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Understanding trophic cascades in terrestrial wildlife communities is a major challenge because these systems are difficult to sample properly. We show how a tradition of non‐random sampling has confounded this understanding in a textbook system (Yellowstone National Park) where carnivore [Canis lupus(wolf)] recovery is associated with a trophic cascade involving changes in herbivore [Cervus canadensis(elk)] behaviour and density that promote plant regeneration. Long‐term data indicate a practice of sampling only the tallest young plants overestimated regeneration of overstory aspen (Populus tremuloides) by a factor of 4–7 compared to random sampling because it favoured plants taller than the preferred browsing height of elk and overlooked non‐regenerating aspen stands. Random sampling described a trophic cascade, but it was weaker than the one that non‐random sampling described. Our findings highlight the critical importance of basic sampling principles (e.g. randomisation) for achieving an accurate understanding of trophic cascades in terrestrial wildlife systems.

 

Periods of water surplus and deficit in Northern California follow a pronounced quasi‐decadal cycle. This cycle is largely driven by the frequency of atmospheric rivers (ARs), affecting the region’s wet and dry periods. Our analyses demonstrate that the quasi‐decadal cycle of AR frequency relies on moisture transport associated with the position and intensity of the Aleutian Low. In observations, the Aleutian Low is shown to covary with tropical Pacific sea surface temperature anomalies. A modeling experiment, which incorporates ocean observations from the equatorial Pacific into the fully coupled climate model, provides support that the quasi‐decadal cycle of the Aleutian Low is forced by the tropical Pacific. Subsequently, the tropical Pacific modulates the wet season moisture transport toward California on decadal time scales, affecting AR frequency. These results provide metrics for improving interannual‐to‐decadal prediction of AR activity, which drives hydrological cycles in Northern California.

 

Daily weather affects total visitation to parks and protected areas, as well as visitors’ experiences. However, it is unknown if and how visitors change their spatial behavior within a park due to daily weather conditions. We investigated the impact of daily maximum temperature and precipitation on summer visitation patterns within 110 U.S. National Park Service units. We connected 489,061 geotagged Flickr photos to daily weather, as well as visitors’ elevation and distance to amenities (i.e., roads, waterbodies, parking areas, and buildings). We compared visitor behavior on cold, average, and hot days, and on days with precipitation compared to days without precipitation, across fourteen ecoregions within the continental U.S. Our results suggest daily weather impacts where visitors go within parks, and the effect of weather differs substantially by ecoregion. In most ecoregions, visitors stayed closer to infrastructure on rainy days. Temperature also affects visitors’ spatial behavior within parks, but there was not a consistent trend across ecoregions. Importantly, parks in some ecoregions contain more microclimates than others, which may allow visitors to adapt to unfavorable conditions. These findings suggest visitors’ spatial behavior in parks may change in the future due to the increasing frequency of hot summer days.

 

As climate change intensifies, global publics will experience more unusual weather and extreme weather events. How will individual experiences with these weather trends shape climate change beliefs, attitudes, and behaviors? In this article, we review 73 papers that have studied the relationship between climate change experiences and public opinion. Overall, we find mixed evidence that weather shapes climate opinions. Although there is some support for a weak effect of local temperature and extreme weather events on climate opinion, the heterogeneity of independent variables, dependent variables, study populations, and research designs complicate systematic comparison. To advance research on this critical topic, we suggest that future studies pay careful attention to differences between self-reported and objective weather data, causal identification, and the presence of spatial autocorrelation in weather and climate data. Refining research designs and methods in future studies will help us understand the discrepancies in results, and allow better detection of effects, which have important practical implications for climate communication. As the global population increasingly experiences weather conditions outside the range of historical experience, researchers, communicators, and policymakers need to understand how these experiences shape-and are shaped by-public opinions and behaviors.

 

Although natural resource managers are concerned about climate change, many are unable to adequately incorporate climate change science into their adaptation strategies or management plans, and are not always aware of or do not always employ the most current scientific knowledge. One of the most prominent natural resource management agencies in the United States is the Bureau of Land Management (BLM), which is tasked with managing over 248 million acres (>1 million km²) of public lands for multiple, often conflicting, uses. Climate change will affect the sustainability of many of these land uses and could further increase conflicts between them. As such, the purpose of our study was to determine the extent to which climate change will affect public land uses, and whether the BLM is managing for such predicted effects. To do so, we first conducted a systematic review of peer‐reviewed literature that discussed potential impacts of climate change on the multiple land uses the BLM manages in the Intermountain West, USA, and then expanded these results with a synthesis of projected vegetation changes. Finally, we conducted a content analysis of BLM Resource Management Plans in order to determine how climate change is explicitly addressed by BLM managers, and whether such plans reflect changes predicted by the scientific literature. We found that active resource use generally threatens intrinsic values such as conservation and ecosystem services on BLM land, and climate change is expected to exacerbate these threats in numerous ways. Additionally, our synthesis of vegetation modeling suggests substantial changes in vegetation due to climate change. However, BLM plans rarely referred to climate change explicitly and did not reflect the results of the literature review or vegetation model synthesis. Our results suggest there is a disconnect between management of BLM lands and the best available science on climate change. We recommend that the BLM actively integrates such research into on‐the‐ground management plans and activities, and that researchers studying the effects of climate change make a more robust effort to understand the practices and policies of public land management in order to effectively communicate the management significance of their findings.

 

Rapid warming in northern ecosystems over the past four decades has resulted in earlier spring, increased precipitation, and altered timing of plant–animal interactions, such as herbivory. Advanced spring phenology can lead to longer growing seasons and increased carbon (C) uptake. Greater precipitation coincides with greater cloud cover possibly suppressing photosynthesis. Timing of herbivory relative to spring phenology influences plant biomass. None of these changes are mutually exclusive and their interactions could lead to unexpected consequences for Arctic ecosystem function. We examined the influence of advanced spring phenology, cloud cover, and timing of grazing on C exchange in the Yukon–Kuskokwim Delta of western Alaska for three years. We combined advancement of the growing season using passive-warming open-top chambers (OTC) with controlled timing of goose grazing (early, typical, and late season) and removal of grazing. We also monitored natural variation in incident sunlight to examine the C exchange consequences of these interacting forcings. We monitored net ecosystem exchange of C (NEE) hourly using an autochamber system. Data were used to construct daily light curves for each experimental plot and sunlight data coupled with a clear-sky model was used to quantify daily and seasonal NEE over a range of incident sunlight conditions. Cloudy days resulted in the largest suppression of NEE, reducing C uptake by approximately 2 g C m⁻²d⁻¹regardless of the timing of the season or timing of grazing. Delaying grazing enhanced C uptake by approximately 3 g C m⁻²d⁻¹. Advancing spring phenology reduced C uptake by approximately 1.5 g C m⁻²d⁻¹, but only when plots were directly warmed by the OTCs; spring advancement did not have a long-term influence on NEE. Consequently, the two strongest drivers of NEE, cloud cover and grazing, can have opposing effects and thus future growing season NEE will depend on the magnitude of change in timing of grazing and incident sunlight.

 

Climate change is creating phenological mismatches between herbivores and their plant resources throughout the Arctic. While advancing growing seasons and changing arrival times of migratory herbivores can have consequences for herbivores and forage quality, developing mismatches could also influence other traits of plants, such as above‐ and below‐ground biomass and the type of reproduction, that are often not investigated.

In coastal western Alaska, we conducted a 3‐year factorial experiment that simulated scenarios of phenological mismatch by manipulating the start of the growing season (3 weeks early and ambient) and grazing times (3 weeks early, typical, 3 weeks late, or no‐grazing) of Pacific black brant (Branta bernicla nigricans), to examine how the timing of these events influence a primary goose forage species,Carex subspathacea.

After 3 years, an advanced growing season compared to a typical growing season increased stem heights, standing dead biomass, and the number of inflorescences. Early season grazing compared to typical season grazing reduced above‐ and below‐ground biomass, stem height, and the number of tillers; while late season grazing increased the number of inflorescences and standing dead biomass. Therefore, an advanced growing season and late grazing had similar directional effects on most plant traits, but a 3‐week delay in grazing had an impact on traits 3–5 times greater than a similarly timed shift in the advancement of spring. In addition, changes in response to treatments for some variables, such as the number of inflorescences, were not measurable until the second year of the experiment, while other variables, such as root productivity and number of tillers, changed the direction of their responses to treatments over time.

Synthesis. Factors affecting the timing of migration have a larger influence than earlier springs on an important forage species in the breeding and rearing habitats of Pacific black brant. The phenological mismatch prediction for this site of earlier springs and later goose arrival will likely increase above‐ and below‐ground biomass and sexual reproduction of the often‐clonally reproducingC. subspathacea. Finally, the implications of mismatch may be difficult to predict because some variables required successive years of mismatch to respond.

 

The advancement of spring and the differential ability of organisms to respond to changes in plant phenology may lead to “phenological mismatches” as a result of climate change. One potential for considerable mismatch is between migratory birds and food availability in northern breeding ranges, and these mismatches may have consequences for ecosystem function. We conducted a three‐year experiment to examine the consequences for CO₂exchange of advanced spring green‐up and altered timing of grazing by migratory Pacific black brant in a coastal wetland in western Alaska. Experimental treatments represent the variation in green‐up and timing of peak grazing intensity that currently exists in the system. Delayed grazing resulted in greater net ecosystem exchange (NEE) and gross primary productivity (GPP), while early grazing reduced CO₂uptake with the potential of causing net ecosystem carbon (C) loss in late spring and early summer. Conversely, advancing the growing season only influenced ecosystem respiration (ER), resulting in a small increase in ER with no concomitant impact on GPP or NEE. The experimental treatment that represents the most likely future, with green‐up advancing more rapidly than arrival of migratory geese, results in NEE changing by 1.2 µmol m⁻² s⁻¹toward a greater CO₂sink in spring and summer. Increased sink strength, however, may be mitigated by early arrival of migratory geese, which would reduce CO₂uptake. Importantly, while the direct effect of climate warming on phenology of green‐up has a minimal influence on NEE, the indirect effect of climate warming manifest through changes in the timing of peak grazing can have a significant impact on C balance in northern coastal wetlands. Furthermore, processes influencing the timing of goose migration in the winter range can significantly influence ecosystem function in summer habitats.

 

The Colorado Plateau has abundant oil, gas, and alternative energy potential. This energy potential is scattered among a patchwork of land ownership, with private, tribal, and public lands being actively developed for energy extraction. Elements of biodiversity (e.g., listed and sensitive plant and animal species) are distributed among all land tenures, yet the laws protecting them can vary as a function of land tenure. It is imperative to understand the spatial distributions of threatened endangered, and sensitive species in relation to land tenure to preserve habitat and conserve species populations in areas undergoing energy development. We developed species distribution models and spatial conservation optimization frameworks to explore the interactions among land ownership, existing and potential energy extraction, and biodiversity. Four management scenarios were tested to quantify how different approaches to energy extraction may impact rare plant distributions. Results show that incorporating risk and land tenure in spatially optimized frameworks it is possible to facilitate the long-term viability of rare plant species. The scenarios developed here represent a different attitude towards the value of rare plants and the risk of energy development. Results gives insight into the financial consequences of rare species protection and quantifies the biodiversity costs of energy development across landscapes.