Functional heterogeneity in resources within landscapes and herbivore population dynamics

Large mammalian herbivores are notorious for their propensity towards population irruptions and crashes, yet many herbivore populations remain relatively stable. I explore how resource heterogeneity within landscapes dampens population instability, using a metaphysiological modelling approach considering patch state distributions. Resource heterogeneity is functionally stabilizing through spreading consumption away from preferred resources before these become critically depleted. Lower-quality resources act as a buffer against starvation during critical periods of the seasonal cycle. Enriching resource quality is destabilizing, even if patch diversity is maintained, because food quantity then becomes the limitation. The potential consequences of landscape fragmentation are explored using the Serengeti ecosystem, characterised by broadscale resource gradients, as a hypothetical example. Further insights provided by the model are illustrated with specific examples concerning the effects of patch scales and waterpoint distribution. A metaphysiological modelling approach enables the basic consequences of landscape heterogeneity to be distinguished from further effects that may arise from specific patch scales and configurations, without the distracting detail of spatially explicit models.     

Animal movements and population dynamics in heterogeneous landscapes

Organisms respond to environmental heterogeneity at different scales and in different ways. These differences are consequences of how the movement characteristics of animals—their movement rates, directionality, turning frequencies, and turning angles—interact with patch and boundary features in landscape mosaics. The interactions of movement patterns with landscape features in turn produce spatial patterns in individual space-use, population dynamics and dispersion, gene flow, and the redistribution of nutrients and other materials. We describe several theoretical approaches for modeling the diffusion, foraging behavior, and population dynamics of animals in heterogeneous landscapes, including: (1) scaling relationships derived from percolation theory and fractal geometry, (2) extensions of traditional patch-based metapopulation models, and (3) individual-based, spatially explicit models governed by local rules. We conclude by emphasizing the need to couple theoretical models with empirical studies and the usefulness of ‘microlandscape’ investigations.     

Scale detection in real and artificial landscapes using semivariance analysis

Semivariance analysis is potentially useful to landscape ecologists for detecting scales of variability in spatial data. We used semivariance analysis to compare spatial patterns of winter foraging by large ungulates with those of environmental variables that influence forage availability in northern Yellowstone National Park, Wyoming. In addition, we evaluated (1) the ability of semivariograms to detect known scales of variability in artificial maps with one or more distinct scales of pattern, and (2) the influence of the amount and spatial distribution of absent data on semivariogram results and interpretation. Semivariograms of environmental data sets (aspect, elevation, habitat type, and slope) for the entire northern Yellowstone landscape clearly identified the dominant scale of variability in each map layer, while semivariograms of ungulate foraging data from discontinuous study areas were difficult to interpret. Semivariograms of binary maps composed of a single scale of pattern showed clear and interpretable results: the range accurately reflected the size of the blocks of which the maps were constructed. Semivariograms of multiple scale maps and hierarchical maps exhibited pronounced inflections which could be used to distinguish two or three distinct scales of pattern. To assess the sensitivity of semivariance analysis to absent data, often the product of cloud interference or incomplete data collection, we deliberately masked (deleted) portions of continuous northern Yellowstone map layers, using single scale artificial maps as masks. The sensitivity of semivariance analysis to random deletions from the data was related to both the size of the deleted blocks, and the total proportion of the original data set that was removed. Small blocks could be deleted in very high proportions without degrading the semivariogram results. When the size of deleted blocks was large relative to the size of the map, the corresponding variograms became sensitive to the total proportion of data removed: variograms were difficult or impossible to interpret when the proportion of data deleted was high. Despite success with artificial maps, standard semivariance analysis is unlikely to detect multiple scales of pattern in real ecological data. Semivariance analysis is recommended as an effective technique for quantifying some spatial characteristics of ecological data, and may provide insight into the scales of processes that structure landscapes.     

Joint effects of habitat configuration and temporal stochasticity on population dynamics

Habitat configuration and temporal stochasticity in the environment are recognized as important drivers of population structure, yet few studies have examined the combined influence of these factors. We developed a spatially explicit simulation model to investigate how stochasticity in survival and reproduction influenced population dynamics on landscapes that differed in habitat configuration. Landscapes ranged from completely contiguous to highly fragmented, and simulated populations varied in mean survival probability (0.2, 0.4, 0.8) and dispersal capacity (1, 3, or 5 cells). Overall, habitat configuration had a large effect on populations, accounting for >80% of the variation in population size when mean survival and dispersal capacity were held constant. Stochasticity in survival and reproduction were much less influential, accounting for <1–14% of the variation in population size, but exacerbated the negative effects of habitat fragmentation by increasing the number of local extinctions in isolated patches. Stochasticity interacted strongly with both mean survival probability and habitat configuration. For example, survival stochasticity reduced population size when survival probability was high and habitat was fragmented, but had little effect on population size under other conditions. Reproductive stochasticity reduced population size irrespective of mean survival and habitat configuration, but had the largest effect when survival probability was intermediate and habitat was well connected. Stochasticity also enhanced the variability of population size in most cases. Contrary to expectations, increasing dispersal capacity did not increase population persistence, because the probability of finding suitable habitat within the dispersal neighborhood declined more for the same level of dispersal capacity when fragmentation was high compared to when it was low. These findings suggest that greater environmental variability, as might arise due to climate change, is likely to compound population losses due to habitat fragmentation and may directly reduce population size if reproductive output is compromised. It may also increase variability in population size.     

不同间作模式对台刈茶园小绿叶蝉及其天敌种群数量的影响

研究不同间作模式对台刈茶园小绿叶蝉及其主要天敌圆果大赤螨种群数量的影响.在试验台刈茶园设置3种不同耕作模式的试验区,即间作藿香蓟的生物覆盖区(A)、对比间种决明的生物覆盖区(B)、清耕区(C).结果表明:9月份,藿香蓟生殖生长的盛花期也是叶蝉的第2高峰期,(C)区叶蝉的平均虫口密度为14.6头/m2,圆果大赤螨的平均螨口密度仅为0.2头/m2,圆果大赤螨与叶蝉的益害比为1∶73.(A)区叶蝉平均虫口密度仅为9.3头/m2,圆果大赤螨的平均螨口密度达3.6头/m2,益害比为1∶2.6.(B)区叶蝉平均虫口密度为13.9头/m2,圆果大赤螨的平均螨口密度为0.7头/m2,益害比为1∶19.8.在盛夏7~8月,(A)、(B)区与(C)区相比,空气平均温度降低2.57~2.84℃,平均相对湿度提高12%~13%.间作的生物覆盖措施均能显著改善茶园的小气候,但有较长花期的藿香蓟的花粉及花蕊上取食的啮虫幼虫可成为圆果大赤螨丰富的食料.所以,在台刈茶园间作藿香蓟可构建良好的茶树-藿香蓟人工复合生态系统,扩大茶园主要害虫小绿叶蝉的天敌圆果大赤螨种群数量,促进茶园以螨治虫的生态控制效应.