Forest responses to last‐millennium hydroclimate variability are governed by spatial variations in ecosystem sensitivity

Forecasts of future forest change are governed by ecosystem sensitivity to climate change, but ecosystem model projections are under‐constrained by data at multidecadal and longer timescales. Here, we quantify ecosystem sensitivity to centennial‐scale hydroclimate variability, by comparing dendroclimatic and pollen‐inferred reconstructions of drought, forest composition and biomass for the last millennium with five ecosystem model simulations. In both observations and models, spatial patterns in ecosystem responses to hydroclimate variability are strongly governed by ecosystem sensitivity rather than climate exposure. Ecosystem sensitivity was higher in models than observations and highest in simpler models. Model‐data comparisons suggest that interactions among biodiversity, demography and ecophysiology processes dampen the sensitivity of forest composition and biomass to climate variability and change. Integrating ecosystem models with observations from timescales extending beyond the instrumental record can better understand and forecast the mechanisms regulating forest sensitivity to climate variability in a complex and changing world

Beyond ecosystem modeling: a roadmap to community cyberinfrastructure for ecological data‐model integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundationsof community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is key to meeting the pressing needs of science and society in the 21st century

Forecasting the Effects of Fertility Control on Overabundant Ungulates: White-Tailed Deer in the National Capital Region - Fig 2

<p>A. The vertical line indicates a manager’s objective for the population. The area that is shaded red indicates the probability that an objective will be met given no action. B. The Posterior distribution conditional on a management action, for example, culling or delivering contraceptives. The blue shaded area under the curve is the probability that a manager will reach the objective given this action. C. The net effect of management is the ratio of the blue shaded area to the red shaded area.</p

The study area included eight parks in the National Capital Region Network in the area surrounding Washington D.C.

<p>Each park used standardized distance sampling methods which produced a time series from 2000 to 2011 of regional estimates of white-tailed deer abundance.</p

Effects of fertility control treatments on white-tailed deer population densities forecasted for 2015 and 2018 after culling to a management objective or 10 deer/km² in 2014 followed by fertility control treatment.

<p>The rows corresponding to the percent of adult females treated from top to bottom: 20%, 40%, 60%, and 90%. The black dotted vertical line represents population density after culling in 2014 to give a baseline for population growth. The dashed vertical lines represent the bounds of the hypothetical management objective. The purple distribution represents the population effect of contraceptives with one year effectiveness which has the potential to maintain the population. The green distribution represents the population effect of contraceptives with three year effectiveness which has a similar effect to the 1 year contraceptives. The blue distribution represents sterilization. Sterilization reduced the population at a faster rate than contraceptives. The red distribution represents culling. Continuing to cull after an initial cull of 90% of the population further decreases the population beyond the management objective.</p

Effects of fertility control treatments on white-tailed deer population densities forecasted for 2014 and 2018 with plot rows corresponding to percent treated from top to bottom: 20%, 40%, 60%, and 90%.

<p>The black distribution represents the change in population with no action to show that the population may decrease without any management action. The dashed vertical lines represent the bounds of the hypothetical management objective. The purple distribution represents the population effect of contraceptives with one year effectiveness. The green distribution represents the population effect of contraceptives with three year effectiveness. The blue distribution represents sterilization. Sterilization reduced the population at a faster rate than contraceptives. Culling (the red distribution) had the most dramatic effect on population density.</p

Posterior (bars) and prior (dashed lines) distributions for vital rate parameters.

<p>One set of parameters was estimated for all parks.</p

The median number of adult females that would need to be treated across all parks after a 90% population reduction for each management scenario over four years.

<p>The median number of adult females that would need to be treated across all parks after a 90% population reduction for each management scenario over four years.</p

Population growth rate (<i>λ</i>) of the white-tailed deer in the National Capital Region without any management action has a median of 0.992 (95% equal tailed Bayesian credible interval, BCI = 0.824,1.16).

<p>The median suggests that the population is currently declining. However, the posterior distribution overlaps 1, suggesting we cannot rule out the possibility that it is increasing.</p

Forecast by park for the years 2001 to 2018.

<p>The solid line is the median of the estimate. The dashed lines are the 95% Bayesian credible intervals (BCI) of the estimate. The dots with vertical lines are the medians of the data with standard deviation error bars. The abbreviations for each park are in the titles of each plot. ANTI: Antietam National Battlefield, CHOH: Chesapeake and Ohio Canal NHP, GWMP: George Washington Memorial Parkway, MANA: Manassas National Battlefield Park, MONO: Monocacy National Battlefield, GREE: Greenbelt Park as part of the National Capital Parks East, PRWI: Prince William Forest Park, ROCR: Rock Creek Park.</p