The effects of seed dispersal on the simulation of long-term forest landscape change
The effects of seed dispersal on the simulation of long-term forest landscape change
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DOI：
10.1007/s100219900082
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发表时间：
1999-07-01
期刊：
影响因子：
3.7
通讯作者：
Mladenoff, DJ
中科院分区：
文献类型：
--
作者：
He, HS;Mladenoff, DJ
森林景观变化的研究需要了解空间和时间因素之间复杂的相互作用。传统上，森林间隙模型被用来模拟小块独立地块的变化。虽然间隙模型是有用的，在检查森林生态动态的时间尺度，大，空间过程，如种子传播，不能在大的景观实际模拟。为了模拟种子传播，空间明确的景观模型，跟踪个别物种的分布是必要的。我们使用这样一个模型，LANDIS，来说明种子传播模拟森林景观变化的影响。在一个人工开放的景观与均匀的环境，圆形的树种建立模式，从模拟结果，与种子源附近的地区更密集覆盖比地区进一步从种子源。由于LANDIS以10年的时间步长进行模拟，因此这种模式反映了由气候和其他环境变量的年度变化引起的各种可能的扩散形状和建立的整合。在真实的景观中，物种扩散半径所决定的格局往往被其他因素所掩盖，如物种竞争、干扰和景观结构等。为了进一步证明种子传播的影响，我们选择了一个相当干扰和破碎的森林景观（约50万公顷）在北方威斯康星州，我们比较了模拟结果的地图与树种（种子源位置）现实参数化（真实的方案）对随机参数化的物种地图（随机方案）。初始种子源分布的差异导致两种情景下物种多度的模拟结果不同，物种多度的起始水平相同。这对于模型运行的前半部分（0-250 y）尤其如此。在随机情景下，不常发生和耐荫的物种往往被高估，而midabundant和midshade耐受物种往往被低估。在检查长期（500年）景观动态时，对物种丰度的过度估计和低估会减少，因为火灾等随机因素往往会使两种情景下的景观趋于收敛。然而，空间格局的差异，特别是物种年龄组分布，可以持续几百年的两种情况下。
The study of forest landscape change requires an understanding of the complex interactions of both spatial and temporal factors. Traditionally, forest gap models have been used to simulate change on small and independent plots. While gap models are useful in examining forest ecological dynamics across temporal scales, large, spatial processes, such as seed dispersal, cannot be realistically simulated across large landscapes. To simulate seed dispersal, spatially explicit landscape models that track individual species distribution are needed. We used such a model, LANDIS, to illustrate the implications of seed dispersal for simulating forest landscape change. On an artificial open landscape with a uniform environment, circular-shaped tree species establishment patterns resulted from the simulations, with areas near seed sources more densely covered than areas further from seed sources. Because LANDIS simulates at 10-y time steps, this pattern reflects an integration of various possible dispersal shapes and establishment that are caused by the annual variations in climate and other environmental variables. On real landscapes, these patterns driven only by species dispersal radii are obscured by other factors, such as species competition, disturbance, and landscape structure. To further demonstrate the effects of seed dispersal, we chose a fairly disturbed and fragmented forest landscape (approximately 500,000 ha) in northern Wisconsin, We compared the simulation results of a map with tree species (seed source locations) realistically parameterized (the real scenario) against a randomly parameterized species map (the random scenario). Differences in the initial seed source distribution lead to different simulation results of species abundance with species abundance starting at identical levels under the two scenarios. This is particularly true for the first half of the model run (0-250 y). Under the random scenario, infrequently occurring and shade tolerant species tend to be overestimated, while midabundant and midshade tolerant species tend to be underestimated. The over- and underestimation of species abundance diminish when examining longterm (500 y) landscape dynamics, because stochastic factors, such as fire, tend to make the landscapes under both scenarios converge. However, differences in spatial patterns, and especially species age-cohort distributions, can persist under the two scenarios for several hundred years.