The long‐term impacts of deer herbivory in determining temperate forest stand and canopy structural complexity

Author(s):  
Samuel P. Reed ◽  
Alejandro A. Royo ◽  
Alexander T. Fotis ◽  
Kathleen S. Knight ◽  
Charles E. Flower ◽  
...  
2013 ◽  
Vol 1 (1) ◽  
pp. 29-43 ◽  
Author(s):  
P. J. Morris ◽  
A. J. Baird ◽  
L. R. Belyea

Abstract. The sloping flanks of peatlands are commonly patterned with non-random, contour-parallel stripes of distinct micro-habitats such as hummocks, lawns and hollows. Patterning seems to be governed by feedbacks among peatland hydrological processes, plant micro-succession, plant litter production and peat decomposition. An improved understanding of peatland patterning may provide important insights into broader aspects of the long-term development of peatlands and their likely response to future climate change. We recreated a cellular simulation model from the literature, as well as three subtle variants of the model, to explore the controls on peatland patterning. Our models each consist of three submodels, which simulate: peatland water tables in a gridded landscape, micro-habitat dynamics in response to water-table depths, and changes in peat hydraulic properties. We found that the strength and nature of simulated patterning was highly dependent on the degree to which water tables had reached a steady state in response to hydrological inputs. Contrary to previous studies, we found that under a true steady state the models predict largely unpatterned landscapes that cycle rapidly between contrasting dry and wet states, dominated by hummocks and hollows, respectively. Realistic patterning only developed when simulated water tables were still transient. Literal interpretation of the degree of hydrological transience required for patterning suggests that the model should be discarded; however, the transient water tables appear to have inadvertently replicated an ecological memory effect that may be important to peatland patterning. Recently buried peat layers may remain hydrologically active despite no longer reflecting current vegetation patterns, thereby highlighting the potential importance of three-dimensional structural complexity in peatlands to understanding the two-dimensional surface-patterning phenomenon. The models were highly sensitive to the assumed values of peat hydraulic properties, which we take to indicate that the models are missing an important negative feedback between peat decomposition and changes in peat hydraulic properties. Understanding peatland patterning likely requires the unification of cellular landscape models such as ours with cohort-based models of long-term peatland development.


2019 ◽  
Vol 278 ◽  
pp. 107699 ◽  
Author(s):  
Dominik Seidel ◽  
Martin Ehbrecht ◽  
Peter Annighöfer ◽  
Christian Ammer

2014 ◽  
Vol 30 (4) ◽  
pp. 291-301 ◽  
Author(s):  
Zoë Diaz-Martin ◽  
Varun Swamy ◽  
John Terborgh ◽  
Patricia Alvarez-Loayza ◽  
Fernando Cornejo

Abstract:The keystone plant resources (KPR) concept describes certain plant species in tropical forests as vital to community stability and diversity because they provide food resources to vertebrate consumers during the season of scarcity. Here, we use an 8-y, continuous record of fruit fall from a 1.44-ha mature forest stand to identify potential KPRs in a lowland western Amazonian rain forest. KPRs were identified based on four criteria: temporal non-redundancy; year-to-year reliability; abundance of reproductive-size individuals and inferred fruit crop size; and the variety of vertebrate consumers utilizing their fruit. Overall, seven species were considered excellent KPRs: two of these belong to the genusFicus, confirming that this taxon is a KPR as previously suggested.Celtis iguanaea(Cannabaceae) – a canopy liana – has also been previously classified as a KPR; in addition,Pseudomalmea diclina(Annonaceae),Cissus ulmifolia(Vitaceae),Allophylus glabratus(Sapindaceae) andTrichilia elegans(Meliaceae) are newly identified KPRs. Our results confirm that a very small fraction (<5%) of the plant community consistently provides fruit for a broad set of consumers during the period of resource scarcity, which has significant implications for the conservation and management of Amazonian forests.


2020 ◽  
Author(s):  
Shawn D. Taylor ◽  
Dawn M. Browning

Abstract. Grasslands provide many important ecosystem services globally and forecasting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well-calibrated at local scales, but generally have some maximum spatial extent in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial extent for parameterization, and thus for subsequently applying it in future forecasts for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and Eastern Temperate Forest ecoregions of North America. The model was not well suited to grasslands in North American Deserts or Northwest Forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term forecasts in areas where model performance has been verified, with gaps filled in by future modelling efforts.


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