Predicting ecosystem pattern across landscapes

被引:2
|
作者
Basquill, Sean P. [1 ,2 ,3 ]
Leroux, Shawn J. [1 ]
机构
[1] Mem Univ Newfoundland, Dept Biol, St John, NF, Canada
[2] Nova Scotia, Dept Nat Resources & Renewables, Kentville, NS, Canada
[3] St Marys Univ, Halifax, NS, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
abiotic features; biotic features; distribution model; ecosystem assembly; predictive modelling; spatial ecology; SPECIES DISTRIBUTION MODELS; META-ECOSYSTEMS; BIODIVERSITY; MULTIVARIATE; COMMUNITY; FRAMEWORK; EXTRAPOLATION; DYNAMICS; SCALE;
D O I
10.1111/oik.09873
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Predictive modelling is fundamental to ecology and essential for objective biodiversity assessment. However, while predictive biodiversity models are generally well-developed, models for predicting patterns within (e.g. composition, structure) and among ecosystems (e.g. ecosystem identity, spatial properties) have not been adequately operationalized. We contend the scarcity of such models marks a concerning gap in the scientific community's ability to make ecosystem predictions across landscapes, and more broadly for supporting the conservation of biodiversity and ecosystem functions. We propose ecosystem spatial pattern models (ESPM) to fill this gap in modelling capacity. Under our approach to ESPM, spatial patterns of ecosystem properties are the basis for resolving ecosystem organization at local and landscape extents. Our integrative modelling framework differs from others in that it accords biotic and abiotic constituents equally, consistent with their joint mechanistic influence on ecosystem establishment and dynamics. Development of ESPM is especially timely for ecosystem assessment is undergoing a groundswell, as scientists and conservation groups propose ambitious targets for ecosystem conservation and restoration.
引用
收藏
页数:18
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