article in Climatic Change: Effects of Warming del clima en la vegetación de Sierra Nevada few months ago I wrote the entry "Your manuscript has-been
Accepted ... ", which had the" adventures and misadventures "lived to publish the paper" Simulating
Potential effects of climatic warming on altitudinal patterns of key species in Mediterranean-Alpine Ecosystems "which is an improved version of my work
get the DEA (and written in 2007), and has finally been published in the journal Climatic Change
. Then I do a small summary of the paper.
One of the effects of climate change observed in plants is the latitudinal and altitudinal displacement of populations. In this displacement occur at the edges of stocks advancing fronts (areas of new colonization) front and back (areas of local extinction). To explore this issue further in Sierra Nevada, this paper simulates changes in the potential distribution of four vegetation types (oak, holm-padded brushwood and grass enebral psicroxerófilo) along the XXI century on four climate change scenarios with two objectives:
- assess the potential effect of climate warming on the Potential area of \u200b\u200bvegetation.
- Describe and apply a simple method called Differential Approval, which allows you to locate fronts advance and retreat of populations, and predict the potential succession patterns between different formations.
The modeling method was fairly simple. Calibrate models of potential distribution (eye, potential distribution refers to the habitat conditions for the species as the variables used to calibrate the model, not the actual distribution) present for the four formations using MaxEnt
, taking as input points presence of training and four predictor variables (mean annual temperature, humidity topographic index, average annual solar radiation and slope), and projected on each of the scenarios of climate warming at intervals of 15 years.
The first analysis did was to calculate the potential areal extent of each formation over time, resulting in something like this:
is clear the general downward trend, especially in formations characteristic of the higher areas.
The concept
Suitability differential works like this: if we have two consecutive distribution patterns over time, the first you subtract the values \u200b\u200bof a second and get the change. Where the values \u200b\u200bare positive, improving the conditions for the species (possible fronts of progress) and which are negative, worse (possible front-back). The figure below explains the concept: you can see the model t0 (
to , the more intense the green, the better), the original model and expanded points of presence (b
), the model t1 (c
, notes the ideal area shift); fitness differential (d
, the more red, worse).
Now 
attention to the following idea: given species A and B, for which they have their own distribution models and future, if in a population of A fitness for A decreases while increases the suitability for B, then the ecological conditions are favoring that B replaces A.
I applied this concept to the four plant communities, and summarized the results in the following diagram, which represents the potential for substitution pattern among the four vegetation types:
Each node represents a vegetation type, and numbers (and arrows as sense and thickness) represent average habitat suitability populations. Within the nodes represents the change of fitness in training, and the arrows represent transfers between training eligibility. To better explain, I focus on the oak: the average fitness of populations of oaks goes from 48 to 3, while the actual populations of oak will win 19 points suitability for oaks. Therefore, we think that the oaks can build on the oak.
Of course, all the results of this study must be interpreted bearing in mind that working with models and scenarios, with all the uncertainty that that implies. The results should not be taken as predictions, but they provide indicators and allow us to gain new perspectives from which to confront the problem of climate change.
I hope you like the original!.
