantly contribute to explaining the inter‐annual variation in stem growth. Our innovative approach – combining a simulation model with historical data on tree‐ring growth and climate – allowed disentangling the effects of strongly correlated climate variables on growth through different physiological pathways. Similar studies on different species and in different forest types are needed to further improve our understanding of the sensitivity of tropical tree growth to climatic variability and change.     

Natural disturbances are spatially diverse but temporally synchronized across temperate forest landscapes in Europe

Natural disturbance regimes are changing substantially in forests around the globe. However, large‐scale disturbance change is modulated by a considerable spatiotemporal variation within biomes. This variation remains incompletely understood particularly in the temperate forests of Europe, for which consistent large‐scale disturbance information is lacking. Here, our aim was to quantify the spatiotemporal patterns of forest disturbances across temperate forest landscapes in Europe using remote sensing data and determine their underlying drivers. Specifically, we tested two hypotheses: (1) Topography determines the spatial patterns of disturbance, and (2) climatic extremes synchronize natural disturbances across the biome. We used novel Landsat‐based maps of forest disturbances 1986–2016 in combination with landscape analysis to compare spatial disturbance patterns across five unmanaged forest landscapes with varying topographic complexity. Furthermore, we analyzed annual estimates of disturbances for synchronies and tested the influence of climatic extremes on temporal disturbance patterns. Spatial variation in disturbance patterns was substantial across temperate forest landscapes. With increasing topographic complexity, natural disturbance patches were smaller, more complex in shape, more dispersed, and affected a smaller portion of the landscape. Temporal disturbance patterns, however, were strongly synchronized across all landscapes, with three distinct waves of high disturbance activity between 1986 and 2016. All three waves followed years of pronounced drought and high peak wind speeds. Natural disturbances in temperate forest landscapes of Europe are thus spatially diverse but temporally synchronized. We conclude that the ecological effect of natural disturbances (i.e., whether they are homogenizing a landscape or increasing its heterogeneity) is strongly determined by the topographic template. Furthermore, as the strong biome‐wide synchronization of disturbances was closely linked to climatic extremes, large‐scale disturbance episodes are likely in Europe's temperate forests under climate changes.     

Generalized additive mixed models for disentangling long‐term trends,local anomalies,and seasonality in fruit tree phenology

Quantifying temporal patterns of ephemeral plant structures such as leaves, flowers, and fruits gives insight into both plant and animal ecology. Different scales of temporal changes in fruits, for example within‐ versus across‐year variability, are driven by different processes, but are not always easy to disentangle. We apply generalized additive mixed models (GAMMs) to study a long‐term fruit presence–absence data set of individual trees collected from a high‐altitude Afromontane tropical rain forest site within Bwindi Impenetrable National Park (BINP), Uganda. Our primary aim was to highlight and evaluate GAMM methodology, and quantify both intra‐ and interannual changes in fruit production. First, we conduct several simulation experiments to study the practical utility of model selection and smooth term estimation relevant for disentangling intra‐ and interannual variability. These simulations indicate that estimation of nonlinearity and seasonality is generally accurately identified using asymptotic theory. Applied to the empirical data set, we found that the forest‐level fruiting variability arises from both regular seasonality and significant interannual variability, with the years 2009–2010 in particular showing a significant increase in the presence of fruits‐driven by increased productivity of most species, and a regular annual peak associated occurring at the end of one of the two dry seasons. Our analyses illustrate a statistical framework for disentangling short‐term increases/decreases in fruiting effort while pinpointing specific times in which fruiting is atypical, providing a first step for assessing the impacts of regular and irregular (e.g., climate change) abiotic covariates on fruiting phenology. Some consequences of the rich diversity of fruiting patterns observed here for the population biology of frugivores in BINP are also discussed.     

Global change and the distributional dynamics of migratory bird populations wintering in Central America

Understanding the susceptibility of highly mobile taxa such as migratory birds to global change requires information on geographic patterns of occurrence across the annual cycle. Neotropical migrants that breed in North America and winter in Central America occur in high concentrations on their non‐breeding grounds where they spend the majority of the year and where habitat loss has been associated with population declines. Here, we use eBird data to model weekly patterns of abundance and occurrence for 21 forest passerine species that winter in Central America. We estimate species’ distributional dynamics across the annual cycle, which we use to determine how species are currently associated with public protected areas and projected changes in climate and land‐use. The effects of global change on the non‐breeding grounds is characterized by decreasing precipitation, especially during the summer, and the conversion of forest to cropland, grassland, or peri‐urban. The effects of global change on the breeding grounds are characterized by increasing winter precipitation, higher temperatures, and the conversion of forest to peri‐urban. During spring and autumn migration, species are projected to encounter higher temperatures, forests that have been converted to peri‐urban, and increased precipitation during spring migration. Based on current distributional dynamics, susceptibility to global change is characterized by the loss of forested habitats on the non‐breeding grounds, warming temperatures during migration and on the breeding grounds, and declining summer rainfall on the non‐breeding grounds. Public protected areas with low and medium protection status are more prevalent on the non‐breeding grounds, suggesting that management opportunities currently exist to mitigate near‐term non‐breeding habitat losses. These efforts would affect more individuals of more species during a longer period of the annual cycle, which may create additional opportunities for species to respond to changes in habitat or phenology that are likely to develop under climate change.     

Xylem phenology and wood production: resolving the chicken‐or‐egg dilemma

Delays in the start of the growing season reduce the period available for growth and the amount of xylem production. However, a higher number of developing tracheids could prolong cell differentiation and, consequently, lengthen the growing season. The relationship between the amount and duration of cell production in the xylem remains an unresolved issue. The aim of this study was to resolve the chicken‐or‐egg causality dilemma about duration of growth and cell production through simple‐ and double‐cause models. This was achieved by (1) analysing the intra‐annual growth dynamics of the xylem in Picea mariana (Mill.) BSP during 2006–2009 in two contrasting sites of the boreal forest of Quebec, Canada, and (2) extracting the dates of onset and ending of xylem formation and the number of radial cells along the tree ring. A higher number of cells was linked to an earlier onset (r = 0.74) and later ending (r = 0.61) of cell differentiation. The absence of a relationship between the residuals of the onset and ending of xylogenesis (r_p = ?0.06) indicated that cell production influenced the correlation between the two phenophases of the xylem. These results demonstrated that a higher number of cells produced delay the ending of xylem maturation, so extending the duration of wood formation.     

Seasonal strengths of the abiotic and biotic drivers of a zooplankton community

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Annual growth rings, rainfall-dependent growth and long-term growth patterns of tropical trees from the Caparo Forest Reserve in Venezuela

1 Tree-ring analyses and dendrometer measurements were carried out on 37 tree species in a semi-deciduous forest of the Reserva Forestal de Caparo, Venezuela, where the mean annual rainfall is about 1700 mm and there is a dry season from December to March. The main purposes of the investigation were to show the seasonality of cambial growth, and the connection between precipitation patterns and tree-ring curves. Long-term rates of wood increment were also estimated.
2 Cambial markings in consecutive years showed that annual rings were formed by many species.
3 The distinctiveness of growth zones was usually greater in deciduous species than in evergreen species, although not all deciduous species had distinct rings.
4 Dendrometer measurements showed that the annual growth rhythm was related to precipitation patterns. Evergreen species tended to show only a short interruption of wood growth (during the later part of the dry season), whereas deciduous species stopped growth completely at the end of the rainy season.
5 For deciduous species, regression analyses showed close relations between tree-ring width and the sum of precipitation outside the rainy seasons (i.e. November to April). Evergreen species reacted to the total annual amount of precipitation.
6 Variation in longest available ring chronology (for Terminalia guianensis ) showed little correlation with the El Niño–Southern Oscillation effect.
7 On average trees from natural forests showed relatively constant growth over the entire life span. Plantation trees grew fast up to an age of 15–20 years, but annual increments then decreased to values seen in natural forest trees.     

Interrelationships among life-history traits in three California oaks

Life-history traits interact in important ways. Relatively few studies, however, have explored the relationships between life-history traits in long-lived taxa such as trees. We examined patterns of energy allocation to components of reproduction and growth in three species of California oaks (Quercus spp.) using a combination of annual acorn censuses, dendrometer bands to measure radial increment, and litterfall traps. Our results are generally consistent with the hypothesis that energy invested in reproduction detracts from the amount of energy available for growth in these long-lived taxa; i.e., there are trade-offs between these traits. The relationships between reproduction and growth varied substantially among specific trait combinations and tree species, however, and in some cases were in the direction opposite that expected based on the assumption of trade-offs between them. This latter finding appears to be a consequence of the pattern of resource use across years in these long-lived trees contrasting with the expected partitioning of resource use within years in short-lived taxa. Thus, the existence and magnitude of putative trade-offs varied depending on whether the time scale considered was within or across years. Collectively, our results indicate that negative relationships between fundamental life-history traits can be important at multiple levels of modular organization and that energy invested in reproduction can have measurable consequences in terms of the amount of energy available for future reproduction and both current and future growth.     

Ecophysiological variation across a forest‐ecotone gradient produces divergent climate change vulnerability within species

Climate change related risks and impacts on ectotherms will be mediated by habitats and their influence on local thermal environments. While many studies have documented morphological and genetic aspects of niche divergence across habitats, few have examined thermal performance across such gradients and directly linked this variation to contemporary climate change impacts. In this study, we quantified variation in thermal performance across a gradient from forest to gallery forest‐savanna mosaic in Cameroon for a skink species (Trachylepis affinis) known to be diverging genetically and morphologically across that habitat gradient. Based on these results, we then applied a mechanistic modelling approach (NicheMapR) to project changes in potential activity, as constrained by thermal performance, in response to climate change. As a complimentary approach, we also compared mechanistic projections with climate‐driven changes in habitat suitability based on species distribution models of forest and ecotone skinks. We found that ecotone skinks may benefit from warming and experience increased activity while forest skinks will likely face a drastic decrease in thermal suitability across the forest zone. Species distribution models projected that thermal suitability for forest skinks in coastal forests would decline but in other parts of the forest zone skinks are projected to experience increased thermal suitability. The results here highlight the utility of mechanistic approaches in revealing and understanding patterns of climate change vulnerability which may not be detected with species distribution models alone. This study also emphasizes the importance of intra‐specific physiological variation, and habitat‐specific thermal performance relationships in particular, in determining warming responses.     

A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level

Understanding large‐scale crop growth and its responses to climate change are critical for yield estimation and prediction, especially under the increased frequency of extreme climate and weather events. County‐level corn phenology varies spatially and interannually across the Corn Belt in the United States, where precipitation and heat stress presents a temporal pattern among growth phases (GPs) and vary interannually. In this study, we developed a long short‐term memory (LSTM) model that integrates heterogeneous crop phenology, meteorology, and remote sensing data to estimate county‐level corn yields. By conflating heterogeneous phenology‐based remote sensing and meteorological indices, the LSTM model accounted for 76% of yield variations across the Corn Belt, improved from 39% of yield variations explained by phenology‐based meteorological indices alone. The LSTM model outperformed least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) approaches for end‐of‐the‐season yield estimation, as a result of its recurrent neural network structure that can incorporate cumulative and nonlinear relationships between corn yield and environmental factors. The results showed that the period from silking to dough was most critical for crop yield estimation. The LSTM model presented a robust yield estimation under extreme weather events in 2012, which reduced the root‐mean‐square error to 1.47 Mg/ha from 1.93 Mg/ha for LASSO and 2.43 Mg/ha for RF. The LSTM model has the capability to learn general patterns from high‐dimensional (spectral, spatial, and temporal) input features to achieve a robust county‐level crop yield estimation. This deep learning approach holds great promise for better understanding the global condition of crop growth based on publicly available remote sensing and meteorological data.     

Increases in residential and energy development are associated with reductions in recruitment for a large ungulate

Land‐use change due to anthropogenic development is pervasive across the globe and commonly associated with negative consequences for biodiversity. While land‐use change has been linked to shifts in the behavior and habitat‐use patterns of wildlife species, little is known about its influence on animal population dynamics, despite the relevance of such information for conservation. We conducted the first broad‐scale investigation correlating temporal patterns of land‐use change with the demographic rates of mule deer, an iconic species in the western United States experiencing wide‐scale population declines. We employed a unique combination of long‐term (1980–2010) data on residential and energy development across western Colorado, in conjunction with congruent data on deer recruitment, to quantify annual changes in land‐use and correlate those changes with annual indices of demographic performance. We also examined annual variation in weather conditions, which are well recognized to influence ungulate productivity, and provided a basis for comparing the relative strength of different covariates in their association with deer recruitment. Using linear mixed models, we found that increasing residential and energy development within deer habitat were correlated with declining recruitment rates, particularly within seasonal winter ranges. Residential housing had two times the magnitude of effect of any other factor we investigated, and energy development had an effect size similar to key weather variables known to be important to ungulate dynamics. This analysis is the first to correlate a demographic response in mule deer with residential and energy development at large spatial extents relevant to population performance, suggesting that further increases in these development types on deer ranges are not compatible with the goal of maintaining highly productive deer populations. Our results underscore the significance of expanding residential development on mule deer populations, a factor that has received little research attention in recent years, despite its rapidly increasing footprint across the landscape.